r-economy, 2022, 8(3), 191–195 doi: 10.15826/recon.2022.8.3.015 191 www.r-economy.ru online issn 2412-0731 editorial © turgel, i.d., 2022 sanctions have a long history, which spans over two thousand years. in fact, the first recorded cases of sanctions go as far back as ancient greece. in the middle ages, such measures were forma lized in legislation and were called repressalia. under their current name, sanctions came to be known after world war i: the power to deploy sanctions was described in the league of nations’ covenant. after the establishment of the united nations, such measures were included into the chapter vii of the un charter. traditionally, sanctions are seen as a foreign policy tool falling between diplomacy and military force and applied in response to the undesi rable actions of a certain state. unlike diplomatic intervention efforts, sanctions have a more pronounced economic effect and are seen as more likely to bring the desired change in the target state’s behaviour on the international arena. unlike military force, sanctions are a less costly alternative and they also carry less risk of further escalation of the conflict. lately, the topic of international sanctions has gained much urgency worldwide and has been actively discussed in the academic circles. the debates mostly centre around the impact of sanctions on the target’s economy and their appropriateness as a foreign policy tool. there is, however, a perceived shortage of studies providing a comprehensive analysis of sanctions’ impact on the regional, national and internatio nal levels as well as the specific tools of sanction policy and their effectiveness. more inquiry is needed into  the challenges faced by target countries as well as the whole international community in relation to sanctions. the papers included in this special issue can be divided into three groups. the first group deals with the theory and methodology of sanctions studies. a.a.  pobedin in his paper ‘reconside ring contemporary classifications of sanctions doi 10.15826/recon.2022.8.3.015 udc 339.5, 339.9 jel f51, e61, f13 sanctions in international politics: expectations and reality i.d. turgel  ural federal university, ekaterinburg, russia;  i.d.turgel@urfu.ru in the light of the russia sanctions regime’ systematizes the approaches to the classification of international economic sanctions and proposes a qualitative model that can be used to examine specific sanctions regimes. the second group of studies includes the papers analyzing specific sanctions episodes. special attention is given to comparative analysis of sanctions in different countries. i.v. lazanyuk and d.  mambu diu investigate the development of the angolan economy under the pressure of sanctions. the authors focus on the role and mechanisms of the sanctions adopted by wes-tern countries against angola and some other african states. o.s.sukharev and e.n.voronchikhina compare the development of iran and russia during their respective sanctions episodes by looking at the dynamics of each country’s macro-indicators. l.l.  bozhko in her paper ‘challenges of anti-russia sanctions for metals and mining enterprises in kazakhstan’ considers the problem from the perspective of kazakhstan, which is not targeted by sanctions but is nevertheless affected by them because of its close trade ties with russia. the study aims to identify and describe the strategies and models of behaviour used by kazakhstani companies to avoid the risks of se condary sanctions. the third group comprises articles discussing the impact of sanctions on specific economic sectors and regions of russia. i.s. belik, n.v. starodubets, a.i. yachmeneva, and k.a. prokopov estimate the potential losses incurred by russian metal exporters due to the introduction of the carbon border adjustment mechanism  in the eu and the sanctions pressure. s.a.  balashova and t. musin analyze the problems and prospects of the russian cloud computing market under sanctions. since further dynamics of the market is surrounded with uncertainty related to the behttps://doi.org/10.15826/recon.2022.8.3.015 https://doi.org/10.15826/recon.2022.8.3.015 mailto:i.d.turgel@urfu.ru 192 www.r-economy.ru r-economy, 2022, 8(3), 191–195 doi: 10.15826/recon.2022.8.3.015 online issn 2412-0731 haviour of the key drivers and the possible introduction of new sanctions, several scenarios are built for the development of the russian cloud market and implementation of cloud technologies. e.a. zakharchuk considers three scenarios of economic development of the yamalo-nenets autonomous district, the largest oil and gas region of russia, under sanctions. the article estimates the impact of the sanctions on specific areas of yamal, especially the development of new hydrocarbon deposits in the arctic. m.y.  ilyushkina, a.v.  stepanov, g.n.  valiakhmetova, and a.s.  burnasov describe the tendencies and prospects of development of russian industrial regions under sanctions. they focus on the case of sverdlovsk region, which has a high concentration of mining and manufacturing (heavy engineering) enterprises. information about the author irina d. turgel – editor-in-chief of r-economy, doctor of economics, professor, ural federal university (19 mira str., ekaterinburg, 620002, russia); e-mail: i.d.turgel@urfu.ru for citation turgel, i.d. (2022). sanctions in international politics: expectations and reality. r-economy, 8(3), 191–195. doi: 10.15826/recon.2022.8.3.015 https://doi.org/10.15826/recon.2022.8.3.015 mailto:i.d.turgel@urfu.ru r-economy, 2022, 8(3), 191–195 doi: 10.15826/recon.2022.8.3.015 193 www.r-economy.ru online issn 2412-0731 редакционная статья история развития санкций насчитывает более двух тысяч лет. первые случаи применения были известны ещё в древней греции. в эпоху средневековья подобные меры получают нормативное закрепление и название «репрессалии». санкциями они стали именоваться после первой мировой войны в уставе лиги наций. после создания оон такие меры были закреплены в vii разделе устава оон. традиционно, санкции рассматриваются как компромиссный вариант ответа на нежелательные действия того или иного государства. в отличие от дипломатических мер воздействия санкции обладают гораздо более выраженным эффектом воздействия на экономику страны-объекта санкций, и с гораздо большей вероятностью могут привести к изменению поведения государства на международной арене. в то же время, в отличие от военных мер, санкции представляют собой намного менее затратный вариант ответа на нежелательные действия другой стороны и  одновременно несут в себе гораздо меньший риск дальнейшей эскалации конфликта. в последнее время тема международных санкций с новой силой привлекла внимание научного и экспертного сообщества. сейчас дискуссии в основном сосредоточены на анализе влияния санкций на экономику конкретной страны, их приемлемости в качестве инструмента международной политики. в то же время недостаточно внимания уделяется изучению комплексного воздействия санкций на региональном, национальном и  международном уровнях, специфике инструментов санкционной политики и оценке их эффективности. недооцениваются вызовы санкционной политики, с которыми сталкиваются как страны, непосредственно подвергшиеся санкциям, так и международное сообщество в целом. содержательно статьи, вошедшие в данный специальный выпуск можно разделить на три блока. первый блок посвящен теории и методологии исследования режима экономических санкций. в статье а.а. победина «оценка санкционного режима в отношении россии» систематизируются подходы к классификации международных экономических санкций, предлагается качественная модель анализа санкционного режима. второй блок включает статьи, анализирующие специфику применения санкций по отношению к отдельным государствам. большое внимание уделяется сравнительному анализу применения санкций в разных странах. и.в. лазанюк и д. мамбудиу изучили развитие экономики анголы в условиях санкций. авторы концентрируются на анализе роли и  механизмов использования таргетированных санкций западных стран против анголы и ряда африканских государств. о.с. сухарев и е.н. ворончихина сопоставляют результаты макроэкономического развития ирана и россии в период санкций путем сравнительного и статистического анализа динамики основных макропоказателей. л.л. божко в статье «санкционные ограничения: новые вызовы для предприятий горно-металлургической отрасли казахстана» попыталась посмотреть на проблему со стороны страны, которая не является объектом санкций, но испытывает их влияние в силу вовлеченности в  международную кооперацию. целью исследования является идентификация моделей поведения казахстанских компаний в условиях санкционных ограничений и выявление сложившихся тенденции. третий тематический блок включает статьи, раскрывающие особенности влияния санкций на отдельные сектора и регионы рф. и.с. белик, н.в. стародубец, а.и. ячменева, doi 10.15826/recon.2022.8.3.015 удк 339.5, 339.9 jel f51, e61, f13 санкции в международной политике: ожидания и реальность и.д. тургель  уральский федеральный университет;  i.d.turgel@urfu.ru https://doi.org/10.15826/recon.2022.8.3.015 https://doi.org/10.15826/recon.2022.8.3.015 mailto:i.d.turgel@urfu.ru 194 www.r-economy.ru r-economy, 2022, 8(3), 191–195 doi: 10.15826/recon.2022.8.3.015 online issn 2412-0731 к.а. прокопов предложили подход к оценке величины потенциальных потерь от введения углеродного налога для отечественных предприятий-экспортеров металлургической отрасли с учетом санкционного давления. с.а. балашова, т. мусин анализируют проблемы и перспективы российского рынка облачных вычислений в реалиях современных ограничений. с учетом неопределенности дальнейших значений основных драйверов и постоянного введения новых санкций строятся возможные сценарии развития российского облачного рынка и внедрения облачных технологий. е.а. захарчук разработала сценарии экономического развития ямало-ненецкого автономного округа (крупнейшего газо и  нефтедобывающего региона рф) в различных условиях реализации санкций. в статье производится оценка влияния рестрикций на развитие отдельных территории ямала, уделяя внимание новым районам разработки месторождений углеводородного сырья в арктической зоне. м.ю. илюшкина, а.в. степанов, г.н. валиахметова, а.с. бурнасов характеризуют тенденции и перспективы развития промышленных регионов россии в  условиях международных санкций. в качестве кейс-метода для анализа использовались данные свердловской области, региона с высокой концентрацией горнодобывающих и обрабатывающих (машиностроительных) предприятий. информация об авторe тургель ирина дмитриевна – главный редактор журнала r-economy, доктор экономических наук, профессор, уральский федеральный университет (620002, россия, г. екатеринбург, ул. мира, 19); e-mail: i.d.turgel@urfu.ru для цитирования turgel, i.d. (2022). sanctions in international politics: expectations and reality. r-economy, 8(3), 191–195. doi: 10.15826/recon.2022.8.3.015 https://doi.org/10.15826/recon.2022.8.3.015 mailto:i.d.turgel@urfu.ru r-economy, 2022, 8(3), 191–195 doi: 10.15826/recon.2022.8.3.015 195 www.r-economy.ru online issn 2412-0731 社論 制裁的历史可以追溯到两千多年前，最 早的应用案例在古希腊。在中世纪，这种措 施被规范化了，被称为 “报复”。第一次世 界大战后，它们在国际联盟条约中被称作制 裁。联合国成立后，该措施被写入了《联合 国宪章》第七章。传统上，制裁被视为对一 个国家不受欢迎行为的妥协性反应。与外交 措施相比，制裁对目标国家的经济有更明显 的影响，更有可能导致该国家在国际舞台上 改变行为。同时，与军事措施不同，制裁是 针对对方不良行动成本较低的选择，而对冲 突进一步升级的风险要小得多。 国际制裁的话题最近重新吸引了学术界 和 专 家 界 的 注 意 。 当 前 的 讨 论 主 要 集 中 在 分 析 制 裁 对 特 定 国 家 经 济 的 影 响 以 及 制 裁 作 为 一 种 国 际 政 策 工 具 的 可 接 受 性 。 但 同 时 ， 相 关 研 究 对 制 裁 在 区 域 、 国 家 和 国 际 层 面 的 综 合 影 响 ， 制 裁 工 具 的 具 体 内 容 以 及 评 估 其 有 效 性 的 关 注 度 不 够 。 直 接 受 制 裁 的 国 家 和 整 个 国 际 社 会 所 面 临 的 制 裁 政 策的挑战被低估了。 这期特刊中的文章可以分为三个板块。 第一板块专门讨论经济制裁的理论和研究方 法。波贝丁的文章《根据对俄制裁来审查目 前的制裁分类》系统地介绍了国际经济制裁 的分类方法，并提出了一个分析制裁制度的 定性模型。 第二板块分析个别国家的制裁问题，主要 关注不同国家受到的制裁。拉扎纽克和吉·曼 doi 10.15826/recon.2022.8.3.015 国际政治制裁：期望与现实 图尔格尔  乌拉尔联邦大学；  i.d.turgel@urfu.ru 布研究了制裁下安哥拉经济的发展。作者重 点分析了西方国家对安哥拉和一些非洲国家 使用定向制裁的作用和机制。苏哈列夫和沃 龙奇金娜通过对关键宏观指标动态的统计分 析，比较了制裁期间伊朗和俄罗斯的宏观经 济表现。博日科在她的文章《哈萨克斯坦冶 金与采矿公司的反制裁问题》中试图从一个 不受制裁，但由于参与国际合作而受制裁影 响的国家的角度来看待这个问题。其研究的 目的是确定哈萨克斯坦公司在制裁限制下的 行为模式，并确定新的趋势。 第三板块揭示了制裁对俄罗斯联邦各个部 门和地区的具体影响。别利克、斯塔罗杜贝 茨、亚赫梅内娃、普罗科波夫考虑到制裁的压 力，提出了一种方法来估计国内出口冶金企业 引入碳税的潜在损失。巴拉索娃、穆辛分析了 俄罗斯云计算市场在当前限制条件下的问题 和前景。文章考虑到主要驱动因素的不确定性 以及新制裁措施的不断出台，提出了构建俄罗 斯云市场和引入云技术的可能情景。札哈楚克 为亚马尔-涅涅茨自治区（俄罗斯最大的天然 气和石油生产地区）在各种制裁下的经济发展 制定了方案。文章评估了制裁对亚马尔地区 开发的影响，并关注了北极油气矿藏开发的新 区域。伊柳什金娜、斯捷潘诺夫、瓦利亚赫梅 托娃、伯纳索夫描述了国际制裁下俄罗斯工业 发展的趋势和前景。斯维尔德洛夫斯克州的数 据被用作分析案例，它是采矿和制造（机器制 造）企业高度集中的地区。 作者信息 图尔格尔·伊琳娜·德米特里耶芙娜 —— r-economy杂志主编，经济学全博士， 教授，乌拉尔联邦大学（邮编：620002，俄罗斯，叶卡捷琳堡，米拉大街19号）；邮 箱：i.d.turgel@urfu.ru 致謝 turgel, i.d. (2022). sanctions in international politics: expectations and reality. r-economy, 8(3), 191–195. doi: 10.15826/recon.2022.8.3.015 https://doi.org/10.15826/recon.2022.8.3.015 https://doi.org/10.15826/recon.2022.8.3.015 mailto:i.d.turgel@urfu.ru mailto:i.d.turgel@urfu.ru 46 www.r-economy.ru r-ecomony, 2018, 4(2), 46–50 doi: 10.15826/recon.2018.4.2.007 online issn 2412-0731 original paper for citation lukić, d., petrović, m. d., & denda s. (2018) cultural indicators of sustainable regional development (the case of serbian national park). r-economy, 4(2), 46–50. doi: 10.15826/recon.2018.4.2.007 for citation лукич, д., петрович, м., денда, с. (2018) культурные индикаторы устойчивого регионального развития. r-economy, 4(2), 46–50. doi: 10.15826/recon.2018.4.2.007 doi: 10.15826/recon.2018.4.2.007 cultural indicators of sustainable regional development (the case of serbian national park) dobrila lukića, marko d. petrovićb, stefan dendab a alfa bk university, belgrade, serbia; e-mail:dobriladjerdap@gmail.com b geographical institute jovan cvijić sasa, belgrade, serbia; e-mail: m.petrovic@gi.sanu.ac.rs; e-mail: s.denda@gi.sanu.ac.rs abstract this study discusses tourism as a means of regional development by focusing on specific cultural indicators. in this paper, we are dealing with the case of the djerdap national park – the largest national park in serbia and one of the most popular of the country’s destinations. this area has an extraordinary diversity of geomorphological forms, it is rich in cultural and historical monuments. at the same time this area is sparsely populated and is demonstrating an insufficient economic growth. for our analysis, we apply comparative indicators to measure sustainable regional tourism development that were proposed by the european union’s experts. this set of indicators consists of five groups and includes the ratio of accommodation capacities to the number of local inhabitants and the intensity of tourism. our calculations are based on the statistical data on accommodation capacities and the tourist traffic provided in several municipalities. these data are provided by the statistical office of serbia (2015). we also use the 2011 census data on the number of local inhabitants. we have found that the ratio of accommodation capacities to the number of local inhabitants in djerdap is in the so-called green zone, which shows the sustainability of tourism in this region and an insignificant impact that tourism has on the cultural identity of the local community. the intensity of tourism in djerdap is in the red zone, however, which demonstrates an alarming trend and requires further analysis, especially regarding the carrying capacity of the area. thus, the conclusion is made that the development of tourism in djerdap should be balanced with the protection of natural resources. keywords cultural indicators, criteria of the european union, sustainable regional development, tourism, djerdap national park культурные индикаторы устойчивого регионального развития д. лукичa, м. петровичb, с. дендаb a алфа бк универзитет, белград, сербия; e-mail:dobriladjerdap@gmail.com b географический институт «йован цвиич» сербской академии наук, белград, сербия; e-mail: m.petrovic@gi.sanu.ac.rs; e-mail: s.denda@gi.sanu.ac.rs резюме в исследовании рассматривается туризм как средство регионального развития с упором на определенные культурные показатели. авторами рассмотрен случай национального парка джердап – крупнейшего национального парка в сербии и одного из самых популярных туристических направлений страны. эта область имеет необычайное разнообразие геоморфологических форм, она богата культурными и историческими памятниками. в то же время этот район малонаселен и демонстрирует недостаточный экономический рост. для нашего анализа мы применяем сравнительные показатели устойчивого развития регионального туризма, которые были предложены экспертами европейского союза. этот набор показателей состоит из пяти групп; он включает соотношение гостиничных площадей к численности местных жителей и интенсивности туризма. наши расчеты основаны на статистических данных, предоставленных статистическим управлением сербии, о гостиничных площадях и туристическом трафике в нескольких муниципалитетах. также используются данные переписи 2011 г. о количестве местных жителей. авторами обнаружено, что отношение гостиничных площадей к числу местных жителей в джердапе находится в так называемой «зеленой» зоне, что свидетельствует об устойчивости туризма в этом регионе и о незначительном влиянии туризма на культурную самобытность местного общества. интенсивность туризма в  джердапе находится в «красной» зоне, что демонстрирует тревожную тенденцию и требует дальнейшего анализа, особенно в отношении пропускной способности района. таким образом, делается вывод о том, что развитие туризма в джердапе должно быть сбалансировано с охраной природных ресурсов. ключевые слова культурные показатели, критерии европейского союза, устойчивое региональное развитие, туризм, национальный парк джердап   http://doi.org/10.15826/recon.2018.4.2.007 http://doi.org/10.15826/recon.2018.4.2.007 mailto:dobriladjerdap@gmail.com mailto:m.petrovic@gi.sanu.ac.rs mailto:dobriladjerdap@gmail.com mailto:m.petrovic@gi.sanu.ac.rs r-ecomony, 2018, 4(2), 46–50 doi: 10.15826/recon.2018.4.2.007 47 www.r-economy.ru online issn 2412-0731 introduction sustainable tourism development requires careful planning and management, which would ensure that tourism contributes to improving the quality of life of the local population and that its negative effects on the local cultural and natural environment should be reduced or mitigated. the concept of sustainable development was defined in 1987 by the world commission on environment and development in the brundtland report, also known as our common future. sustainable development is understood as “development that meets the needs of the present generation without compromising the ability of future generations to meet their own needs”. sustainable development requires us to set certain boundaries, which are not absolute but are defined by the current state of technology and social organization in relation to the environment as well as the ability of the biosphere to absorb the effects of human activities. according to the brundtland commission, sustainable development does not mean a fixed state of harmony, but a process in which a harmony of exploitation of resources, direction of investments, directions of technological development and institutional changes with present and future needs are created. the application of the concept of sustainable regional tourism development thus implies minimizing negative and maximizing the positive impacts of tourism on the environment and the available resources. for this reason, it is necessary to identify, monitor, assess and manage the economic, socio-cultural and environmental effects of tourism. at the core of sustainability lies the balance between the development of tourism and tourism areas, on the one hand, and protection and preservation of the environment, resources and the value of the local community, on the other [1]. theoretical framework by analyzing and processing statistical data, many international, national and local institutions have tried to develop a set of indicators of sustainable regional tourism development. the world tourism organization has published guidelines on sustainable regional tourism development, which included two sets of indicators: basic indicators and indicators for each type of tourist value [2–4]. indicators of sustainable regional tourism development were also set by the european environment agency (eea). recently, a growing number of studies have been focusing on socio-cultural influence of tourism in such areas as spain, great britain, bali, florida, and norway. this research primarily refers to the methodology of estimating the ratio of inhabitants in these areas to the number of tourists, the negative impact of tourism on local communities, and the development of tourism as a whole. g. miller discusses the indicators of sustainable regional tourism development related to environmental protection, employment, finances and visitor aspects [5]. t. g. ko describes several quantitative and qualitative indicators in relation to eight different dimensions such as political, economic, socio-cultural, and industrial [6]. different studies have dealt with indicators of sustainable regional tourism development in serbia by comparing them with those of tourist destinations in other countries. according to в.  stojanović, indicators of sustainable tourism provide the most modern method of measuring the effects of tourism development and usually reflect all the principles of sustainable development [7, p.  264]. m. maksin et al. define these indicators as measurements of the state of the given environment and process in a certain area and in a certain period. thus, the indicators enable researchers not only to determine the current state but also to monitor any changes, primarily in terms of goal achievement [8, p. 284]. d. jovičić, t. ilić maintains that, according to the world tourism organization, since 1996, “indicators measure or evaluate certain information, which helps decision-makers (administrative bodies) minimize the possibility of bad business decisions” [9, p. 277]. the case of the djerdap national park the djerdap gorge is located in the northeastern part of serbia, on the border with romania, in the center of the northern part of the balkan peninsula. it stretches in the west-eastern direction. according to d. dukić, the djerdap gorge begins with the underwater rock germania, which is located on the 1,039.5th kilometer of the danube. at that point, the riverbank narrows from 2,000 m wide to 350 m. dukić believes that the romanian village of guravoj on the 941th kilometer marks the end of the gorge. here the river bed becomes wider again, the fall rapidly decreases and the deposit accumulation begins. in this settlement, the islands of the danube deposits were formed: serbian guravoj, banacansko, karatas and dudas. in this part, djerdap is 98.5 km long [10]. the largest http://doi.org/10.15826/recon.2018.4.2.007 48 www.r-economy.ru r-ecomony, 2018, 4(2), 46–50 doi: 10.15826/recon.2018.4.2.007 online issn 2412-0731 part of the djerdap gorge has a typical v-shaped valley, with steep, even vertical sides, which are rising on average 260–300 m and sometimes over 500 m above the river bed. however, djerdap is a compound river valley comprising four gorges separated by basins: golubac gorge, ljupkovska basin, gorge gospodjin vir, donjomilanovačka basin, gorges great and small kazan, oršavska basin and sipska gorge. the djerdap gorge is an essential part of the national park djerdap. this area, which covers about 65,000 ha, was given the status of a national park in 1974. it is located on the territory of municipalities golubac, kladovo and majdanpek; it extends about 100 km along the right bank of the danube, from golubac to karataš; and it is 2 to 8 km wide. the national park djerdap is rich in geomorphological forms, cultural and historical monuments, fauna and flora, especially beech and oakwoods (over 64% of the territory). the factors contributing to the preservation of the natural environment of the djerdap national park are the low population density, absence of large industrial plants and a fairly sparse transport infrastructure [11]. methodology experts of the european commission have designed a set of core indicators in order to evaluate and determine the degree of sustainability of tourism development in a certain area. these indicators provide a starting point for policy-making in this sphere depending on how they assess the condition of tourism: as critical, tolerable or sustainable. therefore, the three zones are identified: red (critical condition; urgent measures are required); yellow (tolerable; preventive measures are recommended); and the green zone (sustainable). the factors that help us evaluate the current state of development of tourism are divided into five groups: – the economic indicators show the economic effects of tourism on the local area; – the satisfaction of tourists is expressed through their opinion on the attractiveness of the area, the socio-cultural characteristics of the environment as well as on the quality of tourist capacities and services provided; – social indicators reflect the social integrity of the local community in terms of local inhabitants’ subjective well-being; – cultural indicators correspond to the degree of preservation of the cultural identity of the local community under the influence of tourists of different cultural backgrounds; – environmental indicators should reflect the state of the environment and the impacts of tourism on water resources, air, biodiversity, and land [7; 12]. in this paper, the cultural indicators of sustainable regional tourism development in djerdap are analyzed. they show us the effect of tourism on the local cultural identity. table 1 cultural indicators of sustainable regional tourism development cultural indicators ratio of accommodation capacities to the number of local inhabitants < 1.1:1 green zone 1.1–0.5: 1 yellow zone > 1.6:1 red zone intensity of tourism < 1.1:1 green zone 1.1–1.5: 1 yellow zone > 1.6:1 red zone source: [7]. cultural indicators of sustainable regional tourism development include the following: 1. the ratio of accommodation capacities to the number of local inhabitants. this indicator reveals an alarming trend if the number of beds exceeds the number of inhabitants over 1.6 times, because the local community is affected by the intensive construction of tourist accommodation. if this ratio is less than 1.5, then the situation is more favorable for the local community. natural characteristics of space, the type of accommodation, intensity and type of tourist traffic also influence the above-described mentioned correlations. 2. intensity of tourism. this indicator is the ratio of the number of overnight stays during the year expressed in thousands to the number of local inhabitants expressed in hundreds. this indicator shows the degree of cultural saturation in the area: if it exceeds 1.6, it is characterized as unfavorable for the sustainability of tourism [7]. results and discussion in our analysis of cultural indicators of sustainable regional tourism development in djerdap, we used the data on the accommodation capacities and tourist traffic in golubac, majdanpek and kladovo provided by the statistical office of the republic of serbia for 2015. the data on the number of inhabitants in the municipalities of djerdap were also obtained from http://doi.org/10.15826/recon.2018.4.2.007 r-ecomony, 2018, 4(2), 46–50 doi: 10.15826/recon.2018.4.2.007 49 www.r-economy.ru online issn 2412-0731 the statistical office of the republic of serbia and are based on the results of the latest 2011 census. in the municipality of golubac in 2015, there were recorded one two-star hotel and one overnight stay in the category of basic accommodation capacities. the total number of available rooms was 59 with 172 beds in them. in the category of complementary accommodation capacities, in 2015, there were 21 one-star private rooms with 51 beds. thus, the total number of available rooms in golubac in 2015 was 80, with 223 beds. in majdanpek, there were two three-star hotels in the category of basic accommodation capacities with the total number of 300 rooms with 580 beds. in the category of complementary accommodation capacities in the municipality of majdanpek in 2015 there were 70 two-star private rooms with 182 beds. this means that the total number of available rooms was 370 with the total of 762 beds. in kladovo, there were two hotels (one fourstar and one two-star) and one youth hostel registered in the category of basic accommodation capacities. the complementary accommodation capacities included 25 three-star private homes and apartments and 77 private rooms. the total number of available rooms was 561, with 1160 beds. table 2 ratio of accommodation capacities to the number of local inhabitants in djerdap municipality population (2011 census) number of beds in 2015 ratio of accommodation capacities to the number of local inhabitants golubac 8,654 223 0.02:1 green zone majdanpek 19,854 762 0.04:1 green zone kladovo 21,142 1,160 0.05:1 green zone djerdap (total) 49,650 2,145 0.04:1 green zone source: [13; 14]. djerdap has seven business units in the category of basic accommodation capacities. the total number of rooms in 2015 was 1,011, with 2,145  beds. the same year in djerdap, a total of 46,773 tourists were recorded: 37,620 domestic and 9,153 foreign tourists. overall, they spent in djerdap 94,934 nights. the ratio of accommodation capacities to the number of local inhabitants demonstrates that tourism in djerdap is in the green zone, given that this ratio for djerdap is 0.04, according to the data of 2015. therefore, we can conclude that this indicator demonstrates the sustainability of tourism and an insignificant influence that it has on the local culture. however, if we consider the data from other sources, they are likely to show that the cultural influence is more pronounced. table 3 intensity of tourism in djerdap municipality population (2011 census) number of nights in 2015 intensity of tourism golubac 8,654 3,857 0.45:1 green zone majdanpek 19,854 41,751 2.10:1 red zone kladovo 21,142 49,326 2.33:1 red zone djerdap 49,650 94,934 1.91:1 red zone source: [13; 14]. the intensity of tourism in djerdap is 1.91 (red zone), which means that tourism development is not sustainable and that the identity of the local community is under the increasing pressure on the part of tourists coming from places with different cultural characteristics. the reason for this is the decreasing number of local population in djerdap municipalities. however, in the municipalities of djerdap, the level of the cultural saturation of the area is not too high, because the newly built facilities for tourism do not significantly affect the local community. in the analysis of the future development of tourism in djerdap, the carrying capacity of the space should be determined: “carrying capacity is the number of users that a certain space can take within a certain period of time, without irreversible biological and physical degradation, the ability of space to satisfy recreational needs and without significant endangerment of the quality of the recreational experience” [15]. conclusion our analysis of cultural indicators of sustainable regional development in djerdap has shown that the criteria put forward by the eu experts are mostly met, especially when it comes to the ratio of accommodation capacities to the number of local inhabitants. as for the intensity of tourism, the situation is alarming, since only in golubac municipality this indicator is in the green zone. in majdanpek and kladovo, however, the number of tourist overnight stays throughout the year is more than two times higher than the number of inhabitants. in order to harmohttp://doi.org/10.15826/recon.2018.4.2.007 50 www.r-economy.ru r-ecomony, 2018, 4(2), 46–50 doi: 10.15826/recon.2018.4.2.007 online issn 2412-0731 nize the development of tourism in djerdap with the area’s capacity and capabilities, it is necessary to ensure that all tourists and other stakeholders of tourism development should preserve the natural environment and culture of this destination, abide by the standards of ethical behaviour and be aware of the needs of future generations. therefore, there should be a balance between tourism development in djerdap and the protection of its natural environment. this can be achieved through careful resource analysis, co-ordination of environmental protection and tourist activities to prevent any negative impact of tourism on the environment. references 1.  lukić, d. (2015). geonasleđe srpskog podunavlja u funkciji održivog razvoja turizma. doktorska disertacija. beograd: geografski fakultet. 2. ceron, j. p. & dubois, g. (2003). tourism and sustainable development indicators: the gap between theoretical demands and practical achievements. current issues in tourism, 6(1), 54–75. doi: 10.1080/13683500308667944. 3. jovičić, d. (2000). turizam i životna sredina – koncepcija održivog razvoja. beograd: zadužbina andrejević. 4. pavlović, с. & beliј, м. (2012). cultural indicators of tourism sustainability in serbian spas. glasnik srpskog geografskog društva, 92(3), 95–108. doi: 10.2298/gsgd1203095p. 5. miller, g. (2001). the development of indicators for sustainable tourism: results of a delphi survey of tourism researches. tourism management, 22(4), 351–362. doi: 10.1016/s02615177(00)00067-4. 6. ko, t. g. (2005). development of a tourism sustainability assessment procedure: a conceptual approach. tourism management, 26(3), 431–445. 7.  stojanović, в. (2006). održivi razvoj turizma i životne sredine. novi sad: departman za geografiju, turizam i hotelijerstvo. 8. maksin, m., pucar, m., korać, m., milijić, s. (2009). menadžment prirodnih i kulturnih resursa u turizmu. beograd: univerzitet singidunum, fakultet za turistički i hotelijerski menadžment. 9. jovičić, d., ilić, t. (2010). indicators of sustainable tourism. glasnik srpskog geografskog društva, 90(1), 277–305. doi: 10.2298/gsgd1001277j. 10.  dukić, d. (1963). đerdapska hidroelektrana. glasnik srpskog geografskog društva, 44(2), 64–78. 11. lukić, d. (2005). đerdapska klisura. beograd: srpsko geografsko društvo. 12. lukić, d. & punoševac, s. (2015). primena indikatora održivog turizma eu na primeru đerdapa. in: zbornik radova sa 4. srpskog kongresa geografa sa međunarodnim učešćem dostignuća, sktuelnosti i izazovi geografske nauke i prakse povodom 150 godina od rođenja jovana cvijića. beograd: geografski fakultet univerziteta u beogradu, srpsko geografsko društvo. 307–312. 13. statistički godišnjak republike srbije (2011). beograd: republički zavod za statistiku. 14. statistički godišnjak republike srbije (2015). beograd: republički zavod za statistiku. 15. jovičić, d. (1997). razvoj turizma i zaštita prirode u nacionalnim parkovima. beograd: biblioteka „ekologija“ book 3. information about the authors dobrila lukić – ph.d. in geography, assistant professor, alfa bk university (palmira toljatija 3, 11000 belgrade, serbia); email: dobriladjerdap@gmail.com. marko d. petrović – ph.d. in geography, research associate, geographical institute jovan cvijić of the serbian academy of sciences and arts (sasa) (djure jakšića 9, 11000 belgrade, serbia); email: m.petrovic@gi.sanu.ac.rs. stefan denda – m.sc. in tourism, research assistant, geographical institute jovan cvijić of the serbian academy of sciences and arts (sasa) (djure jakšića 9, 11000 belgrade, serbia); email: s.denda@gi.sanu.ac.rs. http://doi.org/10.15826/recon.2018.4.2.007 http://doi.org/10.1080/13683500308667944 http://doi.org/10.2298/gsgd1203095p http://doi.org/10.1016/s0261-5177(00)00067-4 http://doi.org/10.1016/s0261-5177(00)00067-4 http://doi.org/10.2298/gsgd1001277j mailto:dobriladjerdap@gmail.com mailto:m.petrovic@gi.sanu.ac.rs mailto:s.denda@gi.sanu.ac.rs r-ecomony, 2018, 4(2), 67–71 doi: 10.15826/recon.2018.4.2.010 67 www.r-economy.ru online issn 2412-0731 original paper for citation akhmetzianova, o. o. & turgel, i. d. (2018) the role of industrial factors in socioeconomic development of sichuan province in the context of one belt, one road initiative. r-economy, 4(2), 67–71. doi: 10.15826/recon.2018.4.2.010 for citation ахметзянова, о. о., тургель, и. д. (2018) роль индустриальных факторов в социально-экономическом развитии провинции сычуань в контексте инициативы «один пояс – один путь». r-economy, 4(2), 67–71. doi: 10.15826/recon.2018.4.2.010 doi: 10.15826/recon.2018.4.2.010 the role of industrial factors in socio-economic development of sichuan province in the context of one belt, one road initiative oksana o. akhmetzianovaa, irina d. turgelb a harbin institute of technology, harbin, china; email: oksanochka-star@mail.ru b ural federal university, ekaterinburg, russia; email: i.d.turgel@urfu.ru  abstract sichuan province is an important junction area connecting south-western, north-western and central regions of china. for decades, the socio-economic development of this region has been the focus of major effort on the part of the chinese government. at the moment, the regional authorities of sichuan seek to maximize the region’s potential within the framework of the one belt, one road initiative. however, despite the abundance of mineral and other natural resources, modern transport infrastructure, and significant gdp growth, the province faces a number of challenges, primarily in the sphere of domestic and international economic cooperation. sichuan is also suffering from the massive outflow of workforce to other regions and countries. in this article, we discuss the key industrial factors that determine the socio-economic development of sichuan. our analysis of the available statistical data has shown that the region’s participation in one belt, one road initiative would allow it to strengthen its position on the national and international arena, attract new investors and improve its competitive advantage in comparison with the coastal regions of china. another viable option for the regional government would be to establish a special economic zone, which means building an appropriate infrastructure or reconstructing the already existing facilities, offering tax-and-tariff incentives, and introducing simplified bureaucratic procedures. keywords development, industrial factors, transportation, special economic zone, one belt, one road initiative роль индустриальных факторов в социально-экономическом развитии провинции сычуань в контексте инициативы «один пояс – один путь» о. о. ахметзяноваa, и. д. тургельb a харбинский политехнический университет, харбин, китай; email: oksanochka-star@mail.ru b уральский федеральный университет, екатеринбург, россия; email: i.d.turgel@urfu.ru резюме провинция сычуань является важным районом, соединяющим юго-западные, северо-западные и центральные районы китая. на протяжении десятилетий социально-экономическое развитие этого региона было в центре внимания китайского правительства. в настоящий момент, региональные власти провинции сычуань стремятся максимально использовать потенциал региона в рамках инициативы «один пояс, один путь». однако, несмотря на обилие минеральных и других природных ресурсов, современную транспортную инфраструктуру и значительный рост врп, перед областью стоит ряд проблем, прежде всего в сфере внутреннего и международного экономического сотрудничества. сычуань также страдает от массового оттока рабочей силы в другие регионы и страны. в этой статье обсуждаются ключевые промышленные факторы, определяющие социально-экономическое развитие провинции сычуань. наш анализ статистических данных показал, что участие региона в инициативе «один пояс, один путь» позволит ему укрепить свои позиции на национальной и международной арене, привлечь новых инвесторов и улучшить свои конкурентные преимущества по сравнению с прибрежными регионами китая. другим жизнеспособным вариантом для регионального правительства было бы создание особой экономической зоны, которая заключается в создании соответствующей инфраструктуры или реконструкции уже существующих объектов, предоставлении налоговых и тарифных стимулов и введении упрощенных бюрократических процедур. ключевые слова развитие регионов, промышленные факторы, транспорт, особая экономическая зона, инициатива «один пояс, один путь»  http://doi.org/10.15826/recon.2018.4.2.010 http://doi.org/10.15826/recon.2018.4.2.010 mailto:oksanochka-star@mail.ru mailto:oksanochka-star@mail.ru 68 www.r-economy.ru r-ecomony, 2018, 4(2), 67–71 doi: 10.15826/recon.2018.4.2.010 online issn 2412-0731 introduction sichuan province, located in western china, consists of two separate regions. in the east, there is a large sichuan bаsin, covering about 40% of sichuan’s total lаnd area of 48,500 square kilоmeters. sichuan province is a significant junction area between south-western, north-western, and central regions of china. in addition, it provides an important traffic corridor between southern and central china, its south-western and north-western parts. in a more general sense, this province may be seen as a bridge between central, southern and south-eastern asia [1]. sichuan province serves as an important strategic point that connects the socalled economic belts of the silk road initiative and the maritime silk road. this province has a large population and is rich in various resources. in the recent years, the province’s economic strength has increased significantly and sichuan ranks high among other chinese regions by gdp. it is virtually an economic powerhouse of western china. technological industries and emerging pilot-type service industries enhance agricultural modernization, scientific and technological innovation [2]. in terms of its transport infrastructure, sichuan has managed to accomplish a major breakthrough: twenty road channels have already been completed, while the other thirteen are currently under construction. shuangliu international airport has turned chengdu into the fourth aviation city in china. in 2013, thirteen airports were built with the passenger turnover over 37 million. the expressway mileage has reached 5,046 km while the total road mileage exceeded 300,000 km. chengdu european high-speed rail accounts for 40% of china’s total volume of railway freight towards europe [3]. one of the serious challenges that sichuan province has to address nowadays is that it is lacking in domestic and international cooperation. this situation stems from the lingering negative effect of the international financial crisis and the poor business environment. the data we use in this research is provided by input-output manuals of chinese provinces. this reference book consists of matrices which provide data on the production volume for each province. in addition, it includes world and dоmestic commercial activity output for 21 tradable and 10 non-tradable industriеs in 1982–2015. we also obtained the data on sichuan province by analyzing the industrial statistical yearbook (ssb). the province’s development problems were investigated by christopher a. mcnally in his paper sichuan: driving capitalist development westward. he argues that the chinese government’s open up the west campaign has failed to achieve one of its primary goals in this province: to decrease the huge developmеnt gap between resource-poor and resource-abundant areas. simultaneously, sichuan’s phуsical infrastruсture is growing intensively, accelerating the national consolidation of the province’s economy and society. david s. g. goodman points out that “as a result of these different emphases, the campaign encompasses a wide range of development policies, ranging from mainstream efforts to ameliorate physical infrastructure to endeavours to manage human resources better and improve the rule of law” [3]. the role of industrial factors in the socio-economic development of sichuan province regional development is a complex, multi-level process, which can be approached from different social and economic perspectives. effective and efficient economic development depends on such industrial factors as government policy, transport network, raw materials, geography, labor, and industrial inertia [4]. for example, the increased concentration of the transport system and highly connected networks are usually associated with a high degree of development. if transport infrastructure is efficient, it provides the area with multiple economic and social opportunities, which, in turn, enhance employment, investment and availability of markets. inefficiency of the region’s transport system can lead to missed opportunities and lower living standards. at the aggregate level, an efficient transport system decreases the costs in many economic sectors, while inefficient transport network increases these costs. many government programs have been implemented in the province in the recent years, in particular the western development strategy, which comprises objectives for the develоpment of telecommunications, transport, energy and hydropower plants; attraction of fоreign investmеnt, reforestation, promоtion of educаtion, and measures to retain qualified workforce and prevent brain drain. by 2006, 1 trilliоn yuаn had been spent on infrastructural construction in wеstern chinа [6]. http://doi.org/10.15826/recon.2018.4.2.010 r-ecomony, 2018, 4(2), 67–71 doi: 10.15826/recon.2018.4.2.010 69 www.r-economy.ru online issn 2412-0731 it is worth noting that the chinese government, following in the footsteps of deng xiaoping, injected massive funds to boost sichuаn’s developmеnt. deng xiaoping started mаrket rеforms in sichuаn in 1978 as an effort to alleviаte pоverty in the province. the government in a similar way reorgаnized sichuаn prоvince in 1997. chongqing municipаlity was separated from the rest of thе prоvince to create a nеw politicаl and administrаtive еntity that could transition to market economy, [7]. at the moment, sichuan province is involved into the thirteenth national five-year plan (2016–2020) aimed at building a moderately prosperous society while promoting sustainable economic and social development [3]. when the chinese government put forward “one belt, one rоad” initiаtive, sichuаn province joined this project. the regional authorities have аlso been implementing pоlicies thаt foсus on interprоvincial investmеnt as wеll as spеcific industriеs such as trаnsportation infrastructurе and softwаre. thе improvеment of the trаnsportation system in sichuаn was largely achieved through largescale state funding. a cоmprehensive trаnsport netwоrk involving air, rail, road, and wаter transportations connects all parts of the province with chengdu, the cаpital city and hub. thus, siсhuan province hаs a state-of-the-art transpоrt sуstem and is nоw a major trаnsport juncturе in the sоuth-west of сhina. one of the four largest airports in china is shuangliu international airport located in chengdu. in total, sichuan province has thirteen airports. railway plays a vital role in sichuan’s transport network: there are currently five major railways connecting the region’s towns and cities with other provinces. the region also benefits from its well-developed network of expressways and inland water network. an abundаnt supplу of local raw mаterials and the high quаlity of water in the provincе are impоrtant input factоrs for food and bevеrage prоduction. only 4.7% of rаw materials usеd in sichuan’s chеmical industry are impоrted. sichuan ranks high in the country in terms of guaranteed reserves of solid minerals such as vanadium, titanium, sandstone, clay, and so on. rich deposits of minerals are used as sources of raw materials in power, metallurgical and chemical industries, production of building materials and in other important fields, which makes sichuan province an important industrial centre [1]. the province is also known for its coal production [8]. sichuan’s deposits of rare and rare-earth metals are bountiful. lithium and strontium, both of which are extracted in sichuan, play an important role in chinese economy. moreover, sichuan is famous for its gold and silver. sichuan province is located in the tropical zone and has abundant biological resources. the region is characterized by the diversity of landscapes (upland, mountains, hills, plains, etc) and climatic conditions, animal and plant life. sichuan is considered the second-large forest area in the country with its 7.46 million hectares of forests [2]. the variety of soil types make the region’s area suitable for cultivation of diverse crops. there are more than 1,400 rivers in sichuan, with the majority of rivers flowing through gorges, which turns them into massive sources of hydraulic power. the area of the basin of 343 rivers exceeds 500 sq. km. the total amount of water consumption in the rivers is about 300 billion cubic meters [3]. human capital in the region is to a great extent determined by the quality of education provided there. at the moment, the education system in the province comprises primary, secondary and higher education. there are also advanced training and retraining opportunities for adult learners. at the end of 2015, in sichuan there were 43  general higher education institutions with 180 thousand students and 10 thousand graduate students. there are 209 specialized high schools with 257  students; 4,375, general high schools with about 3  million students; 45 thousand elementary schools with 8 million pupils. compulsory education in sichuan includes nine years of training, which has allowed the region to eliminate illiteracy among its population [11]. higher education institutions are, for example, sichuan university, southwest scientific and technical university. five of the region’s higher education institutions participate in the state 211 project [1]. thus, a conclusion can be made that sichuan province has a significant potential regarding skilled labour. since 1982, there has been a considerable outflow of workforce from sichuan province to western regions of the country (see table 1). even though the rate of emigration varied at different times, the general trend persisted [8]. sichuan traditionally is the largest supplier of labor abroad. in 2000, the volume of signed contracts for contract works and labor services abroad was 345 million http://doi.org/10.15826/recon.2018.4.2.010 70 www.r-economy.ru r-ecomony, 2018, 4(2), 67–71 doi: 10.15826/recon.2018.4.2.010 online issn 2412-0731 us dollars. 10 million workers annually leave the province of sichuan. therefore, brain drain is one of the most serious problems that the province faces nowadays [1]. table 1 distribution of emigrants from china by province, % province 1982 1990 1995 2000 2015 central and south henan 2.82 0.25 2.42 1.12 2.28 hubei 4.65 0.66 0.89 0.89 0.86 hunan 4.16 1.11 0.72 0.66 0.57 guangdong 5.18 6.73 3.05 3.37 3.20 guangxi 1.01 0.37 0.64 0.47 0.36 hainan 0.25 0.10 0.10 south-west sichuan 8.04 1.44 2.46 1.50 1.13 guizhou 2.76 0.21 0.13 0.09 0.04 yunnan 1.39 0.78 0.25 29.0 3.00 tibet 0.04 0.13 0.02 0.02 industriаl inertia is ascribed to the persistent residence of an industry in a locаtion, after the initiаl locationаl factors hаve ceased to exist. sichuan province’s market size and its position in chinа, its ampleness of resоurces, the accessibility and modest labor cost, academic and production infrastruсture create favourable conditions for the development of a number of diverse industries. sichuаn province is ideally placed in the mаrket, itself being a practicable substitute for coаstal places as an enticing lоw expenses contribution site [9]. although the province’s functional setting can be defined as conducive regarding such factors as conditions for depositors, there is a need for further improvements in this respect that wоuld boost its attractiveness and stimulate the inflow of fdi. the past experience has shown that mоst foreign investors opt for the establishment of mаnufacturing enterprises in econоmic development zоnes that offer clear and precise rights to use the lаnd and opportunities for more productive handling of оperational threats. in the development of many sichuan’s econоmic development zоnes, a number of problems arise such as the lack of land suitable for construction and chinese land use/ownership laws, creating difficulties for operation of individual investors [2]. moreover, while sichuan is often described as a tempting market in the west of china, it has quite a long way to go in becoming one of the major economic centres to be able to compete with coastal provinces and enter world markets. in 2017, the volume of investment was nearly 2 trillion yuan. such rapid industrial development, undoubtedly, increases the number of jobs in the region [11]. as table 2 shows, siсhuan has abundant nаtural resourcеs and an advanced production sеctor. chengdu, the capital city of siсhuan province, is a vibrant commercial center. the province is one of china’s main agricultural regions growing rice, wheаt, rapeseed, citrus fruit, pеach, sugar cane, sweet potato and hеrbs. table 2 swot analysis of industrial factors strengths weaknesses well-functioning transportation system (railways, highways, roads, waterways, air lines) sichuan has a complex and varied topography with mountains and plateaus human capital socio-economic problems geographical location: no access to the ocean brain drain to the eastern part of china opportunities threats diversity of national economic policies. developed transportation system the province processes its own resources instead of selling them to other regions. sichuan is located at the crossroads of the silk road and the yangtze river economic belt attraction of highly qualified staff back to the province possible deterioration of transport system due to its inefficient use non-renewable resources impeded market access to eastern china brain drain to other regions conclusion our analysis of the key industrial factors that determine the socio-economic development of sichuan province has shown that in the current conditions, the region would benefit from the establishment of a special economic zone, which would allow it to attract new investors and increase the share of tax revenues to the regional budget. moreover, a special economic zone would ensure more balanced development of the region, enhance its competitiveness and business infrastructure, create new jobs and thus raise the living standards of the regional population [12]. to establish a special economic zone, the regional authorities need to build and/or reconstruct appropriate engineering, transport and social infrastructure; lower administrative barriers; simplify the bureaucratic procedures, creating single window clearance mechanisms; offer tax-and-tariff incentives and a flexible system of loans [1; 12]. http://doi.org/10.15826/recon.2018.4.2.010 r-ecomony, 2018, 4(2), 67–71 doi: 10.15826/recon.2018.4.2.010 71 www.r-economy.ru online issn 2412-0731 references 1. mcnally, c. a. (2014). sichuan: driving capitalist development westward. the china quarterly, 178, 426–447. doi: 10.1017/s0305741004000244. 2. sichuan, s. (2012). benchmarking fdi competitiveness in china’s sichuan province. the world bank group. retrieved from www.ipanet.net/snapshot_sichuan 3. goodman, d. s. g. (2010). the politics of the west: equality, nation-building, and colonization. provincial china, 7(2), 127–150. doi: 10.1080/1326761032000176096. 4.  gavrilov, z. g. (2012) regional economy. regional development: purposes, criterion and methods of management. moscow: yuniti-dana. 5. bhattarai, k. (2015) what factors decide the location of a manufacturing industry. insights online prelims test series, 15, 3–15. 6.  chen dongsheng (2013). open up the west and sustainable development. provincial china, 11, 254–257. 7.  bhattarai, k. & chen, n. (2014). rural urban income and consumption gaps across provinces of china, 1978–2008. advances in economics and business, 2(2), 70–77. doi: 10.13189/ aeb.2014.020202. 8. yang wenhua (2015). sichuan and the opening of china’s west. great western development, 32, 364–371. 9. zhang zhongwei (2015). emphasize large restricting. great western development, 32, 153–164. 10. zhou yongkag (2013). to discuss the new step forward. a strategic guide to great western development, 15, 138. 11. liang, z. & morooka, h. (2004). recent trends of emigration from china: 1982–2000. recent trends of emigration, 42(3), 145–164. doi: 10.1111/j.0020-7985.2004.00292.x. 12. musina, s. (2016) industrial parks as a factor of development of regions. molodoy ucheny, 4, 458–461. 13. yu., n., de roo, g., de jong, m. & storm, s. (2016) does the expansion of a motorway network lead to economic agglomeration? evidence from china. transport policy, 45, 218–227. doi: 10.1016/j.tranpol.2015.03.014. 14.  amiti, m. (1999). specialization patterns in europe. weltwirtschaftliches archiv, 135(4), 573–593. 15. rodrigue, j. p. (2016). transport systems. hofstra-geo, 20, 255–300. information about the authors oksana o. akhmetzianova – master’s student majoring in public management at harbin institute of technology; international coordinator of ekaterinburg regional branch russian union of young scientists (harbin, china); e-mail: oksanochka-star@mail.ru. irina d. turgel – doctor of science (economics), professor, ural federal university (19, mira st., 620002, ekaterinburg, russia); email: i.d.turgel@urfu.ru. http://doi.org/10.15826/recon.2018.4.2.010 http://doi.org/10.1017/s0305741004000244 http://doi.org/10.1080/1326761032000176096 http://doi.org/10.13189/aeb.2014.020202 http://doi.org/10.13189/aeb.2014.020202 http://doi.org/10.1111/j.0020-7985.2004.00292.x http://doi.org/10.1016/j.tranpol.2015.03.014 mailto:oksanochka-star@mail.ru j. kaczmarek –khubnaia r-economy vol. 3, issue 4, 2017 189 doi 10.15826/recon.2017.3.3.021 udc 332.02 j. kaczmarek –khubnaia institute of socio-economic geography and spatial management, adam mickiewicz university (poznań, poland; khubnaia@amu.edu.pl ) regional politics in post-socialist states. based on the analysis of georgia since the fall of the soviet union, the post-soviet countries have been undergoing general transformation processes. a change in state regime meant a complete reorganisation of political system. main obstacles for the development processes and structural changes were legislative chaos, rise of nationalism, growing sense of separateness of regional communities, and a tense internal situation, often resulting in armed conflicts. departure from centrally controlled economy, decentralisation of power and the subsequent reduction of the state care level has made the authorities (wanting to ensure sustainable development for all self-government units), start a development process of new regional policy framework. the aim of this article is characterisation of the regional policy of post-soviet states on the example of georgia. due to the specific nature of the historic conditions associated with the 70-year affiliation of the analysed country to the ussr, the author first refers to past regional policy framework, introduced by the soviet authorities (e.g. economic territorial divisions or regional specialism) as the starting point and the determinant of the present regional disparities. the author then presents the characteristics of the present georgian regional policy, in institutional and legal terms, by describing and evaluating its shaping process and the main documents defining key objectives (strategies, plans, projects, laws, et c.). due to a strong difference in development between the post-soviet states, caused by a different internal situation, international position (geopolitical position), economic potential and a degree of advancement in transformation processes, the analysis has been enriched by a comparison of regional policies of two former east bloc states, poland and georgia. keywords: regional politics; region, georgia; poland; post-communist, european union introduction the socio-economic processes, characteristic for former east bloc countries after the collapse of the ussr, are referred to as general transformation processes. the term is used to depict the broad spectrum of changes in systemic, economic and social areas. the abolition of party patronage resulted in the development of new ways of international and domestic functioning of the post-soviet states. the comprehensive restructuring process associated with systemic transformation in these countries, included changes in their regional structures [1]. on one side, there was a significant reduction in the role of central authority (reduced level of state care) in favour of decentralisation, resulting in emergence of self-governments with new and greater competences. on the other side, the change meant a significant raise in the level of local financial independence, which only deepened existing regional disparities. bagdziński and maik (1995) consider unemployment and spatial and functional conflicts the three main problems arising from decentralisation of power in transitional countries. it is important to note that the collapse of the ussr, especially in the caucasus region, resulted in the revival of sense of distinctiveness and separatism among regional communities. the dissolution of the soviet union, where ethnic and cultural differences were being deliberately obliterated, led to a revival of nationalism and separatist tendencies, deepening an already difficult situation of the former states. the decentralisation process called for the development of a new regional policy framework [2,3,1,4]. http://r-economy.ru/ mailto:khubnaia@amu.edu.pl j. kaczmarek –khubnaia r-economy vol. 3, issue 4, 2017 190 regional politics in the post-soviet countries can be seen as a reaction to existing disparities on the socioeconomic level of regional development. its goal is to ensure a decrease in the divisions that differentiate between the problematic, poorer regional units and the richer islands of prosperity. it is therefore important to conduct an in-depth analysis of the regional policy framework as it seems to be one of the key elements shaping the development processes of the regions [5]. the aim of this article is to introduce the regional policy system of georgia by means of analysis of its institutional and legal framework. considering the specific nature of historical determinants, the author has chosen the regional policy of the ussr as her starting point. this is due to the fact that it has been highly influential as far as the specialisms of the regions and their socio-economic level at the time of regaining independence are concerned. the research has been supplemented by a comparative analysis of regional politics of georgia and poland. even though both countries were parts of the east bloc, their development paths (since the 1990s) are very different. the difference can be attributed mainly to the countries’ geopolitical location, economic potential, dynamics and nature of development changes, and internal stability. another significant factor is poland's membership of the european union. regional politics in the soviet union already under the soviet regime, regional politics was associated with development through implementation of relevant programs and several years plans. the first comprehensive plan for economic development was the state commission for electrification of russia (goelro)1, which was meant as a demonstration of the government’s strategic approach to regional policy. in addition to its main objective of improving general access to electricity (especially in the european part of russia), it has divided the country's territory into economic zones, districts and regions. the main assumption of this division, was to determine new regions for which it was possible to specify common development objectives (mainly in the areas of industry, agriculture and transport). one of the major units resulting from the above division was the region of caucasus2 with a territory of the present-day georgia [6]. according to winiarski (1976), the main concepts of regional politics in the ussr were:  activation of poorly developed areas east of ural;  support for the economic development of asian republics;  economic integration of the republics and their regions. in addition to the division into large economic regions, lower-level units within the individual republics were established. in moscow publication, gruzinskaâ ssr : èkonomiko-geografičeskaâ harakteristika (1958), next to administrative regional division of the georgian ssr, the authors describe ten additional geoeconomic units; central (tbilisi), eastern (kakhetian), southern, eastern highlands, black sea, western, western highlands, abkhazian, adjarian and south ossetian. this division system was changed ten years later, though [7]. 1 the plan is regarded as a basis for economic potential of the ussr. its implementation positioned ussr on a second place in the world ranking for electricity production in 1947. and that despite the country’s difficult situation caused by the second world war [9]. 2 apart from the caucasus region, winiarski [6] also describes following regions: central, northern, southern, volga. ural, west-siberian and turkmen. http://r-economy.ru/ j. kaczmarek –khubnaia r-economy vol. 3, issue 4, 2017 191 fig 1. geo-economic regions of georgian ssr in 1958. source: own elaboration based on džavahišvili (1958) in 1972, in another publication, only eight geo-economic regions were mentioned. next to the previously mentioned autonomous units (abkhazian asrr, adrasan asrr and south ossetian autonomous oblast), the authors identified five new regions within the territory of the georgian ssr: middle-eastern, eastern, southern, middle-western and western [8]. this division was associated with the industry specialism of individual regions. for example, the middleeastern region was a home of steel industry (tbilisi-rustavi industrial district), abkhazia specialised in brown coal mining end the eastern region (kakheti and tusheti) was strictly an agricultural one. changes in the territorial-economic divisions were related to ongoing economic transformation, development of new industrial centres and cities as well as to the speciality boost within the existing units. interestingly, the seemingly artificial economic division of the georgian ssr had in fact, taken into account ethnic and cultural divisions of the country3. considering the nature of socio-economic transformations (economy industrialisation, agricultural collectivisation, regional specialism), it seems that the soviet classification of units (based on historical socio-economic territorial divisions) and related activities, have only strengthen the already existing diversity among the georgian regions. more than 70 years of constant development and implementation of new regional policies, have undoubtedly influenced the current state of the regions (specialism and socio-economic level) and, which follows, the objectives of today's regional politics aimed at reducing (mostly historically determined) disparities. regional politics of georgia present research describes two basic models of regional policy implementation. the first one, called interregional policy, refers to the actions taken by the state authorities concerning local governments. the second model, referred to as intraregional policy, is related to the activity of local governments that is 3 more about historic territorial and cultural divisions of georgian territory in [8,10,11]. http://r-economy.ru/ j. kaczmarek –khubnaia r-economy vol. 3, issue 4, 2017 192 focused on regional development. basing on this distinction, the first part of the following analysis, focuses on the legal basis for implementation of intraregional policy making regulating the level of regional empowerment and possibility of self-determination. [5; 3]. as part of systemic transformation, georgia carried out a number of structural reforms concerning among others, decentralisation of power. a decisive event that sped up a legislative process related to the functioning of local governments was mikhael saakashvili's victory in the 2004 election. in 2004, the government ratified the european charter of local self-government. in 2005, the parliament passed the organic law of georgia on local self-government, and in 2006 the law on the budgets of local selfgovernment unit [10]. despite a widespread recognition of the territorial self-government act as a positive step towards decentralisation of power, some remained sceptic criticising its high level of consolidation (a significant reduction in the number of the lowest level units), strong financial dependence on the central authority, and relatively low level of political autonomy. in february 2014, shortly after the georgian dream party (previously an opposition party) had won the presidential and local elections, a new law, local self-government code (organic law of georgia) was introduced. unfortunately, the reform did not yield the required results. the framework of fiscal decentralisation still remains incomplete and its implementation has been neglected. additionally, the level of social participation is low and the central government imposes too many requirements on local governments (e.g. number of officials). one can therefore assume that the process of georgia's systemic transformation in the area of decentralisation is still ongoing and that the legislative framework needs modification (12, 13, 14, 15, 10). an institutional framework is one of the most important elements for developing and executing a regional policy. in 2009, the government established the ministry of regional development and infrastructure of georgia, as executive authority and a higher level agency in the following areas: 1) generation of objectives and coordination of development policy, including the regional system development and management; 2) development and implementation of a uniform system concerning state policy on infrastructure development; 3) ensuring a general access to drinking water, including implementation of water supply systems; 4) distribution and management of waste disposals facilities [16]. the authorities have introduced a number of new strategies, plans and projects to ensure sustainable development of state and territorial self-government units. the planning process for the regional development began with an introduction of the state strategy for regional development 2010-2017. in this document, the ministry has presented the results of a detailed analysis of existing problems at local and regional level. once approved, the government developed and adopted the 2011-2014 action plan with an objective to create a suitable development strategy for each region by 2013 [17]. presently, the main strategic document defining the regional policy framework is ‘the regional development program of georgia for 2015-2017’. its main objectives are set out in relation to ‘georgia 2020’ nationwide strategy plan. the program contains specific objectives (operational priorities) for all entities. at the lower level of the national policy planning are the regional strategies for the years 2014-2021, developed individually for each regional unit (geo.mkhare) [16]. it is worth noting that, apart from the three documents: national strategy, self-governments programmes and individual strategies for each region, the authorities have failed to adopt any other law regarding regional policy making. the only act (statute), indirectly referring to regional development and regional policy is the so-called mountain law. it can be seen as a sort of response to the needs of the inhabitants of one of the most problematic parts of the georgian state, the high mountainous area. http://r-economy.ru/ j. kaczmarek –khubnaia r-economy vol. 3, issue 4, 2017 193 a comparison of regional politics of poland and georgia when analysing the legislative framework and functioning of georgia's regional politics, it is necessary to take into account the development path and advancement level of transformation processes. particularly the ones concerning competences, fiscal decentralisation and regional policy planning. to clearly present the characteristics of the georgian political system, the author has chosen to compare it to the polish one. both countries were members of the eastern bloc with georgia, a former soviet republic, being influenced by soviet policy planning to a greater extent than poland, a former ussr satellite state with greater possibilities of self-determination. both countries regained their independence in the 1990s, but the pace of their socio-economic transformation is very different. this is mainly due to the specificity of the factors driving the process. in georgia, the main deterrents are separatist tendencies, armed conflicts and political instability. these elements are seen as main reasons for development disparities between the two countries. these differences are confirmed by rankings related to economic growth, quality of life or advancement of transformation processes. for example, in 2015 poland was ranked 36th in the human development index, while georgia was 70th 4. in 2016, the transformation index (bti) for poland was 9.23 (5th place in the overall ranking) and the country’s political system was characterised as democracy in consolidation, economically developed and highly advanced in transformational processes (bti, 2016). for georgia the index was 6,31 (45th place). on the basis of the main indicator and its components, transformational processes were described as limited and georgia’s political system was categorised as one of defective democracy. it was further emphasised that economic transformation has significant functional flaws that still need to be addressed [19]5. considering regional policy framework of both countries, it should be noted that, unlike poland, georgia has still to introduce a law on the conduct of regional development policy6. it is also important to mention the factors determining and influencing the functioning of the regional policy system are level and scope of power decentralisation. in the case of georgia, the above process (also regarding the development of relevant legislation) is still ongoing. in contrast, polish legislation clearly specifies not only the competences of regional governments but also provides funding regulations for regional plans and programmes. another factor adding to the already significant difference between the two countries is poland's membership of the european union. the negotiation process has, to some extent, forced the authorities to re-evaluate existing regional policy framework and adapt it to western standards (as evidenced by the legal acts adopted during the transitional period, eg the 2000 regional development assistance act). one of the benefits of poland’s membership of ue is the financial support for the country's development from the preaccession programs (since 2000), the structural and the cohesion funds [5]. georgia has been given a partnership status and became a potential candidate for eu membership in 2010. the socio-economic transformation process necessary for the achievement of the eu required standards, is much less advanced than in the case of poland (eu member since 2004). a facilitating factor in the development process is, undoubtfully, georgia’s membership of the eastern partnership; more than 100 million euros are transferred each year to georgia for projects concerning (among others) management, education and security. poland has been actively supporting the development of georgia, as can be witnessed by numerous projects such as ‘strengthening the efficiency of georgia's public administration in the field of regional and european policy’. since 2004, the country has been recognised by the polish authorities as one of the priority beneficiaries of developmental assistance for regional and local administration [20]. conclusion since regaining its independence, georgia has been undergoing systemic transformation, which includes decentralisation of power. new allocation of competences and the financial independence of territorial units created the need for a new regional policy framework. it is worth noting that (like in most post-soviet states) 4 http://hdr.undp.org/en/content/human-development-index-hdi 5 https://www.bti-project.org/en/index/status-index/ 6 poland adopted a regional policy law in december 2006. http://r-economy.ru/ j. kaczmarek –khubnaia r-economy vol. 3, issue 4, 2017 194 the system used in the times of ussr was an important shaping factor and its influence is still visible in the specialisms and the socio-economic level of the regions today. acknowledging the separatist tendencies of some regions (assigning autonomous status to selected units), development of economic regions and their specialisations, as well as numerous actions undertaken by the soviet authorities to establish and strengthen the (previously described) territorial and administrative division, have only strengthened the strong diversity among the individual regional units. the departure from the centrally controlled economy and the regaining of independence resulted in a new, more independent way of regional functioning, which, in accordance with the principle of capitalism, began to compete with each other. it is worth noting that the current objectives of georgian regional policy are being largely determined by deepening socio-economic disparities between the regional units, a problem which is, to a large extent, historically determined. the analysis of georgia's regional policy system shows that since the 1990s, the country has been gradually changing and is now getting closer to western management standards. the positive developments that confirm this trend are among others, the ratification of the european charter of local self-government, establishment of basic institutional system (e.g. the ministry of regional development and infrastructure of georgia), and the introduction of multiple strategies, plans and projects aimed at ensuring sustainable development and minimising the disparities between regions. apart from listing the positive aspects of the transformation of the regional policy system, the author also describes the biggest obstacles to its further development. first, despite the introduction of the local government act and its subsequent changes, the issue of decentralisation of power remains unresolved, the aspect of fiscal decentralisation in particular. secondly, the country has still not introduced a legal act (law), defining the principles of regional policy. it can therefore be concluded that the current system requires further changes, especially in the areas of competence allocation, and financing the study has been supplemented by a comparative analysis of regional policies of poland and georgia. although it would seem that common historical determinants (belonging to the so-called eastern bloc) should make the present political, social and economic situation of both countries similar, the indicators for level of advancement of political and economic transformation processes as well as for quality of life indicate that the two countries differ significantly. the analysis has shown that the dissimilarities can also be seen regarding the issue of decentralisation of power, regional policy, and related legislative regulations. before joining the european union, as per the pre-accession requirements, poland has completely transformed its national and regional political system. georgia, currently a candidate for membership of the european union, is still undergoing transformation and the degree of modification of its regional policy system and adapting it to western standards is much lower than in the case of poland (as evidenced by the absence of a governing law defining the principles of regional policy making, or by the ambiguity and lack of transparency of legal acts concerning the activities of local self-governments). importantly, as far as direction of regional development and future regional policy are concerned, georgia is a member of the eastern partnership. one of the countries actively supporting georgia’s development is poland, one of the most modern of the former eastern bloc members. the country is supporting and even accelerating the positive internal changes in georgia by offering advice and sharing its successful transformation experience. references 1. gorzelak, g. (1995). transformacja systemowa a restrukturyzacja regionalna. warszawa: uniwersytet warszawski, katedra unesco trwałego rozwoju. 2. bagdziński, s.l, & maik, m., potoczek, a. (1995). polityka rozwoju regionalnego i lokalnego w okresie transformacji systemowej. toruń: umk. 3. smętkowski, m. (2013). rozwój regionów i polityka regionalna w krajach europy środkowo-wschodniej w okresie transformacji i globalizacji. warszawa: wydawnictwo naukowe scholar. 4. artobolevskiy, s.s. (2006). regional policy in europe. london; new york: routledge. 5. churski, p. (2008). czynniki rozwoju regionalnego i polityka regionalna w polsce w okresie integracji z unią europejską. poznań: wydawnictwo naukowe uam. 6. winiarski, b. (1976). polityka regionalna. warszawa: państwowe wydawnictwo ekonomiczne. http://r-economy.ru/ j. kaczmarek –khubnaia r-economy vol. 3, issue 4, 2017 195 7. džavahišvili, a.n (red.), râzancev, s.n.(red.) (1958). gruzinskaâ ssr : èkonomiko-geografičeskaâ harakteristika. moskva : gosudarstvennoe izdatel'stvo geografičeskoj literatury. 8. dawitaj, f.f.(red.). (1972). związek radziecki. gruzja. warszawa: wydawnictwo pwn. 9. olszowiec, p. (2011). energetyka rosji: skutek odwrotny od zamierzonego? energia gigawat, (no. 11), source: http://www.miedzynarodowa-energetyka.cire.pl/pliki/2/energetyka_rosji_skutek_odwrotny_od_zamierzonego.pdf 10. mądry, c., kaczmarek-khubnaia j. (2016). historical determinants of regional divisions of georgia and their implications for territorial governance. quaestiones geographicae 35(2), 131-139 11. kaczmarek – khubnaia, j. (2016). zróżnicowanie społecznogospodarcze gruzji. [in:] współczesne problemy i kierunki badawcze w geografii. vol. 4, franczak p., krąż p., liro j., liro m., listwanfranczak k. (red.), kraków: instytut geografii i gospodarki przestrzennej uniwersytetu jagiellońskiego, 139-154. 12. skorupska, a., zasztowt, k. (2014). georgia’s local government reform: how to escape from the soviet past (and how poland can help). policy paper pism 4(87). source: https://www.pism.pl/files/?id_plik=16394 13. ti georgia (2014). the new local self-government code: overview of the main novelties. retrieved from http://www.transparency.ge/en/blog/new-local-self-government-code-overview-main-novelties 14. matusiak marek (2014). wybory lokalne w gruzji. retrieved from https://www.osw.waw.pl/pl/publikacje/analizy/2014-0625/wybory-lokalne-w-gruzji 15. skorupska adriana (2013). local‐government 
reform 
in
 georgia. retrieved from https://aer.eu/local%e2%80%90government-%e2%80%a9reform-%e2%80%a9in%e2%80%a9-georgia/ 16. georgian news (2017). retrieved from http://www.mrdi.gov.ge/?page=main&lang=2 17. gruzja (2014). retrieved from https://www.polskapomoc.gov.pl/gruzja,17.html author kaczmarek-khubnaia julia – m.sc, phd student in the institute of socio-economic geography and spatial management, faculty of geographical and geological sciences, adam mickiewicz university in poznan (krygowskiego 10, 61–680 poznań, poland, e-mail: khubnaia@amu.edu.pl ) http://r-economy.ru/ mailto:khubnaia@amu.edu.pl 24 www.r-economy.ru r-ecomony, 2018, 4(1), 24–29 doi: 10.15826/recon.2018.4.1.004 online issn 2412-0731 original paper for citation vujko, a., dimitrić, d., gajić, t., penić, m. & gagić, s. (2018) development potential of rural tourism (the case of tešnjarske večeri festival). r-economy, 4(1), 24–29. doi: 10.15826/recon.2018.4.1.004 for citation вуйко, а., димитрич, д., гайич, т., пенич, м., гагич, c. (2018) потенциал развития сельского туризма (пример фестиваля «tešnjarske večeri»). r-economy, 4(1), 24–29. doi: 10.15826/recon.2018.4.1.004 doi: 10.15826/recon.2018.4.1.004 development potential of rural tourism (the case of teš njarske večeri festival) aleksandra vujkoa, dragana dimitrićb, tamara gajića, mirjana penićc, snježana gagićd a novi sad business school, novi sad, serbia; e-mail: aleksandravujko@yahoo.com b faculty of science, novi sad, serbia; e-mail: tamara.gajic.1977@yahoo.com c fife class hotels & spa, istrabez turizem, portorož, slovenia; e-mail: sadranel@gmail.com d university of business studies, faculty of tourism and hotel management (fth), banja luka, bosnia and herzegovina; e-mail: gagicsnjeza@yahoo.com abstract rural tourism is a very broad concept which includes not only holidays in the countryside a range of other tourist activities in rural areas, such as traditional festivals. tourist festivals are devoted to different local products which are famous in rural parts of serbia. some of the most popular serbian festivals are the grape festivals in sremski karlovci, erdevik, banoštor, irig, erdevik, vršac, župa, palić, aleksandrovac, hajdukovo, smederevo, topola; plum days in osečina and koštunići; cabbage days in futog, barbeque in leskovac; baconddays in kačarevo; ham days in mačkat; golden pot of danube in petrovaradin, apatin; mushroom days in fruška gora, valjevo and divčibare, medical herbs days in soko banja; bee days in zaječar. this paper deals with the development potential of rural areas associated with these festivals by analyzing the case of tešnjarske večeri. this festival provides a diverse cultural and ethnographic entertaining program, combining visual and performing arts, and celebrates the vibrant life of the local community. keywords rural tourism, festival, countryside, development, tešnjarske večeri, serbia потенциал развития сельского туризма (пример фестиваля «teš njarske večeri ») а. вуйкоa, д. димитричb, т. гайичa, м. пеничc, c. гагичd a бизнес-школа нови-сада, нови-сад, сербия; e-mail: aleksandravujko@yahoo.com b нови-садский университет, нови-сад, сербия; e-mail: tamara.gajic.1977@yahoo.com c отель lifeclass hotels & spa, порторож, словения; e-mail: sadranel@gmail.com d университет бизнес-исследований, факультет туризма и гостиничного дела, баня лука, босния и герцеговина; e-mail: gagicsnjeza@yahoo.com резюме сельский туризм – очень широкая концепция, которая включает в себя не только отдых в сельской местности, но и ряд других туристических мероприятий в сельской местности, таких как традиционные фестивали. туристические фестивали посвящены различным местным продуктам, которые известны в сельских районах сербии. некоторые из самых популярных сербских фестивалей – винные фестивали в сремских карловцах, эрдевике, баношторе, ириге, эрдевике, вршаце, жупе, паличе, александроваце, хайдуково, смедерево, тополе; дни сливы в осечине и коштуничи; дни капусты в футоге, барбекю в лесковаце; дни бекона в качарево; ветряные дни в мачкате; «золотой горшок дуная» в петроварадине, апатин; грибные дни в фрушка-горе, вальево и дивцибаре, дни лечебных трав в соко-баня; пчелиные дни в заечаре. в данной статье рассматривается потенциал развития сельских районов, связанных с этими фестивалями на примере «tešnjarske večeri». этот фестиваль представляет собой разнообразную культурно-этнографическую развлекательную программу, сочетающую визуальное и исполнительское искусство и прославляет яркую жизнь местного сообщества. ключевые слова сельский туризм, фестиваль, сельская местность, развитие, tešnjarske večeri, сербия   https://doi.org/10.15826/recon.2018.4.1.004 http://doi.org/10.15826/recon.2018.4.1.004 mailto:aleksandravujko@yahoo.com r-ecomony, 2018, 4(1), 24–29 doi: 10.15826/recon.2018.4.1.004 25 www.r-economy.ru online issn 2412-0731 introduction according to vujko et al. [1], rural tourism is an important factor of multifunctional rural development, which has been confirmed by numerous theoretical and empirical studies [2; 3]. rural tourism in serbia is a new phenomenon [1;  4]. rural tourism, like other types of tourism, may have a significant environmental, economic, and social impact on local communities. according to petrović et al. [4], the effect of rural tourism on attitudes and behavior of local residents has been addressed in several theoretical and research papers in the last ten years [5–12]. these studies prove that rural tourism might be an important element in the positive and negative changes in the local rural area and that it might heavily affect the local residents. rural tourism represents tourism in rural locations and themed villages, which also includes participation in various recreation and leisure activities, festivals, handicraft fairs, and so on. therefore, rural tourism can be seen as a way of solving the problem of the declining profitability potential of the local agricultural industry and as a source of additional income for local enterprises. according to vujko et al. [1], rural tourism encompasses all tourism activities carried out in rural areas. rural tourism has many forms, which include the following: – tourism in rural households; – hunting and fishing; – eco-tourism; – sports and recreation; – residential tourism (holiday homes); – educational tourism; – gastronomic tourism, festivals and events; – cultural tourism. thus, we can identify the basic characteristics of rural tourism: first and foremost, it involves rural areas and provides people with an opportunity to be in close contact with nature and to learn about the cultural heritage, traditional societies and «traditional» practices. rural tourism presents a complex of rural environments, economies, histories and locations. most of the revenue generated through rural tourism is used to support the local community and enrich their livelihood. for our study we have chosen event tešnjarske večeri (tešnjar evenings), held in the city of valjevo in the old quarter tešnjar, which is an architectural ambience that is particularly attractive for tourists. the organizers of this event are the municipal assembly of valjevo and cultural and education community of valjevo. tourist event tešnjarske večeri has been held since 1987 and is a traditional event with a diverse cultural program. the municipal assembly describes evenings of tešnjar as a cultural festival with a diverse program including films, theatre and music performances, meetings of writers, publishers, and booksellers. the event is held at several locations: the three key locations are tešnjar, summer stage of the kolubara, and the plateau of the centre for culture. the survey research was done at these three locations as well as on the marble bridge over the summer stage of kolubara, kneza miloša street and vojvoda mišić square. methodology the basic method of our research is a sociological survey, which is a method typically used for studies in cultural geography and event tourism (direct observation and semi-structured interview with the organizers and participants of the festival). during the event of 2016, a survey was done on a random sample of 276 visitors. it was done during the six days of the event. this period was chosen because in these days the event is attended by the largest number of visitors. the survey was anonymous. one of the methods of data analysis was pearson’s chi-square test, which is used to determine whether the obtained (observed) frequency (answers of respondents according to the gender and age structure) deviate from the expected frequencies. the test shows whether there is a connection between these two groups and the likelihood of this connection. we assumed that there would be no differences in responses according to the gender and age of our respodents. in order to detect any differences in the responses we are using a significance level of p < 0.05. result and discussion the survey (table 1) included 126 men (45.7%) and 150 women (54.3%). regarding the age structure of the visitors (table 2), most of them (27.5%) were under 18; 22.8%, from 61 to 70; 1.8%, over 71 (1.8%); from 51 to 60, 7.2%; and from 31 to 40, 9.8%. table 1 gender of visitors gender frequency valid percentage valid male 126 45,7 female 150 54,3 total 276 100 https://doi.org/doi.org/10.15826/recon.2018.4.1.004 26 www.r-economy.ru r-ecomony, 2018, 4(1), 24–29 doi: 10.15826/recon.2018.4.1.004 online issn 2412-0731 table 2 age of visitors age frequency valid percentage valid under 18 76 27.5 19–30 43 15.6 31–40 27 9.8 41–50 42 15.2 51–60 20 7.2 61–70 63 22.8 over 71 5 1.8 total 276 100 in order to detect the differences in the responses, the results are shown depending on the gender and age structure of the participants and the statistically significant difference is taken at the level of p < 0.05. table 3 shows that the majority of visitors – 73 (26.4%) – spent one day at the event. 56 (20.3%) visitors were at the event for six days. not surprisingly, the smallest number of visitors were those who spent at the event 7 days or more than 7 days – 4.3% and 3.6% respectively. table 4 illustrates that young people under the age of 18 mostly chose a one-day visit. visitors from 19 to 30 usually spent two days. visitors from 31 to 40 were there for three days. it is interesting that the smallest number of people attended the event for more than seven days, that is, they came to the festival every day. table 3 number of days days frequency valid percentage valid 1 73 26.4 2 43 15.6 3 27 9.8 4 38 13.8 5 17 6.2 6 56 20.3 7 12 4.3 more than 7 days 10 3.6 total 276 100 interestingly, there were no statistically significant differences in the responses of the people of both genders and age structure p = 0.000 (table 5). table 5 pearson chi-square test value df statistical significance (p) pearson chi-square test 1419.787 42 0.000 as far as the gender is concerned, it should be noted that twice as many female respondents as men came on a one-day visit – 53 (19.2%). table 6 demonstrates that these respondents were under the age of 18. several female respondents came to visit for several days and 9 (3.3%) came to the festival every day. table 4 number of days according to age structure number of days structure of visitors by age total under 18 19–30 31–40 41–50 51–60 61–70 over 71 1 count 73 0 0 0 0 0 0 73 % 26.4 0 0 0 0 0 0 26.4 2 count 0 43 0 0 0 0 0 43 % 0 15.6 0 0 0 0 0 15.6 3 count 0 0 27 0 0 0 0 27 % 0 0 9.8 0 0 0 0 9.8 4 count 0 0 0 38 0 0 0 38 % 0 0 0 13.8 0 0 0 13.8 5 count 0 0 0 0 17 0 0 17 % 0 0 0 0 6.2 0% 0 6.2 6 count 0 0 0 0 0 56 0 56 % 0 0 0 0 0 20.3 0 20.3 7 count 0 0 0 0 1 6 5 12 % 0 0 0 0 0.4 2.2 1.8 4.3 > 7 count 3 0 0 4 2 1 0 10 % 1.1 0 0 1.4 0.7 0.4 0 3.6 total count 76 43 27 42 20 63 5 276 % 27.5 15.6 9.8 15.2 7.2 22.8 1.8 100 https://doi.org/doi.org/10.15826/recon.2018.4.1.004 r-ecomony, 2018, 4(1), 24–29 doi: 10.15826/recon.2018.4.1.004 27 www.r-economy.ru online issn 2412-0731 table 6 number of days according to gender days gender total male female 1 count 20 53 73 % 7.2 19.2 26.4 2 count 30 13 43 % 10.9 4.7 15.6 3 count 10 17 27 % 3.6 6.2 9.8 4 count 19 19 38 % 6.9 6.9 13.8 5 count 10 7 17 % 3.6 2.5 6.2 6 count 27 29 56 % 9.8 10.5 20.3 7 count 9 3 12 % 3.3 1.1 4.3 more than 7 days count 1 9 10 % 0.4 3.3 3.6 total count 126 150 276 % 45.7 54.3 100 interestingly enough, there were no statistically significant differences in the responses of the people of both genders and age structure p = 0.000 (table 7). table 7 pearson chi-square test value df statistical significance (p) pearson chi-square test 31.606 7 0.000 the largest number of visitors (table 8) found out about the event from the radio and television – these were 105 people (38.0%) or more than a third of all the visitors; 63 (22.8%) visitors were told by friends and family; 51 (18.5%), from the advertising materials (e.g. brochures and leaflets); 47 (17.0%), from the internet. the conclusion is that visitors are well informe and actively use all the available sources of information. table 8 sources of information information source frequency valid percentage valid radio and tv 105 38,0 prospectus 51 18,5 family and friends 63 22,8 internet 47 17,0 other 10 3,6 total 276 100,0 by looking at table 9, we can conclude that the younger population (under 18) mostly found about the festival from family and friends – 33 (12.0%). it can be assumed that it was their friends and relatives who recommended the respondents to participate. the majority of those who heard about the festival used radio and television programs. most of these people were 61 to 71 years old – 54 respondents (19.6%). two equal groups of people have found out about the event on the internet: these are young people and those aged between 41 and 50, each of the groups consisting of 13 people or 4.7%. interestingly, there were no statistically significant differences in the responses of people of both genders and age structure p = 0.000 (table 10). table 9 preferred sources of information according to the age structure sources of information structure of visitors by age total under 18 19–30 31–40 41–50 51–60 61–70 over 71 radio and tv count 14 22 7 4 4 54 0 105 % 5.1 8.0 2.5 1.4 1.4 19.6 0 38.0 advertising materials count 16 5 16 13 1 0 0 51 % 5.8 1.8 5.8 4.7 0.4 0 0 18.5 family and friends count 33 13 4 12 1 0 0 63 % 12.0 4.7 1.4 4.3 0.4 0 0 22.8 internet count 13 3 0 13 9 4 5 47 % 4.7 1.1 0 4.7 3.3 1.4 1.8 17.0 other count 0 0 0 0 5 5 0 10 % 0 0 0 0 1.8 1.8 0 3.6 total count 76 43 27 42 20 63 5 276 % 27.5 15.6 9.8 15.2 7.2 22.8 1.8 100 https://doi.org/doi.org/10.15826/recon.2018.4.1.004 28 www.r-economy.ru r-ecomony, 2018, 4(1), 24–29 doi: 10.15826/recon.2018.4.1.004 online issn 2412-0731 table 10 pearson chi-square test value df statistical significance (p) pearson chi-square test 220.472 24 0.000 table 11 shows that most men – 78 (28.3%) – found out about the festival on the radio and television. most women received the information from advertising materials – 47 (17.0%). it is assumed that considerably more women than men read leaflets and brochures. a lot of women also heard about the event from their friends and relatives – 43 (15.6%). as for the internet, both sexes were equally represented. table 11 preferred sources of information according to the gender sources of information gender total male female radio and tv count 78 27 105 % 28.3 9.8 38.0 advertising materials count 4 47 51 % 1.4 17.0 18.5 family and friends count 20 43 63 % 7.2 15.6 22.8 internet count 24 23 47 % 8.7 8.3 17.0 other count 0 10 10 % 0 3.6 3.6 total count 126 150 276 % 45.7 54.3 100 there were no statistically significant differences in the responses of people of both genders and age structure p = 0.000 (table 12). table 12 pearson chi-square test value df statistical significance (p) pearson chi-square test 77.947 4 0.000 conclusion serbia is a country with respect for traditional values, rich cultural heritage and pristine natural environment. therefore, this country has a great potential for the development of rural tourism. there is a variety of rural areas in serbia with different economic, socio-cultural and demographic characteristics. there are, however, a number of problems that impede efficient development of rural tourism: for example, the lack of knowledge about the new approaches to the development of rural economy; the lack of institutional framework (especially legislation) which would ensure the coordinating role of the state and greater involvement of local authorities into rural development; underdeveloped infrastructure; inadequate production and ownership structure; inadequate diversification of activities; and the dominance of the sectoral police [13; 14]. to be competitive on the market, rural destinations must meet the highest standards of quality to satisfy the needs of tourists and to ensure their loyalty. tourists should be encouraged to return to these places again and again and to recommend them to their friends and relatives. this is particularly true of foreign tourists, who have already accumulated considerable travel experience and are seeking the highest quality of hospitality and tourism [15]. customer loyalty is directly related to word-of-mouth communication but we should not underestimate other sources of information such as the media, good advertising materials, and the internet. local authorities play the key role in developing the potential of rural areas. in the past, they mostly focused on construction or maintenance of the infrastructure facilities and the improvement of social and health care. nowadays, they need to invest more funds and effort into the development of rural tourism, organization of various rural festivals and the creation of institutions that would represent the interests of agricultural producers. the authorities should also provide sufficient support to local farmers, for example, through subsidies, educational schemes, awareness raising measures, facilitated administrative procedures, interest-free loans, and so on. all these activities are important for the development of rural tourism. rural tourism provides opportunities which can be used to devise a balanced local and regional strategy ensuring cooperation of a wide range of stakeholders. effective partnerships between the public and the private sectors can serve as the basis for sustainable development. innovations often come from the private sector, that is, from those who live and work in that area. in order to turn tešnjarske večeri into a largescale tourist event, better marketing strategies are required. to make this event more economically profitable it is also recommended to provide a wider range of souvenirs for sale representing the traditional arts and crafts. https://doi.org/doi.org/10.15826/recon.2018.4.1.004 r-ecomony, 2018, 4(1), 24–29 doi: 10.15826/recon.2018.4.1.004 29 www.r-economy.ru online issn 2412-0731 references 1. vujko, a., gajić, t., dragosavac, m., maksimović, b. & mrkša, m. 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(2014). the government policy impact on economic development of tourism. ekonomika poljoprivrede, 61(3), 789–804. information about the authors aleksandra vujko – ph.d. professor, novi sad business school (vladimira perića valtera 4, 21000 novi sad); email: aleksandravujko@yahoo.com. dragana dimitric – ph.d. research associate, faculty of science (trg dositeja obradovica, 21000 novi sad); email: sadranel@gmail.com. tamara gajic – ph.d. professor, novi sad business school (vladimira perića valtera 4, 21000 novi sad); email: tamara.gajic.1977@yahoo.com. mirjana penić – ph.d. f&b manager, fife class hotels & spa, istrabez turizem (portorož, slovenia); email: penicns@yahoo.com. snježana gagić – ph.d. university of business studies, faculty of tourism and hotel management (fth) (banja luka, bosnia and herzegovina); email: gagicsnjeza@yahoo.com. https://doi.org/doi.org/10.15826/recon.2018.4.1.004 http://doi.org/10.1016/s0261-5177(00)00004-2 http://doi.org/10.24193/tras.2017.0009 http://doi.org/10.1016/j.annals.2005.03.001 http://doi.org/10.1016/j.annals.2005.03.001 http://doi.org/10.1177/0047287505274651 https://www.nrs.fs.fed.us/pubs/gtr/gtr_nrs-p-14/54-wang-p-14.pdf https://www.nrs.fs.fed.us/pubs/gtr/gtr_nrs-p-14/54-wang-p-14.pdf http://doi.org/10.3986/ags54406 http://doi.org/10.3986/ags.747 http://doi.org/10.22190/teme1702475v http://doi.org/10.17072/2218-9173-2017-2-253-268 r-ecomony, 2018, 4(2), 41–45 doi: 10.15826/recon.2018.4.2.006 41 www.r-economy.ru online issn 2412-0731 original paper for citation kiseleva, p. s. (2018) regional inflation in russia and ways of controlling it. r-economy, 4(2), 41–45. doi: 10.15826/recon.2018.4.2.006 for citation киселёва, п. с. (2018) инфляция в регионах россии и пути её контроля. r-economy, 4(2), 41–45. doi: 10.15826/recon.2018.4.2.006 doi 10.15826/recon.2018.4.2.006 regional inflation in russia and ways of controlling it polina s. kiseleva ural federal university, ekaterinburg, russia; e-mail: p.s.kiseleva@urfu.ru abstract the article focuses on regional inflation in russia, showing that there are independent regional factors shaping inflation and that there are considerable discrepancies between the levels of regional and national inflation. there is a need for more effective anti-inflationary policy to ensure stable social and economic development of the country and its regions. the problem, however, is that the instruments of anti-inflationary policy targeted at one type of inflation may act as triggers for another type of inflation. therefore, for a successful anti-inflationary policy we must first identify the factors that contribute to the development of inflation. otherwise, the anti-inflation measures may cause a rise in prices rather than help the government maintain them at a lower level. we carried out correlation analysis of the interrelation between the consumer price index and inflation rates over the past few years and found that the cost-related factors play a key role in the inflationary processes in russia and its regions. therefore, a conclusion was made that monetary methods alone are ineffective to control inflation and recommendations were given for improving regional anti-inflationary policies. keywords inflation, regional inflation, cost factors, natural monopoly, anti-inflationary policy инфляция в регионах россии и пути её контроля п. с. киселёва уральский федеральный университет, екатеринбург, россия; e-mail: p.s.kiseleva@urfu.ru резюме статья фокусируется на региональной инфляции в россии и демонстрирует, что существуют независимые региональные факторы, формирующие инфляцию, и что существуют значительные расхождения между уровнями региональной и общенациональной инфляции. существует необходимость в более эффективной антиинфляционной политике для обеспечения стабильного социально-экономического развития страны и ее регионов. политика усложняется тем, что инструменты антиинфляционной политики, ориентированные на один тип инфляции, могут вызывать другой тип инфляции. поэтому для успешной антиинфляционной политики вначале необходимо определить факторы, которые способствуют развитию инфляции. иначе антиинфляционные меры могут привести к росту цен, а не к их удержанию на низком уровне. в статье был проведен корреляционный анализ взаимосвязи между индексом потребительских цен и темпами инфляции за последние несколько лет и было обнаружено, что факторы, связанные с затратами, играют ключевую роль в инфляционных процессах в россии и ее регионах. поэтому был сделан вывод о том, что одни лишь денежные методы неэффективны для борьбы с инфляцией, и были даны рекомендации по совершенствованию региональной антиинфляционной политики. ключевые слова инфляция, региональная инфляция, факторы издержек, естественная монополия, антиинфляционная политика introduction inflation is one of the most acute problems in russia as it affects the national economy as a whole and individual economic entities. the level of inflation, therefore, is one of the key macroeconomic indicators since it has a direct impact on the cost and quality of life in the country. inflation makes calculations more complex and, therefore, leads to mistakes and inaccuracies in financial planning of households and business entities [1]. even a moderate 5% annual inflation is likely to result in doubling of prices in about 14 years. with the creeping inflation of 11.35%, typical of russia in 2014, the overall price level http://doi.org/10.15826/recon.2018.4.2.006 http://doi.org/10.15826/recon.2018.4.2.006 42 www.r-economy.ru r-ecomony, 2018, 4(2), 41–45 doi: 10.15826/recon.2018.4.2.006 online issn 2412-0731 will increase more than 4.5 times in the same period while the inflation which reached the level of 13% in 2015 will lead to a six-time increase in the general price level1. the above-described situation makes saving and implementing long-term investment projects particularly difficult. the study of regional inflation reveals discrepancies in the rates of inflation across russian regions. we need to identify those regional factors that affect inflation in order to avoid inflationary outbursts in regions and develop an efficient anti-inflationary policy. types and characteristics of regional inflation in russia social and economic development of russian regions is increasingly uneven and there are considerable discrepancies between inflation rates in different regions [2]. in particular, in 2017, the highest level of inflation was recorded in the republic of sakha (yakutia) – 4.44%, and the lowest – in dagestan, 1.12%. in 2016, the highest inflation was in the khanty-mansiysk autonomous district (yugra) – 8.52%, and the lowest, in ingushetia – 2.6%2. even more significant differentiation of inflation rates was observed in 2015. at the end of 2015, the highest inflation was found in the republic of crimea – 27.64% (26.4% in the crimean federal district), which is more than twice as high as the federal inflation rate (12.91%)3. it should be noted that in the case of the crimea, high inflation stems from the fundamental changes in the region’s economy, in particular, its integration into the larger economic space. as a result, the crimea turned into another subsidized region of russia. in 2016, the crimea project was allocated over 40 billion rubles worth of gratuitous revenue from the federal budget, including the subsidies exceeding 20 billion rubles intended to equalize the budgetary security4. regarding the amount of gratuitous payments, the crimea ranks fourth among 1 our calculations are based on the data provided by the official website of the federal state statistics service. retrieved from http://www.gks.ru. 2 our calculations are based on the data provided by the official website of the federal state statistics service. retrieved from http://www.gks.ru. 3 our calculations are based on the data provided by the official website of the federal state statistics service. retrieved from http://www.gks.ru. 4 official website of the ministry of finance of the russian federation. retrieved from http://minfin.ru; official website of the ministry of finance of the republic of crimea. retrieved from http://minfin.rk.gov.ru. other russian regions, following dagestan, sakha (yakutia) and kamchatka5. the lowest level of inflation in 2015 was recorded in khakassia (10.33%), the highest (excluding the crimean federal district), in ingushetia (17.54%). such statistics show significant discrepancies in the rates of price growth across different regions. similarly, a significant differentiation of inflation rates was observed in the previous period. in particular, in 2014, the inflation rates ranged from 7.46% in the yamalo-nenets autonomous district to 15.6% in kaliningrad region6. regional inflation requires the government to adjust its social and economic policies on the federal and regional levels, including the anti-inflationary policies. our analysis shows that the cost factors play a key role in inflation processes [3]. if we take a closer look at the dynamics of consumer inflation and price indices (tariffs) of natural monopolies, we will find that these indicators are closely connected and, consequently, that non-monetary factors shape inflation in the entire country as well as in specific regions. the dynamics of quarterly indicators is especially remarkable in this respect because it allows us to take into consideration the time lag of the impact that various factors have on consumer inflation. moreover, the analysis of quarterly indicators over the past decade has revealed the following pattern: the highest level of inflation is observed in the quarter characterized by an increase in tariffs of natural monopolies. for example, until 2012, the increase in electricity and heating tariffs as well as utility tariffs occurred in the first quarter (in january), and the highest rate of inflation was also observed in this quarter (table 1). since 2012, however, there has been an increase in tariffs in the third quarter, which was also characterized by the highest inflation. the above-described pattern characterizes only national economy but also specific regions, for example, sverdlovsk region [4]. in order to ensure long-term price stability, in addition to looking at the regional inflation factors, we should address the problem of the disproportional development of the country’s economic space. at present, there are considerable differences in the development of russian regions in the main macroeconomic indicators. 5 official website of the ministry of finance of the russian federation. retrieved from http://minfin.ru. 6 our calculations are based on the data provided by the official website of the federal state statistics service. retrieved from http://www.gks.ru. http://doi.org/10.15826/recon.2018.4.2.006 http://www.gks.ru http://www.gks.ru http://www.gks.ru http://minfin.rk.gov.ru http://minfin.ru http://www.gks.ru r-ecomony, 2018, 4(2), 41–45 doi: 10.15826/recon.2018.4.2.006 43 www.r-economy.ru online issn 2412-0731 therefore, it is advisable to adjust regional policies in order to make the socio-economic deve lopment more balanced. the growing tariffs on the products of natural monopolies serve as the main catalyst for regional inflation and affect the consumer price index [4]. at the same time, in combination with high freight rates and monopolistically inflated fuel prices, tariffs influence the cost of regional production, increase production cost inflation and are detrimental for local businesses. therefore, monopolistically inflated prices cause a rise in the general price level, thus exacerbating imbalance in industry as certain sectors by virtue of their monopolistic positions get super-profits while others have to make zero profits or even suffer losses. anti-inflationary policy in russia: methods and approaches discrepancies in regional economies are caused by the deviation of regional inflation rates from the national rate. the problem of regional imbalances regarding tariffs for housing and communal services needs to be addressed through state policies that would enable federal bodies to create their own territorial bodies to regulate tariffs. these territorial bodies should be authorized to conduct operational analysis of regional companies’ activities. it is also necessary to create a single executive body responsible for the development and implementation of the pricing policy as well as vertical agencies regulating tariffs and monitoring companies’ compliance with the established pricing procedure. moreover, we recommend to introduce a unified network system of price monitoring. since russian economy is characterized by substantial unloaded production capacities and the declining production, the aggregate demand should be stimulated by increasing investment through tax cuts and the key interest rate. the current tax policy is unstable and does not contribute to the country’s innovative development. it is possible to make the country’s economy more efficient by reducing the tax burden on producers’ incomes, including taxes on wages, profits and added value. furthermore, it is necessary to exempt from taxation the profit that enterprises direct for real investment. taking into account the peculiarities of national economy, such policy may reduce the average production costs and increase the aggregate demand without a significant increase in the general price level. decreasing average production costs can be effective in the conditions of cost inflation, which prevails in national and regional economy and should be distinguished from demand inflation. fears of a rise in the general price level due to the increase of the aggregate demand are unjustified in the current economic conditions. first, as we have noted above, the development of inflationary processes in national and regional economy is mostly caused by cost factors, and therefore, we can conclude that cost inflation prevails in the country. secondly, national economy at the current stage of its development is characterized by incomplete employment, unloaded production capacities and declining production. consequently, an increase in the aggregate demand in the current economic conditions will not have negative consequences, but, on the contrary, will be beneficial for economy. in addition, there is evidence that an increase in wages entails an increase in the average annual gdp while inflation remains at the same level [5, pp. 144–156]. gdp growth is associated with an increase in labor productivity, which has a greater impact on the volume of production of goods and services, which, in turn, leads to lower prices. therefore, in russian economy, inflation does not increase with the growth of the population’s income [5, pp. 155]. to address the problem of cost inflation and stimulate business activity, another effective method is to reduce tax rates, which will reduce the overall prices level. this measure is favoured by table 1 consumer price index in the russian federation in 2005–2015, % of the previous period quarter 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 i 105.27 104.98 103.42 104.78 105.42 103.16 103.81 101.46 101.89 102.32 107.44 ii 102.72 101.18 102.24 103.96 101.98 101.23 101.19 101.75 101.63 102.50 101.08 iii 100.62 101.01 101.86 101.82 100.65 101.84 99.70 101.95 101.22 101.45 101.88 iv 102.31 101.83 104.35 102.72 100.75 102.55 101.40 101.41 101.73 105.08 102.51 souse: calculations were based on the data from the official website of the federal state statistics service. retrieved from http://www.gks.ru. http://doi.org/10.15826/recon.2018.4.2.006 http://www.gks.ru 44 www.r-economy.ru r-ecomony, 2018, 4(2), 41–45 doi: 10.15826/recon.2018.4.2.006 online issn 2412-0731 the proponents of the theory of supply economics. v. v. roshchupkin points out that excessive tax burden can stem from the inefficiency of the tax system [6, pp. 140]. thus, mitigation of the tax burden, for example, a partial tax relief will allow enterprises to use their profits for real investment, which will contribute to the growth of economic activity. by increase the aggregate supply, this measure will help the government deal with cost inflation, which is a dominant type of inflation in russian economy. from the diversity of anti-inflationary policy models, we should choose only those that are aimed at combating the underlying causes of inflation in the economy of a given country. different economic schools propose different approaches to the interpretation of the phenomenon of inflation and the assessment of economic conditions, which creates a great diversity of views on what course an anti-inflationary policy should take. recently, the need to introduce inflation targeting in russia has been actively discussed. however, in the conditions of the current economic recession and high unemployment, this method will not be effective, since keeping inflation at bay should not be an end in itself of the economic policy. in addition, there is no evidence that inflation targeting has a positive impact on the dynamics of production output, neither in the short-term nor in the long-term [7, pp. 107–128]. the same study shows that in developing countries inflation targeting might negatively affect the production output. it should be noted that there is still no clear understanding of how to safely and effectively apply the instruments of inflation targeting [8]. empirical studies on different countries show that in recent years the effect of exchange rate transfer on inflation has subsided [9, pp. 924–947]. nevertheless, in russian economy there is a reverse trend: fluctuations in the ruble exchange rate have a strong negative effect on the dynamics of consumer prices, especially in the food sector. in russia, in the recent years, consumer prices have become more responsive to changes in exchange rates [10]. d. mihaljec and m. klau also demonstrate that in developing countries, the impact of the national currency on the development of inflationary processes is stronger than in developed countries [11]. therefore, it is required, on the one hand, to take measures aimed at strengthening the ruble, and on the other hand, to mitigate the influence of the exchange rate dynamics on inflation. it should be noted that the latter effect is strengthened by inflationary expectations. according to b. p. bosworth, cost factors play the main role in regional inflation, which means that it is necessary to take into account its non-monetary nature and to reduce the inflation of costs [12]. thus, to maximize the effect of an anti-inflationary policy it is necessary to apply an integrated approach: stimulate national production and business activities, which will contribute to the growth of the aggregate supply, and at the same time control the increase in the aggregate demand as a factor of economic growth. it is necessary to strengthen control over natural monopolies’ tariffs, which requires some serious institutional changes. in addition to controlling pricing at the federal level, tariffs should also be regulated on the regional level. more balanced economic development across the regions will enhance the development of the national market and strengthen the unity of the russian state. increasing interregional differentiation, on the contrary, makes it difficult to implement a comprehensive social and economic policy successfully, including an anti-inflationary policy. a number of theoretical models prove that inflation can have a negative impact on the market structure, long-term relationships and their efficiency. r. benabou and m. tommasi describe the mechanisms of inflation that may lead to considerable expenses [13; 14]. the extreme cases of lower inflation are the disastrous consequences of hyperinflation. furthermore, there is a negative interrelation between inflation and investment [15; 16]. conclusion a successful anti-inflationary policy requires the government to adopt an integrated approach to the problem. given the prevailing type of inflation and the current economic conditions, the government’s priority should be the stimulation of domestic production and those business activities that contribute to the growth of aggregate supply. it is also necessary to maintain control over the increase in the aggregate demand as a factor of economic growth. we need serious institutional changes in the sphere of natural monopolies in order to establish more rigorous control over their tariffs. http://doi.org/10.15826/recon.2018.4.2.006 r-ecomony, 2018, 4(2), 41–45 doi: 10.15826/recon.2018.4.2.006 45 www.r-economy.ru online issn 2412-0731 based on our analysis of the characteristics of the country’s economic development and the predominant type of inflation, we would recommend to apply the keynesian theory and the theory of economic proposals to develop a national economic policy. it would, however, be difficult to combine these two approaches as the former seeks to regulate the aggregate demand while the latter, the aggregate supply. nevertheless, taking into consideration the current state of russian economy, we have reasons to expect these measures to be quite efficient. references 1. modigliani, f. & cohn, r. a. (1979). inflation and the stock market. financial analysts journal, 35, 24–44. 2. kiseleva, p. s. & ilyashenko, v. v. (2012). interregional differentiation of the inflation rate in russia. journal of the ural state university of economics, 1, 5–10. 3. ilyashenko, v. v. (2007). macroeconomic and microeconomic factors of inflation in the russian economy being transformed: thesis for the degree of doctor of economics. yekaterinburg: usue. 4. kiseleva, p. s. & ilyashenko, v. v. (2015). factors and dynamics of inflationary processes in the industrial region. journal of the ural state university of economics, 3, 24–29. 5. sulakshin, s. s. (2009). inflation in russia: what kudrin was wrong about. moscow. nauchny expert. 6. roshchupkina, v. v. (2016). the index of the tax burden as an indicator of the effectiveness of state fiscal measures. economics, taxes & law, 9(2), 133–142. 7. kartaev f. c., filippov a. p. & khazanov a. a. (2016). econometric estimation of influence of inflation targeting on gdp dynamics. journal of the new economic association, 1, 107–128. 8. ebeke, c., fouejieu azangue a. (2015). inflation targeting and exchange rate regimes in emerging markets. imf working papers. european department. 9. marazzi, m. & sheets, n. (2006). declining exchange rate pass-through to u.s. import prices: the potential role of global factors. journal of international money and finance, 26(6), 924–947. doi: 10.1016/j.jimonfin.2006.12.003. 10. shmykova, s. v. & sosunov, k. a. (2005). the responsiveness of consumer prices to exchange rate in russia. hse economic journal, 9(1), 3–16. 11. mihaljec, d. & klau, m. (2001). a note on the pass-through from exchange rate and foreign price changes to inflation in selected emerging market economies. bis working papers, 8, 69–81. 12. bosworth, b. p. (2000). nonmonetary aspects of inflation. journal of money, credit and banking, 12(3), 527–539. doi: 10.2307/1991726. 13. benabou, r. (1992). inflation and efficiency in search markets. review of economic studies, 59(2), 299–329. doi: 10.2307/2297956. 14. tommasi, m. (1994). the consequences of price instability on search markets: toward understanding the effects of inflation. american economic review, 84(5), 1385–1396. 15. easterly, w. & bruno, m. (1998). inflation crises and long-run growth. journal of monetary economics, 41(1), 3–26. retrieved from https://ssrn.com/abstract=123168. 16. fischer, s. (1993). the role of macroeconomic factors in growth. journal of monetary economics, 32(3), 485–512. doi: 10.3386/w4565. information about the author polina s. kiseleva – senior lecturer of the department of economic theory and economic policy, ural federal university university (19, mira st., 620002, yekaterinburg, russian federation); email: p.s.kiseleva@urfu.ru. http://doi.org/10.15826/recon.2018.4.2.006 http://doi.org/10.1016/j.jimonfin.2006.12.003 http://doi.org/10.2307/1991726 http://doi.org/10.2307/2297956 https://ssrn.com/abstract=123168 http://doi.org/10.3386/w4565 mailto:p.s.kiseleva@urfu.ru 88 www.r-economy.ru r-ecomony, 2018, 4(3), 88–94 doi: 10.15826/recon.2018.4.3.013 online issn 2412-0731 original paper doi: 10.15826/recon.2018.4.3.013 spatial demographic inequalities and regional development in serbia suzana lović obradović , stefana matović geographical institute jovan cvijić, serbian academy of science and art, belgrade, serbia; e-mail: s.lovic@gi.sanu.ac.rs abstract th e study provides a comprehensive data analysis of demographic and socio-economic characteristics in serbian regions as factors of uneven regional development. th e data were provided by the offi cial population censuses from 1953 to 2011. th e study uses the following demographic indicators: population; the index of population change; population density; the share of migrants in the total population; the share of 65+ population; and the average age of the population. th e indicators of the regions’ socio-economic development were as follows: the level of development of cities and municipalities; the share of uneducated population; the share of the population with secondary and higher education; the share of welfare recipients; the share of employed population; the share of computer illiterate persons; and the share of the unemployed. th e research results have shown signifi cant regional discrepancies: belgrade, kosovo and metohija regions are economically prosperous regions, attractive for migrants from other parts of serbia, the situation is quite the opposite in southern and eastern serbia, characterized by the outfl ow of the population and economic underdevelopment, especially in the border areas. th e other two regions are within the two extremes, vojvodina being closer to belgrade and šumadija and western serbia, to southern and eastern serbia. keywords demographic indicators, socioeconomic indicators, nuts2 region, regional disparities, serbia acknowledgment th e study was supported by the ministry of education, science and technological development of the republic of serbia (project no. 47007). for citation lović obradović s., & matović s. (2018) spatial demographic inequalities and regional development in serbia. r-economy, 4(3), 88–94. doi: 10.15826/recon.2018.4.3.013 региональные демографические различия и региональное развитие в сербии c. лович-обрадович , с. матович географический институт «йован цвиич» сербской академии наук, белград, сербия; e-mail: s.lovic@gi.sanu.ac.rs резюме в исследовании содержится всесторонний анализ данных демографических и социально-экономических характеристик сербских регионов, рассмотренных как факторы неравномерного регионального развития. данные были предоставлены официальными переписями населения с 1953 по 2011 г. в исследовании используются следующие демографические показатели: население; индекс изменения численности населения; плотность населения; доля мигрантов в общей численности населения; доля населения старше 65 лет; и средний возраст населения. показатели социально-экономического развития регионов были следующими: уровень развития городов и муниципалитетов; доля необразованного населения; доля населения со средним и высшим образованием; доля получателей пособий; доля занятого населения; доля граждан, не умеющих пользоваться компьютерами; и доля безработных. результаты исследования показали значительные региональные различия: регионы белград, косово и метохия являются экономически процветающими регионами, привлекательными для мигрантов из других районов сербии, ситуация в южной и восточной сербии является совершенно противоположной, характеризующейся оттоком населения и экономической недоразвитостью, особенно в приграничных районах. остальные два региона находятся в двух крайностях: воеводина находится ближе к белграду, в то время как шумадия и западная сербия – к южной и восточной сербии. ключевые слова демографические показатели, социально-экономические показатели, регион nuts2, региональные различия, сербия благодарности исследование было поддержано министерством образования, науки и технологического развития республики сербия (проект № 47007). для цитирования lović obradović s., & matović s. (2018) spatial demographic inequalities and regional development in serbia. r-economy, 4(3), 88–94. doi: 10.15826/recon.2018.4.3.013 r-ecomony, 2018, 4(3), 88–94 doi: 10.15826/recon.2018.4.3.013 89 www.r-economy.ru online issn 2412-0731 introduction th e republic of serbia has diverse geographical and socio-economic characteristics such as the uneven distribution of the population caused by geographical, social and historical factors. apart from the pronounced geographical diff erences, the regions also have diff erent demographic and socio-economic characteristics. th e geographical factors had prevailed until the end of the second world war, and then social factors took over as industrialization led to intensive migration from rural areas to cities. before that, serbia had mostly been an agricultural country [1]. th e demographic determinant only emphasized the existing differences resulting in signifi cant regional disrepancies. th us, it is necessary to address the issues of unbalanced population distribution in order to ensure sustainable development of all parts of serbia [2]. uneven regional distribution of the population in serbia is not a new phenomenon. historically, it goes back to the post-war period of industrialization, when the intensive economic and demographic growth of belgrade region began. in the same period, southern and eastern serbia experienced the demographic and economic decline caused by the major disproportions in the country’s regional development [3]. disparities in population concentration and excessive population growth of primary regions can have a negative impact on the country’s overall economic development. th erefore, these issues need to be addressed through policies aimed at redirecting the population to other regions; policies promoting investment in infrastructure, marketing, and development of small and medium enterprises [4]. theoretical framework in order to design an adequate policy for balancing regional development it is essential to understand the nature of regional disparities resulting from the unequal distribution of investment and demographic resources. th e vast body of literature on the problem of regional disparities and its causes reveals the complexity of this phenomenon. regional disparities are also among the priority issues in the european union’s policies; most schemes for development and integration of nation states within the eu seek to address this problem as considerable regional disparities are considered to be detrimental for the success of supra-national integration projects (crudu) [5]. vorauer (1997) defi nes regional disparities as a deviation in socio-geographic, economic, social and environmental development within a particular spatial/administrative division resulting in diff erent living standards and unequal economic potential [6]. kutscheraur et al. (2010) approach regional disparity as a divergence or inequality of characters, phenomena or processes with a specifi c territorial allocation, occurring in at least two entities of the territorial structure [7]. tegenu (2011) lists various factors that lead to regional disparities: agro-ecological factors (such as rainfall amount, soil quality, topography and altitude); demographic factors (population density, level of urbanization, reproductive behavior of the households); infrastructure development; income and property; patterns of private investment; and so on. th e researcher also points out that the lack of detailed regional studies and inter-regional analysis may contribute to the lack of attention paid to the problem of regional imbalances [8]. however, there is still no generally accepted answer to the question about the origins of regional disparities [9]. demography places population in the center of research on regional disparities. vojković (2003) considers that regionalization is a complex phenomenon, which means that population must be viewed in the more general context: we need to look at historical demographic trends, territorial organization of the population, its demographic structure and in particular at the spatial laws which determine the demographic development of a certain area [10]. population growth can stimulate economic growth, which may attract more migrants, while the loss of population damages the region’s economy, thereby reducing the resorces for its further development [11]. research methodology and data th is study uses the data of seven successive censuses, starting from the fi rst post-war census in 1953 to the last offi cial census in 2011, conducted on the territory of serbia. in this paper, we provide a comparative overview of the basic demographic indicators for the period of fi ft y-eight years, placing a special emphasis on the last census. th e aim was to point out the complexity of demographic phenomena and processes within the given period. for kosovo and metohija, only the data until 1991 were available for analysis as serbia’s offi cial statistical offi ce did not provide offi cial data for this region aft er 1991. indicators of regional disparities were divided into two classes – demo90 www.r-economy.ru r-ecomony, 2018, 4(3), 88–94 doi: 10.15826/recon.2018.4.3.013 online issn 2412-0731 graphic and socio-economic. in our analysis we used the following demographic indicators: population; the index of population change; population density; the share of migrants in the total population; the share of 65+ population; and the average age of the population. to assess the socio-economic development of the region we used the following indicators: the level of development of cities and municipalities; the share of uneducated population; the share of the population with secondary and higher education; the share of welfare recipients; the share of the employed population; the share of computer illiterate persons; and the share of the unemployed. th e indicators were analyzed at the nuts2 level: in 2011, the government of the republic of serbia adopted the decree on the nomenclature of statistical territorial units, which defi nes the nomenclature of statistical territorial units, as well as the criteria for grouping of subdivisions of countries on three levels – nuts 1, nuts 2 and nuts 3 (nuts1 corresponds to groups of regions; nuts2, regions; and nuts3, districts). th e criteria for nuts grouping are established according to the eu standards: the population size, geopolitical position, natural potential, the existing territorial organization, and cultural and historical heritage [12]. according to the decree, serbia is statistically divided into two large units – serbia-north and serbia-south (nuts 1); fi ve regions (vojvodina, belgrade, šumadija and western sebia, southern and eastern serbia and kosovo and metohia (nuts 2)); and 25 districts (nuts 3) (figure) [12]. nuts 2 and nuts 3 regions in serbia r-ecomony, 2018, 4(3), 88–94 doi: 10.15826/recon.2018.4.3.013 91 www.r-economy.ru online issn 2412-0731 discussion demographic determinants of regional disparities population size. th e available data on the country’s population show that the most populated region in serbia in the given period was šumadija and western serbia. th is region is one of the largest in serbia, which explains its population size (see table 1). on the other hand, the smallest number of inhabitants was recorded in belgrade, which is also the smallest. indices of population change and the data on population density give us a more precise demographic picture of the regions. serbian regions are characterized by a diversity of demographic trends. more prosperous municipal centers attract migrants from other regions, which results in unbalanced spatial distribution of the population across serbia, as the last offi cial census in 2011 showed. th e most economically successful region is belgrade, which attracts people from all other parts of serbia. belgrade is the only region in serbia in which the share of settled population exceeds 50% (51.8%), while the smallest share is found in southern and eastern serbia (41.2%). belgrade attracts the working age population and the reproductive-age population. although this region shows the highest recorded fertility rates (10.7%), there is also a negative natural increase with a rate of –1.5%. th e increase in the number of inhabitants is therefore provided by the positive migration balance. according to the latest 2011 census, there were 968 settlements with less than 100 inhabitants, and there were also 11 deserted settlements. serbia is characterized by distinct spatial diff erentiation in the number of settlements with the population of less than 100 inhabitants. only one such settlement was found in belgrade (0.6%); in vojvodina, 12 (2.6%); in šumadija and western serbia, 128 (14.7%); in southern and eastern serbia, 827 (25.7%). in the latter region there were also 9 deserted settlements. population by age. as in most european countries, in serbia, for several decades, the birth rates have been insuffi cient to ensure simple reproduction of the population, which causes depopulation and demographic aging and refl ects the consequences of the demographic transition [13]. as far as the number of the elderly is concerned, serbia is classifi ed as one of the oldest states not only in europe, but also in the world. life expectancy rates are increasing and there are much more elderly people than young and active, table 1 population by regions region   population index of population change, 1948 = 100 1948 1953 1961 1971 1981 1991 2002 2011 1953 1961 1971 1981 1991 2002 2011 belgrade 634,003 731,837 942,190 1,209,360 1,470,073 1,602,226 1,576,124 1,659,440 115.40 148.60 190.70 231.90 252.70 248.60 261.70 urban 437,053 521,114 721,183 990,272 1,206,235 1,310,920 1,274,924 1,344,844 119.20 165.00 226.60 276.00 299.90 291.70 307.70 other 196,950 210,723 221,007 219,088 263,838 291,306 301,200 314,596 107.00 112.20 111.20 134.00 147.90 152.90 159.70 vojvodina 1,640,599 1,698,640 1,854,971 1,952,560 2,034,782 2,013,889 2,031,992 1,931,809 103.50 113.10 119.00 124.00 122.80 123.90 117.80 urban 655,831 699,575 826,200 978,115 1,095,256 1,115,562 1,152,674 1,146,731 106.70 126.00 149.10 167.00 170.10 175.80 174.90 other 984,768 999,065 1,028,771 974,445 939,526 898,327 879,318 785,078 101.50 104.50 99.00 95.40 91.20 89.30 79.70 šumadija and western serbia 1,776,544 1,902,934 2,006,793 2,111,855 2,243,885 2,266,428 2,136,881 2,031,697 107.10 113.00 118.90 126.30 127.60 120.30 114.40 urban 242,679 305,669 419,233 614,981 829,608 946,535 956,586 963,548 126.00 172.80 253.40 341.90 390.00 394.20 397.00 other 1,533,865 1,597,265 1,587,560 1,496,874 1,414,277 1,319,893 1,180,295 1,068,149 104.10 103.50 97.60 92.20 86.10 76.90 69.60 southern and eastern serbia 1,743,691 1,828,910 1,874,293 1,929,140 1,980,506 1,940,252 1,753,004 1,563,916 104.90 107.50 110.60 113.60 111.30 100.50 89.70 urban 249,836 297,476 391,056 574,370 744,504 841,681 834,295 816,749 119.10 156.50 229.90 298.00 336.90 333.90 326.90 other 1,493,855 1,531,434 1,483,237 1,354,770 1,236,002 1,098,571 918,709 747,167 102.50 99.30 90.70 82.70 73.50 61.50 50.00 kosovo and metohija 732,746 815,798 963,715 1,243,811 1,584,440 1,956,196 ... ... 111.30 131.50 169.70 216.20 267.00 ... ... source: statistical offi ce of the republic of serbia (2014). 2011 census of population, households and dwellings in the republic of serbia. comparative overview of the number of population in 1948, 1953, 1961, 1971, 1981, 1991, 2002 and 2011. vol. 20. belgrade: statistical offi ce of the republic of serbia. retrieved from: http://pod2.stat.gov.rs/objavljenepublikacije/popis2011/knjiga20.pdf 92 www.r-economy.ru r-ecomony, 2018, 4(3), 88–94 doi: 10.15826/recon.2018.4.3.013 online issn 2412-0731 which makes the pension burder heavier [14]. th e smallest share of the population older than 65 was recorded in belgrade and vojvodina (16.3%); a slightly higher share was in šumadija and western serbia (17.7%); and the largest, in southern and eastern serbia, where almost a fi ft h of the population were older than 65 (19.4%). in belgrade, the share of the population aged 65 and older is higher in cities while in other regions, this share is higher in rural areas (table 2). th e lowest average age of the population was recorded in belgrade and vojvodina (41.8 years old); the average age is slightly higher in šumadija and western serbia (42.3 years old); and the oldest population is in southern and eastern serbia (43.3 years old) (see table 2). socio-economic determinants of regional disparities gdp per capita. th e most economically developed regions in serbia are belgrade and vojvodina with the gdp per capita above the national average. šumadija and western serbia, southern and eastern serbia with kosovo and metohija have the gdp level below the national average, and belong to the group of underdeveloped regions. education. th e level of education shows regional disparities. belgrade has the smalest share of uneducated people in the total population (1.2%) and at the same time the largest share of population with secondary and higher education (27.8%). southern and eastern serbia is characterized by the largest share of uneducated population (12.5%) and the smalest share of the population with secondary and higher education (3.8%) (see table 2). social welfare and employment. th ere are considerable regional disparities in the share of welfare recipients and in the share of employed people. th e lowest share of the former is in belgrade, while the largest share of the latter is characteristic of southern and eastern serbia (see table 2). table 2 demographic and socio-economic indicators region th e share of migrants (%) th e share of population 65 and over (%) average age th e share of uneducated population (%) th e share of population with secondary and higher education (%) th e share of welfare recipients (%) th e share of employed population (%) th e share of computer iliterate population (%) th e share of unemployed population (%) belgrade 51.8 16.4 41.8 1.2 27.8 0.9 35.3 38 7.8 urban – 16.5 41.9 0.9 32.1 0.8 36.2 33.9 8.9 other – 15.8 41.4 2.46 9.3 1.3 31.2 56 6.8 vojvodina 46.2 16.4 41.8 2.3 14.1 2.6 30 49.3 9.2 urban – 15.8 41.4 1.58 19.1 2 32 42.1 10.8 other – 17.3 42.3 3.41 6.7 3.4 27.1 59.7 7.7 šumadija and west serbia 41.3 17.7 42.3 3.4 11.7 2.1 30 57.4 9.2 urban – 14.5 40.6 1.6 18.6 2 32 44.3 10.1 other – 20.6 43.7 4.9 5.5 2.1 27.1 69 8.3 south and east serbia 41.2 19.4 43.3 3.7 12.5 2.3 28.5 58.7 11 urban – 15 41 2.1 20.8 2.6 30 46.3 12.1 other – 24.1 45.7 5.5 4.9 2.3 27.2 72 9.9 source: statistical offi ce of the republic of serbia (2013). 2011 census of population, households and dwellings in the republic of serbia. educational attainment, literacy and computer literacy. vol. 3. belgrade: statistical offi ce of the republic of serbia. retrieved from: http://pod2.stat.gov.rs/objavljenepublikacije/popis2011/skolska%20sprema,%20pismenost%20i%20 kompjuterska%20pismenost-educational%20attainment,%20literacy%20and%20computer%20literacy%20.pdf; statistical offi ce of the republic of serbia (2013). 2011 census of population, households and dwellings in the republic of serbia. migrations. vol. 9. belgrade: statistical offi ce of the republic of serbia. retrieved from: http://pod2.stat.gov.rs/objavljenepublikacije/popis2011/knjiga%209_migracije-migrations.pdf; lgrade: statistical offi ce of the republic of serbia. retrieved from: http://pod2.stat. gov.rs/objavljenepublikacije/popis2011/knjiga20.pdf; statistical offi ce of the republic of serbia (2014). 2011 census of population, households and dwellings in the republic of serbia. population. economic activity. vol. 19. belgrade: statistical offi ce of the republic of serbia. retrieved from: http://pod2.stat.gov.rs/objavljenepublikacije/popis2011/knjiga%207_ekonomska%20 aktivnost-economic%20activity.pdf r-ecomony, 2018, 4(3), 88–94 doi: 10.15826/recon.2018.4.3.013 93 www.r-economy.ru online issn 2412-0731 computer literacy and economic activity. when it comes to the share of computer illiterate people and the share of unemployed in the total population, the smalest share of people of both categories is in belgrade, and the largest, in southern and eastern serbia (see table 2). conclusion since there is a correlation between spatial/ regional inequalities and economic growth, more attention should be paid to the question about the connection between the demographic and economic forms of regional inequality as well as other forms, such as social, ethnic, political, religious, and so on [15]. drawing upon the available census data, this paper sought to examine the infl uence of spatial demographic inequalities on regional development. while belgrade, kosovo and metohija (till 1981) are economically prosperous regions, attractive for migrants from other parts of serbia, the situation is quite the opposite in southern and eastern serbia, characterized by the outfl ow of the population and economic underdevelopment, especially in the border areas. th e other two regions are within the two extremes, vojvodina being closer to belgrade, and šumadija and western serbia closer to southern and eastern serbia. in the given period, belgrade and kosovo-metohija were singled out as growth poles. in belgrade, however, the population increase is largely determined by the positive migration balance: as the city is a political, administrative, educational and economic center, it attracts migrants from all other parts of serbia. th e increase in the number of inhabitants in kosovo and metohija was due to the positive natural increase. southern and eastern serbia was a negative pole of growth, with a marked demographic decline, as the last two censuses have demonstrated. a signifi cant decline in population, especially in other (rural) settlements, shows that the old mechanisms of demographic growth are no longer eff ective. given the negative demographic trends, which are refl ected in the negative natural increase and emigration, as a consequence of the historically determined unfavorable age structure of the population, a further decline in the population is expected. references 1. vojković, g. & kokotović, v. 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(2013). regional inequalities and economic growth: th e example of serbia (doctoral dissertation). retrieved from http://nardus.mpn.gov.rs/handle/123456789/2223?locale-attribute=sr_rs information about the authors suzana lović obradović – research associate, geographical institute jovan cvijić, serbian academy of science and art (9 đure jakšića st., 11000 belgrade, serbia); e-mail: s.lovic@gi.sanu.ac.rs. stefana matović – research associate, geographical institute jovan cvijić, serbian academy of science and art (9 đure jakšića st., 11000 belgrade, serbia). 18 www.r-economy.ru r-ecomony, 2018, 4(1), 18–27 doi: 10.15826/recon.2018.4.1.003 online issn 2412-0731 original paper for citation njegovan, n., demirović, d. & vaško, ž. (2018) selection and application of pricing strategies in rural tourism: the case of vojvodina’s farmsteads. r-economy, 4(1), 18–23. doi: 10.15826/recon.2018.4.1.003 for citation ньегован, н., демирович, д., вашко, ж. (2018) отбор и применение ценовых стратегий в сельском туризме: пример хозяйств воеводины. r-economy, 4(1), 18–23. doi: 10.15826/recon.2018.4.1.003 doi: 10.15826/recon.2018.4.1.003 selection and application of pricing strategies in rural tourism: the case of vojvodina’s farmsteads nikola njegovana, dunja demirovićb, željko vaškoc a faculty of economics, university of belgrade, belgrade, serbia; e-mail: nikolanj@ekof.bg.ac.rs b geographical institute jovan cvijić sasa, belgrade, serbia; e-mail: demirovic.dunja2@gmail.com c faculty of agriculture, university of banja luka, banja luka, bosnia and herzegovina; e-mail: zeljko.vasko@agro.unibl.org abstract tourism today is a mass phenomenon involving a large number of actors, both on the demand side and on the supply side. for more efficient and better organized performance, tourism companies need to ensure a high quality of service and apply effective pricing strategies. therefore, the aim of this paper is to outline the key pricing strategies and analyze their advantages and drawbacks. for this purpose we have chosen the specific case of farmsteads in the province of vojvodina, serbia. we focus on the complementary products or services provided by these farmsteads that have a seasonal element to them, that is, they are hard to sell out of season. as a result, we devised guidelines for entrepreneurs to enhance their business opportunities by applying effective pricing strategies such as the marginal costs strategy. keywords strategies, prices, marginal costs, rural tourism, farmstead, vojvodina province (serbia) acknowledgments the research was supported by ministry of education, science and technological development, republic of serbia (grant iii 47007 and 46006) отбор и применение ценовых стратегий в сельском туризме: пример хозяйств воеводины н. ньегованa, д. демировичb, ж. вашкоc a белградский университет, экономический факультет, белград, сербия; e-mail: nikolanj@ekof.bg.ac.rs b географический институт «йован цвиич» сербской академии наук, белград, сербия; e-mail: demirovic.dunja2@gmail.com c университет баня луки, сельскохозяйственный факультет, баня лука, босния и герцеговина; e-mail: zeljko.vasko@agro.unibl.org резюме туризм сегодня представляет собой массовое явление, в который вовлечено большое количество участников, как со стороны спроса, так и со стороны предложения. для более эффективной и высокоорганизованной работы туристические компании должны обеспечивать высокое качество обслуживания и применять эффективные стратегии ценообразования. поэтому цель данной статьи – наметить ключевые стратегии ценообразования и проанализировать их преимущества и недостатки. для этого мы выбрали конкретный случай фермерских хозяйств в сербском регионе воеводина. мы фокусируемся на дополнительных продуктах или услугах, предоставляемых этими фермерскими хозяйствами, которые характеризуются сезонностью, то есть их сложно продать вне сезоны. в результате, мы разработали советы для предпринимателей, направленные на расширение возможностей их бизнеса путем применения эффективных стратегий ценообразования, таких как стратегия «предельных издержек». ключевые слова стратегии, цены, предельные издержки, сельский туризм, фермерские хозяйства, провинция воеводина (сербия) благодарности исследование поддержано министерством образования, науки и технологического развития республики сербия (грант iii 47007 и 46006)   https://doi.org/10.15826/recon.2018.4.1.003 http://doi.org/10.15826/recon.2018.4.1.003 mailto:demirovic.dunja2@gmail.com mailto:demirovic.dunja2@gmail.com r-ecomony, 2018, 4(1), 18–23 doi: 10.15826/recon.2018.4.1.003 19 www.r-economy.ru online issn 2412-0731 introduction the competitive position of enterprises operating in tourism industry, especially small enterprises specializing in rural tourism, depends to a large extent on the applied concept of their growth and development, i.e. on the establishment and implementation of an adequate strategy [1–3]. therefore, to devise an efficient and dynamic strategy, these enterprises need to take into account both internal and external factors such as the level of the company’s development and the market in which it is operating. the term strategy is used so widely nowadays that in practice its significance sometimes seems overrated. everything that is important in an enterprise tends to be referred to as strategic, which makes this concept too broad and, therefore, useless as it confuses more than it clarifies. moreover, it is often misleading in the sense that it emphasizes the elements and aspects which are not crucial for the company. ideally, a strategy should provide a framework for the company’s business for better coordination and more efficient management in order to make the company more responsive to the changing environment [4]. the strategy should articulate the desirable relationships between the company and its environment, take into account the specific nature of the business sector and thus help the company’s management plan, structure and organize the company’s business activities accordingly [5]. based on those assumptions, every strategic decision contributes to the successful performance of the company. all strategic decisions can be divided into two categories: fundamental and applied. it should be noted here that fundamental or the so-called corporate strategies are based on decision-making associated with, for instance, creation of new products. strategies dealing with the implementation of such decisions (e.g. how to set prices or advertise the new product) can be called applied or business strategies. in this paper, we will primarily focus on those corporate and business strategies that can be applied in small enterprises [6], more specifically, the pricing strategies of rural tourism companies, since they have more pronounced peculiarities in the production and marketing phases. these strategies should support the portfolio product / market, i.e. should be applied within small companies in the phase of production and distribution to the final consumer. material and methods our research was conducted at farmsteads in the autonomous province of vojvodina, republic of serbia. the initial stage consisted of interviews with entrepreneurs, who were managers at nine farmsteads. at the second stage, we analyzed the collected data and used them for devising guidelines for entrepreneurs. the age of our respondents ranged from 22 to 64; the average age was 43. the majority (72%) had secondary education; about 12%, higher; and 16%, elementary education. in addition to the interviews, we gathered and analyzed the information about the products and services that these companies were providing to rural tourists, their methods and strategies of calculating the prices and the mutual compatibility of products/services as well as the problems that entrepreneurs faced in sales. the results were calculated for each individual farmstead and on average for the set of farmsteads we studied. in the paper two concepts are used to determine the appropriate price strategy: total costs or costs plus and marginal costs [7; 8]. each concept takes into account the expectations that appear on the input market, since pricing is based on the analysis of the production costs. we believe that the key factor that determines the success of a small business is the sales market. results and discussion in this section we are comparing the results of the application of the two pricing strategies – total costs or costs plus and marginal costs. fixing the prices by using the strategy total costs or costs plus this method of pricing usually includes estimation of the production cost for a product or a service under normal conditions, that is, when there are no fluctuations in capacity utilization, employment or output [9]. the method can be applied to an entire range of products/services and called the strategy of building prices. this procedure is illustrated in table 1. after the implementation of the above-described procedure, we add to the cost of the unit the desired profit of the company. this element is determined according to the company’s position in relation to its competitors, usually by calculating the average profit rate of business in this sphere [10]. however, the drawback of this pricing strategy becomes evident when the cost of a particular product or service turns out https://doi.org/10.15826/recon.2018.4.1.003 20 www.r-economy.ru r-ecomony, 2018, 4(1), 18–23 doi: 10.15826/recon.2018.4.1.003 online issn 2412-0731 to be higher than the competitors’ market price of the same product or service, which makes it impossible to apply the appropriate profit margin because the product would be too expensive. therefore, most businesses choose to apply a more widely spread but also more complicated pricing strategy – the strategy of marginal cost. table 1 strategy total costs or costs plus – suggested selling price all prices in eur product item p1 p2 direct cost of materials 5 10 cost of direct manpower 4 2 direct expenses 1 0 prime costs 10 12 additional production costs variable costs of production 5 5 fixed costs of production 5 10 total cost of production 20 27 marketing and distribution 3 3 variable costs 2 1 fixed costs 1 2 additional administrative costs 1 1 fixed costs 1 1 total costs 24 31 pre-determined profit margin (%) 10 20 selling price 26,4 37,2 marginal costs (total variable costs) 17 18 fixing the prices by using the strategy marginal costs pricing based on the marginal costs strategy is a particularly effective method. it provides information that helps companies manage product selection, markets, sales areas, and market segmenting in relation to individual categories of customers [11; 12]. the ‘marginal cost’ strategy involves the variable costs of a product or a service unit. these are the costs that could be avoided if the product was not produced at all or if the service was not provided. an example of such calculations is given in table 2. we were using the case of farmsteads working as tourism and catering companies. these farmsteads were run as family ventures. our calculations illustrate the profit that can be gained by such enterprises if they sell two basic products or services (see table 3). the assumption is that both products or services are realized, that is, completed and sold to the customer during one calendar year. table 2 marginal cost of a product direct costs per unit eur/unit materials 0.70 staff wages 0.10 expenses 0.25 total prime costs 1.05 additional variable overhead costs per unit production 0.15 marketing and distribution 0.20 administration 0.05 overhead costs 0.40 total additional variable overhead costs per unit 0.80 marginal costs 1.85 table 3 shows an example of an income statement on the company’s performance over a oneyear period table 3 income statement, eur indicators total product p1 product p 2 sales 1.500 800 700 sales revenue 23.000 16.000 7.000 direct materials 11.500 8.000 3.500 direct labour 5.400 4.000 1.400 prime costs 16.900 12.000 4.900 production overhead costs1) 3.100 2.000 1.100 production costs 20.000 14.000 6.000 marketing, distribution and administration costs 2) 2.200 1.000 1.200 total costs 22.200 15.000 7.200 profit / loss 800 1.000 –200 estimated allocation of supplementary and administration costs: 1) variable costs 1.700 900 800 fixed costs 1.400 1.100 300 2) variable costs 500 300 200 fixed costs 1.700 700 1.000 the profit statement shows that the p2 product is selling not very well, which means that the company management might want to consider the question of discontinuing its production. such decision, however, does not take into account the fact that this product whether produced or not, is bound to certain fixed costs of the company itself, such as the rent of space, taxes, fees, equipment depreciation and the salaries paid to administration. therefore, the application of the ‘marginal cost’ strategy should help the entrepreneur get a clearer view of the situation (see table 4). https://doi.org/10.15826/recon.2018.4.1.003 r-ecomony, 2018, 4(1), 18–23 doi: 10.15826/recon.2018.4.1.003 21 www.r-economy.ru online issn 2412-0731 as it is evident from the example in table 3, the p2 product makes a difference of eur 1,100. this is the amount that the company would lose if the production of this product was stopped. on the other hand, the company’s total fixed costs of eur 3,100 would remain uncovered. therefore, if the company discontinued the production of p2 product, it would lose about would eur 300. the previously gained profit of eur 800, despite the negative result of product p2 sales, would thus be lost if the production of p2 stopped. although the fixed costs could be reduced by more than eur 1,100 if p2 was discontinued, table 3 clearly shows that the optimal decision for the company would be to continue its production. table 4 fixing the prices using the strategy marginal costs (as of 31st of december), eur indicators total product p1 product p 2 sales revenue 23.000 16.000 7.000 less variable costs direct materials 11.500 8.000 3.500 direct labour 5.400 4.000 1.400 variable production overhead costs 1.700 900 800 variable marketing, distribution and administration overhead costs 500 300 200 total variable costs 19.100 13.200 5.900 contribution 3.900 2.800 1.100 less fixed overhead costs production overhead costs 1.400 marketing, distribution and administration overheads 1.700 total fixed overhead costs 3.100 profit / loss 800 the application of the marginal cost strategy creates a combined effect but it also has some limiting factors. the application of this strategy makes it easier to search for a combined effect that is caused by price and cost factors, affecting both profits. in order to illustrate this, it is sufficient to make the company’s profit and loss account in two successive years (see table 5). changes within the given period result from an increase in the sales price by 20% and from an increase in the volume of products and services sold. thus, in this case, we need to investigate the effects of individual factors which lead to an increase in the contribution (difference) to eur 150,000 in the second year. each company has one or more limitations. they represent a critical input for business which at some point or during a certain period limits the business [13]. first and foremost, this is the company’s selling potential but the limitations can also be associated with certain characteristics of raw materials or production, with the degree of tourist product integration, the skills of the productive workforce, or with the availability of space or working assets [14]. when these limiting factors are introduced into analysis, the profit will be determined by their contributions. linear programming can be used to investigate each individual influence and choose an optimal plan. this mathematical method successfully addresses cases with a number of limiting factors and interactive variables. table 5 the combined effect of changing the volume of sales, selling prices and costs eur year 1 year 2 sales 200.000 400.000 marginal cost of sales 100.000 150.000 contribution 100.000 250.000 1. сhange related to the volume of sales sales of year 2 at year 1 prices = 400.000 · 4/5 – 320.000 sales of year 1 at year 1 prices – 200.000 change related to the volume = eur – 120.000 % change in volume (120 : 200) · 100 – 60% sales increase = eur – 120.000 marginal costs = eur 60% · 100.000 60.000 contribution change related to the volume = eur 60.000 2. сhange related to the selling price sales of year 2 at prices from year 1 320.000 sales of year 2 at prices from year 2 400.000 contribution change related to the price 80.000 3. reduction in costs change in sales volume = (120,000 : 200,000) · 100 60% marginal costs in year 1 related to the change of volume 100.000 marginal costs in year 2 = 100,000 + (60 : 100 · 100,00) 160.000 marginal costs in year 2 150.000 reduction in costs 10.000 the change in contribution of eur 150.000 related to the following factors: volume change 60.000 price change 80.000 cost change 10.000 contribution in year 2 150.000 https://doi.org/10.15826/recon.2018.4.1.003 22 www.r-economy.ru r-ecomony, 2018, 4(1), 18–23 doi: 10.15826/recon.2018.4.1.003 online issn 2412-0731 consequently, it may be concluded that the marginal cost strategy is most suitable for companies operating in unstable economic conditions. in such cases, it is better to accept orders below the level of the total value of the costs. this recommendation is based on the need to cover the marginal costs, which means that each level of the contribution above the fixed costs will at least reduce the company’s losses and help the company stay afloat until better days retaining its staff and preserving its facilities and equipment. thus, the application of this strategy can help entrepreneurs to set prices [15] in such circumstances as: 1) economic recession in this business sector; 2) excess of the company’s productive capacity; 3) seasonal fluctuations of demand; 4) situations when the company is using the individual employment contract; 5) situations when alternative levels of business activities are included. conclusion starting entrepreneurial ventures in the sphere of rural tourism, such as family farmsteads, is a complex and demanding job, since it requires entrepreneurs to expand their expertise in business and management. it often happens that entrepreneurs lack experience and knowledge when faced with competitive conditions in the target market. there are dozens of farmsteads in vojvodina province that mainly provide tourist and catering services. according to the research we conducted, most of the managers and owners we surveyed do not have sufficient knowledge in finance and business economics, especially in the sphere of standard and/or experimental pricing 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(2001). price determination and price strategy in the marketing view. management & marketing, 3(4), 21–36. information about the authors nikola njegovan – phd in economics, assistant professor, university of belgrade, faculty of economics (kamenička street no. 6, 11000 belgrade, serbia); e-mail: nikolanj@ekof.bg.ac.rs. dunja demirović – phd in tourism, research associate, geographical institute jovan cvijić sasa (đure jakšića street no. 9, 11000 belgrade, serbia); e-mail: demirovic.dunja2@gmail.com. željko vaško – phd in agriculture, associate professor, university of banja luka, faculty of agriculture (boulevard vojvode petra bojovića 1a, 78000 banja luka, republika of srpska, bosnia and herzegovina); e-mail: zeljko.vasko@agro.unibl.org. https://doi.org/10.15826/recon.2018.4.1.003 https://www.sciencedirect.com/science/journal/03605442 https://www.sciencedirect.com/science/journal/03605442/34/11 https://doi.org/10.1016/j.energy.2009.08.015 https://doi.org/10.1016/j.energy.2009.08.015 http://ieeexplore.ieee.org/xpl/recentissue.jsp?punumber=59 http://ieeexplore.ieee.org/xpl/tocresult.jsp?isnumber=19647 https://doi.org/10.1109/59.910776 r-ecomony, 2018, 4(3), 115–120 doi: 10.15826/recon.2018.4.3.016 115 www.r-economy.ru online issn 2412-0731 original paper doi: 10.15826/recon.2018.4.3.016 significance of drone technology for achievement of the united nations sustainable development goals haula kitonsa , sergey v. kruglikov ural federal university, ekaterinburg, russia; e-mail: kitsxauxkissule@gmail.com abstract th e drone technology, which originated in military applications, is now widely used for commercial, professional, industrial and private purposes. applications of unmanned aerial vehicles (uavs), commonly known as drones, include diff erent sectors of economy, for example, agriculture, transport, infrastructure, entertainment, and telecommunications. not only are drones eco-friendly gadgets that allow to reduce the amount of carbon dioxide emissions, but they are also timeand cost-effi cient. th us, drones can prove to be a major force for good as they hold massive potential for being used to meet the sustainable development goals (sdgs) set by the united nations organization and adopted in 2015. developing countries, for instance those of sub-saharan africa, are facing famine, epidemic diseases, poverty and other challenges. all these problems can be addressed with the help of the drone technology. th e main objective of this paper is to identify the sectors that are most likely to be infl uenced by the drone technology and to highlight the scenarios in which this technology can infl uence the achievement of the sdgs. one of the most promising spheres in this respect is the usage of drones as delivery vehicles in agriculture, e-commerce, and health care. moreover, drones can be eff ective for monitoring and surveillance in international and domestic law enforcement, wildlif e preservation and scientifi c research. keywords drone technology, unmanned aerial vehicles, sustainable development goals, united nations, agricultural drones, drone applications, drone risks for citation kitonsa, h., & kruglikov, s. v. (2018) significance of drone technology for achievement of the united nations sustainable development goals. r-economy, 4(3), 115–120. doi: 10.15826/recon.2018.4.3.016 значимость технологии дронов в достижении целей устойчивого развития оон х. китонса , с. в. кругликов уральский федеральный университет, екатеринбург, россия; e-mail: kitsxauxkissule@gmail.com резюме технология беспилотных летательных аппаратов, созданная военными, в настоящее время широко используется в коммерческих, профессиональных, промышленных и частных целях. беспилотные летательные аппараты (бпла), широко известные как «дроны», используются в различных секторах экономики, например, сельском хозяйстве, транспорте, инфраструктуре, развлечениях и телекоммуникациях. дроны не только экологичны и позволяют сократить количество выбросов углекислого газа, но они также экономичны в терминах времени и финансовых затрат. таким образом, беспилотные летательные аппараты могут оказаться серьезной силой, поскольку они обладают огромным потенциалом для использования в целях достижения целей устойчивого развития (sdg), установленных организацией объединенных наций и принятых в 2015 г. развивающиеся страны, например, страны, расположенные к югу от сахары, сталкиваются с голодом, эпидемическими заболеваниями, нищетой и другими проблемами. все эти проблемы можно решить с помощью технологии беспилотных летательных аппаратов. основная цель этой статьи – выявить сектора, на которые, скорее всего, повлияет технология беспилотных летательных аппаратов, и выделить сценарии, в которых эта технология может повлиять на достижение целей устойчивого развития. одной из наиболее перспективных сфер в этом отношении является использование дронов в качестве средств доставки в сельском хозяйстве, электронной торговле и здравоохранении. более того, беспилотные летательные аппараты могут быть эффективными для мониторинга и наблюдения в международных и внутренних правоохранительных органах, охране дикой природы и научных исследованиях. ключевые слова беспилотная техника, беспилотные летательные аппараты, цели устойчивого развития, организация объединенных наций, сельскохозяйственные беспилотные летательные аппараты, применение беспилотных летательных аппаратов для цитирования kitonsa, h., & kruglikov, s. v. (2018) significance of drone technology for achievement of the united nations sustainable development goals. r-economy, 4(3), 115–120. doi: 10.15826/recon.2018.4.3.016 116 www.r-economy.ru r-ecomony, 2018, 4(3), 115–120 doi: 10.15826/recon.2018.4.3.016 online issn 2412-0731 introduction developing countries, in particular those located in sub-saharan africa, have for a long time been facing severe famine, epidemic diseases, poverty and malnutrition issues [1; 2]. social and economic development in africa is aff ected by high mortality rate [3; 4] and poor health which are a result of malnutrition. in addition to environmental issues, the rapidly growing human population leads to an increased poverty rate, which still remains the highest in the world as of 2012 [5]. so far approaches to combating hunger and malnutrition have mostly focused on increased food production and food security paying less attention to the water scarcity problem. water has a vital role in ensuring food security as 70% of the population [6] in sub-saharan africa depends on agriculture for survival and more than 90% of this agriculture is sustained by direct rain. th erefore, agriculture still remains the major response to addressing hunger and malnutrition. in 2015, the international community adopted seventeen global goals for sustainable development (sdgs) to improve people’s lives by 2030. th ese sdgs comprise 169 targets [7–9] measured on local, national, regional and global levels and across various sectors. th e sdgs place greater demands on the scientifi c community to address climate change, renewable energy, food, health and water provision. great emphasis has been put on the need for social inclusion, economic development, and environmental sustainability and on outreach for marginalized groups [10]. “sustainable development is the development that meets the needs of the present without compromising the ability of the future generations to meet their own needs” [11]. th is study aims to provide a brief overview of the role that drone technology may play in meeting the sdgs. potential usage of drones to achieve sdgs recently, there has been a rapid growth in the popularity of unmanned aerial vehicles (uavs) commonly known as drones on the civil market. although originally drones were used in the military sector, they are now widely used both in civil and commercial domains for parcel deliveries and other purposes [12]. regardless of the fact that drone technology is still at its infant stage in terms of commercial usage, its current and speculated commercial applications have already shown the potential to dramatically alter several industries in terms of reducing on workload and general costs of production, time saving, increase on work effi ciency and productivity and also bridge gap between urban and rural areas. various stakeholders and actors, including governmental bodies, such as law enforcement agencies, commercial fi rms, scientific institutions [13] and private individuals, have realized the benefi ts inherent in the use of drones. hence, in the coming years, the adoption of drone technology will undoubtedly turn into a great trend as more and more industries are embracing the technology (figure). research 0.3 other 0.5 scienti�c 0.6 conservation 0.7 government 0.8 insurance 1.0 emergency 1.5 manufacturer 1.5 education 1.9 agriculture 8.0 construction 8.6 utilities 10.9 real estate 20.7 photo 42.9 top industries infl uenced by the drone technology in 2015 source: faa, th e verge drone project, 2015 let us now consider some of the sdgs put forward by the united nations and the potential usage of the drone technology to meet these goals. one of such goals is to end hunger, achieve food security and improved nutrition and promote sustainable agriculture. drone technology can be used in agricultural sector [14] in a number of ways, for example, to survey farm fi elds [15], to ensure product delivery [16] and to spray pesticides. rather than spraying the entire fi eld, the pesticide can be delivered to the right spot, only in the quantity needed, which means reduction in pesticides used, reduction in collateral damage to wildlife and also enhanced cost-effi ciency [17]. th e case of japan provides a good r-ecomony, 2018, 4(3), 115–120 doi: 10.15826/recon.2018.4.3.016 117 www.r-economy.ru online issn 2412-0731 illustration for such applications of the drone technology. since the 1970s, this country has accumulated signifi cant experience in this sphere. nearly 2,000 uavs are being used in japan today for agricultural spraying and planting operations [18]. furthermore, drones can connect farmers to markets and thus ensure that everyone has access to aff ordable nutritious food. chinese retail giant jd.com uses drones for e-commerce shipments to remote areas as well as to small towns or cities. it also transports farm equipment, fertilizers and seeds. apart from the agricultural usage of drones, they can also be successfully employed as delivery vehicles as they are able to traverse diffi cult landscapes and reach remote areas [19]. for instance, company zipline in rwanda has been delivering medical supplies to rural areas since 2016 by using drones and dropping off blood parcels attached to parachutes [29]. over 50 deliveries are made daily, thus saving thousands lives. th is experience has already drawn attention of other countries such as canada and tanzania seeking to adopt this practice [21]. moreover, drones can be employed in emergency situations as ambulances to provide fi rst aid to patients prior to being admitted to the hospital. in remote areas, medical services oft en take long to respond and to reach a patient with cardiac arrest or similar conditions [22]. in case of natural disasters, such as mudslides, earthquake, fl oods, explosions and wild fi res, immediate and swift medical attention is needed as lives some survivors depends on it. so drones can be used to quickly scan the area and locate the victims with the help of on-board cameras providing real-time data [23]. another promising sphere for drone usage is scientifi c research: as drones can withstand extreme conditions and are expendable, which makes them perfect research of diseases, pollution levels in regions with extreme weather conditions, radioactive areas and so on [24]. another important goal set forth by the un is to ensure sustainable economic growth, full and productive employment and decent work for all. in this respect, the drone technology promises diverse and attractive possibilities and is bound to reshape a number of business sectors whilst creating enormous employment opportunities [25]. among other things, drones have the potential to restructure the delivery market and open new business opportunities for small businesses such as local stores, pharmacies, fast-foods as well as large international and national businesses and government entities. drones also hold a lot of potential for the development of tourism. video cameras are attached to drones that can record and capture picturesque aerial views of diff erent places such as historical and natural sites. th ese aerial views and videos can be used to promote tourism [26], once they are shared or uploaded to any social network. moreover, drones can be used for virtual tourism: a tourist may be sitting at home and receiving live videos on the phone or computer in 3d format from a drone fl ying over places of interest [27]. one more signifi cant advantage of drones is that they are a safe and environmentally sound technology. deploying drones for last-mile delivery reduces the amount of carbon dioxide emissions which would have been produced if the goods were delivered by other means of transport [28]. moreover, drones have proven to be an eff ective alternative to fi reworks, which can spark off wildfi res. th erefore, drones were used for this purpose in california, colorado, and arizona in the usa, which suff ered from wildfi res. th us, these states decided to use a fl eet of 500 intel star drones to dance to patriotic music on 4th july celebrations. gas sensors and cameras can be mounted on drones and thus flown over volcanic areas, seas, forests among other places to monitor the situation. drones can detect natural disasters prior to their occurrence, thus alerting the citizens of a particular area and enabling them to evacuate [29]. another sphere in which drones can play an important role is surveillance of wildlife: for instance, kruger national park in south africa is known as the world’s number one poaching site for rhino [30]. having a fl eet of drones with cameras providing real time data and hovering all over the park will help the authorities to fi ght poaching. drones have proven instrumental in the utilities and energy sector to perform long-range aerial inspections of energy infrastructure, including pipelines and electric wires that can run for thousands of miles. power line maintenance and repairs can be very expensive and dangerous for workers. electric companies can use drones to access damaged power lines or structures and transmit pictures and information that can facilitate working on solutions more quickly, hence ensuring the achievement of sustainable development. 118 www.r-economy.ru r-ecomony, 2018, 4(3), 115–120 doi: 10.15826/recon.2018.4.3.016 online issn 2412-0731 th e un have also set the target to signifi cantly increase access to information and communications technology and to provide universal and aff ordable access to the internet in the least developed countries by 2020. mark zuckerberg has recently announced his plans to provide internet access to remote parts of the world by launching an initiative that involves the usage of solar-powered drones, capable of staying airborne for years and acting as movable wireless access points [31]. th e un’s sdg to ensure peace, justice and strong institutions can be met through effi cient law enforcement, for which drones have proven to be indispensable. drones can be deployed to pursue suspects in vast, open areas and areas that are inaccessible or diffi cult to access for human offi cers [32]. moreover, drones can be an eff ective technological solution for border patrol as they are capable of scanning wide areas, see through walls and track individual movements from the sky. th us, drones can be used to monitor the movements of illegal migrants. risks of using drones despite the obvious advantages of drones described above, the potential misuse of the drone technology grows proportionally to its popularity. drone operation can pose a threat to both public and national security, which explains why most legal authorities seem to be in two minds about making fully legalizing this technology. th ere is ongoing communication between the diff erent regulating bodies in diff erent countries such as the federal aviation administration (faa), the european aviation safety agency (easa), transport canada and civil aviation authority (caa), and others. it should be noted here that most of the countries have used the faa’s guidelines for their drone regulations. to balance safety and innovation, international cooperation is required to enable countries work towards the common goal and ensure the maximum safety of drone usage. drone regulations set by the european aviation safety agency [33] were adopted by 27 member states (austria, belgium, bulgaria, cyprus, czech republic, denmark, estonia, finland, france, germany, greece, hungary, ireland, italy, latvia, lithuania, luxembourg, malta, netherlands, poland, portugal, romania, slovak republic, slovenia, spain, sweden, and the uk). conclusion it is evident that drones are going to make a great contribution to the achievement of the sdgs. drone technology not only has a promising robust infl uence in the agricultural sector, but in a number of other sectors. despite all the above-described advantages off ered by the development of the drone technology, legal regulations in some countries, russia in particular, impede effi cient use of drones. full legalization of drone operations is required in all sectors of economy. countries, such as china, rwanda, japan and the usa, have taken steps in this direction. th erefore, it can be concluded that it is only a matter of time until drones are fully legalized for civil and commercial use. in the context of ssa, the drone technology might turn out to be the ultimate path to fi nally reducing or completely eliminating hunger, poverty and malnutrition problems. in future studies, we intend to analyze and compare practices of drone operation in ssa and in russian regions, for example, in the urals and in yakutsk, in order to show the potential for the achievement of sdgs on these territories. references 1. pinstrup-andersen, p., rahmanian, m., allahoury. a., et at. 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(2017). uavs: regulations and law enforcement. international journal of remote sensing, 38(8–10), 3054–3067. doi: 10.1080/01431161.2017.1302115 information about the authors haula kitonsa – researcher, graduate school of economics and management, ural federal university (19 mira st., 620002 ekaterinburg, russia); e-mail: kitsxauxkissule@gmail.com. sergey v. kruglikov – head of academic department of controlled systems, graduate school of economics and management, ural federal university (19 mira st., 620002 ekaterinburg, russia); e-mail: svk@imm.uran.ru. 4 www.r-economy.ru r-ecomony, 2018, 4(1), 4–9 doi: 10.15826/recon.2018.4.1.001 online issn 2412-0731 original paper doi: 10.15826/recon.2018.4.1.001 a comparative study of regional strategies of northeast asian countries sichen zhang institute of northeast asian studies, heilongjiang provincial academy of social sciences, harbin, china; e-mail: sichenzhang@163.com abstract after the global financial crisis in 2008, the us and europe have experienced anemic economic growth, whereas northeast asia has become the most economically dynamic region worldwide. the region faced such challenges as rapid economic globalization and regional economic integration, in-depth adjustment of global economic and trade patterns, the obama administration’s asian pivot strategy, and domestic economic transformations. to address these challenges, northeast asian countries put forward development plans and regional strategies: japan’s abenomics since 2012; china’s silk road economic belt and 21st century maritime silk road since 2013; south korea’s eurasian initiative proposed by president park geun-hye in 2013; mongolia’s prairie road plan since 2014; eurasian economic union led by russia since 2015; the tpp revived by japan as cptpp after the us withdrawal; and the new north policy proposed by south korea’s newly-elected president moon jae-in in 2017. these projects reflect the countries’ determination to play a more active role in the bilateral and multilateral cooperation in the region. the regional strategies are shaped by each country’s specific economic conditions, geopolitical and diplomatic needs. although these strategies are somewhat competitive in such aspects as resources and influence, they also offer more prospects for cooperation and integration of regional economies. keywords northeast asia; regional strategy; comparative study; belt and road initiative; trans-pacific partnership; tpp for citation zhang, s. (2018) a comparative study of regional strategies of northeast asian countries. r-economy, 4(1), 4–9. doi: 10.15826/recon.2018.4.1.001 сравнительное исследование региональных стратегий североазиатских стран с. чжан институт североазиатских исследований, академия социальных наук провинции хэйлунцзян, харбин, китай; e-mail: sichenzhang@163.com резюме после глобального финансового кризиса в 2008 г. сша и европа столкнулись со снижением темпов экономического роста, в то время как северо-восточная азия стала самым регионом с наилучшей динамикой экономики в мире. регион столкнулся с такими проблемами, как стремительная экономическая глобализация и региональная экономическая интеграция, углубленная адаптация глобальных экономических и торговых моделей, стратегия администрации обамы «азиатская ось» и внутренние экономические преобразования. для решения этих проблем страны северо-восточной азии выдвинули ряд планов развития и региональных стратегий, среди которых: японская «абеномика» 2012 г., китайские проекты «новый шелковый путь» и «морской шелковый путь xxi века» 2013 г.; южнокорейская «евразийская инициатива»; монгольский план «прейри-роуд» 2014 г.; «евразийский экономический союз» 2015 г., возглавляемый россией; обновленное после выхода сша транстихоокеанское партнерство; и, наконец, политика «нового севера», предложенная недавно избранным президентом южной кореи мун чжэ ином в 2017 г. эти проекты отражают решимость стран играть более активную роль в двустороннем и многостороннем сотрудничестве в регионе. региональные стратегии определяются конкретными экономическими условиями каждой страны, геополитическими и дипломатическими потребностями. хотя эти стратегии несколько конкурируют в таких аспектах, как ресурсы и влияние, они также предлагают больше возможностей для сотрудничества и интеграции региональных экономик. ключевые слова северо-восточная азия; региональная стратегия; сравнительные исследования; инициатива «один пояс, один путь»; транс-тихоокеанское партнерство (ттп) for citation чжан, с. (2018) сравнительное исследование региональных стратегий североазиатских стран. r-economy, 4(1), 4–9. doi: 10.15826/recon.2018.4.1.001 https://doi.org/10.15826/recon.2018.4.1.001 http://doi.org/10.15826/recon.2018.4.1.001 r-ecomony, 2018, 4(1), 4–9 doi: 10.15826/recon.2018.4.1.001 5 www.r-economy.ru online issn 2412-0731 introduction throughout its history, northeast asia has been dynamically developing and has been an arena for complex relationships and geopolitical tensions. on the one hand, problems like north korean nuclear weapons, island disputes, and superpower games create uncertainty of deve lopment; on the other hand, the centre of global economic growth is moving eastwards, which turns northeast asia into the locomotive of the world economic development. countries in the region devised their plans of national development and regional strategies, which brought about a complex pattern of regional economic cooperation. regional strategies and the recent progress of northeast asian countries in 2013, chinese president xi jinping first proposed the belt and road initiative, which focuses on the idea of peace and cooperation, openness and inclusiveness, mutual learning and mutual benefit as the incarnation of the silk road spirit. the platform of the initiative is provided by the asian infrastructure investment bank and the silk road fund. the central concept for the initiative is the community of common destiny [1]. over the past four years, the positive role of the initiative has become obvious as it gained the support of over a hundred countries. the initiative differs from the existing rule-oriented regional cooperation mechanisms because it offers a new deve lopment-oriented mode, which provides eu rasian countries with an open platform for cooperation and integration of resources. the belt and road initiative comprises six economic corridors with china-mongolia-russia economic corridor as the cornerstone. in june 2016, the heads of the three countries – china, russia, and mongolia – signed the draft plan of the construction of china-mongolia-russia economic corridor. since then, the common concern of the three partner countries has become the question of how to integrate the belt and road initiative, russia’s trans-eurasia railway and mongolia’s prairie road. the economic corridor is expected to strengthen their trade relationships, facilitate the exchange of human resources and promote common prosperity; it serves as a model for strategic integration and cooperation between countries in northeast asia [2]. as a major economy, japan is closely connected with the united states in the political sphere and in terms of security, which makes it difficult for japan to find its proper place and identity and makes japan sway between east asia and asia pacific. from the east asian community to asean +6 (comprehensive economic partnership for east asia – cepea), from the regional comprehensive economic partnership (rcep) to the trans-pacific partnership (tpp), the constant goal of japan’s economic strategy is to fight for dominance in the trade of the asia pacific region. in march 2013, shinzo abe’s administration, despite the protests of the domestic opposition, formally declared japan’s entry into the trans-pacific partnership, the us-led twenty-first century trade agreement as its twelfth participant. japan is interested in the tpp not only because it seeks to dominate in the sphere of trade and investment but also because its government wants to counter the growing influence of china in asia-pacific, which coincides with america’s asia-pacific rebalancing strategy [3]. u.s. president donald trump quit the tpp soon after he took office in 2017. after that, prime minister shinzo abe in vain tried to persuade america to return. failing to do so, he decided to revive the tpp. in november, the eleven remaining members decided that they would continue to move ahead without the us. a new free trade agreement comprehensive progressive trans-pacific partnership (cpttp) will be signed after the conclusion of negotiations. although the scale of cptpp has reduced significantly, japan’s intention to take the lead in this new asia-pacific economic cooperation system remains unchanged. south korea’s eurasian initiative is an important international cooperation initiative and national development strategy, which was proposed by former president park geun-hye in october 2013. it aims to expand south korea’s foreign trade and promote the country’s economic and trade cooperation with european and asian countries for sustainable development of eurasia [4]. as a neighbor and strategic partner of china, south korea has been actively participating in china’s belt and road initiative. in march 2015, south korea decided to join the asian infrastructure investment bank. south korea is also actively involved in promoting the free trade agreement (fta) between china, japan, and south korea. in december 2015, china-south korea fta came into effect, which had a positive impact on chihttps://doi.org/10.15826/recon.2018.4.1.001 6 www.r-economy.ru r-ecomony, 2018, 4(1), 4–9 doi: 10.15826/recon.2018.4.1.001 online issn 2412-0731 na-japan-south korea fta negotiations and was beneficial for south korea’s economic integration in northeast asia. however, the influence of the situation on the peninsula and the us-south korean alliance have soured the close economic and trade relations between china and south korea. in september 2016, south korea, despite the strong opposition from china, russia and other neighboring countries, allowed the us to deploy its thaad missile system on its territory. since then, the relationship between china and south korea have deteriorated. in march 2017, the impeachment of president park made the eurasian initiative face an uncertain future. in september 2017, the incumbent president moon jae-in introduced the new north policy, which aims to connect the korean peninsula, the russian far east, northeast asia and eurasia continent. this policy is expected to enhance economic cooperation in the region, eventually resulting in an integrated regional organization similar to the eu, which would allow the countries to ease the geopolitical tensions and achieve common prosperity [5]. russia is a big eurasian country, whose economic interests are largely oriented towards the eu. since 2014, the economic sanctions imposed by western countries and the following economic downturn forced russia to start seeking new strategic support and opportunities for economic cooperation in asia-pacific. in january 1, 2015, the russian-led eurasian economic union was established. it is expected that this treaty will lay the foundation for multilateral integration within the cis region, compared to that of the european union [6]. it is also planned that the eurasian economic alliance will provide a free flow of goods, services, personnel and funds by 2025. the ultimate goal is to create a supranational alliance and to form a single market. russia has launched a series of projects to accelerate the development of the far east, to stimulate the transition of the russian economy and create a more advantageous environment for attracting investment from the asia pacific countries. in addition, russia is also promoting economic and trade exchanges with china and other asian pacific countries, actively participates in the construction of china-russia-mongolian economic corridor, in the strategic integration of the belt and road initiative and the eurasian economic union. in june 2016, in his speech at st petersburg international economic forum, president putin called for the establishment of the eurasian partnership, which should include the eurasian economic union, india, iran, south korea, china and cis countries. the eurasian partnership is a logical continuation of the look east strategy, expansion of the eurasian economic union, and the companion volume of the belt and road initiative [7]. located between the two great powers of china and russia, mongolia occupies an important geographical position. in order to revitalize its economy, promote industrial innovation and develop its energy and mining industry, mongolia proposed the prairie road plan in september 2014. the plan comprises five projects of building an expressway connecting russia and china, electric circuit, natural gas and oil pipelines, and an electrified railway across mongolia [8]. the idea behind the plan is to strengthen partnership with eurasian countries in logistics, energy and trade and to integrate into the asia pacific economic through the construction of modern infrastructure. in may 2017, mongolian prime minister jargaltulga erdenebat expressed willingness to participate in mutually beneficial cooperation within the framework of the belt and road initiative. the two governments signed the memorandum of understanding integration of mongolia’s development road and china’s belt and road. development road is the new name for prairie road project, with the basic connotation unchanged [9]. a comparison of regional strategies and development trends of northeast asian countries after the global financial crisis in 2008, the us and europe experienced anemic economic growth, whereas northeast asia has become the most economically dynamic region worldwide. the region faced such challenges as rapid economic globalization and regional economic integration, in-depth adjustment of global economic and trade patterns, the obama administration’s asian pivot strategy, and domestic economic transformations. to address these challenges, northeast asian countries put forward development plans and regional strategies: japan’s abenomics since 2012; china’s silk road economic belt and 21st century maritime silk road since 2013; south korea’s eurasian initiative proposed by president park geun-hye in 2013; mongolia’s prairie road plan since 2014; eurasian economic union led by russia since 2015; the tpp revived by https://doi.org/10.15826/recon.2018.4.1.001 r-ecomony, 2018, 4(1), 4–9 doi: 10.15826/recon.2018.4.1.001 7 www.r-economy.ru online issn 2412-0731 japan as cptpp after the us withdrawal; and the new north policy proposed by south korea’s newly-elected president moon jae-in in 2017. these strategies reflect the countries’ determination to play a more active role in the process of bilateral and multilateral cooperation in this region [10]. the similarities and differences of these strategies are largely determined by each country’s different economic, geopolitical and diplomatic needs. the belt and road initiative, covering more than 64% of the world’s population, is the largest in scale since it is open not only for countries located along the belt and road but also for any other countries willing to participate. after the us quit the tpp, the new, japan-led cptpp now includes eleven members in northeast asia, southeast asia, oceania, north america and south america. this organization follows the diplomatic concept of global diplomacy proposed by abe’s administration. the eurasian partnership led by russia has expanded the geographical range of the eurasian economic union from the six former soviet union countries in central eurasia to all asian and european countries and regional economic organizations. south korea’s eurasian initiative is focused on the korean peninsula, russia and china, while the new north policy is designed to create an economic community extended to the northeast asia and even to eurasia. mongolia wants to play a more active role as the eurasian land bridge which connects northeast asian countries with those in central asia, west asia and europe through the prairie road [11]. unlike other ftas in asia pacific region, the tpp has high standards on labour, the environment, rules of origin, intellectual property, and government procurement. compared with the tpp, the belt and road initiative is more development-oriented as it seeks to integrate the resources of regional countries and achieve common development and prosperity [12]. it is a global public product created by china and jointly built by the participating countries. russia’s eurasian economic union is an institutional regional integrated cooperation organization system of high geopolitical significance. the eurasian partnership is an economic development initiative aimed at promoting integration in eurasia. both south korea and mongolia’s development in northeast asia region is closely related to big power politics, which means that both of their policies seek strategic integration with china and russia. as for strategic goals, the tpp aims for bigger external markets, and more importantly, it seeks to establish new global trade and investment rules, play the leading role in asia pacific regional economic cooperation and counter china’s growing regional influence in east asia. the initiative connects the development of china with countries along the belt and road through connectivity policies, infrastructure, trade, finance and people. by fostering interconnections and creation of a new open, inclusive, and balanced regional economic cooperation mechanism, the initiative aims to form a mutually-beneficial community of interests or a community of common destiny. russia’s eurasian partnership puts the eurasian economic union within a wider framework of eurasian integration, treating it as an updated version of look east strategy and as a part of russia’s long-term strategy for revitalization of the far east [13]. the new president of south korea moon jae-in’s policy was designed to address the problem of policy is the escalating north korean nuclear crisis. thus, the aim of this policy is to alleviate the geopolitical tension in northeast asia, create favorable conditions for long-term peace and regional cooperation, and ultimately achieve common prosperity. the belt and road initiative has been implemented for four years now and comprises over a hundred countries and international organizations. more than 30 countries are involved into institutional cooperation and more than 40  countries and international organizations have signed cooperation agreements with china. chinese enterprises invest more than 50 billion us dollars in the countries along the belt and road; they are building 56 economic and trade cooperation zones in more than 20 countries, thus creating a large number of jobs. the concept of building a community of common destiny through the construction of the belt and road is gaining more and more recognition and support in the global community. in february 2016, the tpp agreement was signed by twelve countries representing about 40% of the world’s economic output, which made the tpp the largest fta in the world. after the withdrawal of the us, despite some pessimistic forecasts, the impact of the cptpp on the asia pacific regional integration process is still tremendous. this effect is likely to persist even if the us never returns. in east asia, japan is also involved in rcep negotiations and chihttps://doi.org/10.15826/recon.2018.4.1.001 8 www.r-economy.ru r-ecomony, 2018, 4(1), 4–9 doi: 10.15826/recon.2018.4.1.001 online issn 2412-0731 na-japan-south korea fta negotiations. if the cptpp is successfully signed and comes into force, together eu-japan economic partnership agreement (epa), japan will further enhance its economic influence in the world. this means that other east asian countries should contemplate some countermeasures [14]. compared with the belt and road initiative and the tpp, other regional strategies attracted less attention from the outside world. for example, although the eurasian economic union came into force three years ago, it was weakened by russia’s declining economy and western sanctions, which made member states seek help from europe and the united states. south korea upgraded the eurasian initiative to the new north strategy, mongolia changed the prairie road to development road in order to respond to the changing domestic and international situation better. although the regional strategies of northeast asian countries are competitive in terms of resources and influence, they also complement and support each other, so the collaboration space is far greater than that of competition [15]. china’s belt and road has provided a new type of regional economic cooperation mode in northeast asia. unlike the previous regional cooperation mechanisms, the belt and road is an open platform for cooperation, which enables countries with different development strategies to complement each other. the belt and road initiative is connected with other regional projects seeking to enhance the countries’ competitive advantages and help them build common interests: china’s belt and road and russia’s eurasian economic union; belt and road and mongolia’s prairie road; belt and road and south korea’s eurasian initiative, and china-mongolia-russia economic corridor. the coordinated development of each country should stimulate integration of regional economies and promote the asia pacific regional integration. conclusion although the us is not a traditional northeast asian country, its presence in the region must not be underestimated. barack obama’s asia-pacific rebalance strategy and the tpp agreements have profoundly affected the pattern of economic cooperation in northeast asia. at the beginning of 2017, when president donald trump took office, he announced his withdrawal from the tpp to fulfill the commitments of putting america first and making america great again that he had taken during his presidential campaign. in november, during his first trip to asia, president trump proposed the free and open indo-pacific strategy  – an important symbol of his asia-pacific strategic readjustment. the strategy focused on india as an important strategic partner together with japan and australia, and was, therefore, welcomed in japan. with the introduction of the concept of indo-pacific to replace asia-pacific, the focus of asia-pacific strategy has been extended to the indian ocean. india, which is enjoying a gradual rise in its economic and geopolitical importance, is used to reintegrated the geostrategic layout of the asia-pacific region. the change of the name from asia-pacific rebalance to indo-pacific, however, does not mean that the us government have abandoned their goal to contain china’s growth. at this stage, although the indo-pacific strategy cannot yet be regarded as a mature regional strategy, we should not underestimate its impact on the process of the northeast asian integration. the main driving force behind the reform of the future order in northeast asia will be provided by the growing regional influence of china and the strategic choice of the united states. against the current slowdown in world economic growth and the rising anti-globalization sentiments, the economy of northeast asia, unlike the rest of the world, still maintains its vitality and growth. the year of 2017 saw many events that were important for economic and trade cooperation in northeast asia: for example, in may, china hosted the belt and road forum for international cooperation in beijing, involving delegations from japan and south korea. at the forum, it was announced that 76 major agreements had been signed and 270 deliverable results had been achieved. it was the first such official occasion when japanese prime minister shinzo abe expressed his willingness to cooperate. moreover, japan sent the largest delegation of over 250 businesspeople from three major economic groups to china in november. in november 2017, the apec summit in vietnam reaffirmed the commitment of its participants to supporting sustainable economic growth and cooperation. at the meeting of the rcep participating countries, a joint statement was issued that the rcep would conclude the negotiations in 2018, thus marking an important step towards signing a multilateral free trade agreement in the asia pacific region. https://doi.org/10.15826/recon.2018.4.1.001 r-ecomony, 2018, 4(1), 4–9 doi: 10.15826/recon.2018.4.1.001 9 www.r-economy.ru online issn 2412-0731 references 1. zhao kejin. 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(2015). on strategic connectivity between the obor initiative and mongolian pasture road strategy. global review, 6, 51–65. 9. zhang xiujie. (2017). coordinating “belt and road” initiative and “development road” project. inner mongolia social sciences (chinese), 38(5), 200–205. 10. zhang yunling. (2017). the regional relationship of northeast asia: pattern, order & prospect. journal of northeast asia studies, 2, 3–8. 11. yu hongyang, bekhbaatar odgerel & ba dianjun. (2015). on the basis and obstacle of china-mongolia-russia economic corridor. northeast asia forum, 1, 96–106. 12. ren xiaofei & da zhigang. (2016). northeast asia regional connectivity cooperation prospects. the border economy and culture, 12, 12–14. 13. gao qi. (2016). the historical contexture and prospect of russian regional strategy. russian central asian & east european market, 3, 65–73. 14. zhang yunling. (2017). japan’s regional economic strategy in asia-pacific and east asia. japanese studies, 3, 1–11. 15. wang hao & xu jia. (2016). the cooperation of china-japan-korea fta construction in northeast asia. asia-pacific economic review, 4, 3–8. information about the author sichen zhang – research assistant of institute of northeast asian studies, heilongjiang provincial academy of social sciences (no. 501 youyi road daoli district, harbin, china); e-mail: sichenzhang@163.com. u.s. president donald trump took the first asian trip to japan, south korea, china, vietnam and the philippines. he signed cooperation agreements worth a total of 253.5 billion u.s. dollars during his visit to china, setting a new record of world trade and economic cooperation. although economic and trade cooperation in northeast asia will still suffer from such negative factors such as the us-japan-rok military alliance, north korean nuclear crisis, island disputes and so on, the overall trend is still favo rable. although the cptpp led by japan and the indo-pacific strategy of the u.s. will add uncertainty to the process of regional economic integration in northeast asia, in the long run, the high-standard terms of trade advocated by the tpp will promote other ftas in asia-pacific region. looking ahead, it is highly likely that countries in northeast asia should continue to build common interests, promote modernization and coordinate their development strategies to ensure regional economic integration. https://doi.org/10.15826/recon.2018.4.1.001 82 www.r-economy.ru r-ecomony, 2018, 4(3), 82–87 doi: 10.15826/recon.2018.4.3.012 online issn 2412-0731 original paper doi: 10.15826/recon.2018.4.3.012 diversification of tourism and economic development of kazakhstan aksanat zh. panzabekova institute of economics of the committee of science of the ministry of education and science of the republic of kazakhstan, almaty, kazakhstan; e-mail: aksanat@mail.ru abstract th e article aims to demonstrate how the economic conditions of kazakhstan determine the need for horizontal diversifi cation in the tourism industry by analyzing the correlations between the volume of tourism services and such indicators as the gdp, unemployment, tenge exchange rate, infl ation and the number of small and medium-sized enterprises. th e overview of the tourism industry in the republic and its development prospects shows that tourism has been playing an increasingly important role in the country’s economy. th e negative factors that hinder development of the tourism industry in kazakhstan include the lack of transport and information infrastructure, the unstable banking sector and unaff ordable business loans, the lack of qualifi ed personnel in marketing, catering and hospitality spheres. a conclusion is made that the potential for the development of recreation, sport, cultural, ecological and religious tourism is not fully realized in the country and that a more diversifi ed portfolio of tourism products is required. moreover, it is necessary to enhance the country’s economic growth, that is, to reduce its dependence on oil and gas, support the development of the banking sector and implement structural reforms. th e results of this research can be used for designing state and regional tourism support programs in kazakhstan. keywords identifi cation, diversifi cation, tourism, economic development, kazakhstan for citation panzabekova, a. zh. (2018) diversification of tourism and economic development of kazakhstan. r-economy, 4(3), 82–87. doi: 10.15826/recon.2018.4.3.012 диверсификация туризма и экономического развития казахстана а. пазанбекова институт экономики комитета науки министерства образования и науки республики казахстан, алматы, казахстан; e-mail: aksanat@mail.ru резюме целью статьи является демонстрация того, как экономические условия казахстана определяют необходимость горизонтальной диверсификации в индустрии туризма путем анализа корреляций между объемом туристических услуг и такими показателями, как ввп, безработица, обменный курс тенге, инфляция и количество мелких и средних предприятий. обзор индустрии туризма в республике и перспектив ее развития показывает, что туризм играет все более важную роль в экономике страны. отрицательными факторами, препятствующими развитию индустрии туризма в казахстане, являются отсутствие транспортной и информационной инфраструктуры, нестабильный банковский сектор и недоступные бизнес-кредиты, отсутствие квалифицированного персонала в сферах маркетинга, общественного питания и гостиничного бизнеса. в статье сделан вывод о том, что потенциал развития рекреационного, спортивного, культурного, экологического и религиозного туризма в стране не полностью реализован и что требуется более диверсифицированный портфель туристических продуктов. более того, необходимо усилить экономический рост страны, то есть уменьшить зависимость от нефти и газа, поддержать развитие банковского сектора и провести структурные реформы. результаты этого исследования могут быть использованы для разработки государственных и региональных программ поддержки туризма в казахстане. ключевые слова идентификация, диверсификации, туризм, экономическое развитие, казахстан для цитирования panzabekova, a. zh. (2018) diversifi cation of tourism and economic development of kazakhstan. r-economy, 4(3), 82–87. doi: 10.15826/recon.2018.4.3.012 r-ecomony, 2018, 4(3), 82–87 doi: 10.15826/recon.2018.4.3.012 83 www.r-economy.ru online issn 2412-0731 introduction th e travel and tourism industry is subject to a range of external pressures, such as political and economic instability in tourist destination regions as well as demographic processes in the countries where tourism companies are located [1]. th erefore, diversifi cation of tourist packages, geographical markets, and tourism technologies is widely used in developed countries. in kazakhstan, this can prove to be a viable solution for the problems the tourism industry is currently facing, making this sector more fl exible and adaptable to change. th ere is a vast body of research that deals with various aspects of diversifi cation in tourism: for instance, the question of priorities in diversifi cation on the level of individual enterprises [2–4], on the level of rural areas, regions and countries [5–8]. th is paper aims to show how the current economic conditions in kazakhstan determine the need to diversify the portfolio of tourism products in kazakhstan to make the industry more effi cient. methodology our methodology is based on dialectic, systemic, and descriptive approaches, which allow us to study the problem by adopting the method of scientifi c abstraction, logical analysis, comparison, cause and eff ect analysis. by applying these methods and approaches, we analyze the link between diversifi cation in tourism industry and the country’s economic development and identify the factors that infl uence the development of tourism in kazakhstan. th erefore, we have chosen the following key economic indicators: gdp, unemployment, tenge exchange rate, infl ation, and the number of small and medium-sized enterprises (smes). we also analyzed the data provided by international organizations’ reports. general characteristics of the tourism industry in kazakhstan tourism is one of the main sectors of economy in kazakhstan, crucial for the country’s social, cultural and environmental development. although tourism is one of the world’s largest industries, ranking third in terms of revenues aft er oil and gas industry and car manufacturing [9], in kazakhstan, it accounts for only 0.9% of the gdp. according to th e travel & tourism competitiveness report of the 2017 world economic forum, kazakhstan ranks 81st among 136 countries1. 1 kazakhstan ranks 81st in the wef travel & tourism competitiveness index. retrieved from https://informburo.kz/ novosti/kazahstan-zanyal-81-mesto-v-reytinge-konkurentosposobnosti-v-sfere-turizma.html in  2017, the government of kazakhstan adopted the roadmap for tourism development in kazakhstan, which set the target of increasing the share of tourism in the gdp to 8% by 20252. current trends in the development of tourism in kazakhstan can lead to the improvement of the situation in the future: for instance, while in 2000, 1.47 million of foreign tourists visited kazakhstan, their number rose to 7.7 million in 20163. at the same time, according to international experts, tourism in kazakhstan still has a long way to go, despite the abundance of sites of outstanding natural beauty. th e negative factors that are off -putting to tourists are the poor quality of services and the lack of developed transport infrastructure4. research literature identifi es three major types of tourism – inbound, outbound and domestic. as for the purpose of travel, we can distinguish cultural, ethnic, religious, sport, recreational, educational, exotic, ecological, transit, rural, adventure, medical, space, event and academic tourism [10]. outbound tourism is the most developed type of tourism in kazakhstan: the country’s residents travel to europe, america, middle east, and south-eastern asia. in 2017, there were 23,524.9  thousand of tourists, out of whom 10,260.8 were outbound tourists; 7,701.2, inbound tourists; and 5,562.9, domestic tourists5. in this paper, we are going to focus on inbound and domestic tourism in kazakhstan. according to the statistics committee of the ministry of national economy, the structure of inbound tourism by trip purpose looks the following way (table 1). out of 12,117 visitors arrived in kazakhstan in june 2017, 46% came to see friends and family (which does not exclude other purposes); 20.6%, for recreation; and 24.6%, were business travellers. th e remaining 8.8% had other purposes. 2 decree of the government of the republic of kazakhstan of 30 june 2017 no 406 roadmap for tourism development in kazakhstan until 2023. retrieved from https://online.zakon. kz/document/?doc_id=39370590 3 international tourism, number of arrivals. kazakhstan. workbank. world development indicators. retrieved from http://mecometer.com/topic/international-tourism-number-of-arrivals 4 summer holiday in kazakhstan? astana eases visa restrictions to attract tourists. retrieved from https://www. theguardian.com/world/2014/jul/17/kazakhstan-eases-visa-restrictions-attract-tourists 5 statistics committee, ministry of national economy, kazakhstan (2018) key indicators of tourism. in: statistical bulletin. astana. 84 www.r-economy.ru r-ecomony, 2018, 4(3), 82–87 doi: 10.15826/recon.2018.4.3.012 online issn 2412-0731 table 1 distribution of inbound travellers by the purpose of visit in june 2017 purpose number of visitors leisure, recreation and holiday 2,498 visiting friends and family 5,573 education and professional training 336 health and medical treatment 408 religion and pilgrimage 110 shopping 163 transit 37 business 2,992 total 12,117 source: statistics committee, ministry of national economy, kazakhstan (2018) distribution of inbound travellers by the purpose of visit. in: statistical bulletin. astana. it should be noted that diversifi cation of tourist packages is insuffi cient, which makes the country unattractive for foreign tourists and is detrimental to the revenues of tourist companies. in 2017, the total volume of hospitality services in kazakhstan was 108,359,760.4 thousand tenge, which accounted for 2.1% of the country’s gdp. art, entertainment and leisure accounted for 1.8%. out of 7.7  million of inbound tourists, 1.3  million or 16.4% used the services of resort facilities, hotels, and facilities located in protected natural areas6. tourism diversification and economic development in kazakhstan to analyze the connection between tourism diversifi cation and characteristics of kazakhstan’s economic development we need to look at the key indicators (table 2). table 2 key indicators of macro-economic development in kazakhstan in 2013–2017 year indicator gdp (million tenge) tenge exchange rate (usd/kzt)* unemployment (%) infl ation (%) th e number of smes 2013 35,999,025.1 152.3 5.2 4.8 888,233 2014 39,675,832.9 179.19 5.0 7.4 926,844 2015 40,884,133.6 221.73 5.1 10.4 1,242,579 2016 46,971,150.0 342.16 5.0 8.5 1,106,353 2017 53,101,281.8 326 4.9 7.1 1,145,994 source: statistics committee, ministry of national economy, kazakhstan (2018) key indicators of socio-economic development of the republic of kazakhstan. in: statistical bulletin. astana; (*) average offi cial foreign currency rates in the period 2013–2017. national bank of the republic of kazakhstan. retrieved from http://nationalbank.kz/?docid=763&switch=russian 6 statistics committee, ministry of national economy, kazakhstan (2018). key indicators of tourism. in: statistical bulletin. astana. as table 2 illustrates, there is a stable growth in the gdp in each period; the national currency is unstable (since 2013, the dollar-tenge exchange rate has changed by 138%); the level of unemployment is relatively stable; infl ation is volatile, although it does not reach the critical values; the number of smalland medium-sized businesses (smes) is growing. if we compare these indicators with the volume of services (table 3), we will see the correlation between the development of tourism industry and the key economic indicators. table 3 volume of services provided by accommodation facilities in diff erent years (ths. tenge) year volume of services 2013 59,714,164.2 2014 72,401,941.1 2015 72,597,228.3 2016 82,853,434.6 2017 108,359,760.4 source: statistics committee, ministry of national economy, kazakhstan (2018). volume of services provided by accommodation facilities. in: statistical bulletin. astana. th e results of our calculations are shown in table 4. table 4 coeffi cients of correlation between macro-economic indicators and the volume of services provided by accommodation facilities pairs of indicators correlation coeffi cient gdp – volume of services 0.98 tenge exchange rate 0.82 unemployment – volume of services –0.90 infl ation – volume of services 0.17 th e number of smes – volume of services 0.52 note: based on the data from table 2 and 3. th us, there is virtually no correlation between infl ation and the volume of services provided by accommodation facilities. th ere is, however, a very strong inverse correlation between unemployment and the volume of services since the development of tourism means more jobs and is associated with the decreasing rate of unemployment. th ere is also a strong correlation between the gdp and the volume of services as both of these indicators have been growing steadily. we cannot be absolutely sure about the impact of the gdp on the growth of tourism or vice versa. th e correlation between the volume of services and the two remaining indicators is more evident, though. r-ecomony, 2018, 4(3), 82–87 doi: 10.15826/recon.2018.4.3.012 85 www.r-economy.ru online issn 2412-0731 for instance, the drop in tenge value caused an increase in the demand for services because foreign tourists were attracted by lower prices. th us, the falling exchange rate of the national currency had a positive impact on inbound tourism. th ere is a weak correlation between the number of smes and the volume of services. th erefore, we can conclude that tourism accounts for an insignifi cant share in the overall increase in the number of smes in the country and that the infl ux of new companies in the tourism industry in kazakhstan is comparatively small. th is fact is supported by the data of the statistics committee, which recorded a 9% decline in the sphere of inbound tourism. in the fourth quarter of 2017, kazakh tourists preferred to travel abroad (63% of respondents against 49% in 2016). th ey were attracted by the better developed tourist infrastructure, better cost-quality balance, and the wider choice of accommodation facilities. at the same time, in kazakhstan, there was a rise in demand for overseas tours and a decrease in the employment rate in the tourism sector in comparison with 2016. business owners themselves pointed out that the decline in demand for tourist services had the biggest infl uence on the economic performance of their companies. to gain a better understanding of the problem, let us look at the reports published by international organizations. th e world bank pointed out the three major risks faced by the country’s economy: the weaker external demand, escalation of problems in the banking sector, and weak implementation of the structural reforms. th erefore, it is recommended that the government should make progress in deepening structural reforms aimed at diversifi cation of economy and to enhance the country’s economic potential in non-oil sectors. according to the report, the oil sector was the main driver of economic growth, as oil output increased by 12.5% in the fi rst nine months of 2017 due to the launch of production at the off -shore oil fi eld kashagan7. another factor contributing to this trend was the increase in oil prices by 24%. additionally, the construction sector rebounded due to new large capacity expansion projects in the oil sector. in other sectors, there is a growth in the production sphere, agriculture, transport and trade. 7 world bank kazakhstan’s economy is rising – it is still all about oil. country economic update. retrieved from http://www.worldbank.org/en/country/kazakhstan/publication/economic-update-fall-2017 despite the rise of foreign trade, the volume of direct foreign investment has shrunk. according to the world bank’s forecast, if kazakhstan manages to implement its structural reforms successfully, it will help increase diversifi cation and the potential of the country’s economy. th e 100 concrete steps program and privatization are expected to reduce the role of the state in economy and enhance trade in sectors other than oil and gas. a robust fi scal and monetary policy can maintain the economic and price stability, which help attract more investment to the nonoil sectors. th e government still needs to address such problems as the prevalence of state-owned companies in economy, the lack of qualifi ed workforce, the macro-economic vulnerabilities, and the lack of interregional cooperation8. th e decline in the real income of the population and the falling national currency, which make exchange transactions unprofi table, hamper the development of outbound tourism. at the same time the development of inbound and domestic tourism is diffi cult due to the underperforming national tourist companies, which fail to devise and promote tourist routes to destinations in kazakhstan. th eoretically, it would be possible to stimulate companies through aff ordable business loans. th is, however, seems problematic taking into consideration the unstable banking sector and the comparatively high refi nancing rate in kazakhstan. th us, kazakhstan has potential for tourism development but fi nds it hard to realize it, both in terms of domestic and international tourism. as of 2016, there are 2,031 tourist companies operating in the country. th ere are 2,754 accommodation facilities with 128,062 beds, which is 16.6% more than in 2015. th e occupancy rate in 2016 was 23.8%, that is, over 75% of beds were vacant at the same time9. according to the roadmap for tourism development in kazakhstan until 2023, “accommodation prices in places with a high level of hospitality services are much higher than in their counterparts in other tourist destinations of the world. th e average price for a standard room in a 5* hotel 8 world bank kazakhstan’s economy is rising – it is still all about oil. country economic update. retrieved from http://www.worldbank.org/en/country/kazakhstan/publication/economic-update-fall-2017 9 decree of the government of the republic of kazakhstan of 30 june 2017 no 406 roadmap for tourism development in kazakhstan until 2023. retrieved from https://online.zakon. kz/document/?doc_id=39370590 86 www.r-economy.ru r-ecomony, 2018, 4(3), 82–87 doi: 10.15826/recon.2018.4.3.012 online issn 2412-0731 in astana or almaty is about 20% higher than the average price for a similar room in top european cities and tourist destinations”10. exorbitant prices make tours to kazakhstan even more expensive and are detrimental to the country’s competitiveness on the global market. figure illustrates the demand for kazakhstan as a tourist destination11. 5,000,000 4,500,000 4,000,000 3,500,000 3,000,000 2,500,000 2,000,000 1,500,000 1,000,000 500,000 0 20 04 20 05 20 06 20 07 20 08 20 09 20 10 20 11 20 12 20 13 20 14 20 15 20 16 20 17 residents non-residents th e number of tourists in kazakhstan th is graph shows that the growth rates of domestic tourism exceed those of inbound tourism; the volume of domestic tourism is higher than that of inbound tourism; in general, there has been a growing demand for tourism, although 2007–2008 and 2014–2015 were the periods of recession. in 2014 and 2015, for instance, domestic tourism was in decline while inbound tourism failed to show any signs of growth. th is slowdown was likely to be caused by the falling tenge, which mostly aff ected the country’s residents. th e majority of tourists (82.8%) come from kazakhstan; as for tourists from other countries, russia accounts for the largest share of non-resident tourists (31.4%); china, 7.4%; the usa, 5.9%; turkey, 5.9%; germany, 4.5%; 2.9%, italy; and 42% come from other countries12. 10 decree of the government of the republic of kazakhstan of 30 june 2017 no 406 roadmap for tourism development in kazakhstan until 2023. retrieved from https://online.zakon.kz/ document/?doc_id=39370590 11 statistics committee, ministry of national economy, kazakhstan (2018). economic activity of enterprises in kazakhstan. in: statistical bulletin. astana; statistics committee, ministry of national economy, kazakhstan (2018). th e number of domestic tourists using tourist accommodation facilities (residents). in: statistical bulletin. astana. 12 decree of the government of the republic of kazakhstan of 30 june 2017 no 406 roadmap for tourism development in kazakhstan until 2023. retrieved from https://online.zakon.kz/ document/?doc_id=39370590 as for the purpose of trips, business travellers prevailed (54.1%). 45.6% were holiday-makers. th e majority were private tourists (75.4%) while business travellers accounted for 16.2%13. th erefore, we can conclude that tourism in kazakhstan mostly relies on the country’s residents and on business trips of non-residents, that is, the potential of recreational, sport, cultural, ecological and religious tourism is not fully realized. international experience shows that in order to increase the share of tourism in the country’s gdp, it is essential to attract more foreign holiday-makers14. for instance, europe is overpopulated, which means that european tourists would welcome the opportunity to escape crowds of tourists and enjoy being along with nature15. even though the tourism infrastructure has been improving in the recent years, high prices still discourage foreign tourists from choosing kazakhstan as a place of destination. in this respect, kazakhstan cannot cope with the competition from its neighbours – uzbekistan and kyrgyzstan16. it is possible to lower the prices and improve the quality of services only if there is healthy competition on the market. th erefore, a set of measures should be developed to attract more foreign investment, create a favourable investment climate and address other problems that impede the development of tourism in kazakhstan. as the country is now going through major structural changes, the following types of diversifi cation in tourism seem to be the most promising: business, transit, ethnic, educational, event, and academic tourism. th e rising share of smes in tourism (hostels and private tourist agencies) will make it possible to increase the price and product range. th e most signifi cant problems that need to be dealt with are the poorly developed transport and information infrastructure, the unstable banking sector and unaff ordable business loans, hamper13 decree of the government of the republic of kazakhstan of 30 june 2017 no 406 roadmap for tourism development in kazakhstan until 2023. retrieved from https://online.zakon. kz/document/?doc_id=39370590 14 web-site of business portal kapital.kz. retrieved from https://kapital.kz/economic/71242/kakie-nishi-privlekatelny-dlya-investicij-v-turizm.html 15 web-site of business portal kapital.kz. retrieved from https://www.zakon.kz/4450912-turizm-v-kazakhstane-glazami.html 16 web-site of business portal kapital.kz. retrieved from https://kursiv.kz/opinions/2018-07/turizm-kazakhstana-itogi-2016-perspektivy-2017-goda r-ecomony, 2018, 4(3), 82–87 doi: 10.15826/recon.2018.4.3.012 87 www.r-economy.ru online issn 2412-0731 ing the development of private entrepreneurship, the lack of qualifi ed personnel in the sphere of hospitality, marketing and catering. with its current level of prices and services, kazakhstan as a tourist destination is unable to compete with its international counterparts. taking into account all these considerations, the main form of diversifi cation in kazakhstan should be horizontal, that is, the search for new markets. conclusion our analysis leads us to the following conclusions: 1. diversifi cation of tourism, that is, enhancement of the diversity of markets, products and services within the industry, is an important process infl uenced by diff erent external factors. tourist companies are heavily dependent on the available infrastructure, on natural, cultural and political conditions. 2. only a very small share of inbound and outbound travellers in kazakhstan are tourists; the majority are business travellers. th e fact that kazakhstan attracts few tourists can be explained by the poor quality of the existing transport infrastructure, the poor quality of services and high prices, which means that the country’s tourism market is unstable and undeveloped and that its potential is largely underrealized. 3. diversifi cation may spur the development of recreational, sport, cultural, ecological and religious tourism. 4. to ensure sustainable economic development, kazakhstan needs to reduce its dependence on the oil and gas sector, provide suffi cient support for its banking sector and conduct eff ective structural reforms. kazakhstan should also attract more foreign investment (for example, the case of the chinese infrastructure project western europe – western china). references 1. vasilieva, a. v. 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(2017). role of travel and hotel business in ensuring social and economic development of national economy. socio-economic phenomena and processes, 12(2), 64–67. (in russ.) doi: 10.20310/1819-8813-2017-12-2-64-67 7. kirillina, v. m., kolesnikova, n. v., kolesnikov, n. g., plotnikova, v. s., zakharchenko, s. o., isakova, n. a., et al. (2016). types of tourism and their development in the republic of karelia. penza, nauka i prosveschenie. (in russ.) 8. ashugatoyan, s. g. (2017). diversifi cation strategy as a way of solving problems of turkish tourist industry. vestnik of national tourism academy, 4, 44–45. (in russ.) 9. ovcharov, a. o. (2012). tourism in russia: trends, risks, and potential. moscow: infra-m. (in russ.) 10. nazarkina, v. a., vladykina, y. o., vorotnikova, e. y., komarova, o. s., maletin, s. s., strebkova, l. n., et al. (2014). type and trends of tourism development. novosibirsk: ministry of education and science of the russian federation, novosibirsk state technical university. (in russ.) information about the author aksanat zh. panzabekova – phd in economic sciences, associate professor, deputy director for science of the institute of economics of the committee of science of the ministry of education and science of the republic of kazakhstan (almaty, kazakhstan); e-mail: aksanat@mail.ru. t. gajić, a. vujko, d. cvijanović, m. penić, s. gagić r-economy vol. 3, issue 4, 2017 196 doi 10.15826/recon.2017.3.3.022 udc 332.2 t. gajić a), a. vujko a), d. cvijanović b), m. penić c), s. gagić d) a) novi sad business school (novi sad, serbia; aleksandravujko@yahoo.com) b) faculty of hotel management and tourism (vrnjačka banja, serbia) c) fife class hotels & spa, istrabez turizem (portorož, slovenia) d) university of business studies, faculty of tourism and hotel management (fth), (banja luka, bosnia and herzegovina) the state of agriculture and rural development in serbia serbia is a big chance of europe for all its natural and resource predispositions. primarily when it comes to soil quality, climatic conditions, and location. the entire economy of serbia fell into a stagnation position, after all the turbulent events that hit the region in the late 1990s, and even serbia itself. the developmental chance of serbia is certainly primarily agriculture and rural development. with these values, serbia will become a strong competitor to many countries in the region and europe. the authors of the paper, using the statistical documentation, pointed to the current state of rural development and agricultural development in the country. the preconditions for a more dynamic restructuring of serbian agriculture and rural development: active role of the state, as well as high private sector initiatives. however, the following aspects for the development of rural serbia are of key importance: improving the quality of life of the rural population, a more equal share in the distribution of income and economic opportunities, and their more just social position. balanced and socially sustainable development of rural areas requires synergy and good coordination of all policies that are in contact with rural areas and their resources. the particular responsibility lies in the agricultural policy, which, through the regulation of structural changes in the sector, should ensure the stability of agricultural production, food industry and forestry as the leading rural economy sectors, thus contributing to the economic development of rural areas and reducing the gap in relation to urban centers. keywords: rurality, development, agriculture, economy, transition, serbia. introduction serbia is a country with large agricultural and rural resources, which have not been used sufficiently, precisely because of the difficult political and economic situation that has affected the country and region, in the last years of the twentieth century. today at the time of transition, serbia is trying to survive on the market of europe, but it sees its great development on the russian market of the economy. agriculture accounts for 11% of serbia's gdp and employs a significant number of people, and on the other hand accounts for 23% of total exports and only 7% of the country's imports, creating an annual trade surplus of $ 1.2 billion. the economic development of each country depends on the macroeconomic plan adopted at the state level. this plan must be based on the advantages and potentials of the country, which are either natural resources, or skilled labor, or a third resource. former giants practically do not exist: they are fragmented to small businesses, they are operating with huge losses or are in the process of being extinguished. they were not even helped by the state subsidies they received in the meantime. what serbia has, these are favorable climatic conditions and a relatively fertile land for the development of agriculture, fruit growing and vegetables. however, serious measures have never been taken to take advantage of this advantage. no economic entity, business branch or national economy can exist for several decades if there are no continuous investments. due to the lack of investment today in most of serbia, agriculture is old-fashioned, extensive, unprofitable. the authors of the paper tried to point out the state of rural and agricultural development in serbia. statistical and other secondary documentation were used. http://r-economy.ru/ mailto:aleksandravujko@yahoo.com t. gajić, a. vujko, d. cvijanović, m. penić, s. gagić r-economy vol. 3, issue 4, 2017 197 literature review rural areas in europe represent a large part of the territory. approximately 86% of the territory and approximately 75% of the european union are rural. they present very different environments, a variety of economic activities, unique and ancient, social and cultural traditions [1]. rural development is the second pillar of the common agricultural policy, and financial aids are available for the development of rural regions and communities in the eu [2]. the discussions on what the strategic objectives of sustainable agriculture are, which criteria are to be taken into account, which are the actions to develop, and which are the methodological tools to use for the involved evaluations, are still under development [3, 4]. due to the difficult economic policy, serbia has suffered a huge demographic and social impact, the massive movement of the population from the village to the cities. when the economy collapsed later, there were social cases in the cities, while the villages remained empty and lacked workforce to deal with agricultural production. the serbian agriculture development plan was not in line with the competitive advantages, nor did the expansionary development of rural areas achieve, but a long-term delay, a hard-working. for the new investment cycle in agriculture, it is necessary to change the monetary policy of the national bank, to enable the use of obligatory reserves of commercial banks and open up much more favorable credit than they are now. rural areas are cultural areas more or less close to nature created by the interaction of man's activities and nature and therefore important for understanding the influence of man on the landscape and learning about the contribution to nature conservation through an educational role. rural areas occupy about 90% of the territory of the eu. more than half of the eu population lives in these areas and over 40% of domestic products are produced there, rural areas have their own specific economic and social structures in which agriculture, forestry, crafts, small, medium and large enterprises produce, trade and provide services narrowly local to international. these economic structures and services interact with each other, compete with one another, create, evolve, or evolve. agriculture and forestry use most of the land and play a key role in managing natural resources in rural areas and determining rural landscapes. agriculture provides socio-economic development of rural areas and the use of their potential. rural deterioration means that many leave the village, they remain older, falls natality, and mortality rises. this lowers the standard of living and the culture of housing. agricultural land is abandoned. family stores are usually small and do not provide full employment. in austria, over 300 villages have been included in the tourist offer, which has enabled austria, a continentless landlocked country, to earn $ 7 billion from tourism. level of rural and agricultural development in serbia about 85% of the territory of serbia is a rural area, with about 55% of the population living. it is also pointed out that about 40% of gdp comes from rural areas. however, the problem arises from the fact that many members of the household are not registered as agricultural producers, although they help in everyday agricultural jobs. rural areas continue to be burdened with high unemployment rates, depopulation, low economic activity and a decline in natural resources. rural tourism includes about 2.7 million overnight stays in serbia. there are 6,158 settlements on the territory of the republic of serbia, of which 193 are urban (3,1%) and 5,965 are settlements, which are considered as rural in automation. according to the scope and structure of agricultural resources, serbia has 0.7 ha and 0.46 hectares of per capita land per capita, but the ratio of land surface area and permanent crops to meadows and pastures is among the more favorable compared to other european countries. serbia has 45% of agricultural land suitable for processing, precisely because of climate, geological structure, vegetation, etc. in some areas it is possible to grow crops over 200 days during the year [5]. http://r-economy.ru/ t. gajić, a. vujko, d. cvijanović, m. penić, s. gagić r-economy vol. 3, issue 4, 2017 198 table 1. scope and structure of agricultural land of the republic of serbia (000 ha)1 2006. 2008. 2010. 2012. 2014. 2016. agricultural land 5.056 5.058 5.052 5.056 50.53 5.069 arable land and gardens 3.032 3.031 3.295 3.294 3.282 3.298 non-cultivated land 199 209 226 224 219 242 land under permanent plantation 300 298 297 296 293 289 orchard 242 240 240 240 239 238 vineyards 58 58 57 56 54 51 permanent lawn 1.454 1.459 1.460 1.466 1.478 1.482 meadow 621 625 624 621 641 653 pastures 833 834 836 845 837 829 problems that occur in rural areas of serbia and which limit agricultural development are reduction of organic matter, acidity of soil, pollution of soil, closure of soil structure, erosion of soil. it has been noted that 80% of the land is covered by water erosion, while eolic erosion affects 25% of the land area. there was also a high use of chemicals, which additionally endangers the arable land. currently, only 40.00070.000 ha are irrigated per year. when it comes to protecting the land from the harmful effects of large waters, data shows that 1.25 million hectares of agricultural land are protected. about 2 million hectares are drained through 414 drainage systems, with over 25.600 km of canal network, 210 large and several tens of smaller pumping stations, and 252 gravity outflows [5]. table 2. macroeconomic indicators of the contribution of agriculture and agro-industry to the national economy1 2006. 2008. 2010. 2012. 2014. 2016. participation in total gva (%) manufacture of food products 3,6 3,9 3,9 4,1 4,1 … production of drink 1,1 1,2 1,1 1,1 1,1 … manufacture of tobacco products 0,3 0,3 0,3 0,2 0,2 … total 5,0 5,4 5,3 5,4 5,4 … participation in total employment (%) manufacture of food products 3,2 3,4 3,5 3,5 4 3,6 production of drink 0,4 0,5 0,4 0,4 0,4 0,5 manufacture of tobacco products 0,1 0 0,1 0,1 0,1 0,1 total 3,7 3,9 4 4 4,5 4,2 data say that 75% of companies employ fewer than 10 people, while 90% of them have fewer than 50 employees. vatical characteristic of the food sector is a dual structure, with many small and medium-sized companies and only a limited number of large, modern companies. in the food industry, significant foreign investments have been directed over the last decade. it is very difficult to present the realistic situation of rurality in serbia, precisely because of the lack of data. the overview of the situation is focused on different aspects of the labor market and the income of rural households. movement of basic labor market indicators (unemployment, employment and activity rates) indicates that in the republic of serbia during the last decade there are no significant differences in the relation urban or rural, and that their mutual relationship does not depend on the general picture, according to which the rural areas are somewhat better position in relation to urban. namely, urban areas are characterized by higher participation of the unemployed in the active population and less participation of the employed and active in the working age 1 statistical yearbook of the republic of serbia http://r-economy.ru/ t. gajić, a. vujko, d. cvijanović, m. penić, s. gagić r-economy vol. 3, issue 4, 2017 199 population, and the position of the rural population on the labor market is somewhat more favorable than in the urban population. compared to the average of the eu-27 countries, serbia has a significantly higher share of gdp of the agriculture sector in total gva, and significantly lower the share of services sector. the high share of agriculture in the basic macroeconomic aggregates of serbia in relation to other countries can be attributed, on the one hand, to rich land resources and favorable natural conditions for agricultural production, and, on the other hand, to a slower process of structural reforming of the rest of the economy and delays in that process. although absolute employment in agriculture has recorded high reduction rates (in 2016, it was 56% lower in comparison to 2008), the share of agriculture in total employment in serbia is still very high, among the highest in europe, accounting for around 21%. contrary to expectations, since the beginning of the economic crisis, employment has also been reduced in agriculture, which, as a rule, in conditions of crisis, absorbs labor surpluses from other sectors the rural working age population compared to urban has: higher activity rates (60.9: 59.5%) and employment (47.9: 43.4%) and lower unemployment rates (21.3: 27%) and that rural environments provide a greater possibility of employment of lower educated persons, which is particularly relevant to their work in agriculture. on the other hand, this kind of work engagement points to a significantly higher share of vulnerable employment in rural than in the urban population. the rural working age population, compared to urban, has higher rates of activity and employment, and lower unemployment rates and employment of lower educated persons, especially in their work in agriculture. on the other hand, this type of labor anger indicates a significantly higher share of employment of vulnerable groups in rural than in the urban population. table 3. amount of subsidies (euro) country tangent amount of subsidies serbia 32 eur croatia 200-900 eur slovenia 300-1.100 eur hungary 400 eur agricultural field employment in the countryside is still the largest, if compared with other sectors, and ranges between 43-50%. very few rural employees work in the industry. on the other hand, the rural population is increasingly employed in the tertiary sector, which can be interpreted in two ways: on the one hand, by increasing the stability of jobs in the activities of this sector, and on the other hand by increasing the number of employees in the sector of public administration, education, public utilities and social services. household income mostly (35-42%) comes from income from employment (regular and supplementary), followed immediately by the share of pensions that are very high and growing (around 30% in 2012 available households, which is highly defined by yields of agriculture in some years), [6, 7]. at the same time, the value of natural consumption, which is largely attributed to the consumption of food produced on agricultural holdings, is stable at the level of 12-14%. in any case, the income derived from agriculture is relatively low compared to wages from other sectors and social benefits, which is a clear indicator of low productivity of the sector. in rural areas, gender inequality is expressed. namely, the largest percentage of employed in agriculture are men, and the highest percentage of unemployed are women. young people in these areas face high risks of exclusion from the labor market. young people aged 15-24 years in only 21% of cases are employed in non-agricultural sectors. although in this age group even half of them are inactive, what points to difficulties in accessing jobs is the significantly higher participation of the unemployed, which in this category, as well as the next age categories (25-34 years), is only 15.5%, [8, 9, 10]. poverty in serbia is a predominantly rural phenomenon, since rural areas have been affected in some periods up to twice as much as cities. although there was a much faster decline in rural poverty compared to urban areas before the crisis (2006-2008), in 2009, the overall growth of poverty was launched in rural areas, while the percentage of the poor in urban areas remained virtually unchanged (5% and 4.9%, http://r-economy.ru/ t. gajić, a. vujko, d. cvijanović, m. penić, s. gagić r-economy vol. 3, issue 4, 2017 200 respectively. rural areas reacted faster to the economic crisis and were strongly affected by it, so the overall growth of poverty in the republic of serbia is generated by an increase in rural poverty. in comparison with 2008, the percentage of the poor in rural areas (measured by the absolute poverty line) increased by 6 percentage points in 2010, while the percentage of the poor in the cities grew for less than one percentage point [8, 9, 10]. conclusion in the last decade, incentive policy in serbia has been exposed to the effects of complex and heterogeneous factors such as: political and economic (non) stability of the country, dynamic changes in the volume and structure of production due to unstable weather conditions, and from the second half of the 2000s and global market disorders. the state of agricultural and rural development in serbia is far below the expected. the reasons that contributed to the lagging development are economic and political in nature. however, in recent years, development has been felt, because, while looking globally, serbia is an agricultural country with many rural areas. in the paper, the authors pointed to the current state of development of this branch of the economy, but they pointed out certain problems with which rural development is facing. in order to fully change the situation in the serbian agriculture, it is not enough that in the words of agriculture it is declared a key economic branch [8, 9, 10]. investments and subsidies are also needed. with real investments and modernization, agricultural production in serbia could increase four to five times. the beneficiaries of the new credit policy in the agrarian sector should first of all be individual agricultural producers and family farms. they should be the bearers of agricultural production, primarily in the field of fruit and vegetable growing, where yields are far greater. only in second place are larger agrarian systems, which need support to become important logistics centers, ready to purchase all agricultural products and place them on the global market. they must follow the latest technological advancements and enable the transfer of knowledge to smaller producers and households [11, 12, 13]. the small number of families, the share of land potentials, and the specific patterns of functioning, small family farms are an indispensable part of the rural economy, which requires special attention. their number is reduced under the influence of the aging process of villages, migration, globalization, strengthening of concentration of capital in agriculture and many others. on the other hand, with its own food production and contribution, the rate of self-sufficiency and food stability, the importance for preserving resources and rural environment, participation in the local market of goods and services, small family farms are positioned as subjects that require adequate treatment of agricultural policy [14]. the largest share in support of rural development has funds intended for incentives for investment in the holding. investment in the holding was stimulated by grants for the reconstruction and construction of facilities, the purchase of equipment and mechanization, the renewal and expansion of perennial plantations. criteria for allocating funds are often changed. the general idea was to provide more favorable conditions for farms in hilly and mountainous areas, as well as those registered for persons under the age of 40 years. the general conclusion is that the agricultural sector and rural areas of serbia have significant resources both in terms of volume and diversity, which provides significant opportunities for the growth of production, diversification of products and services and the creation of new, innovative products and practices. on the other hand, serious efforts are needed in the structural reform of the sector and the rural areas in terms of strengthening their economic efficiency and competitiveness rural areas of serbia are distinguished by the diversity of landscapes and biodiversity, rich in cultural heritage and natural resources. on the other hand, they suffer the consequences of demographic discharge. this is the reason for their lagging behind, the presence of all kinds of deprivation and rising poverty. their economy is reduced to exploitation, exhaustion and further degradation of natural resources, based on agriculture and its leaned activities, with a small supply of quality jobs and modest opportunities for generating external revenues [15]. the growth of the attractiveness of rural areas as attractive places for the lives of young families is closely linked to the improvement of physical infrastructure, better access to social services, improvement http://r-economy.ru/ t. gajić, a. vujko, d. cvijanović, m. penić, s. gagić r-economy vol. 3, issue 4, 2017 201 of the social structure and support to the development of entrepreneurship. failure to meet the specific needs of the village and its inhabitants, the lack of systematic and better coordinated activities of various actors, poses a serious threat to the further development of the developmental gap in relation to the city our producers also need subsidies. it is clear to everyone that serbia can not at this moment reach the other countries in the region by subsidies. however, it can also decide to publicly announce in what period it plans to equalize the serbian producers with hungarian or croatian, which are geographically and marketally closest to us under the terms of business. this would also allow our producers and farmers to plan their development in the medium term, including lending in the coming years.with the new investment and subsidy policy, conditions would be created to stop migration from the village to the city. serbia would increase employment and create conditions for people to live in the countryside and to invest in agriculture. such agriculture would directly affect the growth of serbian population standards, better filling of the state budget (through vat payments), as well as the increase in exports. expressed in money, it is about tens of billions of euros, because only the netherlands, which has arable land less than serbia, exports agricultural products twice as high as the total gdp of serbia. finally, it is necessary to brand serbian agricultural products on the world market, where the state can provide key support, gathering of producers, education and forming a strategy for the formation of the national brand. modern, efficient, profitable agriculture, which requires high and continuous investments this is the agriculture that is needed for serbia and it is being introduced into the society of developed countries. in accordance with the vision, and in accordance with the stated principles of the strategy, the following strategic development goals have been identified: 1. production growth and stability of producers' income; 2. increasing competitiveness by adapting to the demands of domestic and foreign markets and technical and technological improvement of the sector; 3. sustainable resource management and environmental protection; 4. improving the quality of life in rural areas and reducing poverty; 5. efficient management of public policies and improvement of the institutional framework for the development of agriculture and rural areas. references 1. ayres, w.s., mccalla, a.f., (1996). rural development, agriculture and food security. financ. dev. 33, 8-11. 2. emerson, h.j., gillmor, d.a., (1999). the rural environment protection scheme of the republic of ireland. land use policy 16, 235-24. 3. gomez-limo n, j.a., atance, i., (2004). identification of public objectives related to agricultural sector support. j. policy model 26, 1045-1071. 4. gajić, t., vujko, a. (2017): tourism as a potential factor of economic development a report from serbia. the second international scientific conference: tourism in function of development of the republic of serbia тourism product as a factor of competitiveness of the serbian economy and experiences of other countries. university of kragujevac, faculty of hotel management and tourism in vrnjačka banja, vol 2. pp. 128-144. 5. vujko, a., gajić, t. (2014): the gouverment policy impact on economic development of tourism. ekonomika poljoprivrede., 61(3), pp. 789-804. 6. heilig, g.k., (2002). european rural development. international institute for applied systems analysis, laxenburg. austria. 7. jonard, f., lambotte, m., ramos, f., terres, j.m., bamps, c., (2009). delimitations of rural areas in europe using criteria of population density, remoteness and land cover. jrc scientific report, eur 23757 en. 8. kitchen, l., marsden, t., (2009). creating sustainable rural development stimulating the eco-economy: beyond the ecoeconomic paradox? sociol. rural. no. 49, 273-294. 9. morgan, s.l., marsden, t., miele, m., morley, a., (2010). agricultural multifunctionality and farmers' entrepreneurial skills: a study of tuscan and welsh farmers. j. rural. stud. 26, 116-129. 10. petrović, m. d., blešić, i., ivolga, a., vujko, a. (2016): agritourism impact toward locals’ attitudes – an evidence from vojvodina province (serbia). zbornik radova gi „jovan cvijić” sanu. 66(1), pp. 95-123 11. gajić, t., vujko, a., penić, m., petrović, m. mrkša, m. (2017): significant involvement of agricultural holdings in rural tourism development in serbia. ekonomika poljoprivrede 64(3), pp. 901-919 12. vujko, a., petrović, m., dragosavac, m., ćurčić, n., gajić, t. (2017): the linkage between traditional food and loyalty of tourists to the rural destinations. teme, 41(2), pp. 475-487 13. vujko, a., petrović, m., dragosavac, m., gajić, t., (2016): differences and similarities among rural tourism in slovenia and serbia perceptions of local tourism workers. ekonomika poljoprivrede, 63(4)/2016, 1459-1469 http://r-economy.ru/ t. gajić, a. vujko, d. cvijanović, m. penić, s. gagić r-economy vol. 3, issue 4, 2017 202 14. petrović, m., radovanović, m., vuković, n., vujko, a., vuković, d. (2017): development of rural territory under the influence of community-based tourism. ars administrandi, 9(2), pp. 253–268 15. petrović, m., blešić, i., vujko, a., gajić, t. (2017): the role of agritourism impact on local community in a transitional society: a report from serbia. transylvanian review of administrative sciences, 50/2017, 146-163 authors gajic tamara – ph.d, professor, novi sad business school (vladimira perića valtera 4, 21000 novi sad), email: tamara.gajic.1977@yahoo.com vujko aleksandra – ph.d. professor, novi sad business school (vladimira perića valtera 4, 21000 novi sad), email: aleksandravujko@yahoo.com cvijanović drago – ph.d. dean, full professor, faculty of hotel management and tourism in vrnjacka banja university of kragujevac (vojvođanska street no. 5a, 36210 vrnjacka banja, serbia), email: drago.cvijanovic@kg.ac.rs penić mirjana – ph.d. f&b manager, fife class hotels & spa, istrabez turizem (portorož, slovenia), email: penicns@yahoo.com gagić snježana – ph.d. university of business studies, faculty of tourism and hotel management (fth), banja luka, bosnia and herzegovina, email: gagicsnjeza@yahoo.com http://r-economy.ru/ mailto:drago.cvojanovic@kg.ac.rs v. a. shamis, o. m. kulikova, s. y. neiman, e. v. usacheva r-economy vol. 3, issue 4, 2017 203 doi 10.15826/recon.2017.3.3.023 udc 332.1 v. a. shamis a), o. m. kulikova a), s. y. neiman b), e. v. usacheva c) a) siberian state automobile and highway university (omsk, russian federation; vitalijshamis@gmail.com) b) omsk state technical university (omsk, russian federation) c) omsk state medical university (omsk, russian federation) agent-based modeling of the impact of advertising on the regional economic cluster lifecycle the aim of the study is the development and testing of an algorithm for modeling the impact of advertising on various stages of the life cycle of economic clusters. it is assumed, that the life cycle of the cluster consists of the stages: a diffuse group, a hidden cluster, an evolving cluster, a mature cluster, a collapsing cluster. using the agent-based simulation methods, hierarchical clustering and chaos theory, the following results were obtained: a conceptual model of the behavior of cluster members for cluster formation processes at each stage of the cluster life cycle and an imitation model of the influence of advertising on the life cycle of the economic cluster; the patterns of various stages of the life cycle of the economic cluster and the functioning of the cluster without influence and under the influence of advertising were revealed. advertising reduces the time at the stages of the associated life cycle of the cluster, increases the stage of maturity of the cluster. companies that do not comply with the principles of clustering are under the influence of advertising and promotional activities. such enterprises most often arise in the cluster at the stages of its formation. keywords: economic clusters, stages of the cluster life cycle, advertising and promotion, simulation and modeling, computational experiment introduction modern economic trends and acceleration of scientific and technological processes lead to increasing numbers of start-ups, development of new production systems and, consequently, to the formation and development of cluster structures in modern world economy, which makes the need for research in this sphere really urgent [1, 2, 3, 4, 5, 6, 7, 8].. although there is vast literature on cluster development, further research is needed to investigate the life cycle of economic clusters, its stages and the factors affecting it. in-depth understanding of these aspects is particularly important when managing the processes of cluster formation in highly changeable modern economy. theoretical studies on regional clusters apply simulation techniques and computational experiments, which requires the development of appropriate methodological tools. bibliographic analysis shows that in recent years modern science has been actively trying to solve the problems of cluster structures by modelling their life cycle [9, 10, 11]. there are studies analyzing evolutional changes in economic clusters [12, 13]; simulating economic clusters’ life cycle with the help of various techniques, including chaos theory, in order to study regularities in cluster development under different conditions [4, 14, 15, 16, 17]. special attention is paid to the impact of various factors on formation and functioning of economic clusters, for example, the influence of the available resources or how a cluster interacts with other clustered structures. at the same time, the mechanisms underlying the behavior of actors on the market and the impact of various factors on clusters’ life cycle are not quite clear yet. one of the major factors that shapes actors’ behavior is advertising and promotion activities, which affect formation and functioning of economic clusters. all the above-mentioned considerations define the main objective of this study, which is to develop an agent model of the impact that advertising has on the life cycle of regional economic clusters and test this model by conducting a computational experiment. http://r-economy.ru/ mailto:vitalijshamis@gmail.com v. a. shamis, o. m. kulikova, s. y. neiman, e. v. usacheva r-economy vol. 3, issue 4, 2017 204 methodology in this paper, we use the term ‘regional economic cluster’ to refer to the association of independent, non-institualized economic reflexive entities in the joint arrangement based on proximity (territorial, sectoral, and cultural); complementarity (product, resource, and process); and interconnectivity (material, immaterial, and informational) [18]. hereinafter a regional economic cluster will be referred to simply as a ‘cluster’. the behavior of cluster agents depends on certain parameters that are determined by these agents’ views and preferences. cluster formation processes involve two types of agents: agents-manufacturers and agents-consumers. agents-manufacturers are responsible for production within the cluster and can be divided into two subtypes: agents-manufacturers producing goods or products of the cluster and agents-manufacturers providing the necessary resources to produce cluster products. agent-consumers purchase and use cluster products. their behavior is determined by the ability to do the following:  to purchase the necessary resources in sufficient quantities to satisfy their needs (views);  to manufacture cluster products or resources necessary for the cluster’s production in sufficient quantities determined by the market volumes and by the predefined indicators, which are relevant to agentconsumers’ ideas and views on the products (resources);  to organize advertising and promotional campaigns to increase the volume of sales;  to restructure production to improve the indicators of the manufactured products and increase their attractiveness for consumers. the main aim of agents-manufacturers is to gain the maximum profit from selling their products or resources. agents’ behavior is determined by consumers’ ability to purchase cluster products that meet their requirements (needs). this aspect determines the goal of agents-consumers: they purchase cluster products if the differences between the vectors characterizing cluster production and their needs are below the specified threshold. agents’ behavior depends on commercial advertising. advertising is a set of information flows aimed to increase the number of agents-consumers purchasing cluster products [19]. clusters, like all economic actors, have their own life cycles, which includes the following phases or stages:  defuse group;  latent cluster;  developing cluster;  mature cluster;  collapsing cluster [20]. the initial phase in cluster development is the stage of defuse group. this stage is the starting and at the same time the final point in the life-cycle of a cluster. there are no processes of cluster formation at this stage. at this stage, an economic entity, which then emerges in the course of cluster formation, is just a set of interactions of the above-mentioned agents in a framework of manufacturing and selling activities. there are no informational, tangible and intangible flows connecting these agents into a unified single system that possesses synergetic properties. agents of each type are not involved into the network that allows the cluster to develop and function. at the second, latent stage of a cluster, a real cluster is starting to emerge. at this stage of cluster formation, cluster products vary significantly in their indicators, the output production by agentsmanufacturers remains either constant or slightly increasing. the volumes of purchased products by agentconsumers remain at the same level or slightly increase as well. moreover, the indicators defining the use of funds by agents-consumers and product purchase by agents-manufacturers change slightly. accumulation of resource potential is necessary for the cluster’s transition to the stage of development. within this stage, http://r-economy.ru/ v. a. shamis, o. m. kulikova, s. y. neiman, e. v. usacheva r-economy vol. 3, issue 4, 2017 205 marketing research is conducted to examine the individual preferences of consumers, and the restructuring is done to minimize the differences between the products manufactured by the cluster’s agents-producers. when restructuring of the production processes is completed, the latent stage finishes and the cluster enters the following stage. at the latent stage, the bifurcation points appear on the graphs characterizing various indicators of agents. at the stage of development, the cluster output grows intensively; differences between the products produced in the cluster are minimal. at the mature stage, the intensity of processes of cluster formation is at its peak, but the volumes of produced and purchased products vary only slightly; the differences between the products produced in the cluster are minimal. the internal capacity of member enterprises is increasing. further development of this capacity increases the entropy of the cluster as the new trajectories of its evolution and innovation, including sabotage, appear. these processes contribute to the cluster’s transition to the stage of decay and collapse. at the stage of a collapsing cluster, the volumes of produced and purchased cluster products are decreasing; new products appear on the market, the difference between cluster products increases. at this stage, the processes of cluster formation are slowing down and then stop completely and the cluster moves into the last phase of its life cycle, that is, the diffuse group phase. results and discussion as our analysis shows, the most significant stage in cluster development is the latent phase. it is the stage when the resource potential is formed to be used at the following phases – development and maturity. thus, it can be said that this is the stage which determines the whole life cycle of a cluster. these considerations define the choice of the latent stage for modeling and conducting a computational experiment. we are going to briefly outline the agent model of cluster formation: the participants are divided into two types – agents manufacturing cluster products and agents consuming products. resource-producing agents are not included in the model. when modeling, we assume that agents-manufacturers produce only one cluster product, agentsconsumers purchase it and spend all their funds on this purchase, if the cluster products correspond to their needs or views. when modeling, logistics and warehousing tasks are not considered, that is, the output is equal to the volume of production purchased by agents-consumers. agents-manufacturers produce cluster products; the number of manufacturing agents is 5. all of them manufacture products with certain attractiveness for agents-consumers, which we shall refer to as the ‘attractiveness vector’. every agent-manufacturer makes products with unique values of the attractiveness vector. the values of this vector are changing in the course of restructuring, which is carried out by the manufacturing agents. the following indicators are included into this vector: • adaptability (this figure varies between 0 and 5, 0 corresponds to the minimum value and 5, to the maximum); • quality (the indicator score ranges from 1 to 5, that is, from minimum to maximum); • price (ranges from 120 to 200 c.m.u.). agents-consumers purchasing the cluster’s products are guided by their preferences, that is, the preference vector, which includes the following indicators, similar to the values of the attractiveness vector:  adaptability;  quality;  price. agents-consumers purchase products if the values of the distance between the above-described vectors is less than the specified threshold value. when modeling, we use the euclidean distance calculation. in the initial cycle of modeling time, agents-manufacturers have zero funds. an increase in funds is caused by the purchase of manufactured products by agents-consumers minus the expenses on manufacturing products, on advertising, and on restructuring of the production. http://r-economy.ru/ v. a. shamis, o. m. kulikova, s. y. neiman, e. v. usacheva r-economy vol. 3, issue 4, 2017 206 the total number of agents-consumers in the initial cycle of modeling time is 1,000. their number increases by 20 % in the cycle of modeling time when an advertising campaign is being prepared; in the next cycles of modeling time, the number of consuming agents returns to the original values. the computational experiment is conducted for seven classes of agents-consumers. in each class, the number of agents-consumers is different: in the first class, it is 150; in the second class, 270; in the third class, 210; in the fourth class, 70; in the fifth class, 120, in the sixth class, 160; in the seventh class, 20. each class is characterized by the same values of the funds for every agent in the initial cycle of modeling time as well as identical values of the preference vector, which defines agents-consumers’ wish or reluctance to purchase cluster products. each class of agents-consumers has the same thresholds that characterize the differences between the preference vector while choosing cluster products and the attractiveness vector. agent-consumers’ funds spent on cluster products have a certain initial value. this value increases in every cycle of modeling time. if a consumer does not use their funds to purchase the products, the funds are saved and can be spent in the next cycle of modeling time. the latent stage of the cluster life cycle begins with the first cycle and ends with the restructuring of production carried out by all agents-manufacturers on the basis of their marketing research. marketing research uses mathematical clustering methods and is simulated by calculating the values of generalized preference vectors for consuming agents. we use the ward hierarchical clustering method [21]. for each agent-consumer group the generalized preferences vector is calculated with the help of the mathematical clustering method to choose cluster products as a mathematical cluster profile. the number of mathematical clusters defining agent-consumer groups and taking into account the original agentconsumer groups determines the number of the vectors. independent firms are supposed to do the marketing research. it is free for manufacturing agents and its results are available to them. based on the generalized preferences vectors for agents-consumers to choose cluster products, agentsmanufacturers restructure their production. the values of attractiveness vectors are changing by approximating it to the agent-consumer generalized preferences vector in order to reduce the threshold value that defines the distance between the vectors characterizing the products and agents-consumers’ wish to purchase these products. production restructuring is based on the capabilities of every class of agents-manufacturers. it means that agents-manufacturers cannot completely and totally change their products so that all indicators of the values of the product attractiveness vector would coincide with the generalized preferences vector for agents-consumers. in restructuring, agents-manufacturers can partially change the product’s attractiveness vector in order to approximate it to the generalized preferences vector for agents-consumers. production restructuring can be done gradually through partial accumulation of funds – 60% of what is needed. the simulation is performed with the help of programming language python 3. the initial data for the computing experiment is shown in table 1. table 1. input data map for modeling the impact of advertising on the cluster life cycle agent type number of classes parameters of death/reproduction agents-manufacturers 5 constant agents-consumers 7 changing when modeling agents-manufacturers 1 2 3 4 5 indicators of agents-consumers indicators of cluster manufacturing products product manufacturability, score 5 3 5 3 1 product quality, score 4 2 5 5 3 product price, conventional monetary units (c.m.u.) 180 130 200 160 140 http://r-economy.ru/ v. a. shamis, o. m. kulikova, s. y. neiman, e. v. usacheva r-economy vol. 3, issue 4, 2017 207 product cost, conventional monetary units 100 60 180 90 80 additional expenses of agents-manufacturers advertising costs, usl. c.m.u. 2000 production restructuring costs, c. m. u. 340000 450000 360000 430000 600000 restructuring rulesa product manufacturability, mark 0 0 0 0 +2 product quality, score +1 +1 0 0 +1 product price, c.m.u. -20 0 -30 -40 +10 product cost c.m.u. 100 65 140 90 90 indicators of consumer agents classes of agents-consumers 1 2 3 4 5 6 7 the number of agents in the class, u. 150 270 210 70 120 160 20 percentage of agents purchasing cluster products before advertising,% 90 percentage of agents purchasing advertised cluster products,% 100 funding, c.m.u. 1000 1000 2500 1000 2000 3000 4000 threshold value describing the differences between the vectors and preference indicators of cluster products 21 10 8 15 9 5 5 preference indicators for choosing cluster products product adaptability, score 2 2 3 5 3 5 5 product quality, score 5 2 3 1 5 5 5 product price, c.m.u. 150 140 150 120 150 120 180 modeling time settings number of cycles 7 model time cycle (tact) 1 a. these rules are based on the results of mathematical cluster analysis performed on the profiles specifying the attractiveness for agents-consumers. the first cluster includes agents-consumers of classes 1, 2, 3, and 5; the second cluster includes agents-consumers of classes 3 and 6. first cluster profile: adaptability of products, 5 points; product quality, 3 points; product price, 120 min. c.m.u. second cluster profile: product manufacturability, 3 points; quality products, 4 points; product price, 154 min. c.m.u. http://r-economy.ru/ v. a. shamis, o. m. kulikova, s. y. neiman, e. v. usacheva r-economy vol. 3, issue 4, 2017 208 a) dynamics of profits for manufacturing agents in a modeling time cycle b) dynamics of funding changes for agentsconsumers fig. 1. input data map for modeling the impact of advertising on the cluster life cycle the computational experiment is conducted in two phases. in the first phase, simulation is developed without promotional advertising, which is aimed at accelerating the accumulation of funds necessary for production restructuring. at this stage, manufacturing agents consider advertising as a regular event in the specified cycle of modeling time. advertising is necessary to change agents-consumers’ behavior and increase the sales of cluster products. in the second phase of the experiment, in the second and third model time cycle, the impact of promotion and advertising is simulated by using an advertising campaign which changes the number of agents-consumers wishing to purchase cluster products, thus increasing the profits of manufacturing agents. in the first phase of the experiment, at the simulated life cycle stage, not all agents-consumers purchase cluster products. classes of consuming agents 3, 5 and 6 do not purchase cluster products because of its low attractiveness. agents-consumers of class 1 purchase cluster products from agents-manufacturers of class 4; agents-consumers of class 2, from agents-manufacturers of class 5; agents-consumers of class 4, from agentsmanufacturers of class 2; agents-consumers of class 7, from agents-manufacturers of class 1. therefore, agents-manufacturers of class 3 do not sell their products and, therefore, they will not be able to restructure their production on time and thus will not be able to catch up with the cluster’s general formation processes, which will negatively affect the cluster’s efficiency. the process of selling and buying of cluster products extends over the entire period that determines the stage of formation in the cluster life cycle. during the second cycle of modeling time, agents 2 and 4 accumulate the funds necessary for restructuring; during the third cycle, they start restructuring their production in accordance with the rules given in figure 1. manufacturing agents 5 accumulate funds in the third cycle of modeling time and start to restructure production during the next cycle of modeling time. in the given period (seven cycles of modeling time), manufacturing agents 1 can accumulate only a portion of the funds – about 60 % – needed for restructuring of production, therefore, they will not be able to change the parameters of manufactured products. if these agents-manufacturers accumulate sufficient funds and start to change their production by the seventh cycle of modeling time, they still won’t be able to finish their restructuring. in the former case, agents-manufacturers cannot start the next stage and will, therefore, leave the cluster. in the latter case, these agents-manufacturers with some degree of probability will be able to enter the cluster at the next stage of its development. manufacturing agents 3 cannot restructure their production due to the lack of profit. these agents leave the cluster. the restructuring of production for agents-manufacturers 2, 4, and 5 ends in the sixth cycle of modeling time. in the seventh cycle, preparations start for transition from the latent stage to the stage of development. fig. 2 (a-b) shows the changes in the basic parameters of agents-manufacturers and agents-consumers when we conducted the computing experiment at the first stage. http://r-economy.ru/ v. a. shamis, o. m. kulikova, s. y. neiman, e. v. usacheva r-economy vol. 3, issue 4, 2017 209 a) dynamics of manufacturing agents’ profits in a modeling time cycle b) dynamics of the changes in agentsconsumers’ funding fig. 2 (a-b). dynamics of changes of the basic parameters of the agents-manufacturers and agentsconsumers when conducting computing experiment at the first stage the second phase of the computing experiment reveals that preparation of a promotional or advertising campaign shortens the period of cluster formation. the period of accumulating funds for restructuring is shortened, too. manufacturing agents 2 and 4 in the first cycle of modeling time have already accumulated sufficient funds for restructuring of production. after the third model cycle, these agents-manufacturers present products to the market with new cluster indicators after the restructuring. agents-manufacturers 2 have improved the product quality and agents-manufacturers 4, in turn, have reduced the cost of production. by using advertising, two agents-manufacturers have managed to start the restructuring earlier, within one cycle of modeling time, which would positively affect their profits in the future. promotional activities and advertising also affect agents-manufacturers 5, who can accumulate enough funds in the third cycle of modeling time and by the beginning of the fourth cycle of modeling time start the restructuring of production, which allows them to bring products with new parameters to the market. product adaptability has been improved as well as its quality; its price has risen slightly. this will increase the cluster’s sales for this class of agents-manufacturers, which will be beneficial for their profits. promotion and advertising have slightly affected manufacturing agents 1; the growth in profit is slow, which does not allow the agents to accelerate accumulation of funds and catch up with the other agents. agents-manufacturers 1 will be able to restructure their production only on the fifth cycle of modeling time, which negatively affects their profits. since most classes of agents-manufacturers have already completed their restructuring in the fourth cycle, there is a possibility that manufacturing agents 1 will leave the cluster at the formation stage. therefore, without manufacturing agents 1 and 3, the process of transition from the latent stage to the development stage will start in the fifth cycle of modeling time. manufacturing agents 3 do not start restructuring and leave the cluster. promotional advertising has not been effective for them. fig. 3 (a-b) shows dynamic changes of the basic parameters of agents-manufacturers and agentsconsumers when we conducted the computing experiment at the second stage. http://r-economy.ru/ v. a. shamis, o. m. kulikova, s. y. neiman, e. v. usacheva r-economy vol. 3, issue 4, 2017 210 a) dynamics of manufacturing agents’ profits in a modeling time cycle b) dynamics of the changes in agents-consumers’ funding fig. 3 (a-b). dynamics of changes of the basic parameters of the agents-manufacturers and agentsconsumers when conducting computing experiment at the second stage the computing experiment reveals the following patterns in the impact of advertising on the life cycle of clusters. 1. advertising enhances growth in manufacturers’ sales profits at all stages of the cluster life cycle, which enhances the formation of the cluster’s resource potential. 2. advertising and promotion enhance cluster formation by coordinating consumers and increasing their number as well as by reducing the time of transition from the stages related to the cluster’s formation and development to the maturity stage. 3. for businesses that do not meet the cluster’s criteria, the impact of advertising and promotion is weak or has no effect. these companies leave the cluster at one of the stages of the cluster life cycle, usually at the stages of formation and development. conclusion our research identifies the patterns and regularities in the cluster formation process in modern economy as well as the impact of advertising on the life cycle of economic clusters. advertising positively influences the operation of an economic cluster and helps it accelerate its development and extend its life cycle by increasing the potential of the member enterprises. this process favorably influences not only the enterprises themselves but the consumers of cluster products because they purchase the products which are more relevant to their needs and which reach the market earlier than if the cluster formation processes developed less intensively and the process of cluster formation deaccelerated. the companies and firms that do not comply with the principles of cluster operation gain little or no benefit from advertising and promotion. such firms tend to leave the cluster more often at the stages of formation and development. the discovered patterns can be used to develop economic activities within regional clusters, which form the economic potential of the countries and contribute to their industrial development, including innovation and modernization. references 1. livi c., jeannerat h., 2015. born to be sold: start-ups as products and new territorial life cycles of industrialization. european planning studies, 23 (10), 1953-1974. 2. arbia g., espa g., quah d., 2008. a class of spatial econometric methods in the empirical analysis of clusters of firms in the space. empirical economics, 34 (1), 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(door 2016). vladivostok, russia. vol. 1623., pp. 545-557. 19. funk t., 2013. advertising and promotion. advanced social media marketing. apress, berkeley, ca. 20. boush g.d., kulikova o.m., shelkov i.k., 2016. agent modelling of cluster formation processes in regional economic systems. reconomy. 2 (1), 89-101. 21. murtagh f., legendre p., 2014. ward’s hierarchical agglomerative clustering method: which algorithms implement ward’s criterion? journal of classification, 31 (3), 274-295. authors shamis vitaliy aleksandrivich – candidate of psychology, siberian state automobile and highway university (russian federation, 644080, omsk, mira, 5; vitalijshamis@gmail.com) kulikova oksana mikhaylovna – candidate of sciences in technology, siberian state automobile and highway university (russian federation, 644080, omsk, mira, 5; ya.aaaaa11@yandex.ru) neiman svetlana yulievna – candidate of philology, omsk state technical university (russian federation, 644050, omsk, mira prospekt, 11; svetlana1414@bk.ru) usacheva elena vladimirovna – candidate of medicine, omsk state medical university (russian federation, 644099, omsk, lenin street, 12; elenav.usacheva@yandex.ru) http://r-economy.ru/ mailto:vitalijshamis@gmail.com mailto:ya.aaaaa11@yandex.ru mailto:svetlana1414@bk.ru mailto:elenav.usacheva@yandex.ru r-ecomony, 2018, 4(2), 59–66 doi: 10.15826/recon.2018.4.2.009 59 www.r-economy.ru online issn 2412-0731 original paper for citation demirović, d., košić, k. & stjepanović, s. (2018) competitiveness in rural tourism between serbia and hungary. r-economy, 4(2), 59–66. doi: 10.15826/recon.2018.4.2.009 for citation демирович, д., кошич, к., степанович, с. (2018) конкуренция на рынке сельского туризма между венгрией и сербией. r-economy, 4(2), 59–66. doi: 10.15826/recon.2018.4.2.009 doi: 10.15826/recon.2018.4.2.009 competitiveness in rural tourism between serbia and hungary dunja demirovića, kristina košićb, stefan stjepanovićc a geographical institute jovan cvijić, serbian academy of science and art, belgrade, serbia; e-mail: d.demirovic@gi.sanu.ac.rs b university of novi sad, novi sad, serbia; e-mail: tinicaus@yahoo.com c university of east sarajevo, vlasenica, bosnia and herzegovina; e-mail: stefan.stjepanovicuis@gmail.com abstract competition between tourist destinations and products has recently become very intense. while the market of rural tourism is on the rise, the future of many rural areas is uncertain due to the changes in agricultural production and the growing attractiveness of cities. in this paper, we are going to identify the factors that may influence the competitiveness of rural tourism in serbia compared with hungary, which is serbia’s main competitor. we examined the views of the key stakeholders involved in the development of rural tourism in serbia and hungary. our findings have led us to the conclusion that the level of rural tourism in hungary is considerably higher than in serbia as we found a statistically significant difference in the assessment of all the factors, except for safety and security. hungarian experts do not see serbia as their country’s competitor, which means that tourism policy makers should consider hungary as a market that requires greater investment and greater efforts to meet the demands of their sophisticated rural tourists, which is impossible to achieve in a short period of time. in the following period, hungary should be seen as serbia’s partner and serbian stakeholders should develop joint projects with their hungarian counterparts, which will improve the quality of rural tourism in serbia. at the moment, the hungarian market of rural tourism presents an example of good practice. keywords competitiveness, tourism destination, rural tourism, serbia, hungary конкуренция на рынке сельского туризма между венгрией и сербией д. демировичa, к. кошичb, с. степановичc a географический институт «йован цвиич» сербской академии наук, белград, сербия; e-mail: d.demirovic@gi.sanu.ac.rs b нови-садский университет, нови-сад, сербия; e-mail: tinicaus@yahoo.com c восточно-сараевский университет, лукавица, босния и герцеговина; e-mail: stefan.stjepanovicuis@gmail.com резюме в последнее время конкуренция между туристическими направлениями и продуктами стала очень интенсивной. в то время как рынок сельского туризма растет, будущее многих сельских районов является неопределенным из-за изменений в сельскохозяйственном производстве и растущей привлекательности городов. в данной статье определены факторы, которые могут повлиять на конкурентоспособность сельского туризма в сербии по сравнению с венгрией, которая является главным конкурентом сербии. мы рассмотрели мнения ключевых заинтересованных сторон, участвующих в развитии сельского туризма в сербии и венгрии. наши выводы привели нас к выводу, что уровень сельского туризма в венгрии значительно выше, чем в сербии, поскольку мы обнаружили статистически значимую разницу в оценке всех факторов, за исключением фактора безопасности. венгерские эксперты не считают сербию конкурентом, а это означает, что разработчики политики в области туризма должны рассматривать венгрию как рынок, который требует большего числа инвестиций и больших усилий для удовлетворения потребностей своих искушенных сельских туристов, чего невозможно достичь за короткий период. в ближайшее время венгрия должна рассматриваться как партнер сербии, а сербия должна разрабатывать совместные проекты со своими венгерскими коллегами, что улучшит качество сельского туризма в сербии. в настоящий момент венгерский рынок сельского туризма может считаться образцовым. ключевые слова конкурентоспособность, туризм, сельский туризм, сербия, венгрия acknowledgments the research was supported by the ministry of education, science and technological development, republic of serbia (grant iii 47007) благодарности исследование поддержано министерством образования, науки и технологического развития республики сербия (грант iii 47007) http://doi.org/10.15826/recon.2018.4.2.009 http://doi.org/10.15826/recon.2018.4.2.009 mailto:d.demirovic@gi.sanu.ac.rs mailto:tinicaus@yahoo.com mailto:stefan.stjepanovicuis@gmail.com mailto:d.demirovic@gi.sanu.ac.rs mailto:tinicaus@yahoo.com mailto:stefan.stjepanovicuis@gmail.com 60 www.r-economy.ru r-ecomony, 2018, 4(2), 59–66 doi: 10.15826/recon.2018.4.2.009 online issn 2412-0731 introduction in many studies, the concept of competitiveness was applied to study tourist destinations [1–3], and the research focused on how to maintain or increase the existing level of competitiveness. in research literature, competitiveness of a tourist destination is defined as “the ability of a destination to maintain its position on the market and/or to improve it over time” [2, p. 239] and “to deliver products and services that are better than in other destinations, especially with regard to those aspects of tourist experience that are important to tourists” [4, p. 374]. according to ritchie and crouch [5], the most competitive destinations are the ones that provide their residents with benefits of sustainable development. thus, it can be concluded that competitiveness implies the application of sustainability principles. in the tourism industry, the competition between tourist destinations and products has become very intense, which has contributed to greater market transparency of prices and other elements of products and services [6]. global competition in tourism has become a challenge for many countries that compete to become a desirable tourist destination, and understanding the factors that contribute to the competitiveness of a destination is essential for maintaining the current level of development of a tourist destination, its growth and vitality [5]. therefore, measuring competitiveness can be considered as a key factor in ensuring the success of tourist destinations. rural tourism is one of the priorities in the tourist development of many european countries. the rural tourism market is on the rise, while at the same time the future of many rural areas is uncertain, due to changes in agricultural production or the attractiveness of urban areas due to a higher standard of living. rural tourism is considered as one of the most effective instruments for revitalization of rural areas and ensuring their sustainable future through job retention or job creation, support for agricultural holdings, nature preservation, or keeping alive traditional rural crafts. destinations of rural tourism are a complex product consisting of several components (accommodation, transport, food, shops, attractions, and so on) [7–9]. these tourist companies are interdependent and interconnected, and they are usually small and medium-sized businesses. problems in rural tourism that are detrimental for the competitiveness of the destinations stem from the fact that local providers of tourism products and services are competing rather than cooperating with each other. to make rural destinations more competitive, it is essential to determine the factors that affect their position on the market [10]. in this paper, we are trying to identify and determine the impact of certain factors on competitiveness of rural tourism in serbia. analyzing tourist attractions, supporting factors and resources, indicators of market participation and others, we will determine how competitive serbia is as a destination of rural tourism, that is, its ability to increase tourist spending, attract more tourists, satisfy their needs, and ensure sustainable development of all the regions. we will also examine the views of the stakeholders involved in the development of rural tourism in serbia and hungary (direct providers of services in rural tourism, employees in tourist organizations and tourist agencies, employees in municipal and provincial services, ministry officials, and university faculty). methodology in the existing literature, there is no universally accepted set of indicators for measuring competitiveness which will be applicable to all tourist destinations at any time [11]. the model used in this study was based on models developed by ritchie and crouch [5], dwyer-kim [4] and enright-newton [12]. the final questionnaire for determining the competitiveness of serbia as a destination of rural tourism has two parts: the first refers to the socio-demographic profile of the respondents (gender, age, education, workplace and work experience), while the second part consists of 17 factors that reflect specific characteristics of rural tourism, and have an impact on the competitiveness of the rural tourist destination. since in tourism, hungary is serbia’s most significant competitor, the same questionnaire was professionally translated into hungarian and sent to tourism experts to assess the current state of rural tourism in hungary and to compare results with serbia. our serbian and hungarian experts were asked to evaluate the current state of all 17 factors that affect or can affect the competitiveness of rural tourism destinations in their countries. the research used the likert scale. since one of the aims of this study is to measure the relative importance of tourist attractions and business functions, it was necessary to conduct a survey among those individuals who have knowledge of both factors. the common characteristic of research in the field of management, inhttp://doi.org/10.15826/recon.2018.4.2.009 r-ecomony, 2018, 4(2), 59–66 doi: 10.15826/recon.2018.4.2.009 61 www.r-economy.ru online issn 2412-0731 cluding competitiveness research, is that the target groups of respondents are managers and other tourism experts, since it is assumed that they have the greatest knowledge of management and competitiveness. apart from the fact that managers and tourism experts know the specific destination they are working in, the majority can be also informed about the situation in the main competitive locations. the need to evaluate the competitiveness of a tourist destination by tourism experts was supported by gearing and associates [13], who argued that tourism experts have a significant experience in working with tourists and that their opinion can reflect the opinion of large groups of tourists. similarly, b. faulkner, m. oppermann and e. fredline [14] pointed out that tourism experts can reflect the views of the tourism market as they are in constant contact with buyers (tourists) who are in the process of making travel decisions. s. hudson, j. r. b. ritchie, and s. timur [15] noted that the input from a larger sample of tourism experts is desirable and identified six major stakeholders whose attitudes can best characterize the situation on the tourism market. these are the following: transport companies; tourist associations or destination management organization; owners of accommodation facilities; tour operators; commercial companies, and specific groups, such as ecological groups or tourist consultants. for our study, we have chosen the tourism experts who possess knowledge and/or experience relevant to this topic or whose field of research and activities are related to rural tourism and competitiveness of tourist destinations. the following tourism experts were interviewed in serbia: the faculty of higher education institutions that educate future tourism professionals; employees of the tourist organization of vojvodina and serbia; employees in local tourist organizations and those employed in national and provincial institutions for development of tourism (tourism department of the ministry of trade, tourism and telecommunications, the rural development department of the ministry of agriculture and environmental protection, provincial secretariat for economy, local self-government and inter-municipal cooperation, development agency bačka, regional development agency srem, chamber of commerce of vojvodina); tourist companies and agencies; owners of tourist companies in rural areas (farms, agricultural households, restaurants, ethnographic houses, museums, wineries, souvenir shops, organizers of village festivals); and so on. in hungary, the following tourism experts were interviewed: the faculty of higher education institutions; employees of the tourism organization of hungary; employees of nine local tourism organizations; those employed in national institutions for development of tourism (the department of tourism and catering of the ministry of economy; the ministry of rural development; and the ministry of national development); managers of tourist agencies and tour operators; owners of tourist companies in rural areas of hungary (restaurants, ethnographic houses, museums, wineries, souvenir shops, organizers of events and others); and representatives of the association of hungarian tourist guides, the association for hungarian rural tourism and agritourism and the center for rural tourism. in serbia, the survey was conducted in two ways: we used personal interviews (face-to-face technique) and questionnaires, which we sent via e-mail. in hungary, the survey was conducted only electronically (using an on-line questionnaire in the form of a web page). the tourism experts in serbia were surveyed in the period from april to june 2017, while the survey in hungary was conducted from may to july 2017. the response rate in both countries was about 50%. statistical analysis of collected data was done in the software statistical program spss 21. results the differences between the hungarian and serbian respondents were analyzed by using the t-test for dependent samples. statistically significant differences were obtained on almost all characteristics, that is, the factors of the competitiveness model. in almost all categories, hungary got higher scores. table 1 shows the differences on the first scale for factors belonging to the determinant key resources and attractions (arithmetic mean, standard deviation, value and significance). at the significance level p < 0.01, statistically significant differences were achieved with the factor geographic environment, accommodation capacities and their authenticity and general infrastructure and tourist suprastructure. hungary is better rated on items (factors) where the difference is statistically significant. the obtained results for factors in which there is a statistically significant difference show that the use of rivers, lakes and canals in rural tourism in http://doi.org/10.15826/recon.2018.4.2.009 62 www.r-economy.ru r-ecomony, 2018, 4(2), 59–66 doi: 10.15826/recon.2018.4.2.009 online issn 2412-0731 hungary is much more intensive and better organized than in serbia. protected natural areas and nature parks are important for rural tourism and in hungary, there is a larger number of organized programs and activities involving natural areas than in serbia. moreover, there is a significant difference for the factor accommodation capacities and their authenticity. in particular, there is a difference in the average ratings of hungary and serbia when it comes to the authenticity of accommodation units. the owners of accommodation facilities in hungary make sure that the appearance of the buildings and their interiors enhance the attractiveness of the facilities. the quality of basic infrastructure in hungarian villages is better than in serbia while the differences between the quality of basic infrastructure in agrotourism are not so significant. figure 1 illustrates that serbia is the closest to hungary when it comes to gastronomy, opportunities for sports, leisure and recreation and cultural heritage. it is interesting that the only factor that has a higher average rating in serbia than in hungary is safety and security. in further research, it is necessary to examine why safety and security in hungary are lower than in serbia, while managers should use this advantage of the hungarian rural market for attracting tourists. the smallest differences in the assessment of competitiveness factors between serbia and hungary are found for the determinant key resources and attractions, while the other two determinants are much more pronounced. in addition to the key resources and attractions, respondents from hungary and serbia assessed the factors within the determinant strategy table 1 t-test for dependent samples – determinant key resources and attractions factor country arithmetic mean standard deviation t significance geographic environment serbia 3.5000 .55830 –7.422 .000 hungary 4.0058 .56773 cultural heritage serbia 3.5257 .66477 –2.184 .030 hungary 3.7099 .72649 opportunities for sports, leisure and recreation serbia 3.7426 .73783 –2.535 .012 hungary 3.9562 .65157 accommodation capacities and their authenticity serbia 3.0931 .65256 –7.602 .000 hungary 3.6788 .62021 gastronomy serbia 3.9669 .83267 –.002 .998 hungary 3.9672 .90180 general infrastructure and tourist suprastructure serbia 2.9326 .70196 –9.736 .000 hungary 3.7117 .61785 safety and security serbia 4.0478 .75738 1.342 .181 hungary 3.9197 .81852 physical-geographic elements of the environment cultural heritage opportunities for sports, leisure and recreation accommodation capacities and their authenticity gastronomy general infrastructure and tourist suprastructure safety and security serbia hungary figure 1. performance of serbia and hungary for factors within the determinant key resources and attractions http://doi.org/10.15826/recon.2018.4.2.009 r-ecomony, 2018, 4(2), 59–66 doi: 10.15826/recon.2018.4.2.009 63 www.r-economy.ru online issn 2412-0731 of the tourist destination. for each of the five factors, a statistically significant difference at the level of p < 0.01 (table 2) is observed. as in the previous case, the factors of the competitiveness model for serbian rural regions are lower than in hungary. there are considerable differences for factors within the determinant tourist destination strategies between serbia and hungary, which again demonstrates that this determinant is the weakest in the competitiveness model and that the policies applied in the sphere of tourism in serbia have been inefficient so far. therefore, it is necessary to improve the quality of rural tourism in serbia in order to boost the demand. significant differences in the assessment of the factor marketing show that hungarian rural tourism is better organized. the emphasis is made on promoting the tourist offer through business entities and especially through tourist organizations and organizations for rural and agritourism. there is also organized distribution of tourist products through several travel agencies, which make this type of tourism more popular in hungary. hungarian policy-makers are aware of the importance of well-trained staff for successful development of rural tourism, and provide multiple opportunities for learning such as seminars and courses. there are also compulsory courses that owners of tourist facilities in rural areas should take. the policy for the development of tourist destinations has a better average rating in hungary due to the improved availability of the relevant data for local authorities since 1998. figure 2 shows that as for the determinant strategy of the tourist destination, there are significant differences between serbia and hungary. the only sphere in which serbia’s competitiveness is closer to that of hungary is the quality management of services. however, when it comes to this factor, the differences in the profitability of rural tourism enterprises are not so obvious, which suggests that tourism companies in hungary are struggling to ensure continued profitability of their business. table 2 t-test for dependent samples – determinant strategy of the tourist destination factors country arithmetic mean standard deviation t significance marketing serbia 2.9779 .58514 –10.166 .000 hungary 3.6616 .52452 employees in the tourist sector and rural tourist facilities serbia 2.7623 .62711 –6.562 .000 hungary 3.2920 .70415 policy of planning and destination development serbia 2.4540 .67165 –9.631 .000 hungary 3.3084 .78898 quality management services serbia 2.7960 .62153 –4.878 .000 hungary 3.1734 .65625 environmental management serbia 2.5404 .77949 –9.308 .000 hungary 3.4489 .83200 marketing employees in the tourist sector and rural tourist facilities policy of planning and destination development quality management services environmental management serbia hungary figure 2. performance of serbia and hungary for the factors within the determinant strategy of the tourist destination http://doi.org/10.15826/recon.2018.4.2.009 64 www.r-economy.ru r-ecomony, 2018, 4(2), 59–66 doi: 10.15826/recon.2018.4.2.009 online issn 2412-0731 within the third determinant of the competitiveness model, determinant tourist destination almost all factors achieved statistical significance at p < 0.01 level, except for the factor local community participation and their attitudes. in this case, hungarian rural areas scored higher (table 3). regarding economic stability, which is an important factor, tourists in hungary have a greater part of their income available for traveling to rural areas for leisure and entertainment, while the economic differences between the two countries are not significant. in hungary, many people tend to take shorter tourist trips throughout the year rather than one long vacation, which can result from better living standards and higher awareness of travel opportunities. tourists who visit rural areas are more aware of the importance of a healthy lifestyle and choose the destinations suitable for active leisure such as hiking, hiking, swimming, and jogging. these tourists are also environmentally conscious and choose protected natural areas and eco-friendly hotels. what rural tourism in serbia and hungary have in common is that tourists visiting rural areas belong to all age categories and that domestic tourists prevail. hungarian experts assessed cooperation between stakeholders more highly, which means that they are aware of the importance between the stakeholders invovled in the development of rural tourism. moreover, the development of rural tourism in hungary receives greater and more efficient financial support. this support is provided not only by state institutions but also by other stakeholders, who are trained to apply for european funds to improve all aspects of the tourist offer. figure 3 shows that the performance of the determinant the environment of the tourist destination for both countries is closest for the factor local community participation and their attitudes, which means that the differences in the average estimates for this factor are not statistically significant. in both countries, the local population is hospitable and the local community is willing to support the development of rural tourism. the problem shared by both countries is the demographic structure of the population in rural areas due to the ageing of the population and their migration to cities in search for better living conditions. table 3 t-test for dependent samples – determinant tourist destination environment factors country arithmetic mean standard deviation t significance economic stability serbia 2.3051 .74826 –7.856 .000 hungary 3.0912 .89775 characteristics of demand and socio-cultural change serbia 3.3544 .63338 –5.857 .000 hungary 3.7912 .59846 local community participation and their attitudes serbia 3.3431 .62320 –.880 .380 hungary 3.4112 .65463 cooperation between stakeholders in tourism serbia 2.4877 .78453 –6.271 .000 hungary 3.1290 .90048 incentives and financial support for the development of tourism by the government and local authorities serbia 2.5423 .77433 –3.896 .000 hungary 2.9599 .98343 economic stability characteristics of demand and socio-cultural change local community participation and their attitudes cooperation between stakeholders in tourism incentives and �nancial support for the development of tourism by the government and local authorities serbia hungary figure 3. performance of serbia and hungary for factors within the determinant the environment of the tourist destination http://doi.org/10.15826/recon.2018.4.2.009 r-ecomony, 2018, 4(2), 59–66 doi: 10.15826/recon.2018.4.2.009 65 www.r-economy.ru online issn 2412-0731 conclusion the key competitors of serbia in rural tourism are hungary, croatia and slovenia (and increasingly romania). our analysis has shown that the level of rural tourism in hungary is much higher than in serbia, since there is a statistically significant difference in the assessment of all the factors (except for safety and security). experts in hungarian tourism do not see serbia as their competitor, which leads us to the conclusion that tourism policy makers should consider hungary as a market that requires greater investment and significant efforts to meet the demands of sophisticated rural tourists, which cannot be achieved in a short period of time. in the following period, hungary should be seen as serbia’s partner and serbian stakeholders should develop joint projects with their hungarian counterparts in order to improve the quality of rural tourism in serbia. at the moment, the hungarian market of rural tourism presents an example of good practice. in the meantime, more attention and effort should be directed towards foreign tourist markets, especially the countries that serbia has good traditional connections with such as montenegro, bosnia and herzegovina, greece, and russia. state and local authorities should work together to ensure serbia’s competitiveness as a destination of rural tourism by addressing the two groups of tasks: general and more specific. general tasks are those related to leadership and innovation in product development and marketing, research on travel patterns, tourist behavior and satisfaction, and efforts to help businesses and other members of the sector in accordance with laws and regulations. specific administrative tasks are those that target certain characteristics of the sector, including, for example, creation and maintenance of a database of rural tourism destinations. it is important to distinguish between the roles that the government and individual businesses play in ensuring the competitiveness of the destination. the government is responsible for realizing systematic tasks and for adopting policies and decisions on the macro-level. in contrast, managerial tasks of the economy sector are carried out on the micro-level, that is, the level of individual owners of rural tourism facilities. these enterprises strive to become more cost-effective and more competitive on the market. it can be concluded that competitiveness of serbia as a destination of rural tourism depends significantly on the ability of each business entity to maintain its competitive position on the market, which will also strengthen the overall regional competitiveness. the support of the government is important for creating a healthy environment for business and for providing clear guidelines that will enable the rural tourism sector to grow. moreover, since a large number of service companies are involved in the provision of services to rural tourists, each section of the sector must make sure to provide high-quality experience for visitors (good value for money). references 1. buhalis, d. (2000). marketing the competitive destination of the future. tourism management, 21(1), 97–116. doi: 10.1016/s0261-5177(99)00095-3. 2. d’ hauteserre, a. m. (2000). lessons in managed destination competitiveness: the case of foxwoods casino resort. tourism management, 21(1), 23–32. doi: 10.1016/s0261-5177(99)00097-7. 3. heath, e. (2003). towards a model to enhance destination competitiveness: a southern african perspective. journal of hospitality and tourism management, 10(2), 124–141. 4. dwyer, l. & kim, c. (2003). destination competitiveness: determinants and indicators. current issues in tourism, 6(5), 369–414. doi: 10.1080/13683500308667962. 5. ritchie, j.r.b. & crouch, g.i. (2003). the competitive destination, a sustainable tourism perspective. wallingford: cabi publishing. 6.  cracolici, m.f., nijkamp, p. & rietveld, p. (2008). assessment of tourism competitiveness by analysing destination efficiency. tourism economics, 14(2), 325–342. doi: 10.5367/000000008784460427. 7. roberts, l., hall, d., mitchell, m. (2003). rural tourism and recreation, principles to practice. london: ashgate. http://doi.org/10.15826/recon.2018.4.2.009 http://doi.org/1016/s0261-5177(99)00095-3 http://doi.org/10.1016/s0261-5177(99)00097-7 http://doi.org/10.1080/13683500308667962 http://doi.org/10.5367/000000008784460427 66 www.r-economy.ru r-ecomony, 2018, 4(2), 59–66 doi: 10.15826/recon.2018.4.2.009 online issn 2412-0731 8.  demonja, d. & ružič, p. (2010). ruralni turizam u hrvatskoj s hrvatskim primjerima dobre prakse i europskim iskustvima. samobor: meridijani. 9. sidali, k. l. (2011). a sideways look at farm tourism in germany and in italy. in sidali, k. l., spiller, a. & schulze, b. (ed.) food, agriculture and tourism: linking local gastronomy and rural tourism-interdisciplinary perspectives (pp. 2–24), berlin, springer. 10.  demirović, d., košić, k., surd, v., žunić, l. & syromiatnikova, y. a. (2017). application of tourism destination competitiveness model on rural destinations. j. geogr. inst. cvijic., 67(3), 279–295. doi: 10.2298/ijgi1703279d. 11. dwyer, l., livaic, z. & mellor, r. (2003). competitiveness of australia as a tourist destination. journal of hospitality and tourism management, 10(1), 60–78. 12. enright, m. j. & newton, j. (2005). determinants of tourism destination competitiveness in asia pacific: comprehensiveness and universality. journal of travel research, 43(4), 339–350. doi: 10.1177/0047287505274647. 13. gearing, c.e., swart, w.w. & var, t. (1974). establishing a measure of touristic attractiveness. journal of travel research, 12(4), 1–8. doi: 10.1177/004728757401200401. 14.  faulkner, b., oppermann, m. & fredline, e. (1999). destination competitiveness: an exploratory examination of south australia’s core attractions. journal of vacation marketing, 5(2), 125–139. 15.  hudson, s., ritchie, j.r.b. & timur, s. (2004). measuring destination competitiveness: an empirical study of canadian ski resorts. tourism hospitality planning and development, 1(1), 79–94. doi: 10.1080/1479053042000187810. information about the authors dunja demirović – phd in tourism, research associate, geographical institute jovan cvijić sasa (đure jakšića street no. 9, 11000 belgrade, serbia); e-mail: d.demirovic@gi.sanu.ac.rs. kristina košić – phd in tourism, associate professor, university of novi sad, faculty of sciences (trg dositeja obradovića 3, 21000 novi sad, serbia); e-mail: tinicaus@yahoo.com. stefan stjepanović – msc, phd student, university of east sarajevo, faculty of agriculture (vlasenica, bosnia and herzegovina); e-mail: stefan.stjepanovicuis@gmail.com. http://doi.org/10.15826/recon.2018.4.2.009 http://doi.org/10.2298/ijgi1703279d http://doi.org/10.1177/0047287505274647 http://doi.org/10.1177/004728757401200401 http://doi.org/10.1080/1479053042000187810 mailto:tinicaus@yahoo.com mailto:stefan.stjepanovicuis@gmail.com 72 www.r-economy.ru r-ecomony, 2018, 4(2), 72–78 doi: 10.15826/recon.2018.4.2.011 online issn 2412-0731 original paper for citation petrenko, d. s. (2018) inframarginal models of spatially allocated economic structures and the analysis of production processes. r-economy, 4(2), 72–78. doi: 10.15826/recon.2018.4.2.011 for citation петренко, д. с. (2018) инфрамаргические модели пространственно разнесенных экономических структур и анализ производственных процессов. r-economy, 4(2), 72–78. doi: 10.15826/recon.2018.4.2.011 doi: 10.15826/recon.2018.4.2.011 inframarginal models of spatially allocated economic structures and the analysis of production processes dmitry s. petrenko regional development center ekaterinburg, central bank of the russian federation, ekaterinburg, russia; e-mail: zlobec@gmail.com abstract the article discusses designing of labor division networks. designing of the economic structure of labor division constitutes the main part of inframaginal analysis. inframaginal analysis normally uses predefined economic structures, which means that in certain cases some economic structures may be neglected. such inaccuracies may be not important in the analysis of small enterprises but in the analysis of spatially allocated economic structures, some important aspects may be left unnoticed, which will lead to wrong decisions regarding labor allocation. to make an enterprise competitive it is essential to understand what is the optimal economic organization and the form of labor division in the given region. if some economic structures are not taken into account in the analysis, the general equilibrium will be incorrect, which will negatively affect the decision-making. if we use inframarginal models to analyze the production process, it will allow us to take a fresh perspective on the problem. all possible structures of the division of labor are designed by using production factors and goods to reduce the risk of errors in the process of decision-making, which will make the production process of the enterprise more efficient. keywords inframarginal analysis, technology, division of labor, network effects, economic structures, regional economy инфрамаргические модели пространственно разнесенных экономических структур и анализ производственных процессов д. с. петренко региональный центр развития «екатеринбург», центральный банк российской федерации, екатеринбург, россия; e-mail: zlobec@gmail.com резюме в статье обсуждается проектирование сетей разделения труда. проектирование экономической структуры разделения труда составляет основную часть инфрамагинального анализа. инфрамагинальный анализ обычно использует предопределенные экономические структуры, а это означает, что в некоторых случаях некоторыми экономическими структурами можно пренебречь. такие неточности могут быть не важны при анализе малых предприятий, но при анализе пространственно распределенных экономических структур некоторые важные аспекты могут остаться неучтенными, что приведет к неправильным решениям относительно распределения рабочей силы. чтобы сделать предприятие конкурентоспособным, важно понять, что является оптимальной экономической организацией и формой разделения труда в данном регионе. если в анализе не учитываются некоторые экономические структуры, общее равновесие будет неверным, что негативно скажется на процессе принятия решений. если мы используем инфрамаргинальные модели для анализа производственного процесса, это позволяет нам взглянуть на проблему с новой точки зрения. все возможные структуры разделения труда разработаны с использованием факторов производства и товаров для снижения риска ошибок в процессе принятия решений, что сделает производственный процесс предприятия более эффективным. ключевые слова инфрамаргинальный анализ, технологии, разделение труда, сетевые эффекты, экономические структуры, региональная экономика http://doi.org/10.15826/recon.2018.4.2.011 http://doi.org/10.15826/recon.2018.4.2.011 r-ecomony, 2018, 4(2), 72–78 doi: 10.15826/recon.2018.4.2.011 73 www.r-economy.ru online issn 2412-0731 introduction there are two types of business decisions: decisions associated with the choice of activity and decisions of resource allocation. decisions of the first type can be illustrated by the choice of majors students make when entering the university. these are inframarginal decisions. then students choose the courses they want to study and decide on the time they want to spend on each of the learning courses. these are decisions of the second type – marginal decisions of time allocation. in the context of the division of labor, inframarginal decisions are more important than marginal decisions. in most cases of inframarginal analysis, a set of economic activities which can be chosen by individuals is set exogenously and inframarginalists are concerned with the problem of mathematical optimization of utility functions [4,  p.  14]. the set of economic activities which can be used in the division of labor is usually limited and well known. in real life, however, managers have enough practical experience to determine the optimality of particular structures of the division of labor in various cases. complex and specific results of inframarginal articles are not practically useful for the decision-making process, which leads to a situation when “inframarginalists write papers mainly for inframarginalists” [6, pp. 177]. the technology-oriented theory of production can be divided into function analysis and activity analysis depending on the object of analysis [1, p. 1055]. inframarginal analysis is based on activity analysis, proposed by koopmans. function analysis was introduced by fandel [7, p. 41] to find the types of possible economic structures in the process of inframarginal analysis. activity was defined by koopmans as “the combination of certain qualitatively defined commodities in fixed quantitative ratios as ‘inputs’ to produce as ‘outputs’ certain other commodities in fixed quantitative ratios to the inputs” [9]. method and model let us now consider the asymmetric model with trading activities and heterogeneous parameters introduced by yang [13, pp. 111]. in the model of specialization, there are three types of goods x, y, and z. the number of goods which are sold on the market have index s. the number of goods which are purchased on the market have index d. the self-provided goods have index c. the transaction cost coefficient is 1− k, k is viewed as a transaction service and depends on the quantity of labor used in transactions. as a service, it can be self-provided or purchased on the market: k = rc + rd. in this case, rc and rd as transaction services relate to the distance between a pair of trade partners and their location problems. all individuals are evenly spaced and the distance between each pair of neighbors is a constant. the distance between a pair of trade partners may differ from the distance between a pair of neighbors. for example, they can be engaged in rural or urban relations. the utility function is identical for all individuals and has a form of the cobb-douglas utility function [5, p. 337]: [ ( ) ] [ ( ) [ ( ) . ] ] c c d d c c d d c c d d u x r r x y r r y z r r z α β γ = + + + + + + × × the set of activities known to an enterprise describes the technical opportunities of this enterprise. this set is called technology and is designated by symbol t [7, p. 43]. therefore, technology can be written the following way: | 1, , , 0 . l x yt l x y z z r −       = = ≥         labor restrictions are equal for all economic agents and can be written as: [ 1, 0 ], 1 , , , , . x y z r i l l l l l i x y z r + + = ∈ + = using the theorem of optimum configuration ‘the optimum decision does not involve selling more than one good, does not involve selling and buying the same good, and does not involve buying and producing the same good’ [11], we can find vectors of activities for technology t. the producer-consumer uses only one production factor l (labor) in the production processes. the economic agent can produce a good only for their own consumption xc or produce an additional part of the good for sale in order http://doi.org/10.15826/recon.2018.4.2.011 74 www.r-economy.ru r-ecomony, 2018, 4(2), 72–78 doi: 10.15826/recon.2018.4.2.011 online issn 2412-0731 to purchase other types of goods that the economic agent does not produce on their own xs. if the economic agent does not produce a good and purchases the good on the market, we put 0 (zero) in the activity vector. all the possible activities vectors can be written the following way: , 0 0 0 , , , , 0 0 , 0 c c c c c c c c s c s c s c c c c s c s c c c c c c c l l x x y y z z r l l l l l x x x x x x x y y y y y y z z z r r r r t − −                               − − − − −               + + +         + +                                                   ′  = 0 0 0 0 0, , , , , 0 0 c c s c c c c c c c c c c s c s c s c c c c c s c s c s l x y y z l l l l l l x x x x y y y y z z z z z z z z r r r r r r r r −      +         − − − − − −                                                           + + +                      + + +            0 0 0 0, , , , , 0 0 0 0 0 0 0 0 0 0 , 0 c s c s c s c c c s c s c s c c c c c c s l l l l l l x x x x x x x y y y y y y y z z r r l l x y z z  − − − − − −                       + + +             + + +                                                           − −         +     0 0 0 0 0 0, , , , 0 0 0 0 0 0 0, , 0 0 0 0 0 c c c c s c s c c c s c s c s c s c s c s l l l l x y z z z z z r r r r r r r l l l x x y y z z − − − −                                                 + +                   + + +          − − −        +     +        +           . , 0 c c c s l x y r r                                                                                −                          +      each element in matrix t represents the production function of an economic agent. the economic agent can choose any production function. the agent’s choice represents their production process, and it will be an inframarginal choice. for each activities vector in matrix t we will find cases in which the utility functions of the economic agent will be positive. combinations of activities vectors will give different types of economic structures. some of these were reviewed earlier [13,  p.  115] and we will use them to show the method of construction of economic structures from technology matrix t. results the simplest case is autarky: an individual self-provides three goods. therefore, the number of goods sold and purchased and the number of transaction services are 0. the technology has only one activity vector . 0 c c c l x yt z  −         =              the utility function can be written as: 0.c c cu x y z α β γ= > in this case only one activity vector is sufficient to achieve a positive value of the utility function and there is no network of labor division. the pattern of labor division is shown as a graph [2] in figure 1. a[y] [x] [z] figure 1. autarky activities 0 0 0 0, , , , , 0 0 c s c s c c c c s c s c c c c s c s c c c c c c l l l l l l x x x x x x y y y y y y z z z z z z r r r r r r  − − − − − −                        + +             + +                         + +                                     exist in cases of partial division of labor. in this case an individual sells one of the produced goods and purchases one of the goods for consumption. the utility function should be positive. for an individual with the activity vector 0 c s c c l x x z r −   +            there should exist an individual with the activity vector 0 c s c c l y y z r −      +         http://doi.org/10.15826/recon.2018.4.2.011 r-ecomony, 2018, 4(2), 72–78 doi: 10.15826/recon.2018.4.2.011 75 www.r-economy.ru online issn 2412-0731 and so on for activities 0 , . 0 c s c c s c c c l l x x y y y z r r − −       +     +                   individuals form an economic structure with production processes described by technology 0 0 , c s c s c c c c l l x x y yt z z r r  − −        +     +=                        (see figure 2). x/y [y][x] [z] y/x [z] [r] [r][xs] [xd] [yd] [ys] figure 2. partial division of labor the complete division of labor (figure 3) is represented by technology 0 0 0 0, , 0 0 c s c s c s c c c l l l x x y yt z z r r r  − − −            +       +=              +                   with three activities vectors. in this case, individuals produce only one of the goods and purchase two on the market. the transaction service is self-provided. y/xz [y] [x] [z][r][r] [xs] [xd] [y d][y s] z/xy [r] market [yd][zd] [zd] [xd] [zs] x/yz figure 3. complete division of labor for a complete production process, an individual with the activity vector 0 0 c s c l x x r −   +            needs two other activities: 0 0 c s c l y y r −      +         and 0 0 . c s c l z z r −         +     if all of these activities vectors are present, the utility functions for all individuals are positive and there is division of labor. partial division of labor and transaction services can be represented by the combination of the following activities vectors: 0 0 0 0, , ; 0 0 c s c s c c c c s l l l x x y yt z z z r r  − − −            +       +=                          +        0 0 , , ; 0 0 0 0 c s c c c c s c s l l l x x y y yt z z r r  − − −            +        =              +           +        0 0, , . 0 0 0 0 c c c c s c s c s l l l x x x y yt z z r r  − − −                    +=              +           +        y/xz [y] [x] [z]r/xy[r] x/yr [z] [z] [r][r] [y] [y] [x] [x] figure 4. partial division of labor http://doi.org/10.15826/recon.2018.4.2.011 76 www.r-economy.ru r-ecomony, 2018, 4(2), 72–78 doi: 10.15826/recon.2018.4.2.011 online issn 2412-0731 the complete division of labor and transaction services can be represented by the combination of the following activities vectors: 0 0 0 0 0 0, , , . 0 0 0 0 0 0 c s c s c s c s l l l l x x y yt z z r r  − − − −                +         +=                  +               +          y/xz [y] [x] [z][r][r] [x] [x] [y] [y] z/xy [r] r/xyz [y][z] [z] [x] [z] x/yz [r][r] [r] figure 5. complete division of labor and transaction service discussion in the case of a complete production process, there should be four individuals who produce one type of goods or transactional service. it is easy to show that the following activity vectors , , 0 0 0 c s c c c c s c c c c s l l l x x x x y y y y z z z z  − − −            +       +             +                   cannot be a part of the production process and a part of labor division because it is impossible to find individuals with the corresponding activity vectors with the positive utility function for these cases. these four basic forms of the division of labor (autarky, partial division of labor, complete division of labor, and complete division of labor and transaction service) were discussed by x. yang and wai-man liu [13, p. 115], but the following activities vectors 0 0, , 0 c c c c c c c s c s c s l l l x x y y z z r r r r r r  − − −                                              + + +        were not considered. activity vector 0 c c c s l y z r r −             +  can exist in the following production process: 0 0 0, , . 0 0 p c s c c sx c c c c s l l l x x y y yt z z z r r  − − −            +       +=                          +        the economic structure for this technology is showed in figure 6. technology txp is characterized by the production process with an intermediate product. we can see that y is the intermediate product and x is the final product because all individuals consume x and y is used for production x. x/yr [y] [x] y/xr [r] market r/x [x] [r] [x] [r] figure 6. division of labor with the intermediate product the utility function for configuration x/yr can be written as: / ( ) .x yr c d d cu x r y z α β γ= the utility function for configuration y/xr can be written as: / ( ) .x yr d d c cu r x y z βα γ= the utility function for configuration r/x can be written as: ( ) .c d c cu r x y z α β γ= another production process with activity vector 0 c c c s l y z r r −             +  http://doi.org/10.15826/recon.2018.4.2.011 r-ecomony, 2018, 4(2), 72–78 doi: 10.15826/recon.2018.4.2.011 77 www.r-economy.ru online issn 2412-0731 can be written the following way: 0 0 0 0 0, , , . 0 0 0 0 0 f c s c c sx c c s c s l l l l x x y y yt z z z r r  − − − −                +         +=                  +               +          in this case, all individuals decide to specialize in production of final goods. an individual who provided a transactional service makes a decision of partial specialization and purchases final product x. 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(1998). an analytical framework of consumer-producers, economies of specialization and transaction costs. in: arrow, k. j., ng, y.-k. & yang, x. (eds) increasing returns and economic analysis (pp. 170–185). uk, palgrave macmillan. 12.  tombazos, c. (2006). inframarginal contributions to development economics. singapore. new york: world scientific publishing co. pte. ltd. 13. yang, x. & liu, w.-m. (2009). inframarginal economics. increasing returns and inframarginal economics. vol. 4. singapore: world scientific publishing co. pte. ltd. 14. yu, x., chai, y., liu, y. & sun h. (2014). infra-marginal analysis model for provision mode selection for e-commerce services. tsinghua science and technology, 19(2), 174–183. doi: 10.1109/ tst.2014.6787371. 15. zhang, y. (2014). climate change and green growth: a perspective of the division of labor. china & world economy, 22(5), 93–116. doi: 10.1111/j.1749-124x.2014.12086.x. information about the author dmitry s. petrenko – regional development center ekaterinburg, central bank of the russian federation (ekaterinburg, russia); e-mail: zlobec@gmail.com. http://doi.org/10.15826/recon.2018.4.2.011 http://doi.org/10.1016/j.ejor.2016.02.053 http://doi.org/10.1109/tst.2014.6787371 http://doi.org/10.1109/tst.2014.6787371 http://doi.org/10.1111/j.1749-124x.2014.12086.x mailto:zlobec@gmail.com 30 www.r-economy.ru r-ecomony, 2018, 4(1), 30–29 doi: 10.15826/recon.2018.4.1.005 online issn 2412-0731 original paper for citation lukić, d., berjan, s., el bilali, h. (2018) indicators of tourism development of the serbian danube region. r-economy, 4(1), 30–37. doi: 10.15826/recon.2018.4.1.005 for citation лукич, д., берьян, с., эл билали, х. (2018) индикаторы развития туризма в придунайских районах сербии. r-economy, 4(1), 30–37. doi: 10.15826/recon.2018.4.1.005 doi: 10.15826/recon.2018.4.1.005 indicators of tourism development of the serbian danube region dobrila lukića, siniša berjanb, hamid el bilalic a alfa bk university, belgrade, serbia; dobriladjerdap@gmail.com b university of east sarajevo, faculty of agriculture, sarajevo, bosnia and herzegovina; email: sinisaberjan@yahoo.com c sustainable agriculture, food and rural development department, international centre for advanced mediterranean agronomic studies (ciheam-bari), valenzano (bari), italy; hamid.elbilali@boku.ac.at abstract protected natural area in the danube region covers 107,200 hectares and includes two national parks, two nature parks, one place of outstanding natural beauty, five special natural reserves, twenty-five nature monuments, and two sites of international significance included in the ramsar list. however, only 140 immovable and 374 movable cultural objects are officially registered. there are 31 cultural objects of exceptional importance and national significance and 89 objects of great importance and regional significance. the objects with this status are protected by the state. two sites are on the preliminary unesco world heritage list. this paper discusses the potential of tourism industry in the serbian danube region and the prospects of its further development. we outline the current state of tourism industry and describe the geographical location of the region, its natural and anthropogenic resources, and accommodation capacities. we analyse such data as the number of tourists and the number of overnight stays by municipalities in 2016, and the average length of stay. the indicators used are the functionality coefficient, the capacity utilization and the intensity of functionality. the conclusion is drawn that the tourism potential of the serbian danube region is not fully realized and that its development should be at a much higher level, given the increasingly important role of the region as a major tourist destination in serbia. keywords serbia, danube region, indicators, development, tourism индикаторы развития туризма в придунайских районах сербии д. лукичa, с. берьянb, х. эл билалиc a алфа бк универзитет, белград, сербия; dobriladjerdap@gmail.com b восточно-сараевский университет, лукавица, босния и герцеговина; email: sinisaberjan@yahoo.com c международный центр средиземноморских агрономических исследований, валенцано, италия; email: hamid.elbilali@boku.ac.at резюме охраняемая природная территория в дунайском регионе занимает 107 200 гектаров и включает в себя два национальных парка, два природных парка, одно место выдающейся природной красоты, пять специальных природных заповедников, двадцать пять памятников природы и два объекта международного значения, включенные в список рамсарской конвенции. однако официально зарегистрировано только 140 недвижимых и 374 передвижных культурных объекта. есть 31 культурный объект исключительной важности и национального значения и 89 объектов, имеющих большое значение и региональное значение. объекты с этим статусом защищены государством. два объекта находятся в предварительном списке всемирного наследия юнеско. в данной статье обсуждается потенциал индустрии туризма в регионе сербского дуная и перспективы его дальнейшего развития. мы описываем текущее состояние индустрии туризма и географическое положение региона, его природные и антропогенные ресурсы, а также гостиничные мощности . мы анализируем такие данные, как количество туристов и количество ночевок в муниципалитетах в 2016 г., а также средняя продолжительность пребывания. используемыми индикаторами являются коэффициент функциональности, использование мощности и интенсивность функциональности. сделан вывод о том, что туристический потенциал сербского дунайского региона не полностью реализован и его развитие должно быть на гораздо более высоком уровне, учитывая все более важную роль региона как важного туристического направления в сербии. ключевые слова сербия, дунайский регион, показатели, развитие, туризм http://doi.org/10.15826/recon.2018.4.1.005 http://doi.org/10.15826/recon.2018.4.1.005 r-ecomony, 2018, 4(1), 30–37 doi: 10.15826/recon.2018.4.1.005 31 www.r-economy.ru online issn 2412-0731 introduction the serbian danube region is a destination that is gaining more and more importance on the tourist market of serbia. the region offers a variety of diverse tourist attractions ranging from natural parks and reserves to cultural heritage sites [1]. however, the abundance of resources does not always guarantee commercial success [2]. therefore, it is important to define the direction for development of tourism in the region, to achieve the synergy of all the key factors, and to cooperate with other local partners to promote the serbian danube region as a major tourist destination. the goal is to boost revenues of the tourism industry by increasing the number of tourists and the number of overnight stays. the growth in the tourism sector would create more jobs, reduce the outflow of the population to other regions and improve the living standards of the local community [3]. theoretical framework until the second half of the twentieth century, the data on tourist arrivals, number of beds and the average length of stay as well as the number of people employed in tourism and hospitality industry had been the key indicators for assessment of tourism development in specific destinations [4]. later, in order to determine the impact of tourism on local economies, the research started to focus on the ratio of accommodation capacities and the number of local population in specific destinations [5; 6]. the first to apply this type of methodology was french geographer pierre defert, who proposed the index of tourist function in 1967. french researcher rene baretje in 1978 improved defert index and brought it in agreement with the spatial unit of destination. numerous studies introduced other indicators, in addition to defert-baretje’s index, for measuring the tourist intensity. for example, polish researchers used charvat’s index to show the development of tourism as a result of urbanization. the intensity of tourism can also be determined with the help of schneider’s index, which is often referred to as the index of tourist traffic intensity [7]. description of the region the serbian danube region extends between 45°48’39” and 44°12’48” north latitude and 18° 51’9”and 22°40’18” east longitude. this region is located in central europe in the southern part of the pannonian basin, in the north of the republic of serbia [8]. the danube region in serbia covers 15,755 km2, which is about 17.8% of its total area. according to the last census, there are 2,957,577  people in 499 settlements, that is, about 40.7% of the total population of serbia. the average population density is 125 inhabitants per km2. the region comprises 24 local self-government units that have a direct access to the danube. the territory can be divided into the following parts: – the upper danube region, the area located along the border with croatia from batina (bezdan) to bačka palanka. recently, this region has significantly changed its spatial and functional characteristics; the central danube region, the area from bačka palanka to ram, which includes the largest and most important centres in serbia. this region has retained its previous characteristics and does not require any changes in the planning and arranging of its territory; the lower danube region, the area from ram to prahovo, located on the border with romania. this region holds considerable potential in the sphere of trans-border cooperation [9]. the serbian danube region comprises 107,200 hectares of protected natural area, which makes it an ecological corridor of international significance. the protected areas include the following: – 2 national parks: fruska gora and djerdap; – 2 nature parks: tikvara and begečka jama; – area of unique natural beauty: veliko ratno ostrvo; – 5 natural reserves: gornje podunavlje, karadjordjevo, bagremara, koviljsko-petrovaradinski rit and deliblatska peščara; – 25 natural monuments covering over one hectare of area: stari park near sonta, park čelarevskog dvorca, kamenički park, dvorska bašta park, mačkov sprud, ivanovačka ada and šalinački lug; – according to the convention on wetlands, gornje podunavlje and labudovo okno are registered as sites of international importance for wetland habitats of bird species [10; 11]. within the serbian danube region, there are areas that enjoy the status of internationally protected areas and those with the candidate status: for example, gornje podunavlje and labudovo okno are already included in the list of ramsar sites, while koviljsko-petrovaradinski rit and donje podunavlje are awaiting to be approved. such areas as gornje podunavlje, deliblatska https://doi.org/10.15826/recon.2018.4.1.005 32 www.r-economy.ru r-ecomony, 2018, 4(1), 30–37 doi: 10.15826/recon.2018.4.1.005 online issn 2412-0731 peščara and djerdap have the status of recognized biosphere reserves within the unesco’s man and the biosphere (mab) programme. djerdap national park is covered by the framework convention on the protection and sustainable development of the carpathians. serbia has also submitted nomination proposals for deliblatska peščara and djerdap national park to be included into the world heritage list on the basis of the convention on the protection of the world cultural and heritage site [10]. there are 1,186 objects of cultural significance in the serbian danube region. however, only 140 immovable and 374 movable cultural objects are officially registered. there are 31 cultural objects of exceptional importance and national significance and 89 objects of great importance and regional significance. the objects with this status are protected by the state. the town of bač and smederevo fortress with its surroundings have been on the preliminary unesco world heritage list since 2010. all these natural and anthropogenic resources of the serbian danube region are a part of the european heritage, which can be used as the starting point for their promotion and marketing as tourist attractions [11]. the peculiar feature of tourism in the serbian danube region is the number and diversity of the natural and anthropogenic landmarks concentrated in a relatively small territory. the problem that needs to be addressed is the low level of their attractiveness for tourists. moreover, tourists’ awareness about these spots is also low [12]. it is known that the danube is one of the most popular river boat destinations: it ranks first in the world by the number of tourists that visit it on boat cruises. in 2008, out of 380,000 german and austrian tourists that travelled on international tourist boats, only 51,000 stopped in belgrade [13]. on the one hand, there are fortresses such as kalemegdan and petrovaradin, whose promotion is ineffective; on the other hand, there are also fortresses that remain largely unknown to tourists. the most attractive cultural landmark in the region is the archaeological park viminacium. another example of successful promotion is lepenski vir: since 2012, the efficient marketing campaign has made it much more interesting for tourists. table 1 the region’s population by municipalities (data of the 2011 census) municipality surface area in sq. km populated places population people per sq. km district serbia 88,509 6,158 7,258,753 – – belgrade 3226 157 1,647,490 514 – apatin 380 5 29,500 84 west backa odzaci 411 9 30,202 73 sombor 1216 16 87,539 74 bela crkva 353 14 17,912 51 south banat kovin 730 10 34,990 48 pancevo 756 10 12,3021 163 novi sad 699 16 333,268 477 south backa backa palanka 579 14 55,898 97 bac 365 6 14,415 39 backi petrovac 158 4 13,418 85 beocin 185 8 15,589 84 sremski karlovci 51 1 8,797 172 titel 261 6 16,070 61 zrenjanin 1327 22 123,536 93 central banak indjiјa 385 11 47,818 124 srem stara pazova 350 9 70,333 200 kladovo 629 23 21,142 34 southern and eastern serbiamaјdanpek 932 14 19,854 21 negotin 1,090 39 38,030 35 pozarevac 477 27 73,975 156 branicevo veliko gradiste 344 26 18,956 55 golubac 367 24 8,654 25 smederevo 484 28 107,170 223 podunavlje (danube basin) source: statistical office of the republic of serbia. https://doi.org/10.15826/recon.2018.4.1.005 r-ecomony, 2018, 4(1), 30–37 doi: 10.15826/recon.2018.4.1.005 33 www.r-economy.ru online issn 2412-0731 tourist infrastructure and tourist traffic in the serbian danube region there is currently no adequate record of accommodation in serbia and it is not possible to give a complete overview of accommodation facilities and complementary accommodation facilities. although many towns and municipalities on the danube hold a great potential for the development of tourism, they have a poor tourist infrastructure [14]. in our analysis we are using the data provided by the statistical office of the republic of serbia. as statistics show, in 2016, 1,250,308 tourists arrived in the serbian danube region and spent 2,647,347 nights. the average length of stay of domestic tourists was 2.3 days, while foreign tourists stayed for 2 days. interestingly enough, twice as many foreign tourists as domestic ones visited the region in the given period. in 2016, 299 accommodation facilities were registered in the serbian danube region. these facilities offer 15,688 rooms and 33,176 beds, with 31,827 permanent and 1,349 extra beds (table 2). accommodation services are predominantly provided by hotels. there are 138 hotels in the serbian danube region, all of them categorized. hotels of a lower category have 8,868 rooms and 15,688 beds. in the region, there are 5 five-star hotels, 38 fourstar hotels, 26 three-star hotels, 14 two-star hotels and 4 one-star hotels. there are also two apartment hotels (a five-star and a four-star). as for garni hotels, there is one five-star, 18 four-star, 25 three-star, 4 two-star, and a one-star. in addition to the hotels, the serbian danube region also has one boarding house, 3 motels, 61  overnight stays, 9 apartments, 17 inns with accommodation, 3 spa centres, 2 mountain huts, 3 children’s and youth resorts, 57 hostels, 4 camps, and a car for sleeping. there are seven other accommodation facilities, including campsites, hun ting lodges and huts, tourist resorts [15]. table 2 tourist accommodation capacities in the serbian danube region in 2016 municipality permanent establishment available rooms bed places permanent beds spare beds belgrade 149 8,047 15,389 14,695 694 apatin 5 269 610 604 6 odzaci 4 28 56 56 0 sombor 9 233 630 613 17 bela crkva 4 346 1,016 1,011 5 kovin 1 32 130 130 0 pancevo 5 29 78 70 8 novi sad 58 4,064 9,129 8,943 186 bac 2 14 33 33 0 backi petrovac 0 93 197 197 0 backa palanka 7 113 228 207 21 beocin 2 36 64 61 3 sremski karlovci 3 129 282 268 14 titel 1 41 93 93 0 zrenjanin 12 323 674 654 20 indjiјa 4 98 210 199 11 stara pazova 6 160 394 314 80 kladovo 4 424 1,173 1,064 109 maјdanpek 2 361 736 716 20 negotin 4 203 530 510 20 smederevo 4 66 129 128 1 golubac 2 84 242 191 51 veliko gradiste 4 338 835 808 27 pozarevac 7 157 318 262 56 total 299 15,688 33,176 31,827 1,349 source: statistical office of the republic of serbia. https://doi.org/10.15826/recon.2018.4.1.005 34 www.r-economy.ru r-ecomony, 2018, 4(1), 30–37 doi: 10.15826/recon.2018.4.1.005 online issn 2412-0731 hotels are well-equipped to accommodate large tourist groups as well as conference guests. however, the average occupancy rate in the serbian danube region is low and, therefore, hotels’ annual revenues are quite modest [14]. the largest number of tourists come to belgrade and novi sad. thus, it is the hotel industry in these areas that has the greatest impact on economy. for more balanced development of tourism industry in the serbian danube region it is necessary to build many more facilities for accommodation of tourists in other parts of the region. the number of foreign tourist arrivals in 2016 was 885,672 or 70.8% of the total number of arrivals. foreign tourists made 1,808,924 overnight stays, which is 68.3% of the total number of overnight stays in the danube region (table 3). the large proportion of foreign tourists indicate the increasing importance of foreign tourism for the development of the region. the absolute values of the tourist traffic as well as the region’s participation in the overall tourist traffic of serbia are likely to increase in the future due to the region’s significant natural potential and the size of its territory. the current data indicate the growth of tourism industry and the systemic approach applied to tourism development and management by the authorities of the serbian danube region. at the moment, the leading municipalities in this respect are belgrade, novi sad, kladovo, majdanpek and veliko gradište. municipalities which have the smallest tourist traffic are also the most underdeveloped. these include odžaci, bač, titel and pančevo. thus, the local trend contradicts the global pattern in which the share of family business in tourism, especially in the domain of accommodation services, is becoming increasingly important [16]. encouraging the construction of facilities in the private sector seems to be a very suitable development option, which could improve the poor social conditions of the local population and compensate for the lack of investment in tourism and hospitality management in serbia. table 3 tourists and overnight stays in 2016 municipality tourists nights spent average number of nights spent total domestic foreign total domestic foreign domestic foreign belgrade 913,150 176,087 737,063 1,867,150 406,674 1,460,476 2.3 2.0 apatin 7,007 5,570 1,437 52,035 46,875 5,160 8.4 3.6 odzaci 58 49 9 319 241 78 4.9 8.7 sombor 11,271 7,369 3,902 21,548 14,058 7,490 1.9 1.9 bela crkva 1,186 1,143 43 8,024 7,929 95 6.7 2.2 kovin 2,520 2,358 162 8,915 8,285 630 3.5 3.9 pancevo 1,190 670 520 2,310 1,300 1,010 1.9 1.9 novi sad 174,489 67,808 106,681 360,578 118,956 241,622 1.8 2.3 bac 547 215 332 1,346 337 1,009 1.5 3.0 backi petrovac 2,708 1,459 1,249 5,386 2,456 2,930 1.7 2.3 backa palanka 3,310 1,338 1,972 6,804 2,725 4,079 1.9 2.0 beocin 1,982 1,601 381 4,700 3,235 1,465 2.0 2.0 sremski karlovci 7,219 5,059 2,160 12,926 8,181 4,745 1.6 2.2 titel 558 473 85 1,444 1,192 252 2.5 3.0 zrenjanin 15,261 8,926 6,335 54,085 31,126 22,959 3.5 3.6 indjiјa 2,503 1,340 1,163 4,762 1,927 2,835 1.4 2.4 stara pazova 12,053 6,308 5,745 32,986 16,949 16,037 2.7 2.8 kladovo 25,651 21,719 3,932 50,187 42,219 7,968 1.9 2.0 maјdanpek 24,774 20,023 4,751 44,245 33,635 10,610 1.7 2.2 negotin 4971 4,492 479 14,043 12,715 1,328 2.8 2.8 pozarevac 13,269 11,004 2,265 30,164 24,839 5,325 2.3 2.4 veliko gradiste 17,891 15,755 2,136 52,861 46,378 6,483 2.9 3.0 golubac 3,186 2,470 716 4,540 3,606 934 1.5 1.3 smederevo 3,554 1,400 2,154 5,989 2,585 3,404 1.8 1.6 total 1,250,308 364,636 885,672 2,647,347 838,423 1,808,924 2.3 2.0 source: statistical office of the republic of serbia. https://doi.org/10.15826/recon.2018.4.1.005 r-ecomony, 2018, 4(1), 30–37 doi: 10.15826/recon.2018.4.1.005 35 www.r-economy.ru online issn 2412-0731 methodology this paper analyses indicators of tourist functions that can help determine the intensity of tourism and its development in a particular destination. the analysis of four indicators is applied to determine the region’s importance and participation in the overall tourist offer of serbia. in order to present the tourist development of the region, we analysed the following indicators as of 2016: the length of stay of tourists, the functionality coefficient, the capacity utilization and the intensity of functionality [17]. length of stay (ls) is the ratio of the number of overnight stays (no) to the number of tourists (nt): . no ls nt = functionality coefficient (fc) is the ratio of number of beds (nb) to the population number (pn): 100 . nb fc pn ⋅ = capacity utilization (cu) is the ratio of the number of overnight stays (no) to the number of beds (nb) during the year. this indicator allows us to assess the profitability of accommodation facilities: 100 . 365 no cu nb ⋅ = ⋅ if the capacity utilization is higher than 60%, the business is profitable; if it ranges between 40% and 60%, then the business is able to cover its costs to stay afloat; and if under 40%, the business is not profitable [17]. the intensity of functionality refers to the volume of tourist traffic in the given location within a certain time period. it can be measured in terms of space, the number of local population or the size of accommodation capacities [17]. in this paper, we measure this indicator by using the population size: 100 , nt if pn ⋅ = where if is the intensity of functionality; nt, the number of tourists; and pn, the local population [7]. results and discussion the results of research show that the serbian danube region is a well-established destination on the tourist market, which is reflected in the number of tourist visits throughout the year. the turnout is particularly intense during the summer months. we should take into consideration that an increase in the number of visitors in general could lead, in addition to positive economic effects, to the decline in the quality of tourist services and excessive pressure on the capacities of certain sites. as table 4 illustrates, the length of tourist stays in 2016 was quite short – on average two days. this fact can be explained by the poor state of tourism and hospitality infrastructure in serbia, for example, the lack of available rooms and beds, accompanied by the decline in the population’s purchasing power and the rising prices of services. the only exception from this trend is odžaci, in which tourists’ average length of stay was about 18 days. the functionality coefficient for the entire region is only 1.12% due to the small number of available beds. however, even if the actual number of beds was increased, we would still have a low coefficient of functionality. this means that we should also work to improve the overall tourist offer in the region. a slightly better picture in this indicator is found in djerdap, sombor and bela crkva. in these areas, the functionality coefficient is significantly higher than the average values for the whole region – over 5% – due to better accommodation capacities. it is also obvious that the local population in these areas does not suffer from intensive construction of tourist infrastructure, which is of great importance for the sustainable development of the whole region. it is recommended that in the municipalities specializing in tourism the ratio of number of beds to the number of inhabitants should be 1.5:1 [18]. the capacity utilization indicator reflects the level of economic development and profitability. unfortunately, its current level of 21.86% indicates the ultimate unprofitability of the local accommodation facilities. the intensity of functionality is an indicator that shows the intensity of tourist traffic, which is estimated by using the number of tourist arrivals. this indicator in the region is comparatively low and amounts to 42.7%, which means that the negative impact of tourists on the local culture and the local identity is low. higher values of this indicator were recorded in kladovo, majdanpek (djerdap), sremski karlovci and belgrade. https://doi.org/10.15826/recon.2018.4.1.005 36 www.r-economy.ru r-ecomony, 2018, 4(1), 30–37 doi: 10.15826/recon.2018.4.1.005 online issn 2412-0731 conclusion the serbian danube region is becoming an increasingly important tourist destination of serbia, along with popular spa areas and mountain destinations. it is rich in natural and anthropogenic tourist attractions, which are underrated and deserve to be better presented in the tourist market. the region’s natural highlights, which could successfully compete with their counterparts in other european countries, require additional investment into the development of their tourist infrastructure. although the general attitude in the region is that each municipality should bear responsibility for the development of its own tourism industry, it would be more productive to foster stronger links between the municipalities. then, more prosperous municipalities such as belgrade and novi sad would also be able to boost the growth of tourism in other municipalities and thus make their economic development more balanced. this way, underdeveloped areas would become more attractive to tourists while more advanced municipalities would be able to reduce the negative impact of tourism on their environment and the population’s culture and way of life. moreover, such strategy would allow the government to redistribute the pressure on the existing infrastructure, which is overloaded in the high peaks of the tourist season. in the future, measures should be taken to preserve the region’s natural beauty, to develop sustainable tourism, and to invest in creating diverse and modern tourist accommodation, transport and service infrastructure. it is also recommended to develop such areas of tourism industry as sports tourism, health and recreation, sightseeing, religious tourism and congress tourism, which are less dependent on weather conditions and can ensure stable tourist traffic throughout the year. table 4 indicators of tourism development in 2016 municipality population (2011 census) tourists nights spent bed places length of stay (day) functionality index (%) accommodation occupancy (%) tourism intensity (%) belgrade 1,647,490 913,150 1,867,150 15,389 2.0 0.93 33.24 55.43 apatin 29,500 7,007 52,035 610 7.4 2.06 23.37 23.75 odzaci 30,202 58 319 56 18.5 0.18 1.56 0.19 sombor 87,539 11,271 21,548 630 1.9 5.59 9.37 12.88 bela crkva 17,912 1,186 8,024 1,016 6.8 5.67 2.16 6.62 kovin 34,990 2,520 8,915 130 3.5 0.37 18.79 7.20 pancevo 123,021 1,190 2,310 78 1.9 0.06 8.11 0.97 novi sad 333,268 174,489 360,578 9,129 2.0 2.73 10.82 52.36 bac 55,898 547 1,346 33 2.5 0.06 11.17 0.98 backi petrovac 14,415 2,708 5,386 197 2.0 1.37 7.49 18.79 backa palanka 13,418 3,310 6,804 228 2.0 1.70 8.18 24.67 beocin 15,589 1,982 4,700 64 2.4 1.70 20.12 12.71 sremski karlovci 8,797 7,219 12,926 282 1.8 3.20 12.56 82.06 titel 16,070 558 1,444 93 2.6 0.58 4.25 3.47 zrenjanin 123,536 15,261 54,085 674 3.5 0.55 21.98 12.35 indjiјa 47,818 2,503 4,762 210 1.9 0.44 6.21 5.23 stara pazova 70,333 12,053 32,986 394 2.7 0.56 22.94 17.13 kladovo 21,142 25,651 50,187 1,173 2.0 5.55 11.72 121.32 maјdanpek 19,854 24,774 44,245 736 1.8 3.70 16.47 124.78 negotin 38,030 4,971 14,043 530 2.8 1.39 7.26 13.07 pozarevac 73,975 13,269 30,164 129 2.3 0.17 64.06 17.93 veliko gradiste 18,956 17,891 52,861 242 3.0 1.28 59.84 94.38 golubac 8,654 3,186 4,540 835 1.4 9.65 1.49 36.81 smederevo 107,170 3,554 5,989 318 1.7 0.30 5.16 3.31 total 2,957,577 1,250,308 2,647,347 33,176 2.1 1.12 21.86 42.27 source: statistical office of the republic of serbia. https://doi.org/10.15826/recon.2018.4.1.005 r-ecomony, 2018, 4(1), 30–37 doi: 10.15826/recon.2018.4.1.005 37 www.r-economy.ru online issn 2412-0731 references 1. gajic, t. (2010). role of tourism in enhancing the development of places of tourist origin and tourist destinations – an example of south backa district. industrija, 3, 139–155. 2. milosevic, s. (2014). factors influencing development of cultural tourism – a case study: bar, montenegro. poslovna ekonomija, 8(1), 259–280. doi: 10.5937/poseko1401259m. 3. milosevic, s. (2017). objective indicators of tourism development in montenegro – an analysis. tims acta, 11, 31–43. 4. durydiwka, m. (2013). tourist function in rural areas of poland. spatial diversity and chancing trends. miscellanea geographica – regional studies on development, 17(3), 5–11. doi: 10.2478/ v10288-012-0041-2. 5. keogh, b. (1984). the measurement of spatial variations in tourist activity. annals of tourism research, 11(2), 267–282. 6. van doren, c. s. & gustke, l. d. (1982). spatial analysis of the u.s. lodging industry 1963– 1977. annals of tourism research, 9(4), 543–563. 7. marković, s., perić, m., mijatov, m., doljak, d., žolna m. (2017). application of tourist function indicators in tourism development. journal o geographical institute „jovan cvijic“of serbian academy of sciences and arts, 67(2), 163–178. doi: 10.2298/ijgi1702163m. 8. milankovic, ј. (2015). danube as a transport artery and axis of development in the republic of serbia. novi sad: faculty of sciences, department of geography, tourism and hotel management, doctoral dissertation. 9. secerov, v. & nevenic, m. (2004). serbian danube basin through the ages: form past to present. journal of serbian geographic society, 84(2), 223–230. 10. transnational cooperation programme (2010) datourway sustainable development strategy in the danube region with a focus on tourism. novi sad: sout east europe. 11. maksin, m., pucar, m., korac, m. & miliјic, s. (2009). management of natural and cultural resources in tourism. belgrade: faculty of tourism and hospitality management. 12. maksin, m. & miliјic, s. (2012). potentials for sustainable tourism development at danube in serbia. arhitektura i urbanizam, 35, 10–21. doi: 10.5937/arhurb1235010m. 13. danube tourist commission (2009) danube facts and figures 2008. 14. lukić d. (2015). the serbian danube region as tourist destination. journal of serbian geographic society, 95 (3), 73–92. 15. sors (2016). statistical yearbook of the republic of serbia. belgrade: statistical office of the republic of serbia. 16. petric, l., & mimica, j. (2011). guidelines for development of private accommodation facilities as an important segment of accommodation offer. acta turistica nova, 5(1), 1–42. 17. beliј m., milosavljevic ј., beliј ј.& perak k. (2014). indicators of tourism development of spa centres in serbia. collection of papers – faculty of geography, university of belgrade, 62, 175–196. 18.  jegdic, v. (2011). tourism and sustainable development. novi sad: faculty of sports and tourism. information about the authors dobrila lukić – phd in geography, assistant professor, alfa bk university (palmira toljatija 3, 11000 belgrade, serbia); email: dobriladjerdap@gmail.com. siniša berjan – phd in agriculture, assistant professor, university of east sarajevo, faculty of agriculture (vuka karadžića 30, 71123 sarajevo, bosnia and herzegovina); email: sinisaberjan@yahoo.com. hamid el bilali – phd in agriculture, assistant professor, university of natural resources and life sciences, department of centre for development research (borkowskigasse 4, 1190 vienna, austria); email: hamid.elbilali@boku.ac.at. https://doi.org/10.15826/recon.2018.4.1.005 http://doi.org/10.5937/poseko1401259m http://doi.org/10.2478/v10288-012-0041-2 http://doi.org/10.2478/v10288-012-0041-2 http://doi.org/10.2298/ijgi1702163m http://doi.org/10.5937/arhurb1235010m r-ecomony, 2018, 4(2), 51–58 doi: 10.15826/recon.2018.4.2.008 51 www.r-economy.ru online issn 2412-0731 original paper for citation kitonsa, h. (2018) drone technology for last-mile delivery in russia: a tool to develop local markets. r-economy, 4(2), 51–58. doi: 10.15826/recon.2018.4.2.008 for citation китонса, х. (2018) использование дронов на последнем этапе доставки: инструмент для развития местных рынков. r-economy, 4(2), 51–58. doi: 10.15826/recon.2018.4.2.008 doi: 10.15826/recon.2018.4.2.008 drone technology for last-mile delivery in russia: a tool to develop local markets haula kitonsa ural federal university, ekaterinburg, russia; email: kitsxauxkissule@gmail.com abstract as the popularity of online shopping increases, last-mile delivery is gaining more and more attention of e-commerce companies. one of the viable solutions to maximizing the benefits of such delivery and cutting its costs is the usage of the rapidly developing drone technology. however, drone delivery is associated with a number of safety and privacy, which makes legislators uneasy about permitting the commercial use of drones. in this paper, we compare the drone regulations applied in various countries with those of russia and analyze the criteria used to develop such regulations. six general approaches are thus outlined: officially banning commercial drone operation; making it virtually impossible for drone operators to acquire the necessary registration and license; allowing to fly drones in exceptional cases over restricted areas; prohibiting to fly drones beyond the pilot’s line of visual sight; allowing to fly drones if standard requirements are met; and, finally, following the substantial precedent principle. this analysis shows us the possible strategies russia could adopt to regulate commercial drone usage. it is thus suggested that russia should follow the example of rwanda and china and allow to experiment with drone delivery in rural areas, where the risk to people’s lives and property in case of drone malfunction are lower than in urban areas. keywords drone technology, last-mile delivery, drone delivery, e-commerce, legal framework использование дронов на последнем этапе доставки: инструмент для развития местных рынков х. китонса уральский федеральный университет, екатеринбург, россия; email: kitsxauxkissule@gmail.com резюме по мере роста популярности онлайн-покупок, проблема заключительного этапа доставки привлекает всё больше внимания компаний, занимающихся электронной коммерцией. одним из наиболее перспективных и наименее затратных решений является использование быстро развивающейся технологии беспилотных летательных аппаратов. тем не менее, доставка с помощью дронов связана с рядом вопросов безопасности и конфиденциальности, что мешает законодателям свободно разрешить коммерческое использование беспилотных летательных аппаратов. в этой статье сравниваются нормы, применяемые в разных странах, и анализируются критерии, используемые для разработки таких правил. таким образом, излагаются шесть общих подходов: официальное запрещение коммерческой эксплуатации беспилотных летательных аппаратов; практически полная невозможность получения необходимой регистрации и лицензии; разрешение на полеты лишь в исключительных случаях и по специальным зонам; запрет полётов вне поля зрения пилота; разрешение полетов при исполнении стандартных требований; и, наконец, следование прецедентам. этот анализ показывает нам возможные стратегии, которые россия могла бы принять для регулирования использования коммерческих дронов. в результате предлагается, чтобы россия следовала примеру руанды и китая и позволила экспериментировать с доставкой беспилотных летательных аппаратов в сельских районах, где риск жизни людей и имущества в случае неисправности дрона ниже, чем в городских районах. ключевые слова дроны, заключительный этап доставки, доставка с помощью дронов, электронная коммерция, правовые вопросы http://doi.org/10.15826/recon.2018.4.2.008 http://doi.org/10.15826/recon.2018.4.2.008 mailto:kitsxauxkissule@gmail.com mailto:kitsxauxkissule@gmail.com 52 www.r-economy.ru r-ecomony, 2018, 4(2), 51–58 doi: 10.15826/recon.2018.4.2.008 online issn 2412-0731 introduction in 2016, the on-line expenditure on physical goods on the russian e-commerce market amounted to approximately $16.3 billion, including estimated $4.3 billion of foreign e-commerce sales, with 80% of parcels and small packages coming from china [1]. the market estimates were speculated to top $17.1 billion in 2017, according to (akit) association of online retail companies. in total, 360 million shipments (both domestic and cross-border) resulted in average spending of 2,500 rbs per e-shopper [2]. online purchases and home delivery have become widely spread because they are less detrimental for the environment and require less effort on the part of the customer [3]. together with the growing internet sales, the growing demand in the delivery industry is also growing. the majority of online shopping companies in russia currently rely on third parties (private carriers). the leading company is the russian post, which accounts for 99% of deliveries in the country due to its large postal network. there are also such services as dpd, sdek, spsr-express, pony express and iml courier [2] whereas some companies offer their own delivery to the customer’s location without any third-parties involved. figure 1 shows a forecast for retail e-commerce sales in russia for the period from 2015 to 2018. there is a gradual increase in sales, which are expected to reach 30.91 billion u.s. dollars by the end of 2018. 2015 2016 2017 2018 35 30 25 20 15 10 5 0 20,30 23,40 26,88 30,91 sa le s in b ill io n u .s . d ol la rs figure 1. forecast retail e-commerce sales in russia from 2015 to 2018 source: e-marketer, statistic 2017 figure 2 demonstrates various types of goods purchased from different online stores in 2016. it is evident that russian online stores, like ulmart. ru, wildberries.ru, mvideo.ru, aliexpress.ru and avito.ru, surpassed their counterparts with a share of over 35% as a result of russian customers’ preference of chinese and foreign online stores. most of the goods were compara 0 5 10 15 20 25 30 35 40 a pp ar el ,fo ot w ea r ph on es , s m ar tp ho ne s, ta bl et s h ou se ho ld a nd ga rd en g oo ds c hi ld re n' s go od s el ec tr on ic d ev ic es (v id eo , a ud io , p ho to ) sp or tin g go od s d es kt op , l ap to ps h an dm ad e go od s c os m et ic s, p er fu m es a ut o pa rt s sm al l a pp lia nc es c on st ru ct io n m at er ia ls fu rn itu re m aj or a pp lia nc es pe t p ro du ct s fo od . d ri nk s, a lc oh ol h ea lth g oo ds sh ar e in a ll on lin e bu ye rs , % russian online stores chinese online stores other international online stores figure 2. types of goods purchased from different online stores in 2016 in russia source: gfk rus and yandex market data, 2016 http://doi.org/10.15826/recon.2018.4.2.008 r-ecomony, 2018, 4(2), 51–58 doi: 10.15826/recon.2018.4.2.008 53 www.r-economy.ru online issn 2412-0731 tively light and, therefore, could be effectively delivered by a drone. as a rule, carriers serving on-line shopping web-sites have to deliver one or several small packages to the customer’s address [4]. the new, increasingly popular strategy is to ship products directly from the seller to the customer by skipping drop-offs at retail stores [5]. comparison between online and conventional shopping has been the core focus of most previous papers concentrating on the grocery retail sector[6]. in the traditional shopping supply chain, goods are delivered to a store for customers to pick them up. typically, the process of online shopping consists of three stages: placing an order, processing the order and delivery. each of these stages is vital for ensuring effective customer services at the expense of potential customers [7]. considering all the phases, starting from the order being placed to home delivery by the seller, logistics providers and transportation companies have found that last-mile delivery to be not only complicated but also expensive [8]. concerns have been expressed about the rapid growth of home deliveries and their efficiency, which might diminish the net benefits from online shopping [9]. in this study, we are going to focus on the third stage, order delivery. last-mile delivery in logistics, last-mile delivery refers to delivering a customer’s order to his or her doorstep [10]. logistics providers [11] face different challenges, including the following: – traffic congestions in downtown areas; – environmental issues caused by inefficient routes in rural areas; – increased delivery costs; – as customers are now more prone to purchasing small quantities of goods, cases of failed deliveries (orders are delivered when no one is at home) have become more frequent as well as the return of unwanted goods [12]. in the traditional shopping system, customers are responsible for picking up their orders and bringing them home, whereas in online shopping, most of the work is done by retailers, who deliver customers’ orders to their respective addresses sometimes within relatively short time slots [4]. trying to address the above-described issues, carriers may resort to such options as collaborative delivery, like colis-voiturage for heavy shipments. moreover, amazon is preparing to launch an uber-style system1 for road transport. there has recently been an increase in the usage of self-employed couriers [4]. the major online retailers now rely on third-party courier networks such as the russian post [2]. other alternatives include drones (jd.com2), autonomous robots (swiss post), green deliveries by boat, e-bikes3 or on foot deliveries and electric buses (wholesale brand métro). sainsbury is planning to switch to electric vans for its on-line shopping delivery by 2010 [13]. the drone technology, which is able to traverse difficult terrains, reduce labour costs and replace fleets of vehicles, proves to be a viable option [14]. it is recommended as one of the best possible solution to the challenges faced by the companies providing last-mile delivery. the drone technology has the potential to significantly reduce the delivery costs and save time required to deliver packages. moreover, drones are less expensive to maintain, they are not limited by the established infrastructure, such as roads, and generally involve less complex obstacle avoidance scenarios as compared to the traditional delivery vehicles such as trucks [15]. there is an opinion that since drones do not need to make frequent stops on the way, they will provide an even faster direct service [16; 17]. this way, packages will no longer have to be individually delivered to customers by couriers. this idea is so alluring that large companies have embarked on developing and testing delivery models considering all the safety precautions in order to obtain permits to use drones for last-mile delivery. international experience of drone delivery the twenty-first century has witnessed an advancement of drone technology and a number of major companies have engaged in drone testing [18]. in 2012, silcon valley startup tacopter [19] made headlines when it publicly announced its plans to launch a delivery service of tacos within the city of san francisco via unmanned aerial vehicles (uavs). in 2013, amazon [20] claimed that it was designing a drone delivery program called prime air to deliver packages within just thirty minutes. in september 2016, an ameri1 postal record (2017). delivery by uber? 2 josh gartner (2017). drone delivery program fact sheet. 3 somit sen (2017). maharashtra to push for e-bikes for delivery of food, goods. http://doi.org/10.15826/recon.2018.4.2.008 54 www.r-economy.ru r-ecomony, 2018, 4(2), 51–58 doi: 10.15826/recon.2018.4.2.008 online issn 2412-0731 can based logistics company ups [19] tested a medical supply drop to an island off the coast of massachusetts; the same month, as a part of alphabet inc’s drone delivery initiative, burritos were sent to students of virginia tech. in 2013, deutsche post dhl [22], a logistics company in germany, also started its parcelcopter project. in march 2016, the largest convenience chain 7-eleven [23] and a drone startup flirtey made a drone delivery in reno, nevada, which was the first such delivery to be approved by the aviation authorities (faa). in april 2016, a japanese e-commerce giant rakuten4 tested its drone on the golf course where players were able to use their phones to request new golf balls or refreshments to be delivered to them. table 1 applications of the drone technology by market category asset management aerial surveying cinematography video marketing other power line inspections forestry management films real estate fire scene inspections railway line inspections geophysical surveys documentaries tourism destinations insurance claims oil pipeline inspections land use planning news property development crash scene inspections wind turbine inspections mapping sporting events сommercials monitoring marine wildlife agriculture anti-piracy operations border controls flood documentation research source: rich, c. (2015). in november 2016, flirtey and domino’s pizza enterprises ltd5 delivered pizzas from domino’s stores to customer homes in new zealand as a part of enterprise’s ongoing drone delivery testing. since mid-march 2017, swiss post [24] has successfully been conducting drone flights in lugano, testing the transportation of laboratory 4 reuters (april 26, 2016). japan’s rakuten demonstrates “first commercial drone delivery service in the world”. retrieved from http://toyokeizai.net/articles/-/115632. 5 flirtey (nov 15, 2016). flirtey launches world’s first pizza-by-drone commercial trials, delivers domino’s pizza to customer homes. samples between two ticino hospitals. in russia, in june 2014, dodo pizza6 became the first company to make a trial deployment of a drone in last-mile delivery. in june 2017, one of russia’s major banks sberbank7, successfully tested cash delivery from their cash handling center to a cash-in-transit van. the table 1 above shows that the drone technology has a wide range of applications, some of which are still waiting to be realized. legalization of drone delivery in russia despite the struggle to develop the drone technology models for commercial use, companies cannot proceed without permission from the corresponding regulatory bodies [23]. the questions to be addressed in this respect are as follows: should the technology be permitted at all? should society permit the development of such a technology, which is likely to threaten people’s privacy? if the development of this technology is unstoppable, should there be a regulatory framework so that only authorized individuals or legal entities could use it for socially acceptable purposes? [25]. let us now compare the existing legal framework in russia with those of other countries. in order to decide on the legal framework to regulate drone use we need to consider the fact that drones can be used for criminal ends, for example, to smuggle weapons and drugs or as a weapon. moreover, there is a number of privacy issues associated with drones as they can carry video equipment and thus can be used for illegal surveillance. it is also essential to decide who should be authorized to operate drones as it requires certain skill and experience while drones can be dangerous to people and objects in their vicinity. commercial drone regulations are different in various countries, which either choose to benefit from the development of this technology or to restrict it for safety reasons [25]. legal regulators around the world are toiling to keep up with the rapidly evolving technology with unlimited capabilities which may be perceived as threatetning the traditional norms and values [27]. 6 lenta.ru (june 25, 2014). dial-a-drone! syktyvkar pizzeria begins unmanned deliveries. 7 sputnik news. (june 16, 2017). retrieved from https:// sputniknews.com/science/201706161054695960-russia-sberbank-drone/. http://doi.org/10.15826/recon.2018.4.2.008 http://toyokeizai.net/articles/-/115632 https://sputniknews.com/science/201706161054695960-russia-sberbank-drone/ https://sputniknews.com/science/201706161054695960-russia-sberbank-drone/ https://sputniknews.com/science/201706161054695960-russia-sberbank-drone/ r-ecomony, 2018, 4(2), 51–58 doi: 10.15826/recon.2018.4.2.008 55 www.r-economy.ru online issn 2412-0731 table 2 laws regulating the use of commercial drones in different countries features australia1) canada2) uk3) china4) new zealand5) usa6) russia7) regulatory body civil aviation safety authority (casa) transport canada (tc) civil aviation authority (caa) civil aviation administration of china (caac) civil aviation authority of new zealand (nzcaa) federal aviation administration (faa) the federal air transport agency (fata) maximum altitude controlled airspace – 120m / 400ft – outside – no limit max 300ft max 120m / 400ft > 120m / 400ft approval required max 120m / 400ft > 120m / 400ft approval (caac) max 120m / 400ft > 120m / 400ft approval required 121m / 400ft not specified maximum takeoff weight < 2kg / 4.4lbs > 2kg / 4.4lbs < 25kg / 55lbs > 25kg / 55lbs permission required not specified 0 ≤ 1.5kg, 1.5 ≤ 4kg, 1.5 ≤ 7kg, 7 ≤ 25kg, 15 ≤ 116kg, 25 ≤ 150kg >5,700kg (agricultural) 25kg / 55lbs < 25kg / 55lbs > 25kg / 55lbs permission required 30kg / 66lbs bvlos flights not allowed – not allowed not allowed not allowed not allowed not allowed competence statement / license < 2kg / 4.4 lbs = registration required > 2kg /4.4lbs = operators certificate + rpa required commercial flight – 5 days notice > 1kg ≤ 25kg required (urban) > 20kg ≤ 150kg caa license required < 250 g/.55lbs – real name registration > 7kg/15lbs – <116kg (caac) license not required > 0.55lbs required < 30kg – not required > 30kg – required night time and bad weather special approval not allowed special approval special approval special approval special approval not allowed and a watcher required labeling requirements not required but recommended not required not required but recommended not required not required required required air traffic control notification required in controlled airspace >4lbs – required > 15lbs – required in controlled airspace required required in controlled airspace – required drone liability insurance not required but recommended required, $100,000 not required but highly recommended not required not required not required but recommended required pilot certification < 4lbs none > 4lbs requires manufacturer conducted training course above 18 years of age – ground school training (commercial)/ basic certificate for uas and ground school < 116kg, required knowledge of airspace restrictions above 16 years of age required drone ban zones state institutes; federal authority constructions; regional authority constructions; airport control zones (ctr); vehicles, boats, buildings, people hospitals; operation sites of police, military, search and rescue forces state institutes; federal authority constructions; regional authority constructions; 9 km from airport control zones (ctr); minimum 150m/500ft from crowds and 90m from built up areas hospitals; operation sites of police, military, search and rescue forces state institutes; federal authority constructions; regional authority constructions; airport control zones (ctr); minimum 150m/500ft from crowds and built up areas hospitals; operation sites of police, military, search and rescue forces state institutes; federal authority constructions; regional authority constructions; airport control zones (ctr); crowds of people hospitals; operation sites of police, military, searchand rescue forces *dji drones programmed not to take off in no-fly zones state institutes; federal authority constructions; regional authority constructions; airport control zones (ctr); national parks; crowds; private property (only with permission of the owner); hospitals; operation sites of police, military, searchand rescue forces state institutes; washington; federal authority constructions; regional authority constructions; airport control zones (ctr); crowds of people (not specified); hospitals; operation sites of police, military, search and rescue forces state institutes; moscow kremlin, red square; federal authority constructions; regional authority constructions; airport control zones (ctr); crowds of people; military installations, power plants sourse: 1) australia uav. retrieved from https://www.casa.gov.au/operations/standard-page/how-become-safe-rpa operator?wcms%3astandard%3a%3apc=pc_101985; 2) transport canada – drone safety. retrieved from http://www.tc.gc.ca/eng/civilaviation/standards/general-recavi-uav-2265.htm?wt.mc_id=1zfhj#safety; 3) civil aviation authority – cap393. retrieved from http://publicapps.caa. co.uk/docs/33/cap%20393_aug2016.pdf; 4) china’s new drone regulations. retrieved from http://www.caac.gov.cn/index.html; 5) caa of newzealand. retrieved from https://www.caa.govt.nz/rules/rule_consolidations/part_101_consolidation.pdf; 6) faa drone regulations. retrieved from http://www.faa.gov/uas/media/part_107_summary.pdf; 7) federal air transport authority. retrieved from http://www.favt.ru. http://doi.org/10.15826/recon.2018.4.2.008 https://www.casa.gov.au/operations/standard-page/how-become-safe-rpa operator?wcms%3astandard%3a%3ap https://www.casa.gov.au/operations/standard-page/how-become-safe-rpa operator?wcms%3astandard%3a%3ap http://www.tc.gc.ca/eng/civilaviation/standards/general-recavi-uav-2265.htm?wt.mc_id=1zfhj#safety http://www.tc.gc.ca/eng/civilaviation/standards/general-recavi-uav-2265.htm?wt.mc_id=1zfhj#safety http://publicapps.caa.co.uk/docs/33/cap%20393_aug2016.pdf http://publicapps.caa.co.uk/docs/33/cap%20393_aug2016.pdf http://www.caac.gov.cn/index.html https://www.caa.govt.nz/rules/rule_consolidations/part_101_consolidation.pdf http://www.faa.gov/uas/media/part_107_summary.pdf; http://www.favt.ru 56 www.r-economy.ru r-ecomony, 2018, 4(2), 51–58 doi: 10.15826/recon.2018.4.2.008 online issn 2412-0731 there are six main parameters commonly used as standards for drone regulation at the national level: maximum altitude; vlos and bvlos flights; licensing; flying drones at night time or in bad weather; pilot certification; and drone banned zones. as we can see, all countries have bodies regulating drone operation. the requirements differ depending on drone capability, payload, mass, altitude, application, operator’s license level and flight area. operation of drones beyond the visual line of sight (bvlos flights) is not allowed in most countries and it is accompanied by a set of requirements concerning the maximum altitude and the restricted distance from a crowd of people. labeling is an optional requirement in many countries but it is obligatory in russia. to use recreational drones no license, insurance, registration or certification is required. the rules are much stricter regarding commercial drone applications: for example, the air traffic control notification is required in all countries; flights are either banned or highly restricted in certain areas, for example, airport control zones, state institutions, power plants and so on. flying drones at night or in bad weather conditions also usually requires a special permission whereas in russia it is prohibited and requires presence of a watcher. thus, russian drone laws are very much in line with those of other countries, with only a few exceptions: – drone operators must have a watcher at all times to monitor the flight and drones must not be operated beyond the visual line of sight; – the air traffic control must be notified prior to the flight with a detailed flight plan to be provided (in other countries, it is only required in controlled airspaces); – a drone has to be labeled for the purpose of identification; – at the moment, no maximum flight altitude is specified but this issue will undoubtedly soon be addressed and limits will be set. there are six general approaches [27] to national commercial drone regulation varying across countries: 1. outright ban: countries that prohibit any commercial drone operation (for example, morocco, argentina, and cuba). 2. effective ban: countries that officially allow commercial drone application but the licensing and registration procedures make it virtually impossible to obtain a legal permission (for example, algeria, belarus, and egypt). 3. drones must not be operated beyond the visual line of sight, which limits the potential of drone usage (for example, belgium, croatia, and thailand). 4. permission can be given in exceptional cases to carry out drone testing within restricted areas (for example, brazil, canada, and germany). 5. commercial drone operation is permitted as long as the standard requirements (registration, licensing, and insurance) are met (for example, sweden, norway, and iceland). 6. substantial precedents: these countries follow the substantial precedent principle regarding drone regulations and monitor the results of the strategies adopted by other countries. conclusion as we have shown above, the development of last-mile delivery is currently facing a series of challenges, which can be met with the help of drones. however, in many countries, including russia, drone delivery is prohibited. in russia, a drone must not be operated beyond the visual line of sight, which considerably limits the possibilities of using drones for last-minute delivery. moreover, the air traffic control must be notified prior to any flight. a more productive approach would be to develop regulations to enable society benefit from the drone technology and at the same time to ensure safe usage of drones and protect people’s privacy. in such countries as rwanda and china, drone operation is permitted beyond the pilot’s visual line of sight, which enhances the development of drone delivery (rwanda was the first country to permit commercial drone delivery in the world). although legal regulators in both countries have issued a green pass to drone delivery, there are still strict restrictions to be met, for example, deliveries must only be carried out in rural, not densely populated areas. this is done to reduce the risk level in case of any drone malfunction. drone laws in russia and other countries are being constantly amended and, in general, the governments seek to broaden the specter of opportunities for commercial drone delivery. the approach adopted in rwanda and china, that is, the usage of drones for delivery in rural areas, might prove to be quite effective in russia as well. what russian legislators could start with is, for instance, permitting experiments with drone delivery in the countryside since the risk level in such areas is low. http://doi.org/10.15826/recon.2018.4.2.008 r-ecomony, 2018, 4(2), 51–58 doi: 10.15826/recon.2018.4.2.008 57 www.r-economy.ru online issn 2412-0731 references 1. khare, a. 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(2017). swiss post drone to fly laboratory samples for ticino hospitals communication dated. retrieved from https://www.post.ch/en/about-us/company/media/press-releases/2017/ swiss-post-drone-to-fly-laboratory-samples-for-ticino-hospitals. 25. wright, d. (2014). drones: regulatory challenges to an incipient industry. computer law and security report, 30(3), 226–229. 26.  lotz, a. (2015). drones in logistics: a feasible future or a waste of effort. retrieved from https://scholarworks.bgsu.edu/cgi/viewcontent.cgi?article=1215&context=honorsprojects. 27. finn, r. l., & wright, d. (2016). privacy, data protection and ethics for civil drone practice: a survey of industry, regulators and civil society organisations. computer law & security review, 32(4), 577–586. doi: 10.1016/j.clsr.2016.05.010. information about the author haula kitonsa – researcher, graduate school of economics and management, ural federal university, university (19, mira st., 620002, ekaterinburg, russia); email: kitsxauxkissule@gmail.com http://doi.org/10.15826/recon.2018.4.2.008 https://www.huffingtonpost.com/2012/03/23/tacocopter-startup-delivers-tacos-by-unmanned-drone-helico https://www.huffingtonpost.com/2012/03/23/tacocopter-startup-delivers-tacos-by-unmanned-drone-helico https://www.theguardian.com/technology/2016/jul/25/amazon-to-test-drone-delivery-uk-government https://www.theguardian.com/technology/2016/jul/25/amazon-to-test-drone-delivery-uk-government http://doi.org/10.24251/hicss.2017.399 http://doi.org/10.2139/ssrn.2732845 https://www.post.ch/en/about-us/company/media/press-releases/2017/swiss-post-drone-to-fly-laboratory-samples-for-ticino-hospitals https://www.post.ch/en/about-us/company/media/press-releases/2017/swiss-post-drone-to-fly-laboratory-samples-for-ticino-hospitals https://scholarworks.bgsu.edu/cgi/viewcontent.cgi?article=1215&context=honorsprojects http://doi.org/10.1016/j.clsr.2016.05.010 mailto:kitsxauxkissule@gmail.com m. s. balandina r-economy vol. 3, issue 4, 2017 228 doi 10.15826/recon.2017.3.3.025 udc 332.1 m.s. balandina ural federal university (ekaterinburg, russia; m.s.balandina@urfu.ru ) international trade as a channel of influence of globalization on the economic development of participant countries of the belt and road initiative the article analyses how the facilitation of open trade among countries-participants of the belt and road initiative affects their economic growth. the impact of free international trade on the economic inequality of the countries of the world represents a serious theoretical problem, and there is no single point of view among the academic community. it is known that the globalization of international trade can stimulate economic growth or slow it down. the latter occurs when developing countries fall into the trap of commodity specialization, including due to a weak diversification of exports. these issues are the key challenges for russia and other former soviet and african countries-participants of the belt and road project. as most of the countries-participants of obor have a strong specialization of exports in the traditional sectors. we discuss the instruments how to facilitate unimpeded trade within obor countries and minimize the risks of the reduction of economic growth. the authors focus on the assessment of the potential for mutually beneficial cooperation in the sphere of international trade between them and offer a set of measures aimed to support and develop the export activities in terms of integration in obor project. we examine an export basket of russia and reveal the new export goods for it, which might be used to transform the productive structure and upgrade export among obor countries. as a result, the authors get a cluster of new and the most attractive export goods. the establishment of industrial cooperation between obor countries, which have a comparative advantage in these complementary areas, can increase the productive capacity of these industries and lead to a win-win result. keywords: one belt one road’, china-mongolia-russia economic corridor, export, international trade, globalization, economic cooperation, economic development introduction the concept of ‘one belt and one road’ was introduced by the president of china xi jinping in 2015 as a part of the international initiative of china, which aims to improve the existing trade routes and create new ones, to establish transport and economic corridors linking more than sixty countries of central asia, europe and africa. the initiative is expected to contribute to the development of trade relations between the participant countries and china. the main content of this initiative is described in the recent literature, for example by makarov, a. sokolova[1], s.ze[2], and d.yi[3]. i.v.stavrov[4] and b. otgonsuren[5] examined the project of the economic corridor china-mongolia-russia as a part of the belt and road strategy. the framework of the initiative rests on five key ‘whales’: promotion of policy coordination, infrastructure development and connectivity, unimpeded trade, financial integration and people-to-people bonds. all these principles lead to increasing globalization among countries in asia, europe and africa. globalization is a highly complex multidimensional process with hundreds of varying definitions used in scholarly literature. for example, guillen [6]. and n. crafts[7] consider globalization as the process of integrating the markets of goods and capital worldwide, accompanied by partial removal of barriers to international trade and foreign investment. http://r-economy.ru/ mailto:m.s.balandina@urfu.ru m. s. balandina r-economy vol. 3, issue 4, 2017 229 nowadays the level of globalization of east asia and the pacific, central asia and africa is still low, which is proven by the indexes measuring the level of globalization (see, for example, the latest dhl global connectedness study). this index is taking into account the mixture of indicators pertaining to what can be called ‘breadth’ and ‘depth’ of globalization and uses flows as their basic measurement units (flows of goods, people, information, etc.). depth refers to the size of the country’s international flows as compared to the relevant measure of the size of its domestic economy. breadth measures how closely the country’s distribution of international flows across its partner countries matches the global distribution of the same flows in the opposite direction. the breadth of the country’s merchandise exports, for example, is measured on the basis of the difference between the distribution of its exports across destination countries versus the rest of the world’s distribution of merchandise imports. fig. 1. regional average scores of the global connectedness index, 2015 source: dhl global connectedness index, 2016 [8]. figure 1 displays average global connectedness, depth, breadth, and pillar scores for countries in each region. in terms of overall global connectedness, countries in europe average the highest levels of connectedness followed closely by those in north america. east asia, the pacific, the middle east and north africa come next and are followed at some distance by south and central america, the caribbean, south and central asia, and sub-saharan africa. the top five ranks on the dhl global connectedness index are held, in descending order, by the netherlands, singapore, ireland, switzerland, luxembourg. the top ten are all among the world’s most prosperous countries, and all but one (the united arab emirates) are classified as advanced economies by the international monetary fund (imf). in 2015, of the 140 countries for which the index of globalization was calculated, hong hong(china) ranked 17th; taiwan (china), 21st; china, 68th; and russia 67th. russia’s connectedness is not high, because, firstly, russia lacks outlets to the sea and, therefore, to sea transport routes, which provide the cheapest way for transporting goods. secondly, russia’s level of development is not very high while globalization is led by developed countries. thirdly, russia has a large territory with an underdeveloped land transport system, which is a significant barrier to the export and import of goods. http://r-economy.ru/ m. s. balandina r-economy vol. 3, issue 4, 2017 230 the belt and road initiative aims to increase connectedness of all countries participating in the project, including china and russia. the main purpose of raising the level of globalization of the project’s participants is to intensify their economic growth. the belt and road initiative is based on the assumption that globalization leads to economic growth of all participant countries. however, the impact of globalization on the economic growth and economic inequality of countries is a serious theoretical problem, which is actively debated within the academic community. according to the neoclassical trend in economic theory, higher openness of countries is beneficial for their economic growth, but different countries can benefit from globalization in different degrees. within the institutional and post-industrial paradigms, the question becomes even more complicated. for example v. inozemtsev[9] introduces the thesis about the divergent nature of globalization in modern world economy . globalization is not a polycentric process leading to the formation of the world community network. globalization is a monocentric process in which the world is divided into the center and periphery, with the periphery being subordinate to the center. the ‘center’ creates a socio-economic model based on new technology and liberal ideology. this model has a high degree of commonality, so it can easily be implemented in ‘peripheral’ countries. since globalization is beneficial to the center, it is the center that regulates the process of globalization. in this sense, inozemtsev questioned the spontaneity of the globalization process. globalization can influence economic growth and convergence of countries through foreign direct investment, international labor movement, and renovation of infrastructure. this type of influence is more or less obvious while the impact of international trade on the same parameters is less evident and, therefore, causes much debate. conceptual framework there are two basic theories of international trade: theory of comparative advantage (hecksher-ohlin model) and the theory of monopolistic competition (p.krugman’s model [10]). in both works, there is no definite conclusion about the direction of the impact of international trade on economic growth and convergence of countries. this topic has also been studied by j.williamson [11], d.ben-david [12], and s.edwards [13]. international trade, according to a large number of authors, facilitates the international transfer of technologies and thus increases productivity in relatively backward countries. empirical study on the impact of trade on economic growth was conducted by j.frankel and romer d.[14]. they found out that between 1960 and 1985, an increase in the ratio of foreign trade to gdp by 1 % lead to an increase in the country’s income and growth rate by 1.5 %. however, m.clemens and j.williamsom[15] in 2001 found that before world war ii this influence had been reverse. p.vorobyev [16] studies the relationship between economic growth and the characteristics of countries’ openness to international operations. this econometric study used the sample of 78 countries between 1991 and 2006. it was found that globalization should contribute to the rapprochement of countries by gdp per capita, that is, to reinforce the convergence of countries. however, different components of globalization have a different impact on convergence of countries in the world. apparently, globalization of world trade can facilitate or impede growth. the latter is the case if globalization supports developing countries’ specialization in exporting raw materials. n.leitão [17] analyzed the connection between economic growth, globalization and trade in the u.s.a and found that globalization increases or provokes economic growth. a.umaru et al. [18] analyzed globalization’s effects on nigeria’s economic performance between 1962 and 2009. he found out that globalization affects petrol, manufacturing industry and solid mineral sectors in negative ways while it positively affects the agriculture, transportation and communication sectors. y.ying [19] analyzed the connection between social and political globalization and economic growth in asean countries in 1970-2008 and found out that economic globalization influences economic growth in a positive way while social and political globalization affects it in negative ways. thus, most authors believe that the impact of international trade on economic growth and convergence of countries depends on whether international trade is associated with the movement of resources in the sectors that create positive externalities for long-term economic growth (for example, research and http://r-economy.ru/ m. s. balandina r-economy vol. 3, issue 4, 2017 231 development, manufacturing, and education). for a developing country, it is very important to follow the trend of developing new high-tech industries. g.grossman and e.helpman [20], r.feenstra [21], and k.matsuyama [22] cite examples of poorly developed countries in which international trade stimulated specialization in traditional sectors of economy, which impeded their long-term economic growth. current cooperation in international trade between russia and countries of the road and belt initiative china’s initiative aims to boost international trade among the participant countries, which makes it interesting to look at the current amount and structure of bilateral trade between them. table 1. russia’s importing and exporting markets with other participants of the belt and road initiative1 countries exported value in 2016 from russia, us dollar thousand share in russia's exports, % imported value in 2016 from russia, us dollar thousand share in russia's imports, % china 28 021 250 10% 38 086 982 20,9% turkey 13 698 261 5% 2 147 525 1,2% belarus 14 050 697 5% 9 406 285 5,2% kazakhstan 9 426 891 3% 3 612 215 2,0% mongolia 895672 0% 35 909 0,0% 11 participant countries* 14 194 143 5% 5 315 783 2,9% world 285 491 052 100% 182 261 656 100% *azerbaijan, georgia, india, iran, pakistan, tajikistan, turkmenistan, uzbekistan, armenia, belarus, kyrgyzstan china is one of russia’s leading trade partners, ranking second in terms of its share in russia’s total export in 2016, and ranking first in terms of its share in import. the second largest russia’s partner among the participant countries is belarus, the third is turkey. the sixteen countries mentioned in table 1 together account for 28% of russia’s export and 32,2% of russia’s import. thus, nearly one third of russia’s exports and imports is associated with these countries. figure 2 illustrates the recent dynamics of bilateral trade between russia and china and figure 3, between russia and the other fifteen participant countries, except for china. fig. 2. the volume of international trade between russia and china, us dollar, million1 1 compiled by the author according to the data from the itc trade map [23] 20 326,4 35 030,1 35 765,8 35 625,4 37 504,8 28 605,3 28 021,3 38 964,4 48 201,8 51 628,0 53 173,1 50 884,4 34 950,3 38 087,0 10 000,0 20 000,0 30 000,0 40 000,0 50 000,0 60 000,0 2010 2011 2012 2013 2014 2015 2016 export import http://r-economy.ru/ m. s. balandina r-economy vol. 3, issue 4, 2017 232 fig. 3. the volume of international trade between russia and the fourteen participant countries: azerbaijan, georgia, india, iran, pakistan, tajikistan, turkmenistan, uzbekistan, armenia, belarus, kyrgyzstan, turkey, belarus, kazakhstan, mongolia, us dollar, million2 the fall in bilateral trade between russia and the above-mentioned countries after 2014 is caused by a general slowdown in the global economy, lower energy prices and a change in the exchange rate of the dollar. by 2014, it is easy to see a quite low growth of indicators of bilateral trade and stagnation, which is especially clearly if we look at the example of russian-chinese trade, in which the index remained at the same level for four years. therefore, we can conclude that the amount of trade and economic cooperation between russia, china and other participants of the belt and road initiative is far from its potential level. table 2. commodity structure of russian exports to china 2010-2016, % 2 name of the product group (commodity nomenclature of foreign economic activity) mineral products (25-27) wood, pulp and paper products (44-49) machinery, equipment and vehicles (84-90) food products and agricultural raw materials (01-24) chemica l products (28-40) metals and products made of them (72-83) other (41-43, 5071,9197, ss) 2 010 55,6% 14,2% 5,3% 4,7% 8,1% 3,4% 8,7% 2 011 72,3% 9,6% 2,4% 2,7% 9,9% 1,5% 1,7% 2 012 75,7% 8,0% 3,3% 2,9% 9% 1,0% 0,5% 2 013 76,0% 8,4% 3,8% 3,0% 5,7% 1,0% 2,1% 2 014 77,0% 8,9% 4,2% 3,8% 5,0% 0,9% 0,1% 2 015 69,0% 10,6% 6,3% 4,8% 6,5% 1,3% 1,4% 2 016 66,7% 12,2% 6,9% 5,8% 5,1% 0,8% 2,5% in the structure of russia's exports to china in 2016 the main part of deliveries accounts for mineral products (67% of the total volume of russia's exports to china); wood and pulp and paper products, 12.15% of the total volume of russia's exports to china (see table 2). 2 compiled by the author according to the data from the itc trade map [23] 107 142,40 103 206,07 97 983,53 75 566,92 78 667,24 35 907,63 33 565,72 32 191,24 20 787,38 20 544,12 20 000,00 40 000,00 60 000,00 80 000,00 100 000,00 120 000,00 2012 2013 2014 2015 2016 export from russia to 14 obor countries (except china) import from russia to 14 obor countries (except china) http://r-economy.ru/ m. s. balandina r-economy vol. 3, issue 4, 2017 233 since 2020, we should also expect a growth in exports of gas from russia to china due to the construction of the eastern route of china-russia natural gas pipeline, which started in june 2015. the pipeline will consist of the northern cut ‘heihe changling’, medium cut ‘changling yongqing county of hebei province’ and the southern segment ‘yongqing shanghai’. the northern section is expected to be commissioned in october 2019, and the whole line will be built until the end of 2020. after the launch of the pipeline, russia will supply to china about 38 billion cubic meters of gas annually. thus, the structure of russian exports will become even more focused on the supply of mineral products. in the structure of russia's imports from china in 2016, the main part of deliveries accounts for the following types of goods: machinery, equipment and vehicles – 58,65% of the total volume of russia's imports from china; textiles and footwear, 11,38%; and chemical products, 9.43%. table 3. indices of exports of russia and china in terms of gross output and value added3 indicator exports final consumption (gross figure) exports of intermediate consumption (gross figure) national value added in the consumption of goods end-use abroad сountry china russia china russia china russia agriculture and forestry 4 153 2 730 7 300 3 426 76 787 6 525 extractive industries 743 15 006 6 828 154 514 71 759 139 380 food products 22 457 3 954 11 980 2 214 23 356 3 445 textiles and articles thereof 142 794 657 58 181 150 70 492 416 woodworking industry 4 439 808 21 169 6 910 24 175 5 045 chemical industry 42 965 36 436 154 204 81 849 113 724 58 790 metallurgy 11 778 5 222 117 723 93 190 79 058 30 625 mechanical engineering 67 176 4 890 78 548 10 470 56 812 7 553 electronic and optical equipment 273 985 4 542 301 252 3 929 116 395 5 570 transport equipment 57 248 3 361 44 659 2 677 39 122 4 960 сonstruction 5 812 4 670 1 032 1 179 2 703 8 397 as table 3 shows, the volume of exports of goods to final and intermediate consumption for russia is higher than the figures for china only in the case of extractive industries. it is important to understand that the industry structure affects the nature of trade in both economies. both in russia and china, trade in goods of intermediate consumption dominates in such sectors as agriculture, extractive manufacturing, wood industry, chemical industry, and metallurgy. these industries are mostly resource intensive, which can stimulate the development of industrial cooperation with those partner countries that have significant resource potential. it is also important to note that such industries as mechanical engineering, manufacturing of electronic and optical equipment, and transport equipment are characterized by a significant length of their production chains. for engineering, the share of trade in goods of intermediate consumption prevails, like in the case of china and russia, which signifies the existing potential for industrial cooperation in this field with the selection of specialized niches, depending on national competitive advantages of the participating countries. table 4 demonstrates the structure of russia’s export to its main foreign trade partners. we have also included mongolia in the analysis because this country participates in the project of the russia-mongoliachina economic corridor. 3 compiled by the author by using the data from the wto-oecd tiva database [24] http://r-economy.ru/ m. s. balandina r-economy vol. 3, issue 4, 2017 234 table 4. commodity structure of russian exports to china, turkey, belarus, kazakhstan and mongolia, %4 name of the product group (commodity nomenclature of foreign economic activity) mineral products (25-27) wood, pulp and paper products (44-49) machinery, equipment and vehicles (84-90) food products and agricultural raw materials (01-24) chemical products (28-40) metals and products made of them (7283) other (41-43, 5071,9197, ss) china 67% 12% 7% 6% 5% 1% 3% turkey 57% 1% 1% 12% 2% 5% 22% belarus 53% 2% 12% 6% 10% 11% 6% kazakhstan 17% 5% 23% 14% 16% 14% 12% mongolia 60% 1% 8% 18% 7% 2% 3% in the structure of russia's exports to mongolia in 2016, the main part of deliveries accounts for mineral products (60% of the total volume of russia's exports to mongolia); food products and agricultural raw materials (18%); machinery, equipment and vehicles (8.3%). russia imports from mongolia mineral products, which accounted for 75% of the total volume of russia's imports from mongolia in 2016 (salt, sulphur, earths and stone, plastering materials, lime and cement); and food products and agricultural raw materials (19% in 2016). due to the sanctions against russia, further increase in imports of meat and livestock from mongolia might be beneficial for the russian federation. as table 3 illustrates, mineral products or raw materials constitute the largest share of russia’s exports to other countries participating in the initiative. the only exception is the trade between russia and kazakhstan. in the structure of russian exports to kazakhstan in 2016, machinery, equipment and vehicles accounted for a major share of supplies, that is, 22.68% of the total volume of russia's exports to kazakhstan; mineral products, 16.77%. this situation can be explained by the fact that kazakhstan has large reserves of fossil fuels and metals (uranium, copper, zinc). an interesting example of an export basket with a higher share of new high-tech industries is the export of sverdlovsk region (russia) to china. the case of this region was recently described by i. turgel et al. [25]. in 2016, chemical products accounted for the largest share of export from sverdlovsk region to china – 37%. the share of metals and products was 21%; the share of mineral products, 22% (mainly ore (16%) as well as asbestos and stone). in january-september 2017, the export from sverdlovsk region to china increased 1.8 times (compared with the same period in 2016) and amounted to $248 million. the structure of export basket of sverdlovsk region to china has changed dramatically (see figure 4). metal and metal products now account for 76% of exports. 4 compiled by the author according to the data from the itc trade map [23] http://r-economy.ru/ m. s. balandina r-economy vol. 3, issue 4, 2017 235 fig. 4. the structure of exports from sverdlovsk region (russia) to china in 2016 and 20175 thus, sverdlovsk region supplies raw materials for chinese industry while the chinese send to the region industrial production of intermediate processes and consumer products. moreover, the range of china's exports is much more diverse than the export of sverdlovsk region; the depth of penetration and the breadth of coverage of chinese products in the ural market are much higher than those of the ural manufacturers in china. there is a strong specialization of russian exports in the traditional sectors, which may lead to a decline in the country’s long-term economic growth in the conditions of open trade within the initiative framework, in particular within the program for creation of the economic corridor china–mongolia–russia. in the next section we shall discuss instruments that may facilitate trade among the participants of the initiative and minimize the risks of damaging their economic growth. opportunities for mutually beneficial ‘win-win’ trade cooperation among the countries of the belt and road initiative to minimize the risk of growth reduction due to the recourse curse and avoid high volatility of exports, it is necessary to diversify the exports basket of russia. in many respects, the prospects for increasing industrial cooperation with partners depend on the competitive advantages of the economic players. to decide on the potential exports of the key manufacturing industries for russia and its main trading partners, we need to identify the comparative advantage goods for each country. to do this, we used the balassa's index (rca): (1) where xji is the value of exports of product i by country j; xj is the value of total exports of the country j (all products); xi is the value of world exports of good i (all countries); x signifies total world exports (of all goods and all countries). 5 compiled by the author according to the data provided by the federal customs service of russia, ural branch [26] 22% 0% 12% 7% 24% 14% 21% 0% 2% 2% 1% 13% 6% 76% 0% 10% 20% 30% 40% 50% 60% 70% 80% other wood, pulp and paper products machinery, equipment and vehicles food products and agricultural raw materials chemical products mineral products metals and products made of them january-september 2017 january-september 2016 http://r-economy.ru/ m. s. balandina r-economy vol. 3, issue 4, 2017 236 the index shows the ratio of the share of exports of a certain product in full export of a particular country to the share of world exports of the same commodity in world exports. to define the structure of the export baskets of the countries, we used two-digit codes of goods according to the sitc classification (standard international trade classification). data on exports of goods by countries was taken from the statistical base of the itc trade map for 2016. figure 5 presents the rca indexes for five participants of the belt and road initiative. the country has a competitive advantage in those products for which the rca index is more than one, that is, when the country's share in the world market of this product is higher that the share of the country's exports in total world exports. fig. 5. comparative competitive advantages of russia in comparison with china, russian economy has competitive advantages in such resource-intensive industries as metallurgy and woodworking industry. however, in such industries as manufacturing, transport, electronic and optical equipment the rca is less than 1. establishment of industrial cooperation with the countries which have a comparative advantage in these areas can increase the productive capacity of these industries in russia. to get more specific results and to find more industries which could diversify russia’s export, we analyzed the rca index for smaller product groups. figure 6 shows the commodity groups in which russia has a comparative advantage in the export of goods. the top five industries (except for mineral products) are fertilizers, nickel and nickel products, cereals, wood and wooden products, iron and steel. nowadays russia has only 17 industries (out of 98 industries), in which the rca index is higher than 1, while turkey has 51 rca industries; belarus, 31; china, 43 industries. 1,47 0,13 0,67 0,47 1,58 1,84 0,46 1,98 1,34 0,59 0,74 1,21 0,38 0,61 1,14 0,64 0,72 1,28 0,63 1,69 0,01 0,08 0,94 1,19 0,59 0,50 1,00 1,50 2,00 2,50 wood, pulp and paper products machinery, equipment and vehicles food products and agricultural raw materials chemical products metals and products made of them mongolia turkey china belarus russia http://r-economy.ru/ m. s. balandina r-economy vol. 3, issue 4, 2017 237 fig. 6. comparative competitive advantages of russia6 members of the economic corridor project can increase the efficiency of their participation in cds by designing the corresponding economic policies, combining tariff regulation with subsequent changes in the scope of non-tariff regulation, by introducing industrial reforms, and improving their institutional environment. conclusion globalization of world trade can facilitate growth or impede it. the latter situation occurs if developing countries specialize in the export of raw materials, which is detrimental to their growth. this is a key challenge for russia in the context of its participation in the belt and road initiative. the current structure of russia's integration into the world economy and its integration with china and mongolia in particular, consists in the export of raw materials and it does not correspond to the model of scientific-technical integration, which is the most significant in the context of globalization. at the same time russia has potential for development in the sphere of technological innovation as it has highly qualified research workforce and opportunities for training of such personnel. 6 compiled by the author according to the data from the itc trade map database [23] 0,84 0,89 1,12 1,16 1,24 1,29 1,41 1,43 1,51 1,54 1,89 2,18 2,50 2,57 2,79 3,17 4,91 5,38 6,71 rubber and articles thereof tobacco and manufactured tobacco substitutes railway or tramway locomotives, rolling stock and parts thereof; railway or tramway track fixtures ... salt; sulphur; earths and stone; plastering materials, lime and cement inorganic chemicals; organic or inorganic compounds of precious metals, of rare-earth metals, ... pulp of wood or of other fibrous cellulosic material; recovered (waste and scrap) paper or ... animal or vegetable fats and oils and their cleavage products; prepared edible fats; animal ... explosives; pyrotechnic products; matches; pyrophoric alloys; certain combustible preparations copper and articles thereof fish and crustaceans, molluscs and other aquatic invertebrates lead and articles thereof aluminium and articles thereof other base metals; cermets; articles thereof iron and steel wood and articles of wood; wood charcoal cereals mineral fuels, mineral oils and products of their distillation; bituminous substances; mineral ... nickel and articles thereof fertilisers http://r-economy.ru/ m. s. balandina r-economy vol. 3, issue 4, 2017 238 today, there are a number of prospective directions to expand industrial cooperation and collaboration between the key players of the initiative. these directions are determined by the competitive advantages of the countries participating in the project. russia has competitive advantages in the global markets of metallurgy and woodworking industry and can put some effort into enhancing the role of russian producers in the markets of partner countries. in the case of engineering and manufacturing of transport equipment, it is necessary to identify the specific niches of domestic producers and to strengthen cooperation with the most competitive foreign partners in order to stimulate the development of the russian mining industry. it is possible to formulate a number of recommendations for russia’s economic policy in the light of the country’s integration into the world economy within the framework of the initiative. first, to benefit from globalization it is necessary to change the raw material orientation of the economy to exports of the manufacturing industry, which implies higher capital intensity and higher requirements to the human capital. it may also be productive to provide support for exporters of non-resource sectors. it is particularly important to providing exporters with packages of privileges and preferences in the period of macroeconomic instability. such measures will be able to stimulate the expansion of non-oil sectors in the economy and the diversification of export activities in russia. second, to ensure technological gains from globalization, it is necessary to develop education and to train highly qualified specialists able to develop and utilize new knowledge and technologies applicable in the world economy. china is already focused on the development of education and is trying to attract more human capital through academic exchange programs. chinese government provides 10,000 scholarships to the countries along the belt and road initiative every year. such policy will enable china to successfully import leading young scientists from the developing countries. for russia, this would be another reminder of the need to devise its own policies to prevent brain drain. thirdly, it is advisable to refrain from excessive liberalization of foreign trade, which can lead to falling into the trap of raw material specialization. to do this, the government can impose physical restrictions on the export of raw materials and products with a low degree of processing. these restrictions may be in the form of quotas or the government may choose not to construct any additional export infrastructure. finally, it is necessary to promote foreign investment in the country's economy. the investment industry should be characterized by high capital intensity and high level of technology. references 1. makarov i., sokolova a. 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(1992). agricultural productivity, comparative advantage, and economic growth. journal of economic theory 58(2), 317-334. 23. itc trade map. retrieved from: http://www.trademap.org/country_selproductcountry_ts.aspx. 24. wto-oecd tiva database. retrieved from: http://www.oecd.org/sti/ind/measuringtradeinvalue-addedanoecdwtojointinitiative.htm 25. turgel i., vlasova n., xu l. (2017) economic links between russia and china: from cross-border to international cooperation (the case of sverdlovsk region and helongjiang provence). r-economy, 3(3), 149-160. 26. the federal customs service of russia, ural branch. retrieved from: http://utu.customs.ru author balandina marina sergeevna — senior lecturer, ural federal university (19, mira st., ekaterinburg, 620002, russian federation; email: m.s.balandina@urfu.ru) http://r-economy.ru/ http://dl.kli.re.kr/dl_image/img/02/000000005835/service/000000005835_01.pdf http://www.trademap.org/country_selproductcountry_ts.aspx http://www.oecd.org/sti/ind/measuringtradeinvalue-addedanoecd-wtojointinitiative.htm http://www.oecd.org/sti/ind/measuringtradeinvalue-addedanoecd-wtojointinitiative.htm http://utu.customs.ru/ mailto:m.s.balandina@urfu.ru 168 www.r-economy.ru r-economy, 2019, 5(4), 168–175 doi: 10.15826/recon.2019.5.4.017 online issn 2412-0731 original paper © i. m. golova, a. f. sukhovey, 2019 doi 10.15826/recon.2019.5.4.017 ‘green economy’ as a strategy of modernization of older industrial areas in the urals i. m. golova, a. f. sukhovey  institute of economics, ural branch of the russian academy of sciences, ekaterinburg, russia; e-mail: alla_suhovey@list.ru abstract this article discusses ‘green economy’ as a crucial principle of regional socio-economic development at its current stage. in the russian context, this principle is particularly relevant in the light of the catastrophic increase in pollution of the human environment and habitat. ‘green’ economy focuses on modernization of production to ensure its sustainability and restoration of human habitat. the empirical part of the study deals with the social, economic and, above all, environmental problems (resource depletion, pollution, increased health risks) faced by older industrial regions in the urals (sverdlovsk, chelyabinsk and kurgan regions). these regions are now struggling with the decline of their key industries, such as mining and metallurgy. it is shown that the problems they currently face largely stem from the orientation of the russian economy towards raw material exports. the article also analyzes the innovation and technological potential of these regions and their priorities of socio-economic development. it is shown that their potential (e.g. human capital) is sufficient to modernize their economies. some recommendations are formulated for these regions’ more efficient transition to the ‘green economy’. these include the development of high-tech industries and eco-friendly technologies, introduction of modern environmental standards of economic activity as the basis of modern regional socio-economic systems. keywords green economy, green growth, sustainable development, environmental modernization, innovation model acknowledgements the research was supported by the project of fundamental studies of the ural branch of the russian academy of sciences № 18-6-7-18 ‘sustainable scientific and technological development of regions based on green economy principles’. for citation golova i. m., sukhovey a. f. (2019) ‘green economy’ as a strategy of modernization of older industrial areas in the urals. r-economy, 5(4), 168–175. doi: 10.15826/ recon.2019.5.4.017 зелёная экономика как стратегия модернизации старых индустриальных районов урала и. м. голова, а. ф. суховей  институт экономики уральского отделения российской академии наук, г. екатеринбург, россия; e-mail: alla_suhovey@list.ru аннотация в этой статье рассматривается «зеленая экономика» как важнейший принцип социально-экономического развития региона на современном этапе. в россии этот принцип особенно актуален в свете катастрофического увеличения загрязнения окружающей среды и среды обитания человека. «зеленая» экономика ориентирована на модернизацию производства с целью обеспечения его устойчивости и восстановления среды обитания человека. эмпирическая часть исследования посвящена социальным, экономическим и, прежде всего, экологическим проблемам (истощение ресурсов, загрязнение, повышенный риск для здоровья), с которыми сталкиваются пожилые промышленные районы урала (свердловская, челябинская и курганская области). эти регионы сейчас борются с упадком их ключевых отраслей, таких как горнодобывающая и металлургическая. показано, что проблемы, с которыми они сталкиваются в настоящее время, во многом связаны с ориентацией российской экономики на экспорт сырья. в статье также анализируется инновационно-технологический потенциал этих регионов и их приоритеты социально-экономического развития. показано, что эти регионы имеют потенциал (например, человеческий капитал), достаточный для модернизации их экономики. сформулированы некоторые рекомендации для более эффективного перехода этих регионов к «зеленой экономике». к ним относятся развитие высокотехнологичных производств и экологически чистых технологий, а также внедрение современных экологических стандартов экономической деятельности. ключевые слова зеленая экономика, зеленый рост, устойчивое развитие, экологическая модернизация, инновационная модель благодарности работа выполнена при поддержке проекта фундаментальных исследований уральского отделения российской академии наук № 18-6-7-18 «устойчивое научно-техническое развитие регионов на основе принципов зеленой экономики». для цитирования golova i. m., sukhovey a. f. (2019) ‘green economy’ as a strategy of modernization of older industrial areas in the urals. r-economy, 5(4), 168–175. doi: 10.15826/ recon.2019.5.4.017 http://doi.org/10.15826/recon.2019.5.4.017 http://doi.org/10.15826/recon.2019.5.4.017 mailto:alla_suhovey@list.ru mailto:alla_suhovey@list.ru r-economy, 2019, 5(4), 168–175 doi: 10.15826/recon.2019.5.4.017 169 www.r-economy.ru online issn 2412-0731 introduction the current social, economic and environmental situation makes it pertinent to adjust and modernize the paradigm of socio-economic development of older industrial areas in the urals. as local reserves of metal ores are exhausted, the ural mining and metallurgical industry is losing its competitive edge, which is accompanied by the disappearance of some traditional industries for this region (mechanical engineering, light industry, etc.) and exacerbation of unemployment, especially in mining cities and towns. on the basis of the official statistical data, we have calculated that by 2017 steel production in the ural federal district (urfd) had declined by 22.5% in comparison with 1990; the production of steel pipes, by 30.5%; the production of metal cutting machines is now only 3.2% from the level of 1990; tractors, 1.4%; excavators, 0.3%). production of household appliances such as washing machines, refrigerators has been stopped completely. as a result, five urban districts in sverdlovsk region and seven in chelyabinsk region, with the population of 284 and 136 thousand people respectively, were included in the national list of mono-profile territories with the most difficult socio-economic situation1. the reasons behind this situation are obvious: the lack of proper state regulation when these areas were adapting to the new market environment during the period of reforms, the redistribution of property of former state-owned organizations, and the widening technology gap. it should be noted, however, that in the last thirty-fifty years of the twentieth century, environmental problems were also seriously exacerbated due to intensive exploitation of natural resources, large concentrations of ‘dirty’ industries and the use of unsustainable technologies. according to the environmental performance index, russia ranks only 52nd out of 180 countries (table 1). the poor environmental performance of russia can be explained by the long-standing orientation of the country’s economy towards raw material exports; high proportion of energy-intensive, environmentally unfriendly industries; significant wear and tear of industrial production facilities; lack of economic incentives for enterprises to develop environmentally friendly technologies; and structural corruption in production monopolies. 1 population of municipalities in the russian federation. retrieved from: https://www.gks.ru/folder/11110/document/13282 table 1 ranking of countries by the environmental performance index, 2018 position countries environment index including indices: environmental health ecosystem vitality 1 switzerland 87.42 93.57 83.32 2 france 83.95 95.71 76.11 5 sweden 80.51 94.41 71.24 6 uk 79.89 96.03 69.13 10 finland 78.64 99.35 64.83 13 germany 78.37 88.68 71.5 27 united states 71.19 93.91 56.4 51 venezuela 63.89 75.74 55.99 52 russia 63.79 75.48 55.99 60 south korea 62.30 73.30 54.96 compiled by the authors by using the data from: environmental performance index. available at: https://epi.envirocenter.yale.edu/ older industrial areas of the ural federal district (urfd) include sverdlovsk region, chelyabinsk region and a number of municipalities in kurgan region. these territories have similar natural environments and, even on the national scale, can be classified as struggling and disadvantaged. regarding emissions of pollutants into the atmosphere from stationary sources, sverdlovsk region ranks fourth among other russian regions while chelyabinsk, seventh. these regions rank among the worst in other indicators such as the volume of contaminated wastewater or waste formation (see table 2). given the reduced capacity for self-healing of the natural environments of northern territories and their water scarcity problems, such man-made pressure on water facilities poses a serious danger not only to local biocenoses, but also to communities and individual residents. older industrial ural areas have for many years been suffering from increased health risks: according to the ministry of natural resources of the russian federation, 63.4% of the population of sverdlovsk region lives in municipal districts where enterprises are major sources of pollution of the natural environment. the most polluted city of the region is nizhny tagil. emissions of harmful substances into the atmosphere by its industrial enterprises now amount to about 200,000  t. the main pollutants are the nizhny tagil metallurgical plant and vysokogorsky ore mining and processing plant, which are responsible for 90% of emissions. the air in the towns of kamensk-uralsky and krasnoturyinsk is contaminated with fluoride compounds (fluoride hydrogen, solid fluohttp://doi.org/10.15826/recon.2019.5.4.017 https://www.gks.ru/folder/11110/document/13282 https://www.gks.ru/folder/11110/document/13282 https://epi.envirocenter.yale.edu/ https://epi.envirocenter.yale.edu/ 170 www.r-economy.ru r-economy, 2019, 5(4), 168–175 doi: 10.15826/recon.2019.5.4.017 online issn 2412-0731 ride), due to the activity of aluminum plants2. in 2017, water samples in sverdlovsk region, including the largest metropolis ekaterinburg, showed that in 15% of cases, water was classified as ‘contaminated’; in 79%, as ‘dirty’; and in 6%, as ‘extremely dirty’. in terms of health risks, sverdlovsk, chelyabinsk and kurgan regions are now classified by the russian consumer watchdog as the most problematic, from the point of view of natural environments. these regions were included in the cluster of regions with a strong impact on public health. in order to change the situation, serious systemic modernization of economy is necessary. industrial development, depletion of resources together with unfavorable natural and climatic factors predetermined neo-industrialization as a mandatory condition for older ural industrial regions to restore their competitiveness, reduce outbound migration and preserve the quality of human potential. at the same time, one of the most important goals of modernization in the urals should be to address the environmental problems and reduce the risks to public health due to the pollution of the natural environment. given the international approaches to longterm sustainable development and the severity of environmental problems in the urals, it seems that particular attention in the process of its economic modernization should be focused on the transition to the principles of ‘green economy’. 2 the current environmental situation and environmental safety issues. retrieved from: https://geografia-sverd.ucoz. ru/index/ehkologicheskie_problemy/0-46 theoretical framework and international experience the concept of green economy is known to have been used for the first time in the work ‘blueprint for a green economy’ in 1989. later, the concepts of green industry, green markets, green employment and others started to be used in international documents. the documents adopted at the un conference on sustainable development, rio+20, held in rio de janeiro in 2012, explicitly stated the need for the world community to transition to a green economy as a new development model3. the term ‘green economy’ is interpreted differently today. a widespread understanding of green economy proposed in the un environment program – unep is that it means ensuring long-term improvement in people’s well-being and reducing inequality and allowing future generations to avoid significant risks to the environment and its impoverishment4. this understanding of green economy, according to blanco, e. [1, p. 16], b. n.  porfiryev [2, pp. 33–40], n. v. pakhomov [3,  pp. 88–98], is close to the well-known concept of sustainable development and is an attempt to resuscitate it due to the increasing crisis in the world economy (falling gdp, rising pressure from multinational companies, environmental problems, etc.). however, we find much more persuasive the view that ‘green economy’ is a new type of economy opposed to the previous man-made type of economic develop3 rio 20 final document – ‘the future we want’. retrieved from: http://grow.clicr.ru/news/81 4 assess europe’s environment. european environment agency, 2011. generalized report. copenhagen. retrieved from: http://www. eea. europa. eu table 2 anthropogenic impact on the environment in the urals, 2017 emissions of pollution into the atmosphere from stationary sources dumping contaminated wastewater into surface water facilities waste generation and consumption thousands of tons rank for russia mln m3 rank for russia thousands of tons rank for russia russia 17,500 13,589 6,220,639 ural federal district 3,840 1,515 281,082 kurgan region 44 58 36 60 777 66 sverdlovsk region 928 4 586 6 174,342 8 hunts-mansi autonomous region 1,412 3 86 36 7,107 30 yamalo-nenets autonomous region 786 5 31 65 715 67 tyumen region, without autonomous districts 138 30 84 40 1,469 55 chelyabinsk region 533 7 691 5 96,672 12 compiled by the authors by using the data from: federal government statistics service. section: environmental protection. available at: https://www.gks.ru/folder/210/document/13209 http://doi.org/10.15826/recon.2019.5.4.017 https://geografia-sverd.ucoz.ru/index/ehkologicheskie_problemy/0-46 https://geografia-sverd.ucoz.ru/index/ehkologicheskie_problemy/0-46 http://grow.clicr.ru/news/81 http://www. eea. europa. eu https://www.gks.ru/folder/210/document/13209 r-economy, 2019, 5(4), 168–175 doi: 10.15826/recon.2019.5.4.017 171 www.r-economy.ru online issn 2412-0731 ment, based on the use of artificial means of production, created without taking into account environmental restrictions [4, p. 34; 5, p. 89]. for example, the acid rains resulting from emissions of industrial waste into the atmosphere in the uk were recorded in norway; sweden was affected by the chernobyl disaster; the great lakes on the u.s.-canada border suffer from the negative effects of the runoffs of american businesses. in the 1990s, environmental problems acquired a new, global dimension. the greenhouse effect, which is a consequence of emissions of inert gases into the atmosphere, caused global warming, which led to radical climate changes in almost all regions of the world (snowfalls and hurricanes in the u.s., floods in germany and other countries western and eastern europe, summer heatwaves, drought and tornadoes in many regions of russia) [6, p. 39]. oecd experts predict that if modern production and consumption levels continue to persist by 2050, between 61 and 72% of the world will lose 61 to 72% of its flora and fauna by 2050, and the conservation of natural areas will be irreversibly disrupted by 7.5 million square kilometers5. the urgent need to overcome these negative changes, which threaten human survival in the foreseeable future, has led the world community to try to develop a universal integrated strategy for environmental modernization [7, р. 147]. this strategy has been referred to as ‘green growth’ and focuses on the idea of stimulating economic progress through a shift to sustainable development [8, p. 21]. this approach initially involves concentration on the development options of societies (countries, regions, etc.) on the consideration of the growth constraints imposed by the assimilation capacity of natural environments and the requirements for maintaining an acceptable ecological condition environment and sources of life for future generations6. in response to the need to overcome the negative changes associated with environmental imbalances, the global community has now set out the priorities of green economy aimed at addressing the most acute environmental problems. according to unep, these areas include: effective use of natural resources; preservation and increase of natural capital reducing pollution; 5 overview of energy technologies. scenarios and strategies until 2050/ oecd/iea; wwf russia. retrieved from: https://wwf.ru/upload/iblock/164/perspective_20x27_new.pdf 6 our common future. icosr report. moscow: progress, 1989. reducing carbon emissions; reventing the loss of ecosystem services and biodiversity; income and employment growth [9, p. 176]. many countries adopt laws and programs to protect and restore the environment: for instance, finland currently has 14 national transition programs for green economy; the uk, 9; germany, 7; and sweden, 4 [10, p. 37]. in 2000, australia passed a law to introduce a mandatory renewable energy standard and bring its share of total consumption to 10% by 2010. this figure was reached in 2009 and in the same year a new goal was set, obliging the state to increase this share to 20% by 2020, as well as the eu average7. in the united states, to combat smog, los angeles passed a special law requiring every car company that has been selling its cars in california since 2005 to produce at least 10% of environmentally friendly vehicles with zero emissions of pollutants into the atmosphere from the total number of cars. in france, a scheme to pay bonuses to buyers of cleaner cars is used, which stimulates demand for ‘green’ cars and contributes to the expansion of their production. in the uk, there are subsidies (2,000–5,000 pounds) for purchase of electric cars [11, pp. 30–31]. japan is considered to be the most ecologically advanced country: producing about 7% of global gdp, it emits only 5% of carbon dioxide and 1% of sulphur oxides from all global emissions [12, p. 41]. south korea was the first country to announce the concept of green growth as a national strategy. sweden plans to phase out oil, coal and gas and switch to renewable energy by 2020. japan deve loped the low carbon action program and set a low standard for carbon emissions as a long-term development goal. in the u.s., the ‘green economy’ already provides products and services worth of more than 600 billion dollars (4.2% of gdp) and jobs for 3 million people. the uk (8.8%) became the world leader in the share of the green sector in gdp.[13]. by 2025, the global market for environmentally friendly equipment is estimated to reach 4.4 trillion euro, which will provide more than 30% annual average growth and increase the contribution to world gdp to 6–7%. by 2020, we can expect that the global market for clean technologies will double, the number of people employed in the relevant sectors will increase almost 4 times and the contribution of the green economy to world gdp, by at least 5% [14]. 7 renewable energy (electricity) amendment 2009. retrieved from: http://parlinfo.aph.gov.au/parlinfo/download/ legislation/billslst/ http://doi.org/10.15826/recon.2019.5.4.017 https://wwf.ru/upload/iblock/164/perspective_20x27_new.pdf http://parlinfo.aph.gov.au/parlinfo/download/legislation/billslst/ http://parlinfo.aph.gov.au/parlinfo/download/legislation/billslst/ 172 www.r-economy.ru r-economy, 2019, 5(4), 168–175 doi: 10.15826/recon.2019.5.4.017 online issn 2412-0731 the foundation of the ‘green’ economy is the use of environmentally efficient innovative technologies (energy-efficient and alternative energy technologies, ‘green’ transport, air and water emissions management, etc) aimed to reduce the human pressure on the environment [15, p. 119]. methodology and data administrative and legal regulation play a key role in environmental protection and transition of a country (region) to the ‘green economy’. economic measures used to influence the behavior of environmental users can play only an auxiliary corrective role due to the fact that implementation of the principles of the ‘green’ economy in the public life usually runs counter the interests of those agents that receive immediate benefits and requires a serious change in the underlying motivations of human behavior. initially, the damage from the use of natural resources (especially the damage caused by the depletion of non-renewable natural resources) and pollution in human economic activities, given all externalities, including long-term consequences such as the future disposal of utility products after the loss of their consumer properties, always exceeds the benefits. calculations carried out by e. v. ryumina have shown that in order to ensure the normative level of waste disposal in production (the maximum permissible concentrations of harmful substances in the environment), russian energy companies need to increase the share of environmental costs in the cost of energy products 6 times; metallurgy, 4.3 times; fuel, 3.3 times; chemistry and petrochemicals, 2.1 times; and engineering, 2 times. this is unacceptable both in terms of maintaining the competitiveness of the remaining russian enterprises and in terms of social parameters. such dramatic increase in payments will lead to immediate bankruptcy of almost all the country’s leading industries (energy, chemistry and petrochemicals engineering), except for the fuel industry, whose profitability will also be halved, and steel industry, whose enterprises will be on the verge of break-even [16, pp. 66, 73]. therefore, in developed countries, the regulation of anthropogenic impact on the environment is usually based on the notion of a socially acceptable level of natural environments and resources, which is consistent with common sense and the idea of a social contract that underpins developed democracies. however, the socially acceptable level of natural environments for a particular country (civilization) and, therefore, the readiness to switch to ‘green’ technologies are mostly determined by people’s environmental literacy, the level of civic maturity and public engagement and the economic situation. in russia, due to the peculiarities of its historical development, the system of life values is severely distorted. moreover, a large part of the population have very low incomes. according to rosstat, in 2018, 12.9% of the country’s population had an income level below the official subsistence level, which is only 10,287 rub.8 as a result, the russian public is largely unaware of the state of the environment, and environmental initiatives, unlike those in developed countries, remain unnoticed by the majority of russian people. therefore, industrial enterprises feel free to use cheap, environmentally harmful technologies, thus increasing the risks of wasteful environmental management. nevertheless, there are certain advances in the national movement towards the ‘green economy’. in 2012, the ‘basics of state policy on the environmental development of russia for the period until 2030’ were adopted. in this document, the strategic goal of the russian economy at the present stage is defined as ‘solving socio-economic problems and ensuring environmentally oriented economic growth, preservation of the favorable environment’9. the document also outlines the basic principles and objectives of public environmental development policies, including: – building an effective environmental and environmental management system; – improving environmental safety regulations; – to ensure environmentally oriented economic growth and the introduction of environmentally efficient innovative technologies; – preventing and reducing the current negative impact on the environment; – restoration of disturbed natural systems, etc.10 a positive shift in the public management of environmental pollution is russia’s transition from emissions control (resets) to establishing allowable emissions (to manage the processes of en8 federal state statistics service. official website. retrieved from: https://www.gks.ru/folder/13397 9 the basics of the state policy in the field of environmental development of russia for the period until 2030. retrieved from: http://kremlin.ru/acts/15177 10 the basics of the state policy in the field of environmental development of russia for the period until 2030. retrieved from: http://kremlin.ru/acts/15177 http://doi.org/10.15826/recon.2019.5.4.017 https://www.gks.ru/folder/13397 http://kremlin.ru/acts/15177 http://kremlin.ru/acts/15177 r-economy, 2019, 5(4), 168–175 doi: 10.15826/recon.2019.5.4.017 173 www.r-economy.ru online issn 2412-0731 vironmental and technological modernization of production technologies used by business entities through the use of the best available technologies (bat) mechanism). the eu model for controlling industrial emissions was taken as the basis11. in 2014, the relevant amendments were made to the federal law on protection of the natural environment12. it should be noted that only objects of the first out of four possible categories fall under the regulation of using the bat mechanism: those that have a significant negative impact on the environment (article 4.2). the best available technologies, however, are not completely the same as ‘green’ technologies. article 1 of the russian environmental protection act interprets the best available technology as a ‘technology of production (goods), work, service delivery, determined on the basis of modern advances in science and technology and best combination of criteria for achieving environmental goals, provided it is technically possible to be applied’13. however, this interpretation is very vague and leaves much room for manoeuvre. due to the absence of proper public control and pressure from monopolistic enterprises, there is a risk that this mechanism will be used not only in the interests of conservation, but also to reduce the responsibility of business owners for pollution environment. the definition of the best available technology in the eu documents is more precise: in accordance with the directives, this term refers to the ‘most effective and advanced stage of development of activities and methods of their implementation, which demonstrates the practical suitability of certain technologies for compliance emission thresholds and other permit conditions designed to prevent or, if not feasible, reduce emissions and impact on the environment as a whole’14. the passport of the federal project ‘best available technologies’ (included in the national 11 directive 2010/75/eu of the european parliament and of the council of 24  november 2010 on industrial emissions (integrated pollution prevention and control). retrieved from: https://eur-lex.europa.eu/legal-content/en/txt/?uri=celex:32010l0075 12 federal law on environmental protection of 10.01.2002 n 7-fz (ed. 27.12.2018). retrieved from: http://www.consultant.ru/document/cons_doc_law_34823/ 13 federal law on environmental protection of 10.01.2002 n 7-fz (ed. 27.12.2018). retrieved from: http://www.consultant.ru/document/cons_doc_law_34823/ 14 directive 2010/75/eu of the european parliament and of the council of 24  november 2010 on industrial emissions (integrated pollution prevention and control). retrieved from: https://eur-lex.europa.eu/legal-content/en/txt/?uri=celex:32010l0075 project ‘ecology’) specifies that in 2019, the first 15  comprehensive environmental permits (cer) will be issued, and by 2022 it is planned that such permits will be granted to 300 enterprises which are the largest polluters of the natural environment in russia. it is too early to say how this mechanism will work, but the fact that the guidelines concerning the best available technologies were prepared without involving public discussion, in the traditional ‘closed-door’ way, can be a cause for alarm both among the owners of businesses and people living in their immediate vicinity. results it should be emphasized that older industrial ural regions hold a considerable potential for r&d development. together with other factors, such as access to highly qualified engineering staff and established traditions of industrial production, this may well provide a good foundation for the development ‘green’ economy, which is one of the most important components of modernization. as our calculations show (see table 3), sverdlovsk region currently occupies the 9th place in the integral index of innovative opportunities. chelyabinsk ranks 16th among other russian regions. both regions have the potential to become federal innovation centers focused on technological support and modernization of steel and high-tech industries. these areas also have good prospects for the development of innovative entrepreneurship aimed at improving technological processes of exploration and mining. for more detailed description of the methodology for assessing the innovative potential of regions see [17]. in our calculations, we took into account such factors as scientific and innovative potential of regions; the potential for innovation demonstrated by their socio-economic environment; and the structure of production. in order to launch the transition of the older industrial regions to ‘green economy’ principles, it is necessary: – to limit monopolies and ensure fair competition; – to stimulate the development of the middle class and reduce poverty; – to create adequate financial institutions with the participation of public funds to stimulate the development of modern high-tech industries and implementation of ‘green’ technologies; – to provide priority support for national science, education and innovation; http://doi.org/10.15826/recon.2019.5.4.017 https://eur-lex.europa.eu/legal-content/en/txt/?uri=celex:32010l0075 https://eur-lex.europa.eu/legal-content/en/txt/?uri=celex:32010l0075 http://www.consultant.ru/document/cons_doc_law_34823/ http://www.consultant.ru/document/cons_doc_law_34823/ http://www.consultant.ru/document/cons_doc_law_34823/ http://www.consultant.ru/document/cons_doc_law_34823/ https://eur-lex.europa.eu/legal-content/en/txt/?uri=celex:32010l0075 https://eur-lex.europa.eu/legal-content/en/txt/?uri=celex:32010l0075 174 www.r-economy.ru r-economy, 2019, 5(4), 168–175 doi: 10.15826/recon.2019.5.4.017 online issn 2412-0731 – to apply modern environmental standards of waste management, waste disposal and so on; – to provide state support for modernization of life support systems of settlements based on the ‘green’ economy principles; – to develop environmental education and education; – to incentivize public environmental organizations. conclusion transfer to the ‘green’ model of economy is a natural stage in the evolution of modern socio-economic systems in russia and other countries. the need for such transfer becomes particularly urgent in the face of the dangers of global climate change, use of environmentally harmful technologies and so on. this problem is relevant for russia and for its older industrial regions in particular. the ural federal district is known as the primary location of the country’s industrial complexes. it is obvious that these complexes are now in need of some serious modernization, as they are still using obsolete and environmentally unsafe technologies of the third and fourth technological ways of production. it is, therefore, vital that these complexes should embark on innovation programs to enhance their competitiveness and improve the quality of life in the surrounding areas. the transition of these ural regions’ economies to the ‘green’ model requires serious mobilization of their management and financial resources. the use of these regions’ innovation and technological potential should play an important role in this process. enhancing the sustainability of their economies will help these regions to tackle such problems as pollution, especially those types of pollution that accelerate climate change, prevalence of energy-intensive industries, loss of biodiversity, depletion of natural resources, increased health risks and poor quality of life, unemployment and low income among the population. table 3 comparative assessment of conditions for development of innovation in the urals, 2017 position in the national ranking ural regions oppor-tunities for innovative development including: feasibility of developing innovation based on:r&d potential innovation high-tech sector metal-lurgy mining kurgan region 53 57 55 40 37 66 sverdlovsk region 9 9 15 7 1 17 tyumen region 33 48 14 43 29 1 including hunty-mansi autonomous region 52 79 16 64 63 2 yamalo-nenets autonomous region 65 82 51 80 78 3 chelyabinsk region 16 17 29 11 2 21 references 1. blanco, e., & razzaque, j. 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(2009) why enterprises do not want and cannot protect the environment: quantitative analysis. ekonomicheskaja nauka sovremennoj rossii = economic science of modern russia, 4, 66–74. (in russ). 17. sukhovey, a. f., & golova, i. m. (2019). innovative component of socio-economic development. yekaterinburg: ie urd ras. (in russ). information about the authors irina golova – doctor of economics, head of the sector of social innovation, senior researcher, institute of economics of the ural branch of the russian academy of sciences (ekaterinburg, russia, moskovskaya str., 29); e-mail: irina_golova@mail.ru. alla sukhovey – doctor of philosophy, professor, chief researcher at the sector of social innovation, institute of economics of the ural branch of russian academy of sciences (ekaterinburg, russia, moskovskaya str., 29); e-mail: alla_suhovey@list.ru. article info: received june 27, 2019; accepted september 26, 2019 информация об авторах голова ирина марковна – доктор экономических наук, зав. сектором социальных инноваций ведущий научный сотрудник, институт экономики уральского отделения российской академии наук (620014, россия, г. екатеринбург, ул. московская, 29); e-mail: irina_golova@mail.ru суховей алла филипповна – доктор философских наук, профессор, ведущий научный сотрудник сектора социальных инноваций, институт экономики уральского отделения российской академии наук (620014, россия, г. екатеринбург, ул. московская, 29); e-mail: alla_ suhovey@list.ru. информация о статье: дата поступления 27 июня 2019 г.; дата принятия к печати 26 сентября 2019 г. this work is licensed under a creative commons attribution 4.0 international license эта работа лицензируется в соответствии с creative commons attribution 4.0 international license http://doi.org/10.15826/recon.2019.5.4.017 http://doi.org/10.1016/j.jclepro.2015.09.007 http://carnegieendowment.org/files/wp_porfiriev_web.pdf http://carnegieendowment.org/files/wp_porfiriev_web.pdf http://doi.org/10.1016/j.ecolecon.2012.04.005 mailto:alla_suhovey@list.ru mailto:alla_suhovey@list.ru r-ecomony, 2018, 4(3), 121–129 doi: 10.15826/recon.2018.4.3.017 121 www.r-economy.ru online issn 2412-0731 original paper doi: 10.15826/recon.2018.4.3.017 evaluation of economic security in the ural region in the context of development of small and medium-sized enterprises natalya yu. vlasova , olesya o. kalganova ural state economic university, ekaterunburg, russia; email: nat-vlasova@yandex.ru abstract enhancing economic security of regions is crucial for the development of the whole country, which is what makes research in this sphere particularly important. th is study aims to analyze and compare the economic security data on the regions constituting the ural federal district (russia). in contrast with current studies in the fi eld, we are conducting detailed analysis of the factors that aff ect the development of small and medium-sized enterprises (smes) and business climate in the regions. th e conceptual framework of this research relies on entrepreneurship theories and theoretical approaches to analysis and evaluation of regional economic security. we develop methodology based on sets of quantitative and qualitative indicators and apply analytical, comparative and statistical methods as well as the method of expert evaluation. th e data are provided by the regional statistic services and business support foundations. we also analyze regional support programs for small and medium-sized businesses. we found that all regions of the ural federal district are characterized by the medium (acceptable) level of economic security and moderate risk. in the economic security ranking, tyumen region is at the top while the second place is occupied by sverdlovsk region; chelyabinsk and kurgan regions are at the bottom. keywords region, regional economic security, small and middle-sized enterprises, entrepreneurship, business support programs, ural federal district for citation vlasova, n. yu., kalganova, o. o. (2018) evaluation of economic security in the ural region in the context of development of small and medium-sized enterprises. r-economy, 4(3), 121–129. doi: 10.15826/recon.2018.4.3.017 оценка экономической безопасности в уральском регионе в контексте развития малых и средних предприятий н. ю. власова , о. о. калганова уральский государственный экономический университет, екатеринбург, россия; email: nat-vlasova@yandex.ru резюме укрепление экономической безопасности регионов имеет важное значение для развития всей страны, что делает исследования в этой сфере крайне важными. данное исследование направлено на анализ и сравнение данных экономической безопасности в регионах, входящих в уральский федеральный округ (россия). в отличие от текущих исследований в данной области, мы провели детальный анализ факторов, влияющих на развитие малых и средних предприятий (мсп) и делового климата в регионах. концептуальные рамки этого исследования основаны на теориях предпринимательства и теоретических подходах к анализу и оценке региональной экономической безопасности. мы разработали методологию на основе наборов количественных и качественных показателей и применили аналитические, сравнительные и статистические методы, а также метод экспертной оценки. данные предоставлены региональными службами статистики и поддержки бизнеса. мы также анализируем региональные программы поддержки малого и среднего бизнеса. мы обнаружили, что все регионы уральского федерального округа характеризуются средним (приемлемым) уровнем экономической безопасности и умеренным риском. в рейтинге экономической безопасности тюменская область находится на вершине, а второе место занимает свердловская область; челябинская и курганская области находятся внизу. ключевые слова регион, региональная экономическая безопасность, малые и средние предприятия, предпринимательство, программы поддержки бизнеса, уральский федеральный округ для цитирования vlasova, n. yu., kalganova, o. o. (2018) evaluation of economic security in the ural region in the context of development of small and medium-sized enterprises. r-economy, 4(3), 121–129. doi: 10.15826/recon.2018.4.3.017 122 www.r-economy.ru r-ecomony, 2018, 4(3), 121–129 doi: 10.15826/recon.2018.4.3.017 online issn 2412-0731 introduction global economic instability has made the question of regional economic security crucial for the prosperity of countries. in its turn, economic security of regions depends on multiple factors and conditions, which include the quality of the human capital, the general level of economic development and associated processes, the quality of the infrastructure, the availability and diversity of resources, political stability and so on. th e region’s attractiveness for investment and the level of entrepreneurial activity are also important factors for its economic security. th e vast majority of studies confi rm that small and medium-sized businesses (smes) are among the key drivers of economic growth. th ere is also evidence that not only does sme development positively aff ect the general economic performance of the region, but also has a signifi cant social impact, which is crucial for regional and local economy. smes contribute to the development of entrepreneurship and improve business climate, moreover, they help the government tackle the problem of welfare mentality by encouraging people to look aft er themselves. small and medium-sized businesses are essential for innovation-driven sectors of economy as it is primarily in such enterprises that new products and technologies are created and tested. th erefore, the development of smes and self-employment is an important factor that determines the region’s economic security. th ere is, however, a lack of adequate methodology to evaluate the impact of sme development on the level of economic security and our study is going to address this issue. theoretical framework th is research is based on two groups of theoretical approaches. th e fi rst group comprises theories on economic security in regions. th ese theories mostly focus on threshold values of various economic and social indicators that are crucial for stable regional development. th e second group includes theories of entrepreneurship, especially the ones that deal with smalland medium-sized businesses. th ere is a vast body of research literature discussing the problems of economic security in regions. a thorough retrospective analysis of these problems was conducted by the ural research school [1]. in general terms, economic security on the regional level is seen as “a complex of conditions and factors that characterize the current state of regional economy, its stability and progressive growth as well the degree of its independence in the processes of integration with federal economy” [1, p. 29]. th e following methods are applied in russian studies to evaluate the level of economic security: a) monitoring of the key macroeconomic indicators, especially when their values approach the threshold values [2]; b) expert evaluation and ranking of regions according to the level of security threat [3]; c) evaluation of the consequences of security threats by measuring the damage [1]. mingaleva and gershanok show the connection between the region’s stability, its competitiveness and the level of economic security [4]. in some studies, economic security of small-sized businesses is seen as an important factor and as a criterion for evaluating economic security of the region and the whole country [5; 6]. undoubtedly, the more active local business life is, the stronger is the positive eff ect that smes have on regional economy [7]. th erefore, we should have a good understanding of the factors and conditions that infl uence the entrepreneurial climate in the region, for example, by analysing policies aimed at supporting entrepreneurship and evaluating their effi ciency [8–12]. some studies focus on specifi c forms of such support that target small businesses. for instance, korchagina analyzes the state policy of stimulating the development of clusters of small and medium-sized enterprises [13]. other studies question the long-term effi ciency of such policies and emphasize the fact that the quality of human capital, population mobility and density are much more important [14; 15]. a big group of studies analyze sme support programs in transitive economies [16–18]. data and methodology our methodology for economic security evaluation relies primarily on the indicators of sme development. th e methodology comprises both quantitative and qualitative parameters. for the former we used the offi cial statistical data while the latter require additional research and expert evaluations. economic security implies stability that ensures sustainable growth of the region’s economy, which means that, in order to evaluate its current state, we should be focusing on the ongoing trends and patterns of regional development. r-ecomony, 2018, 4(3), 121–129 doi: 10.15826/recon.2018.4.3.017 123 www.r-economy.ru online issn 2412-0731 we estimate the parameters by applying a tenpoint scale with the higher values corresponding to better performance: if the current values are lower than the target value, the region scores 0. if the current values are closer to the average value, the region scores 5. if the current values meet the target values, then the region scores 10. th e indicators used to evaluate regional security with the focus on sme development are shown in table 1. table 1 indicators of regional economic security (with the focus on sme development) quantitative indicators qualitative indicators th e number of smes th e number of employees in smes th e share of sme turnover in the grp th e amount of taxes paid by smes to the budget funds for sme support from the federal and regional budgets th e number of fi nancial support recipients th e number of non-fi nancial support recipients th e number of jobs created by support recipients capital investment th e quality of sme support infrastructure effi ciency of sme support programs red tape (registration and re-registration procedures for businesses) th e level of entrepreneurial activity attitude of local inhabitants towards entrepreneurship access to information about the market, its potential and resources, production facilities and equipment opportunities for further development of smes let us now consider these indicators and their impact on regional economic security in more detail. 1. quantitative indicators (better performing regions score 10; if no signifi cant changes are registered, 5; and if the trend is negative, 0): a) the number of smes, that is, the number of legal entities operating in the region as of the end of the fi nancial year. th e growth in the number of smes signifi es that the region’s economic security is improving as enterprises are participating in social and economic development of the region by contributing to its stability and prosperity; b) the number of employees in smes. th e rising number of employees working for small, medium-sized and micro-enterprises has a positive impact on economic security as it means more jobs. smes perform a vital social function as they reduce the level of unemployment and relieve social anxiety; c) the share of people employed by smes. in the way similar to the previous indicator, its growth is benefi cial for regional economic security. we apply the following formula to calculate it: 100%. the share the number of people of sme employees employed the workforce by smes number in the region =∫ (1) d) the turnover of smes. an increase in the turnover of smes shows that the needs of the regional population for products and services are fully (or to the fullest extent possible) satisfi ed and that the contribution of smes to the grp is increasing; e) the share of sme turnover in the grp. an increase in the share of sme turnover indicates an increase in the grp per capita. according to some experts, in order to make businesses and the region competitive and to achieve the necessary level of economic security, the share of sme turnover must be 60%. we apply the following formula to calculate it: 100%. the share of sme sme turnover turnover in the grp grp =∫ (2) f ) the total amount of tax paid by smes. an increase in the total amount of taxes paid by smes also refl ects improved economic security in the region; g) funds spent on sme support from the federal and regional budgets. a decrease in the amount of funds spent on sme support is detrimental to sme development as some of the businesses would then fi nd themselves struggling to survive; h) the number of recipients of fi nancial support, which include both non-repayable subsidies and grants) and repayable assistance (guarantees, microloans, subsidized loans). an increase in this indicator should enhance entrepreneurial activity (the number of smes, the number of employees in smes, sme turnover, and so on); i) the number of recipients of non-fi nancial support, which includes consulting, training, and so on. th is kind of support helps entrepreneurs deal with the lack of the relevant skills and knowledge. a competent entrepreneur is crucial for the success of his or her business and for ensuring economic security of the region; k) the number of jobs created by support recipients. an increase in the number of jobs shows the effi ciency of support programs, which in the long run aff ects the region’s economic performance and economic security; l) capital investment. a business can grow if it receives enough investment, which allows it to 124 www.r-economy.ru r-ecomony, 2018, 4(3), 121–129 doi: 10.15826/recon.2018.4.3.017 online issn 2412-0731 modernize its equipment and production facilities and launch new product lines. th rough capital investment smes enhance the quality of their production and services, which positively aff ects the consumer demand. 2. qualitative indicators: if the value of an indicator is high, the region scores 10; if low (unsatisfactory), 0: a) th e region’s sme support infrastructure is evaluated by looking at the number of business support organizations. development and improvement of the sme support infrastructure shows the level of regional economic security; b) effi ciency of sme support programs is evaluated by comparing indicator values with the total amount of spending on sme support in the region (state programs realized on diff erent levels). to analyze the region’s performance in this indicator we need the data provided by the program implementation reports. if 80–100% of the program’s objectives and targets are met, then the region scores 10; if 50–79%, 5; and if less than 50%, 0. c) red tape and administrative barriers. complexity of the procedure of registration or re-registration can prove to be a serious impediment to the development of smes discouraging people from starting up a new business. th e more complex these procedures are, the harder it is to start a business, which causes a decline in the number of sme turnover in the grp and is detrimental for economic security and vice versa, the simpler the procedure is, the higher the region scores in this indicator; d) the level of entrepreneurial activity. th e growing number of people willing to start their own business means that more new companies will be created in the region and that their contributions to the region’s economic security will be more substantial; e) social attitudes towards entrepreneurship. if local inhabitants demonstrate a positive attitude towards private business, it is benefi cial for the socio-economic and political situation in the region. f ) access to information about the market and its resources, the available production facilities and equipment is vital for the success of a business. if entrepreneurs are well-informed about the available resources, they have more opportunities to contribute to economic development and economic security of the region. g) opportunities for sme development. th is indicator corresponds to the region’s attractiveness for investment and the overall level of economic activity. th us, our methodology comprises eighteen indicators: 11 quantitative and 7 qualitative. in each indicator, the region can score from 0 to 10. th e maximum total score is 180; the minimum, 0. ranking scores: a) the score of 121–180 corresponds to a ranking or a high level of economic security. th e main indicators of sme development show positive dynamics; there is a growth in the number of local businesses. th e contribution of smes to the grp is increasing as new jobs are created and businesses pay more taxes to the budget. th e region is in a riskfree zone. b) the score of 61–120 corresponds to b ranking, which is a medium (acceptable) level of economic security. th e main indicators of sme development remain stable and may show insignifi cant (positive or negative) changes. smes are enjoying sustainable growth; the state support is effi cient although not to the fullest extent. th e region is thus in the zone of acceptable risk, which should be monitored in case the situation deteriorates. c) the score of 0–60 corresponds to c ranking, which is a low (disastrous) level of economic security. th e main indicators of sme development show negative dynamics: enterprises shut down, their turnover falls and so is the number of their employees. th e production of smes is no longer in demand. th e sme sector is in recession and support measures are ineff ective. th e region is subject to severe risk, which requires the authorities to take urgent measures to lower the risk level. results let us now look at the level of economic security in sverdlovsk region in 2016 by focusing on sme development indicators. th e scores for each indicator are shown in table 2. th e exponential growth in the turnover of smes in 2016 in comparison with 2015 was determined by the actual turnover growth but also by the changes in the criteria of classifying businesses according to their size and annual revenues (see the decree of the government of the russian federation no 702 of 13.07. 2015). th e workforce number in sverdlovsk region in 2015 was 2,293.1 thousand people and in 2016, 2,230.1 thousand. th us, by applying formula (1), we have calculated that the share of people employed in smes in the region was 18.8% in 2015 and 19.6% in 2016 of the total workforce. r-ecomony, 2018, 4(3), 121–129 doi: 10.15826/recon.2018.4.3.017 125 www.r-economy.ru online issn 2412-0731 th e grp in sverdlovsk region in 2015 was 1,822.8 billion roubles and in 2016, 1,978.1 billion. by applying formula (1), we can calculate that the sme turnover accounted for 60.2% in 2015 and 73.4% in 2016. for a region to be competitive, this value should exceed 60%. th e state sme support program is a part of the subprogram impetus for business of the state program enhancement of sverdlovsk region’s attractiveness for investment until 2024 approved by the decree no 1002-пп of 17.11.2014 of the government of sverdlovsk region. federal spending cuts caused cuts in fi nancial support for sme development. sverdlovsk region enjoys a well-developed multi-level infrastructure for sme support. th e core of this infrastructure is sverdlovsk regional foundation for business support, created in 2002. th erefore, the region scores high in this indicator – 10. th e effi ciency of sme support programs in ekaterinburg was 87%, which means that the region is quite successful in this indicator and scores 10. analytical centre expert-ural has studied the current state and problems of sme development in sverdlovsk region and found that only 11.8% of entrepreneurs surveyed complained about regulatory and administrative barriers, in particular the complicated procedure of registration and re-registration. since the registration procedure is neither simple nor fast, in this indicator the region scored only 5. as for the level of entrepreneurial activity, the introduction of a tax holiday in the region has proven to be effi cient (see the law on setting tax rates and the introduction of simplifi ed tax compliance procedures for specifi c categories of tax payers in sverdlovsk region). not only did this measure stimulate entrepreneurial activity but it also led to the creation of new jobs, according to the data provided by the press service of the region’s legislative assembly. recent studies have shown that the popularity of entrepreneurship has been increasing among local inhabitants. potential businessmen are able to receive timely and quality access to information about the sme support system in the region. th ere is also a complex of measures being realized to stimulate youth entrepreneurship, for example, career guidance services and entrepreneurial training. as for the access to information about the market, its resources, production facilities and equipment, it does not seem to be a serious problem for regional entrepreneurs. according to the study of expert-ural, the majority of business managers (58.3%) are well informed about the market resources. th e information is provided through on-line sources, governmental agencies and municipal services. th e key factors contributing to the development of smes in sverdlovsk region are the internal market, large enterprises, and comparatively high purchasing power. in expert ra ranking, sverdlovsk region has been classifi ed as having a high investment potential combined with the moderate level of risk. entrepreneurs themselves evaluate the economic situation in their target markets until 2020 the following way: 48.6%, as table 2 quantitative indicators of economic security in sverdlovsk region indicator 2015 2016 absolute change score number of smes 8,589 4,601 –3,988 0 number of employees in smes (ths people) 233.01 134.26 –98.75 0 share of employees in smes (%) 10.16 6.02 –4.14 5 turnover of smes (bln rbs) 546.55 530.32 –16.23 5 share of sme turnover in the grp (%) 29.98 26.81 –3.14 5 total amount of tax paid by smes, ths rbs 23,952,263 26,536,719 +2,584,456 10 funds spent on sme support (from federal and regional budgets) (mln rbs) 815.3 640.7 –174.6 0 number of fi nancial support recipients 744 922 +178 10 number of non-fi nancial support recipients 10,352 8,665 –1,687 0 number of jobs created by support recipients 2,532 2,438 –94 5 capital investment (mln rbs) 9,335.5 7,172.4 –2,163.1 0 total score 40 source: based on the data of sverdlovsk regional business support foundation. retrieved from https://sofp.ru/ 126 www.r-economy.ru r-ecomony, 2018, 4(3), 121–129 doi: 10.15826/recon.2018.4.3.017 online issn 2412-0731 quite favourable; 36.3%, as favourable (the data of expert-ural). th us, in this indicator the region scores 10. th e total region score, both in qualitative and quantitative indicators, is 100. in 2016, sverdlovsk region ranked in the category b, that is, the medium (acceptable) level of economic security. th e values of the main sme-related indicators remained virtually unchanged, that is, the negative/ positive changes were insignifi cant. even though the support programs are not fully eff ective, they manage to provide stable sme development and the region is in the zone of acceptable risk. even with an insignifi cant improvement in the sme-related indicator values the region is likely to go up in the ranking by reaching a category or a high level of economic security. table 3 shows qualitative indicators used for evaluation of economic security in sverdlovsk, chelyabinsk, kurgan and tyumen regions. th e strategy of socio-economic development of the ural federal district until 2020 considers smes as one of the key instruments for using human, innovation and investment potential to raise the living standards and ensure sustainable development of this area. table 4 shows quantitative indicators of economic security in chelyabinsk, kurgan and tyumen regions. we analyzed the offi cial statistical data for the federal and regional levels and implementation reports for state sme support programs. according to rosstat’s data on the workforce in chelyabinsk region, in 2015 there were 1,856.9 thousand people and in 2016, 1,850.2 thousand. in kurgan region, in 2015, 424.6 thousand and in 2016, 411 thousand. in tyumen region, in 2015, 1,934.1 thousand people and in 2016, 1,956.6. by applying formula (1), we can calculate the share of employees in regional smes from the total number of workforce. according to rosstat’s data, in 2015, the grp in chelyabinsk region was 1,209.2 billion roubles; in 2016, 1,260.7 billion. in kurgan region, the grp in 2015 was 179.4 billion roubles and in 2016, 193.9 billion. in tyumen region, in 2015, the grp was 5,851.6 billion roubles and in 2016, 5,922.1 billion. by applying formula (2), we can calculate the share of the sme turnover in the grp of these regions. since 2009, a sme support foundation has been operating in chelyabinsk region. th e sme support infrastructure in this region also includes the regional integrated centre; the state-funded innovation business incubator of chelyabinsk region, the foundation for industrial development of chelyabinsk region, and the engineering centre of chelyabinsk region. in 2017, an organization called business territory was created that united all the existing sme support structures. th us, we can conclude that chelyabinsk region has a well-developed sme support infrastructure and it scores 10 in this indicator. kurgan region has a guarantee fund and a microfi nance fund as well as organizations for non-fi nancial support of smes – four business incubators, a techno-park, kurgan regional export support centre, centre for youth innovation, centre for cluster development of kurgan region, and municipal business consulting centres. th erefore, kurgan region also scores 10 in this indicator. tyumen region has the following sme infrastructure support organizations: foundation investment agency of tyumen region; a microfi nance fund; a guarantee fund; centre for entretable 3 qualitative indicators of economic security in ural regions in 2016 indicator score sverdlovsk region chelyabinsk region kurgan region tyumen region sme support infrastructure 10 10 10 10 effi ciency of sme support programs 10 10 5 10 red tape (registration and re-registration of businesses) 5 5 5 10 level of entrepreneurial activity 10 5 5 10 social attitudes towards entrepreneurship in the region 10 5 5 5 accessibility of information about the market, its potential and resources for development; about the available production facilities and equipment 5 5 5 5 potential for further sme development 10 10 10 5 total score 60 50 45 55 note: based on expert evaluations. r-ecomony, 2018, 4(3), 121–129 doi: 10.15826/recon.2018.4.3.017 127 www.r-economy.ru online issn 2412-0731 preneurship support; centre for coordination of export-oriented sme support; state-funded regional business incubator, which has offi ces in tyumen, tobolsk and ishim; techno-park western siberian innovation centre of oil and gas. th us, tyumen region also scores 10. our calculations have shown that in 2016, the effi ciency of the subprogram sme support and development in chelyabinsk region in 2016–2019, which is a part of the larger state program economic development and innovative economy of chelyabinsk region in 2016–2019, was 84% (0.844). as for the implementation of the sme support model, tyumen region is the top perfromed by reaching the level of 98%. according to the sme organization opora russia, in chelyabinsk region starting a new business is diffi cult rather than easy while the situation in tyumen region is the opposite: it is easy rather than diffi cult. both tyumen and chelybinsk regions have created favourable conditions for business development, which means that they both score 10 in this indicator. as for kurgan region, it scores lower in all the rankings. table 4 quantitative indicators of economic security in chelyabinsk, kurgan, and tyumen regions indicator chelyabinsk region kurgan region tyumen region 2015 2016 absolute change score 2015 2016 absolute change score 2015 2016 absolute change score number of smes 4,185 3,142 –1,043 0 1,111 913 –198 0 4,185 5,804 +1,619 10 number of employees in smes (ths people) 135.61 124.44 –11.17 0 38.46 34.94 –3.52 5 135.61 164.04 +28.43 10 share of the population employed in regional smes (%) 7.3 6.7 –0.6 5 9.1 8.5 –0.6 5 7.0 8.4 +1.4 5 turnover of small enterprises (bln rbs) 312.80 308.83 –3.97 0 44.76 43.02 –1.74 0 312.80 547.82 +235.02 10 share of sme turnover in the grp (%) 25.9 24.5 –1.4 5 24.9 22.2 –2.7 5 5.3 9.3 +4 10 total amount of tax paid by smes, mln rbs 15,863.5 15,612.8 –250.7 0 2,489.5 2,612.5 +123 5 112,769.1 124,455.7 +11,686.6 10 funds spent on sme support (from federal and regional budgets) (mln rbs) 411.1 302.5 –108.6 0 301.9 114.8 –187.1 0 319.8 172.0 –147.8 0 number of fi nancial support recipients 96 120 +24 10 3,968 1,245 –2,723 0 – – – – number of non-fi nancial support recipients 18,230 18,250 +20 5 – – – – 5,191 – – – jobs created by recipients of sme support 120 363 +243 10 2,100 2,800 +700 10 1,204 733 –471 0 capital investment (bln rbs) 8306.4 5604.3 –2702.1 0 1860.6 1495.2 –365.4 0 1641.5 1753.0 +111.5 5 total score 35 30 60 source: based on the data of the report on the implementation of state program comprehensive support for sme development in chelyabinsk region in 2015–2017 as of 2015; report on the implementation of state program economic development and innovation economy of chelyabinsk region in 2016–2019 as of 2016; report on the implementation of state program in tyumen region development of smes and the knowledge-intensive sphere until 2020; the decree of 16 june 2015 no 3817 on the information of tyumen government about the implementation of the law on sme development in tyumen region; annual report on the implementation and effi ciency evaluation of state program in kurgan region on sme development and support in kurgan region in 2014–2020 as of 2016; report on the performance results and key activity areas of the economic development department of kurgan region in 2018–2020 as of 2017; no 1-нм form report on taxies and levies paid to the budget system of the russian federation (federal tax service). 128 www.r-economy.ru r-ecomony, 2018, 4(3), 121–129 doi: 10.15826/recon.2018.4.3.017 online issn 2412-0731 th e business information agency rankings and news ranks tyumen higher than chelyabinsk and kurgan, which ranked almost identically, in terms of entrepreneurial activity. th us, tyumen region scores 10 in this indicator while chelyabinsk and kurgan, only 5. conclusion th e economic security ranking of the ural federal district looks the following way: chelyabinsk region, 85; kurgan region, 75; and tyumen region, 115. all the regions in our analysis were classifi ed as ‘b’ regions, which means that they have a medium (acceptable) level of economic security. th e risk level is also acceptable but it should be under constant monitoring. th e development of smes in these regions is stable and the state support in this sphere is effi cient. th e ranking of the regions according to their economic security levels looks the following way: 1. tyumen region (115). 2. sverdlovsk region (100). 3. chelyabinsk region (85). 4. kurgan region (75). on average, the ural federal district scores 92.5 and is characterized by a medium (acceptable) level of economic security. tyumen region, which also includes the khanty-mansiysk autonomous district and the yamal-nenets autonomous district, is the top performer in this respect. in this region, purchasing power is quite high and the same can be said about the factor endowments. risks are comparatively low and are compensated for by the region’s signifi cant economic potential. sverdlovsk region enjoys such advantages as a well-developed internal market, large enterprises and comparatively high purchasing power of the population. th ese are the key factors contributing to the development of smes in this region. improved indicators in sme development will signify that the region has achieved a higher level of economic security and will allow sverdlovsk region to rise in the ranking. as for chelyabinsk region, there is a whole set of problems that need to be addressed in order to enable the region to make any short-term improvements in its economic security. moreover, both sverdlovsk and chelyabinsk regions are heavily dependent on federal subsidies. kurgan region is characterized by a rather low level of development of local market outlets, of the factor endowments and, therefore, has to deal with considerable risks. references 1. tatarkin, a. i., & kuklin a. a. 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(2016). retaining winners: can policy boost high-growth entrepreneurship? research policy, 45(1), 42–55. doi: 10.1016/j.respol.2015.06.002 11.  bondonio, d., geenbaum, r.t. (2014). revitalizing regional economies through enterprise support policies: an impact evaluation of multiple instruments. european urban and regional studies, 21(1), 79–103. doi: 10.1177/0969776411432986 12. kuril, j. (2018). protection of the state and society: public administration and public (state) service. journal of security and sustainability, 7(3), 409–416. doi: 10.9770/jssi.2018.7.3(3) 13. korchagina, i. v. (2016). characteristics of regional economic policy to develop clusters of small-size enterprises. strategia ustoychivogo razvitia regionov rossii, 35, 113–117. 14. fotopoulos, g., & storey, d. j. (2018). public policies to enhance regional entrepreneurship: another programme failing to deliver? small business economics, doi: 10.1007/s11187-018-0021-9 15. huggins, r., prokop, d., & th ompson, p. (2017). entrepreneurship and the determinants of firm survival within regions: human capital, growth motivation and locational conditions. entrepreneurship and regional development, 29(3–4), 357–389. doi: 10.1080/08985626.2016.1271830 16. aidis, r. (2005). institutional barriers to smalland medium-sized enterprise operations in transition countries. small business economics, 25(4), 305–317. doi: 10.1007/s11187-003-6463-7 17. bateman, m. (2000). neo-liberalism, sme development and the role of business support centers in the transition economies of central and eastern europe. small business economics, 14(4), 275–298. doi: 10.1023/a:1008170805013 18. nguyen, b., mickiewitcz, t., & du, j. (2018). local governance and business performance in vietnam: the transaction costs’ perspective. regional studies, 52(4), 542–557. information about the authors natalya yu. vlasova – professor, department of state and municipal management, ural state economic university (62/45, 8 marta/narodnoi voli st., 620144 ekaterinburg, russia); e-mail: nat-vlasova@yandex.ru. olesya o. kalganova – master student, department of state and municipal management, ural state economic university (62/45, 8 marta/narodnoi voli st., 620144 ekaterinburg, russia). r-ecomony, 2018, 4(3), 105–114 doi: 10.15826/recon.2018.4.3.015 105 www.r-economy.ru online issn 2412-0731 original paper doi: 10.15826/recon.2018.4.3.015 the danube inland waterway transport and its role in serbia’s economic development jelena milanković jovanov , dragoslav pavić, jasmina đorđević, aleksandra dragin, smiljana đukičin vučković, minucsér mészáros university of novi sad; novi sad, serbia; e-mail: milankovicjovanov@gmail.com abstract th e danube river waterway, i.e. the pan-european corridor vii, is considered as one of the most signifi cant transport corridors in europe. it runs through ten countries, including serbia (the serbian part of the river is 588 km long), which is why it is one of serbia’s priorities to develop inland water transport. th e system of waterways provides a viable alternative to roads and rail systems. moreover, it is crucial for regional development. th e danube river off ers excellent opportunities for freight, passenger and tourist inland water transportation. however, the navigability potential of the danube river still remains largely underrealized in serbia: despite the high quality of waterways, inland water transport accounts for only 4.7% of the total transport. th is paper deals with the advantages of inland navigation and the major characteristics of the danube waterway in serbia. in serbia, the danube is mainly used for freight and passenger transportation and for the development of nautical tourism. th ere are a number of important projects that are currently being implemented in serbia, such as the construction of new port facilities and marinas. th e paper also discusses the negative factors impeding regional development in the sphere of waterways and water transport in serbia, primarily the lack of funding for maintenance and improvement of the river’s navigability. keywords danube, inland waterway, serbia, transport, sustainable regional development, tourism acknowledgments th is research was supported by the provincial secretariat for science and technological development, ecap vojvodina (project 114-451-2465/2018-02). th is paper is based on phd thesis danube as a transport artery and axis of development in the republic of serbia defended by jelena milanković jovanov at the department of geography, tourism and hotel management in 2015 and phd thesis cruising along the corridor vii and nautical tourism in serbia defended by aleksandra dragin at the department of geography, tourism and hotel management in 2008. for citation milanković jovanov j., pavić d., đorđević j., dragin a., đukičin vučković s., & mészáros, m. (2018) th e danube inland waterway transport and its role in serbia’s economic development. r-economy, 4(3), 105–114. doi: 10.15826/recon.2018.4.3.015 дунайский национальный водный транспорт и его роль в экономическом развитии сербии е. миланкович , д. павич, ж. джордевич, а. драгин, с. джукичин вучкович, м. месарош нови-садский университет, нови-сад, сербия; e-mail: milankovicjovanov@gmail.com резюме дунайский водный путь, т. е. паневропейский коридор vii, считается одним из самых значительных транспортных коридоров в европе. он проходит через десять стран, включая сербию (сербская часть реки составляет 588 км), и поэтому является одним из приоритетов сербии по развитию внутреннего водного транспорта. система водных путей является жизнеспособной альтернативой дорожным и железнодорожным системам. более того, это важно для регионального развития. река дунай предлагает прекрасные возможности для грузовых, пассажирских и туристических внутренних водных перевозок. однако потенциал судоходства в реке дунай по-прежнему реализован в сербии не полностью: несмотря на высокое качество водных путей, внутренний водный транспорт составляет лишь 4,7% от общего объема перевозок. в этом документе рассматриваются преимущества внутреннего судоходства и основные характеристики водного пути дуная в сербии. в сербии дунай в основном используется для грузовых и пассажирских перевозок и для развития водного туризма. в настоящее время в сербии реализуется ряд важных проектов, таких как строительство новых портовых сооружений и пристаней для яхт. в статье также обсуждаются негативные факторы, препятствующие региональному развитию в сфере водных путей и водного транспорта в сербии, в первую очередь отсутствие финансирования для поддержания и улучшения судоходства реки. ключевые слова дунай, внутренний водный путь, сербия, транспорт, устойчивое региональное развитие, туризм благодарности исследование поддержано провинциальным секретариатом по науке и технологическому развитию, ecap vojvodina (проект 114-451-2465 / 2018-02). статья основана на кандидатских диссертациях, защищенных на кафедре географии, туризма и гостиничного менеджмента е. миланкович йованов «дунай как транспортная артерия и ось развития в республике сербия» в 2015 г. и а. драгиной «крейсерская по коридору vii и морской туризм в сербии» в 2008 г. для цитирования milanković jovanov j., pavić d., đorđević j., dragin a., đukičin vučković s., & mészáros, m. (2018) th e danube inland waterway transport and its role in serbia’s economic development. r-economy, 4(3), 105–114. doi: 10.15826/recon.2018.4.3.015 106 www.r-economy.ru r-ecomony, 2018, 4(3), 105–114 doi: 10.15826/recon.2018.4.3.015 online issn 2412-0731 introduction th e danube river has always played a significant role in human geography, serving men as a pathway in migration, trade, and war. nowadays the danube is a popular transport route connecting central and eastern europe. th e river fl ows through the regions of intensive industrial and agricultural production, densely populated areas with substantial development potential. prior to the construction of the suez canal, the role of the danube had been extremely important due to the fact that the shortest route connecting europe and asia went through the black sea. over sixty of the danube’s tributaries are navigable, which contributes to the transportation importance of the river. th e role of the danube was enhanced by the construction of the main-danube canal, which connects the northern sea and the black sea and creates a 3,500 km waterway [1]. th e republic of serbia lies at the crossroads of the most important pan-european traffi c routes, such as the road and railway corridor x and waterway corridor vii (the danube navigable corridor), which has a great signifi cance for the country as it links north and south, east and west. th e danube with the total length of 1,600 km is the backbone of inland waterways in serbia [2]. in addition, there are the danube’s large tributaries, the tisza and the sava rivers, and the navigable canals within the hydrosystem danube-tisza-danube. all these navigable routes are connected to the danube river and are a part of the trans-european corridor vii waterway from rotterdam to sulina. high population density also refl ects the importance of the upper danube basin in serbia. th e total population in municipalities located near the danube river is 2,013,646 people or 28.8% of the total population of serbia. population density in this area is 150 inhabitants per km², which is twice as many as the country’s average (80.5 inhabitants per km²)1. th e danube river is crucial for the development of trade, services and tourism in serbia [2; 3]. th e serbian part of the danube is navigable and is actively used for freight transportation. th e level of the river traffi c varies from country to country and depends on the political and economic situation. political stability and closer economic ties have had a positive impact on the development of the transport system in former yugoslav republics such as serbia and croatia. for instance, there has been a tenfold 1 republic statistical offi ce. 2012. census of population, households and dwellings in the republic of serbia, 2011, vol. 2, age and gender, data by settlements, belgrade. increase in freight traffi c on the danube as compared to twenty years ago. yet, the transport capacity of the river is still underused, especially we if compare it to that of the rhine, which is ten times higher2 [4]. in the serbian part of the danube, the lack of investment into the maintenance of waterways and the lack of careful planning has led to deterioration of river and canal navigation in such spheres as freight and passenger transportation and nautical tourism. inland navigation through the danube waterway in europe and serbia th e danube has a great signifi cance for all the countries which it fl ows through: germany (14.54%), austria (8.82%), slovakia (4.34%), hungary (10.49%), croatia (3.47%), serbia (14.82%), romania (27.1%), bulgaria (11.87%), moldova (0.01%) and ukraine (4.54%). 1,070.9 km of the river (or 37% of its total length) are state borders. four countries: croatia, bulgaria, moldova and ukraine are positioned on only one riverbank3. th ere are numerous ways to use the danube river for freight transport, hydropower generation, industrial and residential water supplies, irrigation, and fi shing. navigation and freight transport play the greatest role in economic development, especially aft er the construction of the canals such as the danube-black sea canal and the main-danube canal. th e water of the danube is used in industry, but also in agriculture, especially for irrigation4. river transport has a number of advantages such as cost eff ectiveness and profitability: as jean pierre rissoan (1994) said, “river-sea transport pollutes less and can also provide an alternative to congested roads and railways. door-to-door journeys by river-sea transport seem destined for future growth” [5]. according to the economic commission for europe (1996; 2011), some of the advantages of inland waterway transportation include cost eff ectiveness; the lowest propulsion energy consumption; navigation safety; reduced pollution, and so on5. 2 danube navigation statistic for 2009–2010; encyclopedia britannica. retrieved from http://www.britannica.com/ 3 danube commission. retrieved from http://www.danubecommission.org/ 4 encyclopedia britannica. retrieved from http://www. britannica.com/ 5 th e white paper on trends in and development of inland navigation and its infrastructure. retrieved from www. unece.org/trans/doc/fi naldocs/sc3/trans-sc3-138e.pdf; th e white paper on effi cient and sustainable inland water transport in europe. retrieved from http://www.unece.org/fi leadmin/dam/trans/main/sc3/publications/whitepaper_inland_ water_transport_2011e.pdf r-ecomony, 2018, 4(3), 105–114 doi: 10.15826/recon.2018.4.3.015 107 www.r-economy.ru online issn 2412-0731 th e serbian part of the danube is a typical lowland river 400–1,200 m wide, approximately 19 m deep with the water speed of 3.5–4.0 km/h. prior to the building of the hydroelectric power plant and navigation system djerdap, the danube had had the characteristics of a mountain river (approximate speed of 18 km/h) in djerdap sector. th e construction of the above-mentioned system signifi cantly reduced the river’s speed to only 0.3 m/s or 1.1 km/h. th e danube is the most important element of the inland waterway system in serbia. with the sava and the tisa rivers, it creates a network of waterways 1,680 km long [2]. serbia was one of the seven countries that established the danube commission in 1948, thus accepting the obligation to maintain and improve navigation conditions of the river. one of the most signifi cant recommendations of the danube commission is to assure the minimum depths of 2.5 m and fairway widths of 180 m at low water levels. th e danube’s section in serbia (588 km) is navigable for all types of river ships; it may be divided into four sectors, corresponding to two waterway classes (european conference of ministers of transport, 1992)6: – the sector between the hungarian border (km 1433 + 000) and belgrade (km 1166 + 000) has hydrologic and hydraulic regime characteristics; – the sector between belgrade (km 1166 + 000) and the dam djerdap i (km 942 + 000) is slowly moving canalled water and corresponds to the waterway class vii; – the sector between the dam djerdap i (km 942 + 000) and djerdap ii (km 863 + 550) was also canalled corresponding to the highest waterway class vii; – downstream the dam djerdap ii (km 863 + 550) up to the bulgarian border (km 845 + 000), the danube’s course is regulated by various constructions. th e maximum vessel dimensions are similar to those in the upstream sectors. however, 6 european conference of ministers of transport (1992). resolution no. 92/2 on new classifi cation of inland waterways (report). retrieved from http://www.internationaltransportforum.org/intorg/acquis/wat19922e.pdf figure 1. th e danube river in serbia (corridor vii) source: base map source (global map v2). retrieved from http://www.iscgm.org/gmd/ 108 www.r-economy.ru r-ecomony, 2018, 4(3), 105–114 doi: 10.15826/recon.2018.4.3.015 online issn 2412-0731 there is a serious threat for the navigation as there are about 200 sunken wwii ships, some of them still loaded with explosive substances, which also endangers vib waterway class in this sector. fleet according to the danube navigation statistics, from 1962 (3,142 vessels) to 1990 (5,754 vessels), the fl eet size grew steadily. in 2000, there was a considerable decrease in the number of vessels. aft erwards, the number of vessels fl uctuated insignifi cantly (figure 2). however, despite the fl uctuations, there was a general upward trend in the number of vessels from 1962 to 2013; the ships’ loading capacity increased as well. 2015 2014 2013 2009 2005 2000 1990 1980 1970 1962 0 1000 2000 3000 4000 5000 6000 figure 2. th e total number of vessels of the danube countries (1962–2015) source: danube navigation statistics for 2009–2010, 2012–2013, 2014–2015 most vessels in the danube fl eet are used in germany, austria, romania and ukraine. th e number of vessels in serbia, croatia and moldavia is 5% lower than the total number of vessels on the danube. regarding the tonnage of ships on the danube, romania ranks fi rst with its share of 40%, then follows ukraine with 21%, serbia with 13%, whereas croatia and moldova have the smallest shares, 2.5% and 1% respectively7. th e priority areas for the development of the danube fl eet are as follows8: modernisa7 european conference of ministers of transport (1992) resolution no. 92/2 on new classifi cation of inland waterways (report). retrieved from http://www.internationaltransportforum.org/intorg/acquis/wat19922e.pdf; inventory of data on the strategic inland waterway projects. 2011. platina. retrieved from http://www.naiades.info/repository/public/ article_downloads/file/422_d5-5_24-03-2011_(final_web_ version).pdf 8 th e white paper on effi cient and sustainable inland water transport in europe. retrieved from http://www.unece.org/ fi leadmin/dam/trans/main/sc3/publications/whitepaper_inland_water_transport_2011e.pdf tion of the fl eet; introduction of new logistics systems; implementation of the river information services and introduction of new transport technologies. table 1 fleet, its structure and main types of vessels in serbia in 2015  indicator motorized vessels tugs pusher vessels towed barges pushed barges total number of units 97 94 65   228 180 664 total power (kw) 37,929 24,768 55,388 – – 118,085 total carrying capacity (t) 88,066 – – 294,001 169,101 551,168 source: danube navigation statistics for 2014–2015. according to the danube navigation statistics for 2014 and 2015, the total carrying capacity of vessels in serbia is 551,168 tonnes, whereas the total power is 118,085 kw. port infrastructure according to the danube commission data, there are 91 commercial ports on the danube river and its tributaries, out of which 11 ports are situated in serbia. th ere are 8 international ports in the serbian sector of the danube: apatin, bezdan, bačka palanka, novi sad, beograd, pančevo, smederevo and prahovo, the remaining three national ports are titel, veliko gradište and kladovo. according to the danube navigation statistics for 2014–2015, the port pančevo is one of the largest ports on the danube, belonging to the group of ports with the annual cargo turnover of more than 1 million tonnes (figure 3). ports in serbia have signifi cant capacity but they are also technologically outdated, due to the lack of fi nancial support for their maintenance and development. th e usage of port capacities reaches only 30% on average due to the lack of transhipment goods. low capacity utilisation occurs for several reasons, such as the outdated technical equipment in ports; fl awed systems for combined and intermodal transport; and declining industrial production in serbia. th e development of intermodal transport and the promotion of combined transport are crucial for future development of transport in europe [6]. most ports in serbia are connected to the main rail and road traffi c routes in the country. only the ports in pančevo and r-ecomony, 2018, 4(3), 105–114 doi: 10.15826/recon.2018.4.3.015 109 www.r-economy.ru online issn 2412-0731 belgrade have container terminals and none of the ports have ro-ro terminals, which is a serious drawback. ro-ro transport and ro-ro terminals could be used not only for domestic lorry carriers, but also for foreign ones (from turkey, bulgaria, and macedonia), which would make it possible to transport lorries by ship and thus cut transportation costs. th e project for constructing multimodal facilities in port dunav in pančevo is already well under way. th is project has turned out to be successful as it requires minimum investment (primary infrastructure, ground preparation)9. in addition to commercial ports, in line with the latest trends in nautical tourism, a new marina has recently been built in apatin, which is the fi rst international marina on the danube in serbia, out of the seventeen planned, and it off ers berths for 400 (120 for large yachts) vessels and dry-docking covering the area of 2,500 m². the development of freight and passenger transportation and nautical tourism in serbia until the mid-twentieth century, the danube waterway in serbia was primarily used for trans9 regional development strategy of the republic of serbia for the period 2007–2012 (2005). government of republic of serbia, belgrade. portation of passengers and goods. th e development of road and railway transport somewhat reduced the passenger traffi c on the danube, although this trend was partially compensated for by diff erent forms of nautical tourism. nowadays, this waterway is mostly used for transportation of goods and tourism. heavy load transport despite the favourable conditions for the operation of inland waterway transport in serbia, there are a number of impediments to its development such as the bad infrastructure. the most important ports are belgrade, pančevo, smedervo and prahovo and they enjoy a very good connection with surface roads. ports belgrade and pančevo have container terminals. according to the statistical offi ce of the republic of serbia, the tonnage carried via the serbian part of the danube abruptly decreased aft er 1990. th e period of decline coincided with the period of political instability and economic recession in the country. aft erwards, there was a period of growth, which reached its peak in 2005. since then, there has been a decline and this indicator’s values have never got back to the 2005 level (figure 4). regensburg (de) vienna (at) budapest (hu) pančevo (ps) oriahova (bg) svishtov (bg) tulcea (ro) galaţi (ro) izmail (ua) 0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 2015 2014 2013 figure 3. major ports on the danube with cargo turnover of more than 1 mln.t (2013; 2014; 2015) source: danube navigation statistics for 2012–2013 and 2014–2015 110 www.r-economy.ru r-ecomony, 2018, 4(3), 105–114 doi: 10.15826/recon.2018.4.3.015 online issn 2412-0731 7000 6000 5000 4000 3000 2000 1000 0 19 95 19 96 19 97 19 98 19 99 20 00 20 01 20 02 20 03 20 04 20 05 20 06 20 07 20 08 20 09 20 10 20 11 20 12 20 13 20 14 20 15 figure 4. th e total tonnage carried on the danube in serbia in 1995–2015 (thousands of tons) source: statistical offi ce of the republic of serbia. transport, storage and connections bulletin 2004, 2010 and 2016 out of the total tonne-kilometres handled in inland waterways in serbia, the danube accounts for 97%. inland traffi c makes up over 50% of goods turnover; transit only has a small share, while the transport of goods between foreign ports is almost negligent (see figure 5). th e goods transported via the danube are very diverse: iron ore (25.6%); processed and unprocessed metals (22.7%); coal (9.1%); oil and oil derivatives (8.5%); cement (7.5%); grain goods (6%); processed metals of metal industry (5.4%); wood (4.3%); coloured metals ores (3%); fi nished metal products (2.7%); and agricultural goods such as fodder (1.6%) [7]. th e inventory of data on the strategic inland waterway projects (2011)10 10 inventory of data on the strategic inland waterway projects. 2011. platina. retrieved from http://www.naiades. info/repository/public/article_downloads/fi le/422_d5-5_2403-2011_(fi nal_web_version).pdf demonstrates that the transportation of agricultural, industrial, chemical and metal products will continue to grow due to the improvement in the infrastructure between budapest and belgrade, between romania and bulgaria and in the area of vienna. th e increase is to be expected in east europe, including serbia. passenger transport th e danube holds a lot of potential as a waterway for passenger transport. th is potential, however, is largely underused, as only a few countries in the danube region have strategies for water transport development. according to the data of the danube commission, the highest number of registered passenger ships was recorded in hungary, germany, ukraine and romania in 2010. th ese are also the leading countries in terms of domestic passenger-kilometres, whereas the largest number of international passengers is recorded in ukraine and germany. furthermore, according to the danube commission, the total passenger kilometres on the danube in all countries is 21,047 km in national transport and 22,404 km in international transport11. domestic passenger transport virtually does not exist in serbia and is mostly tourism-oriented. about seventy years ago, passenger ships were travelling along the danube not only from novi sad to sremska kamenica, but also to vienna, regensburg and constanca. hydrowing ships were running regularly between belgrade and novi sad thirty years ago. at that time, passenger ships 11 danube commission. retrieved from http://www.danubecommission.org/ 2015 2013 2011 2009 2007 2005 2003 2001 1999 1997 1995 0 10 20 30 40 50 60 70 80 90 100 inland tra�c export import transit among foreign ports figure 5. share of goods transported through the danube waterway in serbia between 1995 and 2015, % r-ecomony, 2018, 4(3), 105–114 doi: 10.15826/recon.2018.4.3.015 111 www.r-economy.ru online issn 2412-0731 were operating on the tisza river, too. small ships ran from novi sad to bečej several times a day (on the danube from novi sad to the mouth of the tisa, then on the tisa to bečej), and three times per week from belgrade to senta (on the danube from belgrade to the mouth of the tisa, then on the tisa to senta). th ere have been attempts to revive this form of transport lately. for instance, the water taxi is very popular in budapest (hungary): it runs at the speed of 50 km/h and transports passengers from southern districts to the centre and to the north of the city. similarly, there is daily transport service between regensburg, deggendorf, passau, linz and vienna12. nautical tourism nautical tourism has been developing worldwide due to the boom of cruise industry in the last four decades. th e main forms of nautical tourism include individual navigation of vessel owners, boat charter (renting of ships and sailboats) and river cruises (international tourist cruises). according to the strategy of tourism development in the republic of serbia13, nautical tourism in serbia uses the strategic potential of the danube, the leading river cruising destination in europe. furthermore, according to the same source, the main spheres for the development of nautical tourism in the country are individual navigation (this segment is mostly based on local demand); charter (this segment requires the appropriate infrastructure and is underdeveloped at the moment); and river cruising (this segment is very popular and is enjoying explosive growth). as for individual cruises on the danube, most of the vessels currently in use are old and the equipment is outdated, which explains the low demand for ship berths in marinas. th e current number of vessels used for recreational purposes on the danube in serbia is negligible (for example, in apatin it is less than ten vessels a year). it is expected that old vessels will soon be replaced by new ones and that the number of vessels will be increasing together with the development of nautical tourism in serbia. it has been estimated that the demand for ship berths in marinas on the danube (domestic vessels) is unlikely to increase by more than 20% in the following years. 12 donauschiff ahrt wurm+koeck. retrieved from http://www.donauschiff ahrt.de/en/ 13 strategy of tourism development of the republic of serbia for the period 2015–2025 (2015). ministry of traffi c, tourism and telecommunications, belgrade. th e well-equipped nautical route on the danube and the excellent off er of marinas and other tourist products in serbia are expected to attract approximately 30% of the estimated number of vessels to marinas annually. according to the study of marina network in vojvodina region, the total number of vessels using marinas is likely to reach 4,100. moreover, it is expected that vojvodina (16 of 28 municipalities on the danube in serbia) would need about 500 berths for foreign vessels in marinas on the danube by 2025. th e serbian sector of the danube has been suff ering from the lack of investment. until recently, there have not been any marinas, i.e. the nautical tourism infrastructure still leaves much to be desired. th is problem could be addressed through the reconstruction of the existing piers and ship berths, which could be converted into marinas. a case to illustrate this solution is the marina in apatin opened in 2009, which is the only serbian marina on the danube. lately, more investment has been made in pier reconstruction in belgrade and novi sad14 [8]. cruise industry, which has been growing dynamically, has a powerful impact on the world economy. cruises generate over 450,000 jobs with total salaries of about 15 billion us dollars. in 1998, the world tourist organisation described fi ve types of tourism types that would be in most demand in the next two decades: tourist cruises, cultural tourism, event-based tourism, eco-tourism and thematic tourism. th e highest increase in tourism cruises demand is expected in the danube region countries: hungary, romania, slovakia, croatia, and serbia. th e target markets are the usa, germany, france, great britain, and austria. serbia holds considerable potential for the development of nautical tourism that needs to be realized [3]. th is fact has been confi rmed by the constant increase in the number of cruise ships arriving in belgrade and other ports in serbia (figure 6). according to the data of the danube tourist commission, over 10,000 tourists cruised along the lower danube15 and about 119,000, along the middle and upper danube in 2002. by october 2004, over 22,000 tourists from cruise ships visited novi sad, over 43,000 belgrade, and 14 hadžić, o. (2005). th e growth of the cruise tourism as a chance for repositioning serbia on tourism market. (paper presented at the meeting of university of novi sad, faculty of natural science and mathematics, novi sad). 15 danube tourist commission. retrieved from http:// www.danube-river.org 112 www.r-economy.ru r-ecomony, 2018, 4(3), 105–114 doi: 10.15826/recon.2018.4.3.015 online issn 2412-0731 over 60,000, the danube delta. in 2004, the turnover on the danube was 150,000 tourists. th e data indicate signifi cant increase in the demand for cruises in the lower danube. th e number of tourists buying river cruises increased by 26.1% in 2004 (compared to 2002) (figure 6). th erefore, we can conclude that there was a dramatic increase in the demand for cruises in the lower sector of the danube [9–11]. moreover, there are two national parks located on the right bank of the danube – fruška gora and djerdap, which could potentially attract large number of visitors in the future [12; 13]. priority projects for the improvement of the danube waterway in serbia th e republic of serbia aims to improve its system of inland waterways, provide their maintenance and ensure safe navigation. th e pending law on navigation safety and ports would regulate navigation on the rivers; modernisation of ports and piers, application of river information services, and so on. th e european strategy for the danube encompasses a number of projects for the development of infrastructure, transport, logistics and tourism on the corridor vii. th e focus is on three priority areas: mobility and multimodality (road, rail, and air routes, inland waterways); promotion of sustainable energy; and promotion of culture and tourism. in line with the strategy, serbia’s is now implementing the following priority projects on the danube river16: 16 general master plan for transport in serbia. annex iii (2009). transport on inland waterways, belgrade. – major overhaul of the navigation lock at djerdap i and djerdap ii (the works on djerdap i are already in progress); – removal of world war ii sunken vessels near prahovo; – removal of the old bridge and construction of the new railway bridge in novi sad (in progress); – hydro-technical works; – implementation of the river information services (ris implementation project on the danube river in serbia, started in 2009, reached its fi nal phase). th e key projects for improvement of tourism infrastructure on the serbian part of the danube are as follows: – marina on the danube river near novi sad; – establishment of the information centre for nautical tourism and smaller information points on the danube; – pier in zemun; – marina oasa (belgrade). th eir realization would contribute to safe and effi cient navigation on the danube and would set higher ecological standards on the serbian section of the corridor vii. most of the above-mentioned projects have already been launched, except for the project for removal of sunken vessels and unexploded bombs near prahovo, which is being delayed due to the lack of funds. conclusion serbia’s location at the crossroads of the major european transport corridors (water, road, rail, and air) provides it with opportunities 600 500 400 300 200 100 0 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 figure 6. th e total annual number of river cruisers in belgrade in 2002–2015 source: offi cial data of the port of belgrade r-ecomony, 2018, 4(3), 105–114 doi: 10.15826/recon.2018.4.3.015 113 www.r-economy.ru online issn 2412-0731 for sustainable economic development, which makes the danube or the corridor vii crucial for the country’s prosperity. however, despite the advantages the danube off ers, its navigation potential remains underrealized for a number of reasons, primarily economic ones. although serbia accounts for 13% of the ship tonnage in the danube region, it’s fl eet is old and outdated and on average only 30% of the port capacities due to the lack of goods for transhipment. as serbia is currently in the process of joining the eu, it has become evident that modernization and maintenance of its fl eet are required as the country is likely to receive more foreign investment and engage in international cooperation projects. furthermore, the danube strategy has been adopted with the aim of synchronizing the activities of the danube region countries for sustainable development. improvement and stimulation of water transport development are crucial for economic prosperity of the region as water transport is a good alternative to road and rail transport, it is also energy effi cient and environmentally safe. according to the general transport master plan of the republic of serbia (2009), the aim is to increase of the share of water transport in cargo and freight transportation and to modernize the river fl eet. hence, it is extremely important to implement the system of the river information services that would cut transportation time and make transportation more cost eff ective. intermodal transport development is recognised as yet another factor contributing to sustainable economic development of serbia. th e danube in particular has several high priority projects which could fi nally improve the condition of the navigation: for example, removal of the sunken german ships and unexploded bombs left from world war ii near prahovo. another key project is the reconstruction of the ship locks djerdap i and djerdap ii and construction of a new bridge near novi sad. surprisingly, in our research we faced diffi culties when gathering data on the use of the danube inland waterways: the statistical data provided by offi cial sources are oft en inaccurate, moreover, such data are oft en hard to obtain. for instance, cruise tourists are excluded from the data on the overall tourist turnover by the statistical offi ce, although they on average spend 2–3 days in national waters. th is study has provided evidence that more attention should be devoted to trans-border cooperation in the danube region. further research is necessary into the problem of inadequate communication between border regions, particularly if such regions share renewable energy resources. references 1. štetić, s. (2007). special forms of tourism. belgrade. 2. milanković, j. (2015). danube as a transport artery and axis of development in the republic of serbia (phd thesis). novi sad: faculty of sciences, department of geography, tourism and hotel management. 3. dragin, a., jovičić, d. &  bošković, d. (2010). economic impact of cruise tourism along the pan-european corridor vii. economic research. 23(4), 127–141. doi: 10.1080/1331677x.2010.11517438 4. radmilović, z., & maraš, v. (2011). role of danube inland navigation in europe. international journal for traffi c and transport engineering, 1(1), 28–40. retrieved from http://ijtte.com/ uploads/2011-04-16/d4c8811d-9674-f24aijtte%20r01%2028-40.pdf 5. rissoan j. p. (1994). river-sea navigation in europe. journal of transport geography, 2(2), 131–142. 6. wiegmans, b. w., masurel, e. & nijkamp, p. (1999). intermodal freight terminals: an analysis of the terminal market. transportation planning & technology, 23(2), 105-128. doi: 10.1080/03081069908717643 7. mihić, s., golušin, m. & mihajlović, m. (2011). policy and promotion of sustainable inland waterway transport in europe-danube river. renewable and sustainable energy reviews, 15(4), 1801–1809. doi: 10.1016/j.rser.2010.11.033 8. dragin, a. (2010). international cruising the corridor 7. novi sad: university of novi sad, department of geography, tourism and hotel management. 9. dragin, a., dragin, v., košić, k., demirović, d., ivkov-džigurski, a. (2017). tourists motives and residents attitude towards cruisers. in: southern and eastern europe 2017: tourism and 114 www.r-economy.ru r-ecomony, 2018, 4(3), 105–114 doi: 10.15826/recon.2018.4.3.015 online issn 2412-0731 creative industries: trends and challenges: 4th international scientifi c conference, opatija, croatia, 4–6 may 2017. vol. 4 (pp. 133–144). opatija: university of rijeka, faculty of tourism and hospitality management. doi: 10.20867/tosee.04.42 10. demonja, d. (2012). th e importance of the danube strategy for tourism and culture development of the croatian danube region. geographica pannonica, 16(3), 112–125. doi: 10.5937/ geopan1203112d 11. vujko, a., & gajić, t. (2014). opportunities for tourism development and cooperation in the region by improving the quality of tourism services-the ‘danube cycle route’ case study. economic research-ekonomska istraživanja, 27(1), 847–860. doi: 10.1080/1331677x.2014.975517 12. dragićević, s., mészáros, m., djuridjić, s., pavić, d., novković, i., & radislav, t. (2013). vulnerability of national parks to natural hazards in the serbian danube region. polish journal of environmental studies, 22(4), 1053–1060. retrieved from https://www.researchgate.net/publication/255828318_vulnerability_of_national_parks_to_natural_hazards_in_the_serbian_danube_region 13. lukić, d., berjan, s., & el bilali, h. (2018). indicators of tourism development of the serbian danube region. r-economy, 4(1), 30–37. retrieved from http://r-economy.ru/wp-content/uploads/2018/03/r-economy_2018_v4_1_05.pdf information about the authors jelena milanković jovanov – phd in geosciences, teaching assistant at the department of geography, tourism and hotel management, faculty of sciences, university of novi sad (1 dr zorana đinđića, 21101 novi sad, republic of serbia); e-mail: milankovicjovanov@gmail.com. dragoslav pavić – phd in geosciences, full professor at the department of geography, tourism and hotel management, faculty of sciences, university of novi sad (1 dr zorana đinđića, 21101 novi sad, republic of serbia); e-mail: dragoslav.pavic@dgt.uns.ac.rs. jasmina đorđević – phd in geosciences, full professor at the department of geography, tourism and hotel management, faculty of sciences, university of novi sad (1 dr zorana đinđića, 21101 novi sad, republic of serbia); e-mail: jasminadjordjevic@live.com. aleksandra dragin – phd in geosciences, associate professor at the department of geography, tourism and hotel management, faculty of sciences, university of novi sad (1 dr zorana đinđića, 21101 novi sad, republic of serbia); e-mail: aleksandra.dragin@dgt.uns.ac.rs. smiljana đukičin vučković – phd in geosciences, assistant professor at the department of geography, tourism and hotel management, faculty of sciences, university of novi sad (1 dr zorana đinđića, 21101 novi sad, republic of serbia); e-mail: smiljanadjukicin@gmail.com. minucsér mészáros – phd in geosciences, assistant professor at the department of geography, tourism and hotel management, faculty of sciences, university of novi sad (1 dr zorana đinđića, 21101 novi sad, republic of serbia); e-mail: minucer.mesaros@dgt.uns.ac.rs. r-ecomony, 2018, 4(3), 95–104 doi: 10.15826/recon.2018.4.3.014 95 www.r-economy.ru online issn 2412-0731 original paper doi: 10.15826/recon.2018.4.3.014 the determinants of budget revenues of russian regions marina yu. malkina lobachevsky state university of nizhny novgorod, nizhny novgorod, russia; e-mail: mmuri@yandex.ru abstract this paper discusses the determinants of regional budget revenues and evaluates their impact on the level of budget provision of russian regions. we used the panel data on 80 russian regions in 2006–2014 embracing average population, grp disaggregated by main economic activities, tax revenues both collected and allocated at the regional level, intergovernmental aid and total budget revenues of consolidated budgets. we applied the least-squares methods with fixed and random effects to estimate the regressions between the structure of employment in main economic activities and the collected tax revenues in russian regions. the constructed model allowed us to distinguish activities with positive and negative influence of employment on the general tax level and to determine the elasticity of the collected tax revenue per capita with respect to the shares of employees engaged in various economic activities. further we applied the weighted least-squares method to estimate the model, demonstrating dependency of the budget revenue per capita in russian regions on the collected tax revenue per capita, the level of tax absorption and the share of intergovernmental transfers in consolidated regional budgets. the constructed model demonstrated high elasticity of budget provision of russian regions with respect to the general tax level, and even more with respect to the level of tax absorption. nevertheless, the inter-budgetary transfers showed a very slight positive impact on the dispersion of the regional budget revenue per capita over the given period. our findings are applicable to the management of budget revenues at the regional level and to the improvement of the russian model of fiscal federalism. keywords region; budget revenue, determinants, economic activities, grp per capita for citation malkina, m. yu. (2018) the determinants of budget revenues of russian regions. r-economy, 4(3), 95–104. doi: 10.15826/recon.2018.4.3.014 детерминанты бюджетных доходов российских регионов м. ю. малкина нижегородский государственный университет, нижний новгород, россия, e-mail: mmuri@yandex.ru резюме в данной статье обсуждаются детерминанты доходов региональных бюджетов и оценивается их влияние на уровень бюджетной обеспеченности регионов российской федерации. мы использовали данные по 80 регионам россии за 2006–2014 годы, включающие среднее население, врп с разбивкой по основным видам экономической деятельности, налоговые поступления, как собранные, так и оставшиеся на уровне регионов, размер межправительственной помощи и общие доходы консолидированных бюджетов субъектов рф. мы применили метод наименьших квадратов с фиксированными и случайными эффектами для оценки регрессионных зависимостей между структурой занятости в основных видах экономической деятельности и собранными налоговыми поступлениями в российских регионах. построенная модель позволила выявить, занятость в каких видах экономической деятельности оказала положительное, а в каких отрицательное влияние на общий уровень налоговых поступлений и определить эластичность собранных налогов на душу населения относительно долей занятых в различных видах экономической деятельности. далее мы применили взвешенный метод наименьших квадратов для оценки модели, демонстрирующей зависимость доходов бюджетов на душу населения в российских регионах от собранных налоговых поступлений на душу населения, уровня абсорбции налогов и доли межбюджетных трансфертов в консолидированных бюджетах субъектов рф. построенная модель продемонстрировала высокую эластичность бюджетной обеспеченности регионов россии к общему уровню налогообложения и еще большую эластичность – к уровню абсорбции налогов. в то же время межбюджетные трансферты оказали незначительное положительное влияние на снижение разброса среднедушевых доходов региональных бюджетов в рассматриваемом периоде. наши выводы могут быть использованы для управления доходами бюджетов на региональном уровне и улучшения российской модели фискального федерализма. ключевые слова регион; доходы бюджета; детерминанты; виды экономической деятельности; врп на душу населения для цитирования malkina, m. yu. (2018) the determinants of budget revenues of russian regions. r-economy, 4(3), 95–104. doi: 10.15826/recon.2018.4.3.014 http://doi.org/10.15826/recon.2018.4.3.014 http://doi.org/10.15826/recon.2018.4.3.014 mailto:mmuri@yandex.ru mailto:mmuri@yandex.ru 96 www.r-economy.ru r-ecomony, 2018, 4(3), 95–104 doi: 10.15826/recon.2018.4.3.014 online issn 2412-0731 introduction russia occupies a vast territory spread over different climatic zones. a variety of natural conditions predetermine the diversity of economic structures of russian regions and levels of their development. moreover, the spatial location of regions, their proximity to the center and to economically advanced or, on the contrary, poor territories play a significant role in their development. the conditions of regional economies are also influenced by their previous paths of development, the functions that were attributed to these regions earlier in the centrally planned economy, the authority of regional leaders and their interrelationship with the federal center. there were substantial disparities in the levels of development and budget provision of russian regions during the entire period of market transition, although these disparities were steadily decreasing until recently. indeed, in 2009, the gap in the grp per capita between the most prosperous region, nenets autonomous district, and the most lagging region, the republic of ingushetia, amounted to 67.1 times, while the national average was 224.2 thousand rubles per capita. in addition, in 2009, the interregional population-weighted coefficient of variation of the grp per capita was .84. in 2014, the gap in the grp per capita decreased noticeably – up to 39.5 times, while the coefficient of variation declined slightly and reached 0.81. after 2014, the opposite tendency was observed: the gap in the grp per capita grew up to 54.5 in 2016 while the coefficient of variation decreased slightly to the level of 0.786. despite these changes, both the top and the bottom regions in the ranking remained the same in 2016 as in 2009. regarding the budget provision of russian regions, the situation was much better due to the active redistribution policy of the state. the interregional inequality in budget provision of russian regions was considerably lower compared to the above-described regional disparities in the grp per capita but still significant and growing in recent years. thus, in 2011, the gap between the revenue per capita of the consolidated budget of the most prosperous region, nenets autonomous district, and the revenue of the most lagging region, the republic of dagestan, amounted to 12.1 times. the interregional population-weighted coefficient of variation of budget provision of russian regions was .55 in 2011. by 2015, the gap between chukotka autonomous district, ranked first by budget revenue per capita, and the republic of dagestan, which ranked last, had increased to 15.7 times, and the interregional coefficient of variation reached .61. in our study we assume that the sectoral structure of the country’s economy plays a decisive role in budget provision of regional economies. it determines the level of the tax revenue that can potentially be collected there. indeed, the largest level of tax return in the inter-crisis period of 2009–2013 was found in the mining industry, where the ratio of the collected tax revenue to the gross added value amounted to 53.7%, followed by the manufacturing industry (21.3%). the lowest level of the tax return rate was in agriculture (2.3%). at the same time, the tax rules in russia are set in such a way that the least evenly distributed taxes, namely the mineral extraction tax and the value added tax, are fully allocated at the federal budget level. consequently, the tax revenues of more productive sectors, such as the extractive industry, are shared with the federal center in a larger proportion compared to tax revenues of other sectors. this partially mitigates the influence of the sectoral structure of economy on the budget provision of regions. in addition, the regional level of the tax return within economic activities varies significantly, which is mainly due to the differences in structures and conditions of these activities in regions, and, regarding the mining and quarrying industry, different quality of fields and different stages of their extraction. the distribution of tax returns in russian regions is influenced not only by the sectoral structure of regional economies, but also by differences in the application of tax exemptions and privileges. for instance, preferential tax regimes in special economic zones of some manufacturing regions significantly affects their level of tax returns. moreover, the amount of collected taxes in regions depends on behavioral practices of the population and enterprises in these regions, the levels of tax discipline, tax compliance and tax evasion, and the quality of tax administration. the distribution of intergovernmental transfers from the federal center to regions increases their financial resources and supports the alignment of regional budget provision. in addition to the equalization of budget revenues per capita, the system of intergovernmental aid in russia is aimed at other purposes: balancing of regional budgets, funding of social mandates delegated to the sub-federal level from the higher authorities, and stimulation of investment activity in the regions. to achieve these goals, various types of budgetary http://doi.org/10.15826/recon.2018.4.3.014 r-ecomony, 2018, 4(3), 95–104 doi: 10.15826/recon.2018.4.3.014 97 www.r-economy.ru online issn 2412-0731 assistance were elaborated, including subsidies, subventions, grants and other inter-budgetary transfers. meanwhile, some of these objectives may be in conflict with others. thus, stimulation may contradict equalization. in this research, we examine the determinants of regional budget revenues per capita related both to the sectoral structure of regional economies and to the institutional features of the tax and budgetary systems in russia. literature overview in research literature, different approaches are applied to studying regional budget revenues. first of all, there are papers that analyze the impact of macroeconomic factors (the exchange rate, oil prices, economic growth and inflation) on the total revenue of the budgetary system [1] or more specific factors such as tax revenues, interbudgetary transfers and so on. some researchers have developed the ways to exclude the combined influence of macroeconomic factors on budget revenue [2]. other authors examined the problems of sub-federal budgets in russia in their relation to the current geopolitical situation, the impact of mutually imposed sanctions and the high dependence of russian economy on the global energy market condition [3]. castro and camarillo [4] analyzed the impact of economic, structural, institutional and social factors on tax revenues in oecd countries in 2001–2011. they found that tax revenues as a percentage of gdp in these countries were positively related to gdp per capita, the industry value added as a percentage of gdp and civil liberties, whereas they were inversely dependent on the agriculture value added as a percentage of gdp and the share of foreign direct investment in gross fixed capital formation. other authors focused on institutional and behavioral factors affecting budget revenue and budget deficit of sub-federal entities in federal states. for example, breuille and vignot [5] modeled the impact of redistribution policy on financial behavior and fiscal discipline of the recipient regions. the authors concluded that such policy can encourage the regions to create overlapping schemes that could exacerbate the problem of a soft budget constraint. huber and runkel [6] developed another theoretical model simulating the relationship of the federal center and regions with different rates of time preference. the authors showed that the asymmetry of information can lead to ineffective redistribution of resources in favor of recipients. they proposed to establish differentiated institutions for two types of regions within the fiscal constitution: weak debt limits for contributors and strict debt limits for recipients. such institutions should allow the federal center to overcome the information asymmetry through self-selection of regions. in the context of our research, we should also mention the works on shortand long-term effects of redistribution of financial resources through the budgetary system. there are studies pointing out that the efficiency of inter-budgetary aid for development of a territory and the subsequent increase of its level of budgetary provision depends on how the received funds are spent. for instance, kappeler, solé-ollé, stephan and välilä in their study [7] found that the use of intergovernmental transfers for production of public goods and investment in infrastructure of regional economies can stimulate economic growth. it should be emphasized that a considerable part of inter-budgetary transfers in russia is aimed at equalization of budgetary provision of regions, balancing sub-federal budgets according to the specific needs and the cost of living in regions, and financing the so-called social mandates, which are delegated from the federal center to the regional level. based on the econometric models of various specifications, the researchers came to contradictory conclusions about the efficiency of inter-budgetary aid in russian economy. for example, yushkov [8] found that intergovernmental transfers positively affected economic growth in russian regions in 2005–2012. at the same time, isaev [9] demonstrated that inter-budgetary transfers from the federal centre to russian regions had a negative impact on their economic growth in 2005–2014. meanwhile, martinez-vasquez and timofeev [10] found that intraregional budget transfers, distributed among municipalities for equalization of their budgetary provision, positively affected regional economic growth in 1999–2008. however, centralized funding of large investment projects aimed at regional development has been a prevalent trend. some researchers studied the consequences of allocation of financial resources within the framework of national projects. belov [11] showed that investment from sub-federal budgets is more conducive to growth and development of russian regions than investment from the federal budget. therefore, the author came to the conclusion that the transfer of investment funds http://doi.org/10.15826/recon.2018.4.3.014 98 www.r-economy.ru r-ecomony, 2018, 4(3), 95–104 doi: 10.15826/recon.2018.4.3.014 online issn 2412-0731 from the federal center to russian regions should foster regional economic development. other researchers applied the deterministic factor analysis to study sub-federal budget revenues in the russian federation. a multiplicative model of the regional budget revenues was used to measure the changes in budgetary provision of russian regions at consequent stages of budgetary process such as collection of tax revenues in regions, tax sharing with the federal center, attraction of non-tax revenues in regions, intergovernmental transfers and the regions’ borrowing from other levels of the budgetary system and outside it [12]. in addition, the changing level of regional disparities in sub-federal budget provision was evaluated and the conclusion was drawn about the efficiency of various stages of the budgetary process in addressing interregional inequality. in yet another study [13], the author proposed an additive model of sub-federal budget revenues in russia and carried out decomposition of the general inequality in the provision of regional budgets by various tax and non-tax sources. some authors analyzed the interrelationship between sectoral structures of regional economies and their budget revenues [14]. in particular, paredesa and rivera [15] found that in countries with a high share of mining, in gdp the mineral extraction tax can displace other taxes. the regression model constructed for russian regions in [16] showed that more specialized economies had a higher level of tax return, while more diversified economies showed a higher degree of its stability. in this study, we apply the panel data of russian regions in 2006–2014 to econometric modeling of regional budget revenues. the purpose of this research is to select and substantiate exogenous factors that have a complementary impact on the level of the per capita revenue of the consolidated budgets of russian regions. we also intend to show the connection between the budgetary provision of russian regions, their economic structures, and the peculiarities of their participation in inter-fiscal interactions. we are also going to construct alternative econometric models and interpret their results. data and methods the study is based on the pooled spatial-temporal sample covering 747 observations on 83 russian regions in 2006–2014. the initial data are provided by the federal state statistic service and the federal tax service of russian federation. we tested a set of the following independent variables presumably influencing the budget revenue per capita in russian regions: 1. variables related to the sectoral structure of regional economies: – the gross value added in main economic activities per capita; – the labor productivity in main economic activities calculated as the ratio of the gross value added to employment in these activities; – the share of economic activities in the total gross value added; – the share of economic activities in total employment; 2. variables related to the state of the tax and budgetary systems and interbudgetary relationships: – the general level of taxation (determined as the ratio of the collected tax revenues to grp and to constant population of regions); – the level of tax absorption – the share of tax revenues remaining in the consolidated regional budgets after the distribution of the total tax revenues collected in the regions between the levels of the budgetary system; – the share of remittances transferred to regional budgets from the federal center in the total revenue of regional budgets. to bring the nominal values of these variables in various years to a single scale of prices, we calculated their real values. for this purpose, we used the cumulative gdp deflator indices determined on the accrual basis. since we constructed the regressions of the logarithmic type, individual observations with negative and zero values were omitted. the selection of independent variables for regression was carried out on the basis of the correlation matrix, taking into account both the relationship of these variables with the dependent variable and the absence of multicollinearity. we tested models of different specifications, including the models with fixed and random effects to which the least squares method was applied. the significance of the models was estimated on the basis of the fisher criterion, and significance of its coefficients – on the basis of the students tests. we also checked the models for the presence of heteroscedasticity using the white test. results and discussion figure 1 shows a wide dispersion of the budgetary provision of russian regions in real terms on average in 2006–2014. http://doi.org/10.15826/recon.2018.4.3.014 r-ecomony, 2018, 4(3), 95–104 doi: 10.15826/recon.2018.4.3.014 99 www.r-economy.ru online issn 2412-0731 124.07 115.74 104.66 82.65 70.45 63.59 60.35 59.44 51.92 37.90 36.61 33.30 32.11 29.96 29.66 29.30 28.14 27.76 27.30 25.92 25.39 25.01 24.90 24.78 24.64 24.37 23.42 23.37 23.35 23.34 23.06 23.06 22.57 22.51 21.64 21.64 21.52 21.46 20.97 20.28 19.89 19.33 19.08 18.87 18.78 17.93 17.80 17.54 17.34 17.07 16.95 16.84 16.52 16.48 16.11 15.94 15.91 15.91 15.79 15.65 15.42 15.32 15.17 15.17 14.94 14.89 14.81 14.79 14.78 14.52 14.40 14.30 14.10 14.05 13.77 13.69 13.56 13.46 13.30 12.94 12.36 11.65 0 20 40 60 80 100 120 140 160 chukotka autonomous district nenets autonomous district yamal-nenets autonomous district tyuman region khanty-mansiysk autonomous district – yugra kamchatka krai magadan region republic of sakha (yakutia) moscow city sakhalin oblast saint-petersburg city arhangelsk region murmansk region krasnoyarsk region komi republic jewish autonomous region khabarovsk region amur region altai republic vologda region republic of karelia republic of buryatia kaliningrad region republic of tatarstan tomsk region irkutsk region moscow region leningrad region primorsky krai belgorod region yaroslavl region perm region chechen republic tyva republic lipetsk region novgorod region transbaikal region kemerovo region samara region sverdlovsk region novosibirsk region kaluga region omsk region republic of mordovia republic of bashkortostan chelyabinsk region tula region tver region nizhny novgorod region orenburg region pskov region astrakhan region kursk region republic of khakassia udmurt republic ryazan oblast penza region kirov region krasnodar region tambov region altai region kostroma region smolensk region kabardino-balkar republic republic of adygea rostov region oryol region saratov region ulyanovsk region kurgan region mari el republic karachay-cherkess republic bryansk region vladimir region republic of north ossetia-alania stavropol region republic of ingushetia chuvash republic voronezh region volgograd region ivanovo region republic of kalmykia republic of dagestan 147.69 russian regions’ annual average budget revenue per capita in 2006–2014 in constant prices of 2005, thousand deflated rubles http://doi.org/10.15826/recon.2018.4.3.014 100 www.r-economy.ru r-ecomony, 2018, 4(3), 95–104 doi: 10.15826/recon.2018.4.3.014 online issn 2412-0731 according to the results obtained, the budget revenue per capita in the richest region (chukotka autonomous district) was 12.7 times higher than that of the poorest region (dagestan). only in 17 out of 83 regions the level of budget provision exceeded the country average. the ratio of the median value to the mean value of budgetary provision was 70.6%, which indicated a left bias in the distribution of this variable. it should be noted that the deflation of indicators in time series reduced the level of interregional inequality of budget provision. however, we did not take into account the initial distribution of prices and differences in the cost of living in the base period of study, which could decrease the measured inequality to a greater extent. among the leaders by the level of budgetary provision, we can primarily find the regions specialized in extractive industry and characterized by the relatively low population density (namely, nenets autonomous district, which is a part of arkhangelsk region; khanty-mansiysk and yamalo-nenets autonomous districts, which are parts of tyumen region; chukotka autonomous district, kamchatka krai, the republic of sakha, magadan and sakhalin regions, all situated in the far eastern federal district). a high position by the level of budget revenue is also occupied by the capital city of moscow, where a large number of state agencies and financial institutions are located. among the laggards, we see the regions deprived of any comparative advantages of both natural and artificial origin, such as the republic of kalmykia, ivanovo region and the chuvash republic. moreover, almost all north caucasian republics (except for the chechen republic) are lagging behind as well as stavropol region. this situation in russian regions is the result of many processes. the budgetary provision is affected by the volume of the collected tax revenue, which is shared with the federal budget, non-tax revenues (income from public and municipal property and sale of tangible and intangible assets etc.) and availability of inter-budgetary aid. meanwhile, the initial level of budgetary provision in each region is predetermined by the tax revenue collected on its territory, the amount of which depends to a large extent on the sectoral structure of regional economy. table 1 compares the following three sectoral structures of regional economies: the distribution of employed persons, production of grp and collected taxes in main economic activities. it indicates the outstanding role of the mining sector in tax revenues. in this sector, both the labor productivity and the tax return level were 3.7 times higher than the national average. as a result, the tax revenue per employee in mining and quarrying exceeded the average level in all sectors by almost 14 times. at the same time, an increased table 1 structural parameters of tax revenues in russian regions in 2006–2014, % economic activities share in total employment share in total grp share in collected tax revenue mv sd cv mv sd cv mv sd cv agriculture, hunting and forestry (a) 11.4 5.9 0.52 9.3 6.3 .68 .6 2.0 3.29 fishing, fish farming (b) .4 1.2 2.83 1.1 6.7 6.11 .1 2.3 16.26 mining and quarrying (c) 2.3 4.3 1.86 8.7 15.1 1.73 32.5 23.0 .71 manufacturing (d) 14.5 6.3 .44 18.4 11.3 .62 18.1 19.9 1.10 electricity, gas and water (e) 3.4 1.5 .44 4.5 2.7 .61 2.8 4.3 1.53 construction (f) 7.5 2.5 .33 7.9 4.1 .52 4.9 4.6 .94 wholesale and retail trade; repair (g) 15.9 3.6 .23 16.7 7.0 .42 11.5 13.6 1.19 accommodation and food service activities (h) 1.7 .5 .30 0.9 .5 .52 0.6 .5 .82 transport and telecommunications (i) 8.0 1.9 .24 11.7 4.9 .42 8.1 7.1 .88 real estate, leasing and services (j) 1.3 .5 .41 0.2 .5 2.22 5.2 4.6 .88 financial activities (k) 6.3 2.4 .38 7.4 3.1 .43 9.9 4.8 .48 public administration and defense 6.8 2.3 .33 4.8 3.0 .63 1.7 5.6 3.19 education 9.5 2.3 .24 3.4 1.8 .52 1.4 2.0 1.40 health and social services 7.3 1.3 .18 3.8 1.8 .46 1.1 1.9 1.65 public utilities 3.7 .7 .19 1.2 .5 .43 1.3 .9 .66 note: mv — interregional mean value, sd — interregional standard deviation, cv — interregional coefficient of variation, which is the ratio of sd to mv. http://doi.org/10.15826/recon.2018.4.3.014 r-ecomony, 2018, 4(3), 95–104 doi: 10.15826/recon.2018.4.3.014 101 www.r-economy.ru online issn 2412-0731 level of labor productivity in certain spheres (fishing, fish farming; transport and telecommunications; manufacturing; electricity, gas and water; finance) and a higher level of tax return in some other spheres (real estate, leasing and services; finance) ensured greater profitability of the tax system. thus, the contribution of economic activities to overall tax revenues in regions and in the country as a whole depended on their share in employment and production. due to the fact that economic structures in the regions differ, their tax revenue levels also differ, which is evident from the corresponding standard deviations and coefficients of variation in activities. thus, according to the distribution of employment, the regions are the most diverse in mining and quarrying, fishing and fish farming. by the share in grp, they differ more in the aforementioned two activities, as well as in real estate, leasing and services. finally, the share of regions in tax revenues varies most in fishing, fish farming, as well as in agriculture, hunting and forestry. our selection of structural variables that presumably shape the tax revenue per capita in regions was based on the criteria specified in the methodological part of the work. we proposed a model of the following specification: β β ε = = + +∑0 1 ln( ) ln( ) , n it i it it i trpc x emp where trpcit is the tax revenue per capita and xempit is the share of the corresponding activity in the total employment of the ith region in the period t. the model was estimated by means of three alternative methods presented in table 2. the constructed models are significant according to the fisher criterion; the significance of their parameters (except for the intercept term) is confirmed by the students test. in addition, they do not have multicollinearity and the residuals of the models are normally distributed. according to the results obtained, those regions whose population is employed mainly in the sectors of mining and quarrying; electricity, gas and water production; construction; transport and telecommunications; real estate, leasing and services and finance had a higher level of collected tax revenues per capita on average. at the same time, those regions whose employment concentrated mainly in agriculture, hunting and forestry; manufacturing; wholesale and retail trade, repair; table 2 models: dependent variable ln(trpcit) variable coefficient of regression (standard error), significance model 1: pooled ols regression model 2: ols with fixed effects model 3: gls with random effects const –1.154 (.836) .129 (.789) –.591 (.795) ln(a_emp) –.250 (.029) *** –.242 (.031)*** –.245 (.029)*** ln(c_emp) .073 (.014) *** .058 (.015)*** .068 (.014)*** ln(d_emp) –.097 (.042) ** –.122 (.044)*** –.106(.042)*** ln(e_emp) .300 (.077) *** .306 (.076)*** .354(.073)*** ln(f_emp) .269 (.079) *** .325 (.082)*** .279 (.079)*** ln(g_emp) –1.287 (.088) *** –1.207 (.089)*** –1.290 (.088)*** ln(h_emp) –.125 (.059) ** – – ln(i_emp) .653 (.097) *** .605 (.098)*** .602 (.094)*** ln(j_emp) .188 (.071) *** .275 (.075)*** .211 (.070)*** ln(k_emp) .627 (.085) *** .669 (.091)*** .626 (.085)*** ln(l_emp) –.878 (.088) *** –.811 (.095)*** –.894 (.088)*** ln(m_emp) –.470 (.135) *** – –.425 (.134)*** ln(n_emp) –.531 (.170) *** –.689 (.156)*** –.510 (.170)*** ln(o_emp) –.540 (.104) *** –.761 (.109)*** –.609 (.099)*** adjusted r-squared .822 .821 – durbin-watson statistic 1.810 1.962 – number of observations 693 693 693 note: * means that the coefficient is significant with p < .1; ** means that the coefficient is significant with p < .05; *** means that the coefficient is significant with p < .01. http://doi.org/10.15826/recon.2018.4.3.014 102 www.r-economy.ru r-ecomony, 2018, 4(3), 95–104 doi: 10.15826/recon.2018.4.3.014 online issn 2412-0731 accommodation and food service activities; public administration and defense; education; health and social services and public utilities have a lower level of the collected tax revenues per capita on average. the coefficients of regressions show the elasticity of tax revenues with respect to the share of employment in the corresponding activity. the second step of our research was modeling the interrelationship between budget revenues per capita as a dependent variable and the general level of taxation, the level of tax absorption and the share of transfers in regional budget revenues as independent variables. table 3 shows the descriptive statistics of the explained and explanatory variables. table 3 descriptive statistics of the parameters related to the consolidated budgets of the russian regions in 2006–2014, % variable note mv sd cv budget revenue per capita, thousand deflated rubles brpcit 28.11 36.99 1.32 general level of taxation, thousand deflated rubles trpc 34.16 79.72 2.33 level of tax absorption selt .74 .20 .26 share of transfers in total budget revenues transf .34 .19 .54 note: mv is the mean value; sd, the standard deviation; and cv is the coefficient of variation. the general tax level turned out to be a statistically significant parameter that positively affected the average budget revenues, which was completely correspondent with the logic of economic processes. the linear coefficient of the correlation between the tax revenue per capita and the budget revenue per capita in russian regions in the given period equaled .57. however, the strong heteroscedasticity in this dependency was observed even visually. the relationship between the level of tax absorption in regions and the total budget revenues per capita appeared to be slightly negative. indeed, the pearson correlation of these variables was only –.13. at the same time, we found a significant negative relationship between the collected tax revenues per capita and the share of taxes left in regional budgets after their distribution among the levels of budgetary system. the dependency between the general tax level and the level of tax absorption was described by the power function of the following specification: selfit = 7.6trpcit–2.036, r2 = 0.47. as for transfers, we did not obtain any strong evidence showing their connection to the level of budget provision, albeit the inverse dependency was expected. we identified several reasons for this phenomenon. first of all, significant and diverse inter-budgetary transfers received from the federal budget by some lagging regions, for example, the republics of chechnya, tyva, altai, in fact, raised their level of budgetary provision even higher than the national average. secondly, when determining the needs of regions in intergovernmental transfers, fiscal authorities take into account not only the available regional budget revenues, but also the necessary expenses, which depend on the cost of living and on the specific needs of each particular region. hence, some seemingly more affluent regions of the far eastern federal district, such as chukotka autonomous district, magadan region and kamchatka, receive significant transfers from the center, which further increases their level of budget provision. despite the ambiguity of some dependencies, we proposed a regression of the following specification: β β β β ε = + + + + + 0 1 2 3 ln( ) ln( ) ln( ) ln( ) . it it it it it brpc trpc self transf to cope with the heteroscedasticity and abnormality of the distribution of residues, we estimated this model using the weighted least-squares method, which means that the natural logarithm of gdp per capita was treated as a weight parameter. moreover, in the estimation of the regression we used robust standard errors. the resulting model is presented in table 4. table 4 model: dependent variable ln(brpcit) variable pooled wls regression const 1.652 (.063) *** ln(trpcit) .649 (.029) *** ln(seltit) .809 (.074) *** ln(transfit) .063 (.017) *** adjusted r-squared .705 number of observations 747 note: *** means that the coefficient is significant with p < .01; **, the coefficient is significant with p < .05; * the coefficient is significant with p < 0.1. in this regression, all exogenous variables are statistically significant and the directions of relationship between the exogenous and endogenous variables are completely consistent with the logic of economic processes. indeed, the higher the levhttp://doi.org/10.15826/recon.2018.4.3.014 r-ecomony, 2018, 4(3), 95–104 doi: 10.15826/recon.2018.4.3.014 103 www.r-economy.ru online issn 2412-0731 el of taxation, the level of tax absorption and the aid received from the federal center, the higher is the level of budget provision of russian regions. despite the concerns about possible multicollinearity, the vif test did not confirm its existence in this model. the estimated coefficients of the model can be interpreted as indicators of elasticity of the tax revenue with respect to the examined factors. for example, an increase in the tax revenue per capita collected in russian regions by 1% leads to an increase in the budget revenue of the regions by .65% on average. the elasticity of budget provision with respect to the level of tax absorption has proven to be even higher compared to the level of tax collection. eventually, inter-budgetary transfers demonstrated the weakest impact on the changes in the budget revenue per capita in regions over time. it evidenced the diminishing role of intergovernmental aid in equalization of russian regions’ budget provision. conclusion in this study, we analyzed the factors that influenced the revenues of consolidated regional budgets by using the panel data of russian regions in 2006–2014. in the theoretical part of our paper, we studied the influence of the sectoral structure of economy, macroeconomic conditions, institutional features of the tax and budgetary systems, and public behavior on the level of average budget revenues of states and their constituent entities. in the empirical part of the paper, we selected the most relevant variables and constructed the models related to the two stages of budget revenue formation. in the first step, using ordinary least-squares methods with fixed and random effects, we built the dependency of the tax revenue per capita in real terms on the shares of economic activities in total employment in russian regions. it allowed us to reveal the positive impact of employment in certain sectors (e.g. mining and real estate activities) and the negative impact of employment in other sectors (e.g. agriculture, trade and social sphere) on the general tax level in russian regions. in the second step, by means of the weighted least-squares method, we constructed a regression model of the logarithm type, which demonstrated a positive impact of the general tax level, the level of tax absorption and the share of inter-budgetary transfers in consolidated budgets of russian regions on their budget revenue per capita. we demonstrated the greatest influence of the level of tax absorption and the smallest effect of transfers on the reduction of regional disparities regions by budget provision. the results obtained are basically consistent with some of our previous findings [12; 13] and develop approaches to modeling regional differences on the level of budgetary provision. for further research, it is necessary to improve the methods of construction of regression models based on spatial-temporal data and to provide a more precise specification of the basic model by including proxy variables for institutional parameters of budgetary and tax systems as well as general public behavior. references 1. balaev, a., gurvich, e., prilepskiy, i., suslina, a. (2014). effect of oil price and exchange rate on the fiscal revenues. financial journal, 1(19), 5–16. (in russ.) 2. balaev, a. (2017). factor analysis of the russian budget system revenues. economic polycy, 12(3), 8–37. (in russ.) doi: 10.18288/1994-5124-2017-3-01 3. povarova, a. i. (2017). alarming prospects of russian regional budgets. territorial development issues, 2(37), 1–10. retrieved from http://vtr.isert-ran.ru/article/2200?_lang=en (in russ.) 4. castro, g. á., & camarillo, d. b. r. (2014). determinants of tax revenue in oecd countries over the period 2001–2011. contaduría y administración, 59(3), 35–59. doi: 10.1016/s01861042(14)71265-3 5. breuillé, m.-l., vigneault, m. (2010). overlapping soft budget constraints. journal of urban economics, 67(3), 259–269. 6.  huber, b., runkel, m. (2008). interregional redistribution and budget institutions under asymmetric information. journal of public economics, 92(12), 2350– 2361. doi: 10.1016/j.jpubeco.2008.01.008 7. kappeler, a., solé-ollé, a., stephan, a., välilä, t. (2013). does fiscal decentralization foster regional investment in productive infrastructure? european journal of political economy, 31, 15–25. doi: 10.1016/j.ejpoleco.2013.03.003 http://doi.org/10.15826/recon.2018.4.3.014 http://doi.org/10.18288/1994-5124-2017-3-01 http://vtr.isert-ran.ru/article/2200?_lang=en http://doi.org/10.1016/s0186-1042(14)71265-3 http://doi.org/10.1016/s0186-1042(14)71265-3 http://doi.org/10.1016/j.jpubeco.2008.01.008 http://doi.org/10.1016/j.jpubeco.2008.01.008 http://doi.org/10.1016/j.ejpoleco.2013.03.003 104 www.r-economy.ru r-ecomony, 2018, 4(3), 95–104 doi: 10.15826/recon.2018.4.3.014 online issn 2412-0731 8.  yushkov, a. (2015). fiscal decentralization and regional economic growth: theory, empirics, and the russian experience. russian journal of economics, 1(4), 404–418. doi: 10.1016/j. ruje.2016.02.004 9. isaev a. g. (2016). distribution of financial resources within the budget system of the russian federation and regional economic growth. prostranstvennaya ekonomika = spatial economics, 4, 61–74 (in russ.). doi: 10.14530/se.2016.4.061-074 10. martinez-vazquez, j., timofeev, a. (2014). intra-regional equalization and growth in russia. comparative economic studies, 56(3), 469–489. doi: 10.1057/ces.2014.7 11. belov, a. (2018). tax revenues, public investments and economic growth rates: evidence from russia. journal of tax reform, 4(1), 45–56. doi: 10.15826/jtr.2018.4.1.044 12. malkina, m. (2016). evaluation of the factors of russian regions’ convergence / divergence in the level of budget provision based on the decomposition of the theil – bernoulli index. prostranstvennaya ekonomika = spatial economics, 3, 16–37 (in russ.) doi: 10.14530/se.2016.3.016-037 13.  malkina, m. (2017). decomposition of spatial inequality in budget provision by income sources: case of modern russia. in: nešleha, j., plíhal, t., & urbanovský, k. (eds). european financial systems 2017. proceedings of the 14th international scientific conference, part 2. brno: masaryk university, 35–43. retrieved from https://is.muni.cz/do/econ/sborniky/70896034/efs2017-proceedings_2_final.pdf 14.  liu, j., hu, x., wu, j. (2017). fiscal decentralization, financial efficiency and upgrading the industrial structure: an empirical analysis of a spatial heterogeneity model. journal of applied statistics, 44(1), 181–196. doi: 10.1080/02664763.2016.1252733 15. paredes, d., rivera, n. m. (2017). mineral taxes and the local public goods provision in mining communities. resources policy, 53, 328–339. doi: 10.1016/j.resourpol.2017.07.007 16. malkina, m. (2017). influence of the industrial structure of economy on the risk level of russian regions’ tax systems. acta universitatis agriculturae et silviculturae mendelianae brunensis, 65(6), 2025–2035. doi: 10.11118/actaun201765062025 information about the author marina yu. malkina – professor of economics, lobachevsky state university of nizhny novgorod (23 gagarin avenue, 603950 nizhnij novgorod, russia); e-mail: mmuri@yandex.ru. http://doi.org/10.15826/recon.2018.4.3.014 http://doi.org/10.1016/j.ruje.2016.02.004 http://doi.org/10.1016/j.ruje.2016.02.004 http://doi.org/10.14530/se.2016.4.061-074 http://doi.org/10.1057/ces.2014.7 http://doi.org/10.15826/jtr.2018.4.1.044 http://doi.org/10.14530/se.2016.3.016-037 https://is.muni.cz/do/econ/sborniky/70896034/efs2017-proceedings_2_final.pdf https://is.muni.cz/do/econ/sborniky/70896034/efs2017-proceedings_2_final.pdf http://doi.org/10.1080/02664763.2016.1252733 http://doi.org/10.1016/j.resourpol.2017.07.007 http://doi.org/10.11118/actaun201765062025 r-economy, 2022, 8(1), 57–67 doi: 10.15826/recon.2022.8.1.005 57 r-economy.com online issn 2412-0731 original paper © savin, i.v., letyagin, d.k., 2022 doi https://doi.org/10.15826/recon.2022.8.1.005 udc 331.5 jel d40, l16, l50 estimating the role of labor resources reallocation between sectors on the growth of aggregate labor productivity in the russian economy i.v. savin1, 2 , d.k. letyagin1 1 ural federal university, ekaterinburg, russia; ivan.savin@uab.cat 2 autonomous university of barcelona, barcelona, spain abstract relevance. economic growth can be achieved in two different ways: through technological improvements and reallocation of market shares from less to more productive units. despite the significant research literature on innovation in russia, the literature on market selection, especially at the sectoral level, is relatively scarce. this is the research gap that this study aims to address. research objective. the article assesses how labor resource reallocation between sectors has influenced the dynamics of aggregate labor productivity in the russian economy over the past two decades. data and methods. for this purpose, the growth of aggregate labor productivity was decomposed into the growth of productivity within the sectors themselves and the reallocation of labor resources between them. this allowed us to conduct a quantitative estimation of the role of market selection at the sectoral level. for our study, we used data from rosstat (from 2002 to 2018) and the world input-output database (from 2000 to 2014). results. for rosstat data, the ratio of the effect of changes in labor productivity and labor resource reallocation by sector on total labor productivity over the period was 0.71/0.29, and for wiod data it was 0.44/0.56. this indicates that labor resources are more likely to be reallocated to related sectors (e.g. between manufacturing industries). conclusions. the results suggest that there is competitive market selection at the sectoral level and that labor has generally been reallocated to more productive sectors of the economy, contributing significantly to the growth of aggregate productivity in the economy. our study shows the sectors of the economy where this reallocation has taken place, which may help to determine where this process is successful and where it needs additional stimulation. keywords competition, competitive selection, labor productivity, productivity growth, resource allocation, structural change, decomposition, value added awknowledgements this research was supported by grant no. 19-18-00262, “modeling of balanced technological and socio-economic development of russian regions», from the russian science foundation. for citation savin, i.v., & letyagin, d.k. (2022). estimating the role of labor resources reallocation between sectors on the growth of aggregate labor productivity in the russian economy. r-economy, 8(1), 57–67. doi: 10.15826/recon.2022.8.1.005 оценка роли перетока трудовых ресурсов между секторами на рост совокупной производительности труда в российской экономике и.в. савин1, 2 , д.к. летягин1 1 уральский федеральный университет, екатеринбург, россия; email: ivan.savin@uab.cat 2 автономный университет барселоны, барселона, испания аннотация актуальность. экономический рост может быть достигнут двумя различными способами: за счет технологических усовершенствований и перераспределения доли рынка от менее производительных единиц к более производительным. несмотря на значительный объем исследовательской литературы по инновациям в россии, литература по выбору рынка, особенно на отраслевом уровне, относительно скудна. на устранение данного пробела и направлено данное исследование. цель исследования. в статье оценивается как переток трудовых ресурсов между секторами влиял на динамику совокупной производительности труда в российской экономике за последние два десятилетия. ключевые слова конкуренция, конкурентный отбор, производительность труда, рост производительности, распределение ресурсов, структурные изменения, декомпозиция, добавленная стоимость https://doi.org/10.15826/recon.2022.8.1.005 https://doi.org/10.15826/recon.2022.8.1.005 mailto:ivan.savin@uab.cat mailto:ivan.savin@uab.cat 58 r-economy.com r-economy, 2022, 8(1), 57–67 doi: 10.15826/recon.2022.8.1.005 online issn 2412-0731 introduction one of the key determinants of economic development is labor productivity. countries that have been able to move from the category of developing to developed economies are those that have been able to diversify their economies by redirecting resources from low-productivity sectors of the economy to more productive ones. the idea of this paper is to examine how the reallocation of labor between sectors of the economy has influenced labor productivity growth in russia. numerous papers have been written on the impact of structural change on labor productivity in sectors of the economy (bessonov, 2004; gimpelson et al., 2014; savin et al., 2020; mcmillan and rodrick, 2011; savin, 2021; tang and wang, 2004; timmer et al., 2014). one of the earliest articles to discuss labor shifts beданные и методы. с этой целью была осуществлена декомпозиция роста совокупной производительности труда на рост производительности внутри самих секторов и переток трудовых ресурсов между ними. для проведения исследования нами были использованы данные росстата (с 2002 по 2018 год) и всемирной базы данных «затраты-выпуск» (с 2000 по 2014 год). результаты. по данным росстата соотношение влияния изменений производительности труда и перетока трудовых ресурсов по секторам на совокупную производительность труда за указанный период составило 0,71/0,29, а для данных wiod – 0,44/0,56. это указывает на то что трудовые ресурсы более склонны перераспределяться в смежные сектора (например, между отраслями обрабатывающего производства). выводы. полученные результаты свидетельствуют о наличии конкурентного отбора на уровне секторов экономики, а также о том, что трудовые ресурсы в целом перераспределялись в более производительные отрасли экономики внося весомый вклад в рост совокупной производительности труда в экономике. наше исследование оценивает в какие именно сектора экономики это перераспределение происходило, что может помочь определить, где данный процесс успешен, а где этот процесс нуждается в стимулировании. благодарности исследование выполнено при поддержке гранта рнф (проект №19–18–00262 «моделирование сбалансированного технологического и социальноэкономического развития российских регионов»). для цитирования savin, i.v., & letyagin, d.k. (2022). estimating the role of labor resources reallocation between sectors on the growth of aggregate labor productivity in the russian economy. r-economy, 8(1), 57–67. doi: 10.15826/recon.2022.8.1.005 评估行业间劳动力资源流动对俄罗斯经济中总劳动生产率的作用 萨文1, 2 ，莱蒂亚金1 1乌拉尔联邦大学，叶卡捷琳堡，俄罗斯；邮箱：ivan.savin@uab.cat 2巴塞罗那自治大学，巴塞罗那，西班牙 摘要 现实性：经济增长可以通过两种不同的方式实现：技术改进；将市场份 额从生产力较低的单位转移到生产力更高的单位。尽管俄罗斯有大量关 于创新的研究，但关于市场选择，尤其是在行业层面的学术研究相对稀 缺。本研究旨在填补这一空白。 研究目标：本文评估了在过去的20年里，行业间劳动力资源的流动是如 何动态影响俄罗斯经济中总劳动生产率的。 数据和方法：因此，总劳动生产率的增长被分解为各行业内部的生产率 增长和行业之间的劳动力资源流动。为了进行这项研究，我们使用了来 自俄罗斯联邦国家统计局（2002年至2018年）和世界投入产出数据库 （2000年至2014年）的数据。 研究结果：根据俄罗斯联邦国家统计局的数据，在此期间，各行业的劳 动生产率和劳动力资源流动对总劳动生产率的影响比率为0.71/0.29，而 世界投入产出数据库比率为0,44/0,56。这表明劳动力资源更有可能重新 分配到相似行业（例如，制造业之间）。 结论：结果显示，在行业层面存在竞争性选择，劳动力通常流动到更有 生产力的部门，这大大促进了经济总生产力的增长。我们的研究准确评 估了这种劳动力流动发生在哪些经济部门。这有助于确定这一过程在哪 些方面是成功的，以及在哪些方面需要优化。 关键词 竞争力，竞争淘汰，劳动生产 率，生产率增长，资源分配， 结构变化，分解，增加值 供引用 savin, i.v., & letyagin, d.k. (2022). estimating the role of labor resources reallocation between sectors on the growth of aggregate labor productivity in the russian economy. r-economy, 8(1), 57–67. doi: 10.15826/recon.2022.8.1.005 https://doi.org/10.15826/recon.2022.8.1.005 mailto:ivan.savin@uab.cat r-economy, 2022, 8(1), 57–67 doi: 10.15826/recon.2022.8.1.005 59 r-economy.com online issn 2412-0731 tween economic sectors was written by denison (1962), who found that significant job cuts in the agricultural sector of the economy and resource shifts to other sectors can significantly increase aggregate labor productivity and accelerate countries’ development. most of the literature on the effects of structural change on economic growth (pasinetti, 1981; mcmillan et al., 2014; mironov and konovalova, 2019) also emphasize that as resources are shifted from agriculture to modern and more productive sectors, economies grow and expand. the key factor that separates successful economies from laggards is the speed of these structural changes. russia is a country in transition which has great heterogeneity in labor productivity between different sectors. this feature is characteristic of many developing countries in eastern europe, asia and africa. typically, the economies of such countries have high productivity in one or more sectors of the economy (e.g., natural resource extraction), while others remain at the same level of development or progress very slowly. at the same time, the difference in productivity between individual firms and entire sectors is much smaller in developed economies than in developing ones (mcmillan et al., 2014; dosi et al., 2015; savin, 2020). what makes this heterogeneity in resource allocation special is that it has the potential to be an important engine of growth. when labor and other resources shift from less productive to more productive activities, the economy grows even if the sectors themselves do not gain in productivity. this situation is described by the “simpson paradox” (simpson, 1951), which has previously been discussed in terms of gdp growth (ma, 2015) and energy consumption (gross, 2012). for example, one-third to one-half of the lag in total factor productivity in countries such as india and china compared to the united states could be reduced if the inequality between the outsider and leader sectors in productivity were eliminated (bartelsman et al., 2006; hsieh and klenow, 2009). there are two factors that contribute to the growth in aggregate labor productivity: increases in productivity within sectors of the economy (the so-called “within-effect”) and the flow of labor from less productive sectors to more productive ones (the so-called “between-effect”). the latter is also called the “competitive selection” factor (savin, 2020; savin et al., 2019; simachev et al., 2018). if the between-effect turns out to be positive, we can conclude that there is competition between industries for labor resources, as more productive industries increase their share by taking employees from less productive industries (savin et al., 2020). the first way of increasing labor productivity is more often seen in economically advanced countries because their economies are sufficiently balanced, and reallocation of resources does not increase productivity. however, reallocation of resources due to competitive selection can increase productivity in developing countries with stronger heterogeneity between the sectors. such an effect is positive for the economy as a  whole, as it increases both aggregate producti vity and smooths out the inequalities between its individual sectors. this effect is also referred to in research literature as “structural change” (mcmillan et al., 2014). labor productivity refers to the amount of value added per worker. aggregate labor productivity is a measure of labor productivity for the economy as a whole. competitive market selection is the process of competition between individual economic actors for market share (savin et al. 2019, 2020), when the strongest and most adaptable firms in an industry survive and grow. the term was coined by an analogy with charles darwin’s theory of evolutionary selection, and in economics it traditionally refers to the expansion of the market share of the most productive and efficient firms (metcalfe, 1994). in this research we study the influence of competitive selection between economic sectors for labor resources and labor productivity in different sectors on the change of aggregate labor productivity in russian economy. by competitive selection we mean that economic sectors are to various degrees attractive for labor resources, and as workers migrate to more productive sectors of the economy, productivity of the whole economy increases. this study has the following objectives: first, to conduct a quantitative assessment of the role of competitive selection on the growth of aggregate labor productivity, reflecting the flow of labor resources between the sectors of the economy, in russia; and second, to identify the sectors of the economy where labor resources were predominantly reallocated in the period 2002–2018. this paper is organized as follows: section 2 deals with the data and methods of analysis; section 3 describes the decomposition of labor productivity growth, and section 4 presents our conclusions. https://doi.org/10.15826/recon.2022.8.1.005 60 r-economy.com r-economy, 2022, 8(1), 57–67 doi: 10.15826/recon.2022.8.1.005 online issn 2412-0731 methods there are many approaches to decomposition of productivity in research literature (baily et al., 1992; olley and pakes, 1996; cantner et al., 2019). more common, however, are the approaches presented in foster (2001) and griliches and regev (1995). savin et al. (2019) show that the methods proposed by griliches and regev (1995) and foster (2001) are essentially equivalent. both approaches are distinguished by their analytical simplicity as well as the ability to compare the results to those obtained by many other researchers using the same approaches. to conduct the decomposition of labor productivity, we apply the approach proposed by griliches and regev (1995), which has subsequently been used by many economists including mcmillan et al. (2014), dosi et al. (2015), cantner et al. (2019), foramitti et al. (2021a), foramitti et al. (2021b), and mundt et al. (2021). we preferred this method over alternatives as we can later compare our results with those of mcmillan et al. (2014). first, formula (1) calculates the total labor productivity of economy j over time t as a weighted sum of labor productivity for all sectors of the economy: ∈ π = π∑, , , ,j t i t i t i j r (1) where ri, t is a measure of the share of sector i in time t (measured by the number of employees employed in the sector); πi, t is a measure of labor productivity for sector i in time t. the decomposition of the change in the aggregate index is calculated by using formula (2): ∈ ∈ ∆π = ∆ π + ∆π∑ ∑, , , , , ,j t i t i t i t i t i j i j r r (2) where ∈ ∆ π∑ , , i t i t i j r is the variable characterizing the redistribution of  labor between sectors of the economy (“between” effect); ∈ ∆π∑ , , i t i t i j r is the result of changes in productivity at the level of the sectors of economy themselves (“within” effect). the upper line above the variable denotes the average value for two consecutive years; delta (∆) is the measure of the difference between the two years (subtract from the value for year t + 1 the value for year t). finally, in order to compare the results obtained for two different data sets more conveniently, we calculate the proportion of betweenand within-effects by normalizing their sum to unity as shown in formulae (3–4): , , , , i t i t t i j j t t r between ∈ ∆π = ∆π ∑ ∑ ∑ (3) , , , . i t i t t i j j t t r within ∈ ∆ π = ∆π ∑ ∑ ∑ (4) at this point it is worth mentioning the previously published studies which conducted the decomposition of labor productivity for the russian economy. there was a study on competitive selection and efficiency which showed that for firms operating in russia the between-effect is on average 8%, while everything else can be explained by the productivity growth in the firms themselves (savin et al., 2020). similar estimates were previously obtained for a subsample of firms from the ural federal district (savin et al., 2019). savin et al. (2020) conclude that the role of competitive selection for large firms is much lower than for small firms because small and medium-sized firms are less secure and the competition among large firms should be encouraged within the economy. however, it is worth noting that both studies investigating the effectiveness of competitive selection in russia only cover industrial firms from 2006 to 2017. for our study a different time period was chosen: from 2002 to 2018. moreover, we are looking at all the sectors of the russian economy (accor ding to the okved2 classifier). we investigate competition not between enterprises, but between the entire sectors of the economy. we use decomposition to estimate the redistribution of resources between sectors of the economy and to measure the betweenand withineffects. since the study by voskoboynikov and gimpelson (2015) is the most relevant to our analysis, further in this paper we are going to compare our results with theirs. data in the course of our work, we used two sets of data from different sources. the first data set was obtained from the database of the federal state statistics service (“rosstat”1) and contains information on gross value added, employment, 1 https://rosstat.gov.ru/ https://doi.org/10.15826/recon.2022.8.1.005 https://rosstat.gov.ru/ r-economy, 2022, 8(1), 57–67 doi: 10.15826/recon.2022.8.1.005 61 r-economy.com online issn 2412-0731 depreciation, and output in 13 economic sectors for the period from 2002 to 2018. the sectors used are agriculture, hunting and forestry, and fishing; mining; manufacturing; electricity, gas, and water production and distribution; construction; wholesale and retail trade; hotels and restaurants; transportation and communications; financial activities; real estate, rental, and service operations; public administration and military security; compulsory social security; education; health care and provision. all figures for value added as well as labor productivity were converted to constant prices in usd in 2005 prices using producer price indices as deflators2. in order to assess the robustness of our results, we also use as an alternative data source the world input-output database (wiod3), which contains more detailed information on 33 sectors of the russian economy from 2000 to 20144. thus, the manufacturing sector in rosstat is broken down in the wiod into 24 subsectors. the data come from the latest available 2016 edition and supplementary socioeconomic accounts (wiod sea), which provides information on annual trade flows of intermediate goods, the amount of goods and services sold to final consumers, total gross out2 investing, https://ru.investing.com/ 3 https://www.rug.nl/ggdc/valuechain/wiod, release 2016. 4 the global input-output database covers 56 sectors of the economy, but contains non-zero values for russia for 33 sectors: crop and livestock production, mining, food production, clothing production, timber production, paper and paper products production, coke production and production of petroleum products, manufacture of chemical products, manufacture of rubber and plastic products, manufacture of other non-metallic mineral products, manufacture of base metals, manufacture of computers, manufacture of machinery and equipment n.e.c., manufacture of automobiles, manufacture of furniture, electricity, construction, retail trade, wholesale trade, land transport, water transport, air transport, warehouse services, accommodation and catering services, telecommunications, financial services, operations with real estate, administrative and support activities, public administration and defense, education, human health and social work, other service activities. therefore, in the future, we will analyze only these 33 industries. put, value added, and employment. all these data are in u.s. dollars and adjusted for inflation using national price indexes with a base year of 2010. using a more disaggregated wiod database, we will thus be able to get an estimate of labor reallocation not only between the large sectors such as agriculture and manufacturing, but also between the industries within manufacturing that vary widely in their level of productivity. this, in turn, will provide a more accurate estimate of the effect of competitive selection. table 1 presents descriptive statistics for the sectors of the russian economy and thus allows the reader to form their first impression of the data which we will work with. this table shows that industries grow at an average rate of 2% per year (the median is 4%, indicating negative values in a number of sectors). the high value of the standard deviation of value-added growth (0.22) indicates significant heterogeneity in the growth rates between sectors of the russian economy. looking at this table, we can conclude how unevenly labor productivity is distributed across different sectors of the economy. the standard deviation of the logarithm of labor productivity is 0.74. this means that  an industry where labor productivity is by one standard deviation above the mean is four to five times more productive than an industry where labour productivity is by one standard deviation below that level (e1.5 = 4.5). if we consider the wiod data instead of the rosstat data, the spread is even larger, which can easily be explained by the fact that a more detailed division of the economy into subsectors increases the difference between its most and least productive industries. all this clearly shows the high heterogeneity of labor productivity between sectors in the russian economy which we discussed earlier. in the future we are planning to assess how this heterogeneity led to the overflow of labor resources between the sectors. table 1 descriptive statistics of the data used labor productivity value-added growth number of observations, in units average value, in usd median, in usd standard deviation, in logarithm number of observations, in units average value, in usd median, in usd standard deviation, in logarithm data rosstat 221 21525.6 13995.99 0.74 208 0.020 0.04 0.22 data wiod 495 18997.9 11578.38 0.87 462 0.016 0.04 0.16 own calculations based on rosstat data https://rosstat.gov.ru/ and wiod https://www.rug.nl/ggdc/valuechain/long-runwiod?lang=en (accessed on 13.03.2021). https://doi.org/10.15826/recon.2022.8.1.005 https://ru.investing.com/ https://www.rug.nl/ggdc/valuechain/wiod https://rosstat.gov.ru/ https://www.rug.nl/ggdc/valuechain/long-run-wiod?lang=en.(accessed https://www.rug.nl/ggdc/valuechain/long-run-wiod?lang=en.(accessed 62 r-economy.com r-economy, 2022, 8(1), 57–67 doi: 10.15826/recon.2022.8.1.005 online issn 2412-0731 it is worth noting that many studies (de vries et al. 2015; mcmillan et al., 2014) show that high heterogeneity in labor productivity across sectors is a sign of a developing (but not yet developed) economy. they are the highest for the poorest countries and tend to decrease because of sustained economic growth and development. based on these results, it can be argued that russia can be classified as a still developing economy. following dosi et al. (2015), we measure labor productivity as the amount of value added per employee, where value added, in turn, is defined as revenue minus production and sales costs excluding labor costs. results applying the decomposition described in equations (1-4), we produced the results presented in table 2. the analysis based on rosstat data shows that the within-effect in the russian economy prevails. its share is approximately 71% against 29% for the between-effect. this suggests that the growth of the economy is caused to a greater extent not by the reallocation of resources from one sector to another but by the growth in productivity in the sectors themselves. nevertheless, the role of competitive selection in the growth of aggregate labor productivity is positive, which is good news, especially in view of the more modest (and sometimes close to zero) values obtained for firm-le vel data (savin et al., 2020). it is worth noting that voskoboynikov and gimpelson investigating the data that are similar to ours but for an earlier period (1995–2012) came to similar conclusions (in their study, the share of between-effects was about 23%). this indicates that in the later period, the contribution of labor reallocation to the growth in aggregate labor productivity increased slightly. moreover, using the more disaggregated wiod data, the total share for the between-effect becomes larger than for the within-effect, indicating that in the russian economy the growth of aggregate labor productivity is still largely due to the reallocation of labor resources from low-productive activities to more productive ones. the difference in the results obtained by using different data sources can be explained by the fact that one sector of the economy from the rosstat database is divided into several smaller sectors in the wiod database. thus, using the wiod data, we can better estimate the flow of labor between sectors of the economy. indeed, a person who used to work in metal production is more likely to move to a job in metal production than in mining or in the financial sector. this can be explained by the fact that the above transition will require a different set of knowledge and skills as well as work experience, which is difficult to obtain even by undergoing special training and advanced trai ning. from this we can conclude that a more accurate assessment of labor reallocation on changes in aggregate productivity requires deeper sectoral detail in order to get a more accurate estimate of competitive selection. regardless of the level of detail of the sectoral classifier, the results obtained in table 2 indicate that the russian economy showed a posi tive dynamic of structural change in terms of reallocation of labor resources from less to more productive sectors. previously, mcmillan et al. (2014) showed that while most countries in africa and latin america over the period 1990–2005 exhibited a negative between-effect, indicating a  negative structural change, only asian countries have managed to consistently achieve effective reallocation of labor to more productive sectors. our estimates place russia in the latter group of countries. there are several findings worth noting. first, the negative value of the between-effect can be interpreted as an indicator of the overall inefficiency of the economy: labor is transferred from more efficient sectors of the economy to less productive ones. second, for some years a negative sign of the within-effect can be observed, which indicates a decrease in labor productivity in the sector of the economy itself. in some years such a sign can be explained by a sharp fall of the national currency against the u.s. dollar. this interpretation is also true for the shares of these two effects, but only when the sum of the absolute values is positive. otherwise (for example, 2009 example for both databases) the interpretation of the signs of the shares is reversed (e.g. in 2009 the share of the within-effect was close to one, but in fact its contribution was negative). to take a closer look at where the labor force was flowing from and to where, in table 3 we calculated the ratios of employment in 2018 to the same figure in 2002 for all the 13 major sectors of the economy as well as the absolute change in the number of employed over the same period. we use rosstat data here rather than the wiod to get a more general picture of labor shifts among the major 13 sectors of the economy. similar results can be obtained for the 33 sectors of wiod. https://doi.org/10.15826/recon.2022.8.1.005 r-economy, 2022, 8(1), 57–67 doi: 10.15826/recon.2022.8.1.005 63 r-economy.com online issn 2412-0731 table 2 results of total labor productivity decomposition year rosstat wiod within effect between effect share of within effect share of between effect within effect between effect share of within effect share of between effect 2001 – – – – –140 160 –6.68 7.68 2002 – – – – –240 10 1.06 –0.06 2003 843 –5.69 1.01 –0.01 450 -20 1.06 –0.06 2004 1364 16.61 0.99 0.01 1010 100 0.91 0.09 2005 764 55.95 0.93 0.07 530 –070 1.16 –0.16 2006 1481 47.03 0.97 0.03 960 120 0.89 0.11 2007 1962 60.59 0.97 0.03 1390 170 0.89 0.11 2008 1038 92.97 0.92 0.08 2200 –140 1.07 –0.07 2009 –4944 –56 0.99 0.01 –3820 250 1.07 –0.07 2010 1099 24 0.98 0.02 760 –210 1.38 –0.38 2011 257 76.99 0.77 0.23 870 90 0.91 0.09 2012 10152 65 0.99 0.01 –500 180 1.56 –0.56 2013 –540 84 1.18 –0.18 –450 420 17.04 –16.04 2014 –4256 46.52 1.01 –0.01 –2040 150 1.08 –0.08 2015 –8058.2 11.25 1.00 0.00 – – – – 2016 32.01 14.09 0.69 0.31 – – – – 2017 791 29.13 0.96 0.04 – – – – 2018 –570 9.36 1.02 –0.02 – – – – total 1416.48 572.86 0.71 0.29 980 1230 0.44 0.56 source: own calculations based on data from rosstat and wiod. table 3 changes in the amount of labor used in economic sectors from 2002 till 2018 share in the total amount of labor used in the economy in 2002, % share in the total amount of labor used in the economy in 2018, % absolute change in the amount of labor used agriculture, hunting and forestry, fishing 13.20 7.32 –3412562.00 mining and quarrying 1.84 1.69 –21103.00 manufacturing 19.11 14.92 –2015144.00 production and distribution of electricity, gas and water 2.99 3.47 452949.00 construction 7.05 9.47 1932901.00 wholesale and retail trade 15.65 20.26 3777382.00 hotels and restaurants 1.70 2.55 646203.00 transportation and communications 8.09 10.11 1702070.00 financial activities 1.13 2.05 670665.00 real estate operations, renting and services 7.77 8.11 558955.00 public administration and military security; compulsory social security 4.97 5.41 511493.00 education 9.55 8.09 –581601.00 health care and social services 6.95 6.53 6536.00 source: own calculations based on rosstat data. we can see that the largest outflows were observed in agriculture and manufacturing. while the former is a natural process associated with the automation of production and characteristic of most transition economies, the latter is rather an unpleasant signal for the structure of the russian economy given the large role of manufacturing in the creation of value added. the largest inflow of labor resources, in turn, was observed in construction, wholesale and retail trade as well as transport and communications. construction and transport are sectors with relatively high labor productivity and it is a good signal to the russian economy. figure 1 shows the more detailed dynamics of employment in these sectors of the economy. https://doi.org/10.15826/recon.2022.8.1.005 64 r-economy.com r-economy, 2022, 8(1), 57–67 doi: 10.15826/recon.2022.8.1.005 online issn 2412-0731 figure 1. dynamics of the number of employed labor in various sectors: (a) agriculture, (b) manufacturing, (c) construction, (d) wholesale and retail trade, and (e) transportation and communications. the number of employed (people) is shown vertically, the years are shown horizontally. source: our own calculations are based on rosstat data. accessed on 18.03.2021. 0 2000000 4000000 6000000 8000000 10000000 2000 2005 2010 2015 2020 0 5000000 10000000 15000000 2000 2005 2010 2015 2020 0 2000000 4000000 6000000 8000000 2000 2005 2010 2015 2020 0 5000000 10000000 15000000 2000 2005 2010 2015 2020 0 2000000 4000000 6000000 8000000 2000 2005 2010 2015 2020 (а) (b) (c) (d) (e) this result can be interpreted in different ways. on the one hand, the outflow of resources from manufacturing can hardly be called a positive trend for the russian economy. on the other hand, the inflow of resources in transport and construction is a positive trend. interestingly, mining has lost labor resources, while sectors such as financial activity and hotel business have increased. overall, the resulting picture differs from the one obtained earlier by voskoboynikov and gimpelson (2015) for 1995–2012, where the labor reallocation was into manufacturing. thus, we found that the role of competitive market selection for labor productivity growth has increased somewhat in russia in recent years, but predominantly this reallocation occurs not in (but rather from) manufacturing but in construction, transport, and trade. this suggests that we should consider how to stop the outflow of labor from manufacturing by creating innovative directions in production and encouraging domestic enterprises to expand their market share both in the domestic market and by exporting their goods abroad (savin and winker, 2009; savin and winker, 2012). https://doi.org/10.15826/recon.2022.8.1.005 r-economy, 2022, 8(1), 57–67 doi: 10.15826/recon.2022.8.1.005 65 r-economy.com online issn 2412-0731 conclusions labor productivity varies widely across sectors in the russian economy. this indicates the potential for economic growth through the reallocation of labor from less productive sectors to more productive ones as well as the potential for productivity growth within the sectors themselves. we assessed the role of these two factors in changing the aggregate productivity of the russian economy. to test the reliability of the results obtained, a decomposition was carried out on two data sets: rosstat and wiod. the results of the decomposition lead us to a conclusion about the presence of competitive selection in the sectors of the economy, which indicates positive structural changes and the flow of resources from less to more productive sectors. for the rosstat data, the ratio of the effect of changes in labor productivity and labor resource spillovers by sector on aggregate labor productivity over the period was 0.71/0.29, and for the wiod data it was 0.44/0.56. this indicates that labor resources are more likely to be reallocated to related sectors (e.g., between manufacturing industries). it was found that as the granularity of sectors in the sample increases (from 13 to 33), the effect of resource spillovers begins to dominate the economy over productivity growth within the sectors themselves. thus, we can conclude that for a more accurate assessment of labor reallocation on changes in aggregate productivity, a deeper sectoral detail is needed to obtain a more accurate estimate of competitive selection. we also determined that the largest outflows of labor were in agriculture and manufacturing, while the inflows were in construction, wholesale and retail trade. this study can be useful in determining industrial policy priorities to maintain labor resources in productive sectors of the economy in the future. references baily, m.n., hulten, c., campbell, d., bresnahan, t., & caves, r.e. 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(in russ.) doi: 10.32609/0042-8736-201511-30-61 information about the authors ivan v. savin – professor at the department of economics, graduate school of economics and management, ural federal university (19 mira str., 620002 ekaterinburg, russia); researcher, institute of environmental science and technology, autonomous university of barcelona (icta-icp building (z), uab campus, cerdanyola del vallès, 08193 barcelona, spain); e-mail: ivan.savin@uab.cat denis k. letyagin – ma student at the department of economics, graduate school of economics and management, ural federal university (19 mira str., 620002 ekaterinburg, russia); e-mail: denletyagin@gmail.com article info: received january 23, 2022; accepted march 18, 2022 информация об авторах савин иван валерьевич – phd, профессор, кафедра экономики, институт экономики и  управления, уральский федеральный университет (россия, 620002, екатеринбург, ул.  мира,  19); научный сотрудник, институт экологических наук и технологий, автономный университет барселоны (испания, 08193 серданьола-дель-вальес, icta-icp); e-mail: ivan.savin@uab.cat летягин денис константинович – магистр экономики, кафедра экономики, уральский федеральный университет (россия, 620002, екатеринбург, ул. мира, 19); e-mail: denletyagin@ gmail.com информация о статье: дата поступления 23 января 2022 г.; дата принятия к печати 18 марта 2022 г. 作者信息 萨文·伊万·瓦列里耶维奇——在读博士，教授，经济系，经济管理学院，乌拉尔联邦 大学（俄罗斯，邮编: 620002, 叶卡捷琳堡，米拉街19号）；科研人员，环境科学与技术学 院，巴塞罗那自治大学（西班牙，邮编：08193，萨尔达尼奥拉-德尔巴列斯，icta-icp研 究中心）；邮箱：ivan.savin@uab.cat. 莱蒂亚金·丹尼斯·康斯坦丁诺维奇——经济系硕士，经济系，乌拉尔联邦大学（俄罗 斯，邮编: 620002, 叶卡捷琳堡，米拉街19号）；邮箱：denletyagin@gmail.com. https://doi.org/10.15826/recon.2022.8.1.005 https://doi.org/10.1111/j.0008-4085.2004.00009.x https://doi.org/10.1257/9780203387061 https://doi.org/10.32609/0042-8736-2015-11-30-61 https://doi.org/10.32609/0042-8736-2015-11-30-61 mailto:ivan.savin@uab.cat mailto:denletyagin@gmail.com mailto:ivan.savin@uab.cat mailto:denletyagin@gmail.com mailto:denletyagin@gmail.com mailto:ivan.savin@uab.cat mailto:denletyagin@gmail.com a. s. luchnikov, r. s. nikolaev r-economy vol. 3, issue 4, 2017 212 doi 10.15826/recon.2017.3.3.024 udc 331.3 a. s. luchnikov, r. s. nikolaev perm state national research university (perm, russian federation; e-mail: aluchnikov@yandex.ru) economic framework optimization as an instrument for regional development modern economic development of territories requires a comprehensive, interdisciplinary approach. this article discusses the geographical model of the supporting framework of economy (sef) as a constructive tool in regional economic policy. the sef has a linear-nodal structure and includes such key elements as large urban agglomerations (economic nodes and local clusters), economic centers and connecting lines between the basic elements of regional economy. sef is a universal concept which allows us to describe the main features of economic territorial organization, its shortcomings and advantages, and identify areas for implementation of large investment projects. this article focuses on the case of the volga federal district, in particular perm region, and analyzes the main problems in this region’s economic development. these include the hypertrophied role of the regional capitals, struggling periphery, lack of sufficient transport, marketing, production and other connectivity between different elements of the regional network for the development of a large domestic consumer market; and shortage of innovation and modern investment infrastructure. a particular problem of regional economy is the limited accessibility of some territories and the impossibility to build the shortest routes between disparate centers and nodes, which reduces the productivity of labor and the competitiveness of manufactured goods and services. based on the analysis of these problems in the economic territorial organization by applying the sef model, we outline possible solutions to this region’s problems. keywords: territorial organization of regional economy, supporting economic framework, linear-nodal structure, hypertrophied economic node, distribution of functions between economic elements, transport connectivity of regional economy. introduction as many regions are transitioning to the mode of ‘self-governing’ and are trying to become more selfsufficient, their economic efficiency, which includes efficient use of the available resources, becomes a matter of vital importance. economic prosperity of regions increases the wealth and standards of living of their population. economic stimulation can take different forms and focus on different spheres: for instance, it can allow room for a variety of ownership forms; promote technological innovation; enhance the region’s independence from the intraregional economic ties; encourage cooperation between enterprises of different sizes and profiles, and so on. the geographical distribution of economic objects and the results of their activities are of utmost importance in this respect. the basis of the territorial organization of regional economy in russia is the supporting economic framework (sef), which has a linear-nodal structure. let us consider the possibilities of applying this model in theory and in practice by focusing on the case of perm region, which is one of the oldest industrial regions of russia and has now reached a turning point in its economic history. methodology the concept of a supporting framework in territorial systems was first introduced by nikolai baransky in the 1920s, who referred to such framework as the ‘carcass of the territory’. his followers developed this theory by putting forward the concept of a supporting frame of a settlement between the 1960s and 1980s. at a later stage, the concept of an ecological framework of regions was proposed. in the 1990s, human geography and related sciences (for instance, geo-informatics and territorial planning) started using the concept of framework when referring to the spheres of transport, tourism and recreation. today we can talk http://r-economy.ru/ mailto:aluchnikov@yandex.ru a. s. luchnikov, r. s. nikolaev r-economy vol. 3, issue 4, 2017 213 about a regional framework of sustainable development as a combination of elements of territorial structure and spatial relations inside the region. nowadays ‘framework’ and other related concepts are widely used in theoretical and applied geographical studies within the so-called framework approach. table 1 illustrates the evolution of this approach. table 1. evolution of the framework approach in geography concepts scholars and spheres of application period framework (‘carcass’) of the territory nikolay baransky [1] late 1920s supporting framework of a settlement boris khorev [2], georgy m. lappo, pyotr polyan [3] 1960s-1980s ecological framework of regions vladimir preobrazhensky [4] 1980s-1990s transport, tourism, recreation, historical and cultural planning framework in documents of territorial planning, cityplanning code of the russian federation [5] midand late2000s regional framework for sustainable development nikolay nazarov, tatiana subbotina, mikhail sharygin [6] mid-2000s the evolution of the framework approach in geographical studies was accompanied by the development of theoretical and empirical research in this sphere. initially, the ‘framework’ was seen as a static phenomenon (‘carcass of the territory’) and this term was applied to describe territorial patterns of settlements or other economic and regional objects. following the proliferation of system-structural methods, the sef is currently considered to be a dynamic phenomenon that involves constant transformations of territorial configurations inside the specific spheres of human life and among them. the sef also encompasses the ever-changing spatial relations between different locations and areas. therefore, it is important to emphasize the dual nature of the framework concept: it combines inertia and dynamism, concentration and dispersion, differentiation and integration, a tendency toward self-development and external regulation, and so on (see figure 1). fig. 1. the main aspects of the framework approach in geographical studies among the different frameworks mentioned in scientific literature and formal documentation, the supporting frame of the regional economy (sef) is one of the most important and useful concepts. we define it as a concentrated invariant of territorial organization of economy, a model for spatial combination of the largest (central, focal) elements of the territorial structure of a regional economy connected through feeding lines and systems. the sef has a linear-nodal structure (see figure 2) as it contains both nodes and linear components. the most complex elements of sef are areas. among the nodes, we can distinguish between economic centers and hubs as well as individual objects of production, market, innovative, scientific and technical infrastructure, which are seen as optional elements although their importance has been growing in regional supporting framework static properties dynamic properties research of the territorial organization of society, its advantages and disadvantages research of the positive and negative transformations in the territorial organization of society. territorial organization can also be planned, regulated and managed. http://r-economy.ru/ a. s. luchnikov, r. s. nikolaev r-economy vol. 3, issue 4, 2017 214 the recent years. as for areas, we can distinguish between economic areas (agglomerations, territorial complexes, regional and clusters) and zones formed in the process of long-term and joint development of various territorial and economic combinations. linear objects are distribution highways (general and specialized transport routes, energy and electronic communication lines, telephone communications), connecting elements of the sef and ensuring their interaction with each other [7]. at present, the main documents of territorial planning in russia refer to the framework of urbanization, transport, tourism and recreation and even historical and cultural resources, but they do not mention the framework of economic development. however, modeling of such frameworks may be valuable when designing policies for optimization of different aspects of regions’ economic development. further we are going to describe some of the ways that sefs can be used to enhance regional development by focusing on the case of the volga federal district and in particular perm region. fig. 2. general scheme of the regional sef [7] 1. the sef model can help regional governments address the problems their regions are facing. the agglomeration-nodal structure of regional development means that there is one economic hub that dominates over the others while the peripheral areas are in decline. table 2 shows hyperconcentration of value in different industrial parts of the regional center. this indicator – the total value of manufactured goods – allows us to avoid a possible statistical error, which usually manifests itself in exaggerating the value of extracted natural resources in the headquarter-city of the extracting company instead of the area where these resources are extracted. on the contrary, if we take into account only the profitability of the processing types of industry, we will be able to assess the concentration of added value in the regional capital and the peculiarities of added value redistribution among other cities and territories. economic hubs economic centers economic points transport and other infrastructural objects objects of innovation infrastructure transport highways non-material connections economic areas (agglomerations, territorial complexes, regional clusters) http://r-economy.ru/ a. s. luchnikov, r. s. nikolaev r-economy vol. 3, issue 4, 2017 215 table 2. dynamics of the share of regional capitals according to the total value of manufactured goods in 20052015, %1 regional center 2005 2007 2009 2010 2011 2013 2015 izhevsk 57,6 60,6 46,2 45,8 48,4 48,8 50,5 yoshkar-ola 40,3 33,4 35,2 33,7 34,2 38 32,8 kazan 20,9 17,6 23,1 21 19,5 19,9 20,9 kirov 49 51,3 45,2 46 44,7 43,7 42,7 nizhny novgorod 33,4 30,2 21,8 22,3 22,9 29,8 29,5 orenburg 20 16,6 18,5 17 18,1 41,3 38,7 penza 64,7 68,3 67,1 66,9 64,9 64,9 48,6 perm 56,7 61,2 64,2 65,5 64,2 68,2 57 samara 24,7 26,3 30,7 28 26,8 25,2 25,8 saransk 46,5 51,4 49,4 48,1 44 43,1 44,7 saratov 50,1 47,7 51,5 50,2 43,3 46,6 41 ufa 52,6 49 58,6 58,3 57,4 67 52,7 cheboksary 61,2 65,6 66,7 65,2 50,1 59,9 52 ulyanovsk 58,6 64,3 72,5 75,7 69 64,3 71,1 average share by years: 45,45 45,96 46,48 45,98 43,39 47,19 43,43 the most interesting situation is in ulyanovsk, penza region, udmurtia, bashkortostan, chuvashia and perm region. in each of these regions, the role of ‘metropolitan’ cities in the value of manufactured products in 2005-2015 was more than 50 %. in addition, until recently, the dynamics of this indicator was positive, which meant the growing influence of the regional center in the economic complex. a relatively more balanced situation is in samara and orenburg regions as well as tatarstan, where there are two or more established and regulated economic nodes (large industrial agglomerations) which receive some of the load from the capital ‘node’ (tolliati, orsk-novotroitsk, nizhnekamsk and naberezhnye chelny). they perform a significant part of their regions’ economic functions and compete for resources, people, finances and investment, ensuring a more even distribution of added value across the region and thus making their regional economies more balanced. when economic resources are concentrated in regional capitals, the so-called capital effect occurs, which has not been sufficiently studied in modern geographical and regional economic literature. this effect was described by alexander druzhinin and natalia zubarevich. according to the former, ‘in the regional political and economic contexts of post-soviet russia, the metropolitan areas (the largest cities) are rentoriented (they are oriented towards obtaining and redistributing rents, mostly resource and positional rents). the conditions that metropolitan areas are functioning in are determined by the dominance of economic and political monopolies. the monopoly on power (including the priority access to the resource potential of the territory) and on institutions creates conditions for emergence of metropolises; for their prolonged territorial, social and economic dominance and the ‘profit margin’ these metropolises receive on a regular basis (positional rent); for new quantitative and qualitative changes that demonstrate and support their 1 source: database on social and economic development of russian cities. retrieved from http://www.gks.ru/wps/wcm/connect/rosstat_main/rosstat/ru/statistics/publications/catalog/doc_1138631758656 http://r-economy.ru/ a. s. luchnikov, r. s. nikolaev r-economy vol. 3, issue 4, 2017 216 privileged status’ [8, p. 57]. alexander druzhinin also points out territorial-social segregation as one of the main problems that stem from the domination of a large city. in perm region, in 2015, the capital city (perm) concentrated 57% of the total value of the goods manufactured in the region. in 2016, perm also accounted for a large share of the region’s population (40%), attracting direct investment in the economic sector (50%), the total cost of industrial products (including extractive production, production and distribution of electricity) (69%). as a result, the economy and the population of peripheral areas started to decline. other problems include a sharp reduction in intra-regional connectivity and opportunities for development of the domestic market, concentration of added value within a limited number of cities. thus, perm can be compared to an island of extensive growth surrounded by the deteriorating periphery. figure 3 shows the distribution of the value of manufacturing industries between different economic nodes and centers of perm region. such situation is obviously abnormal and some serious policy adjustments are needed to solve this problem in the future. fig. 3. the distribution of value of manufacturing industries among groups of municipalities of perm region in 2015, %2 at the same time, we should not adopt a negative perspective on large cities as sources of problems for territorial development. different studies clearly show that for russia and many other countries with 2 source: database of indices of municipalities in perm region. retrieved from http://permstat.gks.ru/wps/wcm/connect/rosstat_ts/permstat/ru/municipal_statistics/main_indicators/ http://r-economy.ru/ a. s. luchnikov, r. s. nikolaev r-economy vol. 3, issue 4, 2017 217 transitional or developing economies, the importance of largest cities cannot be overlooked. according to cumulative models of development of economies and territories (in particular, h.hirsch’s model of a ‘cityvolcano’ [9]; f.perroux’s concepts of growth poles [10] and his followers j.-r. boudeville, j. r. lasuen; the diverging effects pointed out by g. myrdal; h. richardson's agglomeration economy [11]; j. friedmann's theory of center-peripheral relations, [12], further stimulation of a new type of economy is possible, mainly, in the key territorial elements, which are characterized by concentration of financial, industrial, scientific and educational resources for stimulating innovation in regional economy. an interesting idea was proposed by a.i. tatarkin, who pointed out that ‘nowadays the largest cities are leaders of investment, innovation, social processes, and points of economic growth. it is the strategy of their development that determined the country’s economic growth’ [13]. large cities have both the potential and the tools for becoming drivers of economic growth. large cities’ opportunities are connected with administrative and agglomeration effects. while administrative effects are more likely to have negative consequences, agglomeration effects, according to paul r. krugman [14], act as a ‘second nature’ factor that stimulates the development of regional economy. positive effects of the agglomeration approach are shown in figure 4. fig.4. positive agglomeration effects in regional development [15] thus, by adjusting agglomeration effects in regional development (they should be used in a balanced way), we can handle the situation when the largest city receives more advantages than any other cities, towns and settlements. in our opinion, the role of the largest city in regional and national development should be changed by balancing the interests of cities on different hierarchical levels and redistributing their regional functions. self-organization of urban space, the acquisition of excess profits (rents) and additional benefits should not be the main focus of the urban policy. in other words, regional capitals and large cities, which are the main poles of economic growth in the country, the ‘carcass’ of the territorial organization of modern russian society (sef), must participate in the lives of their subordinate territories, take responsibility for their development, create opportunities for equitable distribution of functions in the regions. as a result, the apparent centripetal tendencies that have developed in modern russia would be replaced by bilateral – centripetal and centrifugal – tendencies. the city of perm should become the leader of such new ‘smart’ and balanced development policy in the region. its main functions should include uniform organization of the regional space, creation of incentives for common and individual development, territorial branding, etc. the city has the necessary human, scientific and economic resources to accomplish these aims (see figure 5). for example, the innovative cluster – technopolis ‘novy zvezdny’ – is currently used for development and testing of new engines for space launch vehicles and aviation. other examples include the itand fiber-optic cluster ‘photonics’ and the pharmaceutical cluster that is now under construction. other branches of machine manufacturing and chemical industry have a great potential for clustering and enhancing the region’s competitiveness by completing new value chains, upgrading the existing ones and restoring old values chains in technological (energy-related) cycles. these include electro-technical and oilfield engineering; production of plastics and positive agglomeration effects in regional development more even distribution of regional functions, incl. territory management creating conditions for intensive development of the space surrounding any large city creating conditions for intensive development of the city's internal environment impulses for internal and external development of the whole region http://r-economy.ru/ a. s. luchnikov, r. s. nikolaev r-economy vol. 3, issue 4, 2017 218 other synthetic products made of hydrocarbons; wood processing; development of technologies for processing paper raw materials; development and production of new types of composite materials. fig. 5. modern positive (‘smart’) functions of perm in the regional sef in addition to positive leadership in the secondary sector of economy, perm is already a national leader in terms of culture: music, theater, and ballet. moreover, it is now being widely promoted as a tourist destination (the ‘great perm’ project). the secondary and higher education systems in the city are also developing. however, in our opinion, social technologies in health care and insurance medicine, leisure and recreation still leave much to be desired. the level of transport and logistics in the city is also lower than could be expected. these areas of development should become the main priorities for urban and regional planning in the future. another area of development involves transfer of certain functions (secondary economic activities) from the regional center (perm) to towns and villages of perm urban agglomeration. according to a.p. burian and a.m. korobeynikov [16], a similar or alternative development of perm urban agglomeration is based on deconcentration and decentralization of the socio-economic extensive development of perm and the accelerated development of small towns and villages on the periphery, enhancing the connection between its various elements and the integrated realization of the agglomeration’s potential. the functions that can be transferred from the regional capital to its immediate surroundings may include industrial processing (food, woodworking enterprises, medium-sized machine manufacturing enterprises that do not require skilled labor, etc.), tourist-recreational, cultural-cognitive, transport-logistic, and social services. among the most important agglomeration subcenters are towns dobryanka, krasnokamsk, okhansk, nytva; villages polazna, ilyinsky, yugo-kamsky, kukushtan, sylva and uralsky. a possible distribution of functions among these settlements is shown in figure 6. perm innovative clusters in manufacturing industries that correspond to the current scientific and technological trends development of traditional industrial production and application of advanced technologies for processing of raw materials innovative approaches in the development of secondary and higher education; development of the ‘schooluniversity’ system; support of economic development through implementation of programs of three national research universities development of culture (music, theatre, literature) creation of a tourist-attractive image of the region (the ‘great perm’ project) perm is an all-russian sports center http://r-economy.ru/ a. s. luchnikov, r. s. nikolaev r-economy vol. 3, issue 4, 2017 219 fig. 6. subcenters of perm urban agglomeration and their possible specializations 2. alignment of an economic landscape should result not only from redistributing the load of the region’s central nodes proportional to their capacities but also from stimulating the development of new functional economic centers on lower levels of the regional hierarchy. the strategy of improving the framework of the regional economy was described by jose r. lasuen [17], who studied the links between urbanization processes and spatial features of economy. he believed that growth poles (geographic locations with the potential for economic development) need not necessarily be related to the national economy and the export of goods abroad. a growth pole could be a regional complex of enterprises (rather than branches) located in one of the ‘geographical concentrations’ of the region and associated with its exports. growth poles appear due to the growth in the nationwide demand. through market ties (not only through links of supply and sales), the growth momentum from such centers is transferred to secondary industries and peripheral sectors. thus, growth poles can occupy the middle parts of economic areas and contribute to a more even distribution of regional income. according to j.r. lasuen, ‘development in developed countries is becoming less polarized, due to a more diversified business structure, which leads to a vast spatial spread of innovation and economic development, which means that developing countries can accelerate their growth by creating diversified corporate structures that reduce the severity of polarized strategy’ [17]. following the ideas of the spanish scientist, we can note that economic centers located within the regional semi-periphery have potential for innovative growth. the most important task is to identify the local potential and to identify the optimal functions for new economic centers. moreover, the search for new functions or modernization of the existing ones is also possible, for instance, most semi-peripheral parts of the ural-volga region traditionally specialize in industry while their new functions could lie in the service sector. development of the economic centers with the help of modern technologies based on infrastructural sylva: food production, farming, kukushtan: transport and logistics, polazna: transport and logistics, tourism and dobryanka: machine building, woodworking, yugokamskiy: transport and okhansk: transport and logistics, food il’inskiy: woodworking, food production, tourism krasnokamsk: transport and logistics, nytva: transport and logistics, http://r-economy.ru/ a. s. luchnikov, r. s. nikolaev r-economy vol. 3, issue 4, 2017 220 and managerial mechanisms and encouraging these areas to capitalize on their geographical and other advantages can also be a point (or focus) of growth of these territories. in our opinion, the following assumptions are relevant for qualitative growth and modernization of the territorial-industrial combinations that have developed in the semi-periphery of perm region: a) studies of technological added value chains (in the form of energy and production cycles) [18] in order to improve the main production process and develop auxiliary (including environmental and recycling) technologies; b) stimulation of industrial production through innovation and development of investment infrastructure. in the first sphere, we can point out that energy and production cycles (or epc, the term introduced nikolay kolosovsky) include technological processes that allow us to combine various stages of raw materials processing and energy transformation. analysis of the existing chains enables us to anticipate the development of new types of industrial activity (with higher added value), and to plan the integration of industries for recycling of industrial waste and inter-branch relations into other types of manufacturing industries. thus, epcs comprise geographic, technological, economic, environmental, innovative and other aspects of production. table 3 shows that it is possible to modernize industry in perm region by targeting specific epcs in the region’s industrial centers and by capitalizing on the territory’s unique potential. table 3. energy and production cycles at industrial centers of perm region industrial center energy and production cycles manufacturing industries gubakha gas-chemical cycle production of synthetic resins, plastics, technical spirits and related products, nitrogenous compounds timber and wood chemical cycle hydrolysis of wood with the production of food and technical spirits, wood-fiber boards, dry lumber kungur industrial-agrarian cycle manufacturing of confectionery, grain products, meat and milk products industrial-building cycle products from limestone rocks, incl. wall panels, roofing materials group of machine-building cycles production of equipment for oil and gas extraction, construction industry, metal processing lysva pyrometallurgical cycle of ferrous metals modern types of steel and rolled products, metal products, blanks for machine-building enterprises group of machine-building cycles electro-technical engineering, production of equipment for oil and gas extraction, instrument engineering tchaikovsky group of machine-building cycles production of equipment for oil and gas extraction, production of household appliances, instrument engineering gas-chemical cycle processing of petroleum gas for manufacturing of simple and complex polymers, synthetic fibers and threads, synthetic rubber and rubber products particular importance should be given to the development of new types of production in local epcs in towns kudymkar, osa, vereschagino, chusovoy and kizel. these towns used to be reasonably stable industrial centers, but today their industy is declining and their contribution to the regional economy has reduced. it is possible to realize production functions through the development of manufacturing, engineering, innovation, service and investment infrastructure in these areas, which may include establishment of http://r-economy.ru/ a. s. luchnikov, r. s. nikolaev r-economy vol. 3, issue 4, 2017 221 business incubators, industrial parks, technoparks, local innovative clusters, and so on. the choice of locations for infrastructural objects is also a vital planning task. despite the fact that industrial functions still determine the trends (often negative) in municipal and regional economy of perm region, it becomes clear that gradual but systematic transformation of economic functions is required. more emphasis should be made on social services. as we have indicated earlier, the leader in this sphere is the regional capital, but towns and districts of the regional semi-periphery and periphery can also be actively involved in this process. in some of them (tchaikovsky, lysva, gubakha, and kudymkar), post-industrial functions are already important components of the urban economy, affecting the rebranding of the territory, investment attraction, the life of the local community, etc. we can provide some examples of such transformations. the town of tchaikovsky is a major center of musical culture not only of regional but also of national significance. the town has a theatre of comedy and drama and a music school. it also hosts the national competition of young composers named after peter tchaikovsky. one more postindustrial function of this town is the development of sports and sports infrastructure. on the territory of village prikamsky, located near tchaikovsky, there is the federal training center of the russian olympic team ‘snowflake’. thus, tchaikovsky is a well-known center of the country’s sports life, a popular venue for russian and international sports forums (russian and international summer biathlon championships, the summer grand prix stage for ski jumping, etc.). a more significant role in the future will be played by tourist-recreational (ecological, sport, historical and cultural, etc.) and transportlogistic functions (exits from the western urals to the middle volga region). fig. 7. development potential of the sef of perm region http://r-economy.ru/ a. s. luchnikov, r. s. nikolaev r-economy vol. 3, issue 4, 2017 222 in gubakha, a town located in the east of the region, local inhabitants are interesting in changing the urban environment and landscape by developing the post-industrial sector of economy. among the main service functions of this town there are tourist-recreational (ski center, fishing, festivals); cultural (theaterstudio ‘dominanta’, participation in various russian theater festivals; a unique museum of coal; interactive displays and games offered by the town library); and sports (competitions in sport fishing, ski cross). the growth of the postindustrial sector is accompanied by changes in the attitudes of the local inhabitants to their town, changes in the urban infrastructure (small architectural forms, year-round ice rink, a park of culture and recreation) and renovation of streets and squares. so, tourist-recreational, transport-logistical, sports, cultural and educational, financial and other services could stimulate economic life in small and medium-sized towns of the ural-volga region. in general, the two spheres that we have indicated can make the region’s sef more balanced. this process should involve careful strategic and territorial planning as well as active involvement of the local population (see figure 7). we are convinced that as a result, the region's economy will be less concentrated in the capital city and that more even distribution of income will provide more resources to the struggling peripheral areas. 1. transport systems and nets of regions, especially their territorial structure, require modernization. for the economic and socio-demographic development of the country, it is necessary to optimize transport and logistics flows [19]. optimization of transport and logistics will accelerate innovation processes in regional and national economies. optimization also implies improved transport connectivity between economic entities inside the region and between different regions, which means cutting transportation costs: temporal, spatial, material, financial and so on [20]. transport connectivity of economic nodes does not always coincide with the actual flows associated with technological, economic, sales and marketing other connections. on the one hand, the economic framework forms a transport frame and, on the other hand, the transport frame is necessary to form an economic framework. in a certain period of regional development, both of these processes become interconnected and run simultaneously. at later stages, the economic framework can be transformed without taking into account optimization of the transport system, or vice versa, the transport framework can develop or deteriorate, regardless of the economic framework transformation (see figure 8). the most obvious way to optimize the economic framework is to adjust the flows to the existing transport infrastructure. the processes of expansion, rectification, reduction, variation (or alternativization) are essential for the development of transport and logistics systems. co-development of several frameworks occurs asynchronously due to many factors of both natural (endogenous) and subjective (exogenous) character. if the time and resources are unlimited, all the locations constituting the territorial framework or the economic framework tend to be connected by shortest paths and by several means of transport. in the context of competitive economy and market relations as well as limited opportunities and resources, transport planning is based on a complex hierarchy of priorities and values. http://r-economy.ru/ a. s. luchnikov, r. s. nikolaev r-economy vol. 3, issue 4, 2017 223 fig. 8. formation of transport and economic frameworks at a certain moment, the transport frame starts expanding extensively, encompassing more and more new locations. actively interacting locations tend to reduce the time distances between each other, although sometimes it takes some time to achieve this effect. hydrographic and orographic objects are the most serious obstacles [21]. but if the strength of communication between such locations is great and they manage to maintain stable interaction and the regular flows of goods of sufficient volume, then overcoming the obstacles becomes just a matter of time. transport communication between such points gradually improves and the efficiency of transportation increases (see figure 9). another factor that shapes the configuration of land routes is that the network needs to cover as many locations as possible, which creates additional potential for the development of new industries and can be a factor in the transformation of the settlement system. this potential, however, is not always realized. in an ideal situation, with unlimited resources and time, all points will sooner or later be interconnected by shortest routes, thereby significantly reducing the transport and logistics potential of any nodes, formed due to the configuration of the transport network and (or) the availability of transport infrastructure. at the same time, some points in the transport system still have a higher logistics potential [22] due to the possibilities of distribution within the system and between the systems. this potential depends exclusively on the characteristics of settlement systems and their economies. it should be noted that in each type of resettlement there are strengths and weaknesses from the perspective of logistics. in some settlement systems, conditions for intrasystem logistics are more favorable, in others, on the contrary, competitive conditions are formed for intersystem logistics. http://r-economy.ru/ a. s. luchnikov, r. s. nikolaev r-economy vol. 3, issue 4, 2017 224 i. two actively interacting centers (a and b) are connected to each other indirectly ii. all centers are directly connected but with a high degree of curvature iii. all centers are directly connected with a minimum degree of curvature iv. although there is a transit flow (between a and b), a new transport and logistics node on the transit route does not evolve v. a large production center (b) loses its importance in the regional system and is attracted to another regional center (y) with which it has closer ties. the transformation of the industrial-technological relations (i) leads to transport-logistic restructurization of the system fig. 9. various scenarios of the formation of transport networks and frameworks a change in the spatial organization of economy and the transformation of production and technological links leads to a change in transport and logistics potentials and creates conditions for development of new nodes with the functions of accumulation and distribution of flows (see figure 9). one of the key indicators of the transport framework’s effectiveness is the degree of curvature of the real route between the actively interacting nodes within the economic framework. in fact, it reflects the deviation of the real routes between the points in the transport system from the minimum physical distances between them. the largest integral degree of curvature of the roads in perm region is observed for lysva (1.44) and krasnokamsk (1.41) (table 4). the integral index of the curvature of railways reflects the weak connection between railway junctions in the transport system of perm region, from which tchaikovsky is virtually excluded (the degree of curvature is 2.59) (table 5). http://r-economy.ru/ a. s. luchnikov, r. s. nikolaev r-economy vol. 3, issue 4, 2017 225 such deviation may be caused by the need to bypass settlements, physical and geographical objects. as a rule, such deviations insignificantly affect the curvature of the route. a significant index of curvature will be indicative of the fact that there is no direct communication between the points. in the case of a high level of socio-economic interaction between the points, the curvature of the communication between them should tend to the minimum. in reality, however, this is not always the case because one of the frameworks (‘carcasses’) is lagging behind the other in its development. table 4. degree of curvature of the real car route from the minimal (physical) distance between the ten largest cities of perm region i ii iii iv v vi vii viii ix x integral i. perm х 1,09 1,09 1,38 1,28 1,73 1,33 1,29 1,17 1,32 1,28 ii. berezniki 1,09 х 1,04 1,30 1,21 1,29 1,36 1,24 1,21 1,21 1,26 iii. solikamsk 1,09 1,04 х 1,30 1,19 1,26 1,34 1,21 1,18 1,20 1,22 iv. tchaykovsky 1,38 1,30 1,30 х 1,47 1,49 1,24 1,38 1,38 1,23 1,36 v. kungur 1,28 1,21 1,19 1,47 х 1,38 1,36 1,21 1,29 1,34 1,29 vi. lysva 1,73 1,29 1,26 1,49 1,38 х 1,65 1,60 1,59 1,36 1,44 vii. krasnokamsk 1,33 1,36 1,34 1,24 1,36 1,65 х 1,34 1,81 1,50 1,41 viii. chusovoy 1,29 1,24 1,21 1,38 1,21 1,60 1,34 х 1,32 1,29 1,30 ix. dobryanka 1,17 1,21 1,18 1,38 1,29 1,59 1,81 1,32 х 1,28 1,33 x. chernushka 1,32 1,21 1,20 1,23 1,34 1,36 1,50 1,29 1,28 х 1,29 one of the most striking examples is the lack of direct transport connection between large economic centers perm and tchaikovsky. despite the fact that the nodes actively cooperate in chemical, petrochemical, machine-building, and food production, there is no direct railway communication between them (see figure 10). moreover, the automobile routes between them are curved considerably. physical and geographical characteristics of the territory, features of the settlement system and administrative boundaries are reflected in the ‘refraction’ of transport routes. table 5. degree of curvature of the real railway route from the minimal (physical) distance between the main railway nodes of perm region i ii iii iv v vi integral i. perm х 1,63 2,72 1,17 1,47 1,46 1,85 ii. berezniki 1,63 х 2,32 1,94 1,63 1,34 1,91 iii. tchaykovsky 2,72 2,32 х 2,68 3,37 2,34 2,59 iv. vereshagino 1,17 1,94 2,68 х 1,45 1,34 1,83 v. kungur 1,47 1,63 3,37 1,45 х 2,21 2,16 vi. chusovoy 1,46 1,34 2,34 1,34 2,21 х 1,86 another example is that for a long time there was no direct connection (185 km) between the two key economic centers of perm region – perm and berezniki. up until 1996, the car traffic between these two cities passed through kungur, lysva, and chusovoy, which increased the route to 400 km, that is, the distance was more than doubled (see figure 10). another example is the south of perm region, where the development of the transport framework did not lead to economic growth. despite the fact that the bimodal corridor connecting moscow, nizhny novgorod, kazan and ekaterinburg passes through these regions, there are no visible positive changes in the http://r-economy.ru/ a. s. luchnikov, r. s. nikolaev r-economy vol. 3, issue 4, 2017 226 economy of chernushka, kuyeda and oktyabrsky (see figure 10), which is a consequence of the discrepancy between the transport and economic frameworks. 1. for a long time there was no direct road connection between the main economic nodes in perm region – perm and berezniki. the direct road was built only in 1996. 2. there is no direct railway connection between perm and tchaikovsky, despite the fact that these nodes are actively interacting in the chemical industry. 3. although in the south of perm region, the transport network is sufficiently developed (there is a multimodal line), there are no significant economic benefits. fig. 10. various examples of asynchronous development of transport and economic frameworks the discrepancy between the development of the transport and economic frameworks can lead to liquidation of the existing industries that emerged at previous stages and thus cannot cope with the competition on the market. in perm region, such situation occurred in krasnovishersky district (liquidation of pulp and paper production) and in komi-permian district (dissolution of wood processing and food production enterprises). an opposite situation occurs when the transport frame is developing while the economic framework is deteriorating. thus, the bimodal meridional corridor solikamsk-chusovoy was not sufficient for building new large production facilities in the area of the former kizelovsky coal basin. another important area of optimization of transport frameworks is alleviating the load on large economic and administrative centers. if these nodes are overloaded, it becomes necessary to create a transport-logistic buffer on their periphery in the form of logistics infrastructure (terminals, centers, complexes). such transport-logistic buffer will allow to reduce congestion by accumulating and distributing cargo flows in space and time, thus helping the centers to cope with some of their transport problems. in perm region, due to its specific transport configuration, a large number of forced transit flows pass through perm [23]. therefore, it is necessary to create a logistic buffer for perm agglomeration along the line of chusovoy – kungur – kukushtan – yugo-kamsky – okhansk (a kind of ‘deep southern bypass’ around perm). the above-described list of ways of sef optimization is by no means exhaustive. all these ways should be considered as instruments of sustainable development, aimed at improving the quality and standards of living in the region. http://r-economy.ru/ a. s. luchnikov, r. s. nikolaev r-economy vol. 3, issue 4, 2017 227 acknowledgements the research was carried out at the expense of a grant from the russian science foundation (project no. 17-78-10066) “optimization of the transport and logistics system of russia and the regions as an instrument of sustainable development”. references 1. baransky, n. n. 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(2013). prostranstvenno-vremennaya struktura territorial'noy transportno-logisticheskoy struktury permskogo kraya [spatial-functional structure of the territorial transport-logistical system of the perm region]. perm. 21. rodrigue, j.-p., comtois, c., slack, b. (2009). the geography of transport systems. routledge. 22. hesse m., rodrigue, j.-p. (2004). the transport geography of logistics and freight distribution. journal of transport geography, 12 (3), 171–184. 23. nikolaev, r. s. (2013). funktsional'nyye i formatsionnyye osobennosti transporta i logistiki na regional'nom i mestnom urovnyakh (v sluchaye permskogo kraya) [function and formation features of transport and logistics in regional and local levels (the case of perm region)]. upravleniye ekonomicheskimi sistemami: nauchnyj elektronnyj zhurnal [management of economic systems: scientific electronic journal]. kislovodsk. authors luchnikov andrey sergeevich – lecturer of the department of social and economic geography, perm state national research university (15, bukirev st., perm, 614990, russian federation; e-mail: aluchnikov@yandex.ru) nikolaev roman sergeevich – candidate of geography, senior lecturer of the department of social and economic geography, perm state national research university (15, bukirev st., perm, 614990, russian federation; e-mail: rroommaa27@mail.ru) http://r-economy.ru/ mailto:aluchnikov@yandex.ru mailto:rroommaa27@mail.ru 208 r-economy.com r-economy, 2022, 8(3), 208–218 doi: 10.15826/econ.2022.8.3.017 online issn 2412-0731 original paper © lazanyuk, i.v., mambu diu, d., 2022 doi 10.15826/recon.2022.8.3.017 udc 339.5, 339.9 jel f13, f51, f55 angola’s economy under sanctions: problems and solutions i.v. lazanyuk , d. mambu diu peoples’ friendship university of russia (rudn), moscow, russia,  lazanyuk-iv@rudn.ru abstract relevance. africa is the continent most targeted by sanctions. african states were made subject to sanctions by the united nations and various regional organizations such as the african union, economic community of west african states, and the european union. there is, however, still a lack of understanding of these sanctions’ intended and unintended effects in the african context, which is the research gap this study seeks to address. research objective. this paper analyzes the role and mechanisms of the sanctions imposed by western countries (especially the usa) against angola and other african states to achieve certain geopolitical goals. data and methods. this study relies on the comprehensive and recently updated dataset of the global sanctions data base (gsdb). the gsdb lists over 1,101  sanction cases by country and international organization. sanctions are classified according to the three parameters: their type, objective and degree of success. the methodological framework of this study comprises the historical-logical, statistical, comparative, and analytical methods. results. we analyzed the dynamic of the macro-economic indicators targeted by the sanctions against angola and its political elite in 1995–2021 and found that the effects of these sanctions were not very profound. the un sanctions, however, had a statistically and economically significant effect on the country’s economic growth as they led to a considerable exports shrinkage and decline in gdp. the latter effect was possible because angola’s economy is heavily reliant on oil exports. as the imports curbed, since 1995 angola’s trade structure has undergone some significant changes: the share of the imports from china grew by 12% between 1995 and 2019 while the share of france decreased by 8.2%, portugal, by 9.6%, and the usa, by 10.8% conclusions. analysis of the gsdb data has led us to the following conclusions: first, sanctions are becoming an increasingly popular tool of international relations; second, european countries are the most frequent users of sanctions and african countries are their most frequent targets; third, sanctions are becoming increasingly diverse; and, finally, the share of trade sanctions is decreasing while the share of financial and travel sanctions is growing. at the current stage, the effect of the sanctions is weak in comparison with the declared goals although they have a negative impact on the living standards in the target countries. keywords africa, economy, economic sanctions, sanctions policy, effectiveness of sanctions, angola, global sanctions data base acknowledgements this paper has been supported by the rudn university strategic academic leadership program. for citation lazanyuk, i.v., & mambu diu, d. (2022). angola’s economy under sanctions: problems and solutions. r-economy, 8(3), 208–218. doi: 10.15826/recon.2022.8.3.017 экономика анголы в условиях санкций: проблемы и решения и.в. лазанюк , д. мамбу диу российский университет дружбы народов, москва, россия;  lazanyuk-iv@rudn.ru аннотация актуальность. африка является континентом, который чаще всего подвергается санкционному давлению. африканские государства представляет собой точку слияния санкционной практики оон и различных региональных организаций, таких как африканский союз, экономическое сообщество западноафриканских государств и европейский союз. преследуемые цели часто различаются, но их объединяет то, что они нацелены на африканские государства. ключевые слова африка, экономика, экономические санкции, санкционная политика, эффективность санкций, ангола, глобальная база данных о санкциях https://doi.org/10.15826/recon.2022.8.3.017 https://doi.org/10.15826/recon.2022.8.3.017 mailto:lazanyuk-iv@rudn.ru r-economy, 2022, 8(3), 208–218 doi: 10.15826/recon.2022.8.3.017 209 r-economy.com online issn 2412-0731 цель исследования. цель данной работы проанализировать роль и механизмы использования таргетированных санкций западных стран против анголы и ряда африканских государств в интересах достижения геополитических задач стран запада и сша. данные и методы. данное исследование основано на основе обширного и обновленного набора данных из глобальной базы данных о санкциях. в данной базе собраны сведения о более чем 1101 санкциях по странам и международным организациям. санкции, представленные в данных базах классифицированы по трем параметрам: по видам, по политическим целям, по степени результативности. для достижения результатов исследования в работе использовались историко-логический, статистический, сравнительно-типологический и аналитический методы. результаты. проведенный анализ экономической динамики ряда макроэкономических показателей анголы, попавших под санкционное давление показал, что эффективность санкций, введенных против анголы, и  целевых санкций, ориентированных на различные рода политических элит, невысока. санкции оон оказывают статистически и экономически значимое влияние на экономический рост государства-мишени. в анголе под влиянием санкций значительно сократился экспорт и это привело к  сокращению ввп, так как экономика анголы базируется исключительно на экспорте нефти. также на фоне сокращения импорта, начиная с 1995 г. произошли структурные изменения географических партнёров анголы. доля импорта из китая выросла с 1995 г. на 12%, в то время как доли всех остальных сократилась, доля франции – 8,2%, португалии на 9,6%, сша – 10,8%. выводы. анализ санкций, применяемых к африканским государствам, согласно данным глобальной базы данных по санкциям (gsdb) позволил выделить несколько важных фактов: санкции со временем применяются все чаще; европейские страны являются наиболее частыми пользователями, а африканские страны – наиболее частыми целями; санкции становятся все более разнообразными, при этом доля торговых санкций снижается, а доля финансовых или туристических санкций увеличивается. современный этап санкций характеризуется низкой эффективностью по отношению к декларируемым целям, однако оказывает негативное влияние на качество и уровень жизни граждан, страны, которых подвергаются санционному влиянию. 制裁下的安哥拉经济：问题与解决方案 拉扎纽克 ，吉·曼布 俄罗斯人民友谊大学，莫斯科，俄罗斯；  lazanyuk-iv@rudn.ru 摘要 现实性：非洲是最常受到制裁压力的大陆。非洲国家是联合国制裁实施 和各种区域组织的结合点，如非洲联盟、西非国家经济共同体和欧盟。 他们的制裁目标往往不同，但它们的共同点都是都针对非洲国家。 研究目标：本工作旨在分析西方国家对安哥拉及一些非洲国家实施定向 制裁以实现西方国家和美国的地缘政治目标的作用和机制。 数据与方法：本研究基于来自全球制裁数据库的一组广泛且最近更新的 数据。这个数据库包含了超过1101个国家和国际组织的制裁信息。这些 数据库中提供的制裁根据三个参数进行分类：按类型、按政治目标、按 有效性程度。为了获得研究结果，文章使用了历史逻辑法、统计法、比 较类型法和分析法。 研究结果：对遭受制裁压力的安哥拉多项宏观经济指标的动态分析表 明，对安哥拉实施制裁和针对各类政治精英的定向制裁成效不高。联合 国的制裁对目标国的经济增长有统计学和经济上的重大影响。因为安哥 拉的经济完全基于石油出口，在制裁的影响下，出口大幅下降，这导致 了国内生产总值的下降。此外，在进口减少的背景下，从 1995 年开始， 安哥拉的地理伙伴发生了结构性的变化。自 1995 年以来，来自中国的 进口份额增加了 12%。而所有其他国家的份额均有下降，法国 – 8.2%， 葡萄牙 – 9.6%，美国 – 10.8%。 关键词 非洲，经济学，经济制裁，制 裁政策，制裁的有效性，安哥 拉，全球制裁数据库 致謝 本文得到了 rudn 大學戰略學 術領導計劃的支持。 благодарности работа выполнена при поддержке программы стратегического академического лидерства рудн. для цитирования lazanyuk, i.v., & mambu diu, d. (2022). angola’s economy under sanctions: problems and solutions. r-economy, 8(3), 208–218. doi: 10.15826/recon.2022.8.3.017 https://doi.org/10.15826/recon.2022.8.3.017 http://r-economy.com mailto:lazanyuk-iv@rudn.ru 210 r-economy.com r-economy, 2022, 8(3), 208–218 doi: 10.15826/recon.2022.8.3.017 online issn 2412-0731 introduction after colonialism in africa collapsed, the majority of african states had to choose an economic model and ways of integrating into the world economy. in the last 60 years, some african states have demonstrated considerable socio-economic growth (davidson, 2020). the average growth rate of gdp in benin, ghana, côte d’ivoire, tanzania, rwanda, and ethiopia exceeds 3%. following the 1.6% drop in 2020, in 2021 gdp rose by 6.9%. it is predicted that average growth in africa will slow down by 4.1% in 2022 and 2023. the majority of african economies, however, are heavily dependent on the exports of raw materials and agricultural products1. countries of the african continent have a significant demographic potential. a major barrier to their development is the problem of high unemployment among people of  different education levels. unemployment has a negative influence on public sentiment2. african states are going through crises inherent to the evolution of their systems of political control. to a certain extent the problems they face also stem from the desire of the international community and western countries in particular to retain their influence over their former colonies. to curb the risk of political instability spreading from africa to other countries of the world, the united nations and western states are using a variety of strategies and tools, including sanctions, although their efficacy, in our view, is debatable. african economies are often extremely vulnerable to exogenous shocks as the institutions in these countries are still immature and the literacy rates are low. all of the above makes it difficult for these countries to withstand the effects of sanctions imposed by the un or various regional organizations, including the eu. 1 african economic outlook, 2022. https://www.afdb. org/en/documents/african-economic-outlook-2022 (accessed: 14.07.2022) 2 world employment and social outlook: trends 2022. https://www.ilo.org/wcmsp5/groups/public/---dgreports/--dcomm/---publ/documents/publication/wcms_834081.pdf (accessed: 14.07.2022) the aim of this study is to conduct a comprehensive analysis of the actual mechanisms of western countries’ sanctions against angola and other african states in 1995–2021 and to evaluate the outcomes of these sanctions and their efficacy. the key questions this study focuses on are as follows: how effective were the sanctions imposed on angola? which macro-economic indicators proved to be the most sensitive in the cases of angola and other african countries? theoretical framework although sanctions have a long history dating back to ancient greece, it was not until the 20th century, especially after world war ii, that economic sanctions became more common and turned into a popular tool of coercive diplomacy. in the usa and other western countries there is growing consensus that economic sanctions are powerful tools to handle major foreign policy crises (peksen, 2019).  despite sanctions’ popularity as a foreign policy tool, there is still a perceived lack of understanding of  their intended and unintended socio-economic effects, which calls for further research in this area (felbermayretal, 2020). sanction mechanisms may be different but their effectiveness depends primarily on the strength of their impact on elite  interests  in the target countries (fituni, 2019; zakharov, 2021). there is a vast body of literature dealing with sanctions’ effect or lack thereof (dashti-gibson et al., 1997; davis et al., 2003; hart, 2000, grigoryan, 2019). there is substantial research evidence of the ne gative effects of economic sanctions on almost all types of economic activity: it was found, for instance, that the economic sanctions imposed by the un and usa affected gdp growth in the target countries (neuenkirch, 2015; neuenkirch & neumeier, 2015; nureev & busygin, 2017); their gross national product (gnp) (drezner, 2000; gharehgozli, 2017); the key economic variables (government consumption, imports, investment, income)  (dizaji and van bergeijk, 2013); and the banking sector (bolgorian, m., & mayeli, a., 结论：根据全球制裁数据库 (gsdb) 对非洲国家的制裁分析揭示了几个 重要事实：随着时间的推移，制裁的实施越来越多；欧洲国家是最频繁 的实施者，非洲国家是最频繁的目标；制裁正变得更加多样化，贸易制 裁的份额减少，金融或旅游制裁的份额增加。制裁现阶段的特点是相对 于所谓的目标，实际效率低下，但它对受制裁国家公民的生活质量和水 平产生了负面影响。 供引用 lazanyuk, i.v., & mambu diu, d. (2022). angola’s economy under sanctions: problems and solutions. r-economy, 8(3), 208–218. doi: 10.15826/recon.2022.8.3.017 http://r-economy.com https://doi.org/10.15826/recon.2022.8.3.017 https://www.afdb.org/en/documents/african-economic-outlook-2022 https://www.afdb.org/en/documents/african-economic-outlook-2022 https://www.ilo.org/wcmsp5/groups/public/---dgreports/---dcomm/---publ/documents/publication/wcms_83 https://www.ilo.org/wcmsp5/groups/public/---dgreports/---dcomm/---publ/documents/publication/wcms_83 r-economy, 2022, 8(3), 208–218 doi: 10.15826/recon.2022.8.3.017 211 r-economy.com online issn 2412-0731 2019). sanctions affect international financial flows (besedes, goldbach, & nitsch, 2017) and may instigate currency crises (dreger, kholodilin, ulbright, & fidrmuc, 2016; peksen & byunghwan, 2015). in some countries, sanctions may result in a decline in civil liberties, measured by the freedom house civil liberties index (adam, 2019). a  similar conclusion was made by peksen and drury (2009, 2010), who used the same index and found that sanctions have an adverse impact on the level of democratic freedoms: in the long-term, their effect is equivalent to a  one-point drop in the index. peksen (2009) and wood (2008) found similar effects using the human freedom index and political terror scale as dependent variables. sanctions-induced economic disruptions and problems in target economies distort the normal incentive structure, which leads to an increase of the shadow sector (early & peksen, 2019). the differential impact of the global economic system on global banking relationships depends on the type of sanctions. the consequen ces of global sanctions become more severe for countries with higher information asymmetries, captured by a high level of world uncertainty, an occurrence of crisis and shocks or by a weak institutional system (ha et al., 2021, sharova, 2019). moreover, there is a significant growth in the number of sanctions aimed at changing the policy of the target countries and countering terrorism (kassaye nigusie & ivkina, 2020). despite the vigorous debate revolving around the effectiveness of sanctions, there is still a perceived shortage of works about their impact on african countries. we have not found any papers reporting research on  the sanctions against angola. this fact is surprising since africa is the continent most targeted by sanctions imposed by the un and various regional organizations such as the african union, economic community of west african states, and the european union. the goals of the sanctions may be different but one thing that they have in common is that all of them are targeted at african states. according to the global sanctions database, while the un continues to use sanctions to end hostilities, regional organizations have cited unconstitutional changes to government as the principal reason to sanction african states (charron, 2015). the un security council (unsc) and regional organizations have been using sanctions as means of crisis management and control in africa. sanctions against african states may also be viewed as a way for the former colonial powers to control their former colonies after the end of the traditional colonial order. in other words, sanctions are part of the mechanism through which former colonial hierarchies are maintained in the modern  globalized post-colonial world (fituni, 2020). methodology and data to analyze the actual mechanisms of western countries’ sanctions against angola and other african countries, to evaluate the effectiveness of these sanctions, we used the data from the global sanctions database (gsdb) for 2020 and 2021. the gsdb contains data on more than 1,101 economic sanctions by country and international organization for the period between 1950 and 2019. the latest version of the database covers 381 previously unregistered sanction cases, including 75 cases from the period of 2016–2019. the gsdb classifies sanctions according to the three parameters: sanction type (for example, trade sanctions, financial sanctions, travel restrictions, etc.); sanction objectives; and sanction success. the second parameter can be used to divide sanctions into separate categories, for example, policy change, regime destabilization, war prevention, human rights, etc. the amount of data in the gsdb makes it suitable for a comprehensive analysis of the use of sanctions in the world in general and in africa and angola in particular. an important characteristic of the gsdb is its special focus on trade sanctions, which means that these data reflect the impact of sanctions on various spheres, including financial flows, tourism, etc. moreover, a more nuanced analysis of the gsdb data on the influence exerted by different types of sanctions can reveal the relationships between different sanction policies and the most effective types of sanctions with the maximum effect on target economies. the methodological framework of this study comprises the historical-logical, statistical, comparative, and analytical methods. results and discussion the gsdb encompasses unilateral, bilateral, and multilateral sanction cases over the period of 1950–2016 classified according to the three parameters: sanction type, objective and degree of success. an important advantage of the gsdb is that it comprises virtually all the cases of sanctions which, according to the organizations that imhttps://doi.org/10.15826/recon.2022.8.3.017 http://r-economy.com 212 r-economy.com r-economy, 2022, 8(3), 208–218 doi: 10.15826/recon.2022.8.3.017 online issn 2412-0731 posed them, have proven to be effective. the sanctions in question include arms embargo, travel, trade, financial and military sanctions. sanctions imposed for political purposes may be aimed at policy change, regime destabilization, prevention of conflicts, prevention of human rights abuse, support of democratic institutions, countering terrorism, and so on. depending on the sanctions’ success, we may distinguish between those that had partial success, full success, those that were settled through negotiations, and those that failed to achieve the intended outcomes. analysis of the sanction data has led us to the following observations: sanctions tend to be used more frequently; european countries are the most frequent users of sanctions while african states are their most frequent targets; sanctions tend to become more and more diverse; the share of trade sanctions is declining and the share of financial and travel sanctions is growing (fig. 1). the main objectives of sanctions are increasingly related to democracy and human rights protection. trade sanctions tend to have a negative but heterogeneous impact on trade, which is particularly pronounced in the case of complete bilateral sanctions followed by complete export sanctions (felbermayr, 2021). the global supply and demand chains and global bank connections act as a constraint for the system of sanctions (le, 2022). although angola is not the most sanctioned country in africa, its history of sanctions imposed by the un and usa is quite impressive. the sanction episode in angola lasted from 1986 to 2003. the sanctions against angola were adopted in an attempt to curb the armed conflict, to prevent human rights violations, and to destabilize the political regime. the united nations security council (unsc) imposed sanctions on angola three times in an attempt to  end hostilities. their sanctions had three iterations: initially, it was the arms embargo (1993–2002) which was not very effective and was followed in 1997 by travel bans, which also failed to bring the intended result. in 1998, financial restrictions were added. they were lifted in 2002 in the light of the continuing peace process. the us sanctions against angola were aimed at destabilizing the regime, fighting human rights violations, supporting democratic institutions, and countering terrorism. the sanctions were imposed twice: the first stage lasted from 1986 to 1992; the second stage, from 1993 to 2003. the main restrictions were imposed on arms exports and financial services, the latter being associated primarily with currency restrictions. it should be noted that these sanctions had but a partial success and not all of the intended goals were achieved. in december 2015, the bank of america discontinued the supply of u.s. dollar banknotes to angolan banks over concerns about money laundering and terrorist financing. the effect of this measure on the country’s economy is also worthy of interest. oil has always been angola’s major source of foreign currency funds. this potential started to decline in the first half of 2014, especially in june, due to the drop in oil prices (fig. 2). 13 20 28 33 50 47 66 116 84 1 4 25 16 29 55 61 84 65 0 4 5 15 25 40 48 67 54 2 10 20 43 67 74 89 162 148 2 5 9 5 9 29 60 91 93 3 10 15 16 24 23 34 38 29 0 20 40 60 80 100 120 140 160 180 1950 1960 1970 1980 1990 2000 2010 2014 2019 trade, numbers arms, numbers military, numbers financial, numbers travel, numbers other, numbers figure 1. types of sanctions imposed on african states in 1950–2019 source: the global sanctions database. retrieved from https://ideas.repec.org/p/ris/drxlwp/2021_010.html (accessed: 14.07.2022) http://r-economy.com https://doi.org/10.15826/recon.2022.8.3.017 https://ideas.repec.org/p/ris/drxlwp/2021_010.html r-economy, 2022, 8(3), 208–218 doi: 10.15826/recon.2022.8.3.017 213 r-economy.com online issn 2412-0731 despite the country’s increasing macro-economic stability and successful structural reforms, the angolan economy is still heavily dependent on oil prices as oil exports account for 93% of all the exports. the oil sector, which makes up one third of angola’s gdp, shrank during the covid-19 pandemic due to the falling oil prices3. in 2020, real gdp fell by more than 5%, which made 2020 the fifth consecutive year of recession. in 2021, the angolan economy showed some signs of recovery, its gdp rising by 0.2%, which signified the end of the long recession cycle. as the restrictions associated with the pande mic were lifted and the somewhat belated effects of the macro-economic reforms started to take shape, the oil industry also started to recover. these improvements compensated for the new slump in the oil sector which occurred despite higher oil prices. the country enjoys fairly favourable prospects for 2022, especially in the light of the rising oil prices and increased oil production. since the transition from an oil-dependent economy to a more diversified model is a lengthy process, in the near future the oil sector will continue playing a crucial role in angola’s economic development. the government’s ongoing efforts to enhance economic diversification are targeted at developing non-oil sectors. 3 оfficial web-site of instituto nacional de estatistica de angola, overview of angola's economy. summary statistics. url: https://www.ine.gov.ao/inicio/estatisticas (accessed: 14.07.2022) as for the influence of the sanctions on angola’s economy, it should be noted that since the beginning of the first stage of sanctions in 2002, the national economy has started to recover somewhat and the imports have been growing noticeably (fig. 3). as figure 3 illustrates, the sanctions affec ted not only the country’s exports but also its imports. after the sanctions were lifted in 2022, the imports of vehicles rose 6 times, and the imports of me-tals, 3 times. what made the angolan economy so sensitive to various sanctions was the significant role of imports, including food imports. sanction pressure has also led to certain structural changes regarding angola’s trade partners (fig. 4). as figure 4 illustrates, the share of angola’s main partners in the imports has been falling while the scale of economic cooperation between angola and china has been growing. interestingly, the share of imports from china in 1995 was only 1.3% while the imports from france was 23.1%; portugal, 20.6%; and the usa, 15.3%. after the sanctions were lifted, the shares of the trade partners changed significantly (see table 1). as table 1 shows, the share of china grew in 2019 and reached 16.7% while the shares of all the other partners shrank: the share of portugal became 11%; the usa, 4.5; and france, 14.94. 4 calculated by the authors by using the data from the observatory of economic complexity retrieved from https:// oec.world/en/profile/country/ago (accessed: 14.07.2022) 0 500 1000 1500 2000 2500 3000 3500 4000 0 10000 20000 30000 40000 50000 60000 70000 80000 19 95 19 96 19 97 19 98 19 99 20 00 20 01 20 02 20 03 20 04 20 05 20 06 20 07 20 08 20 09 20 10 20 11 20 12 20 13 20 14 20 15 20 16 20 17 20 18 20 19 20 20 mineral products (us$ million, le� axis) precious metals (us$ million, right axis) figure 2. key exports of angola source: the observatory of economic complexity. retrieved from https://oec.world/en/profile/country/ago (accessed: 14.07.2022) https://doi.org/10.15826/recon.2022.8.3.017 http://r-economy.com https://www.ine.gov.ao/inicio/estatisticas https://oec.world/en/profile/country/ago https://oec.world/en/profile/country/ago https://oec.world/en/profile/country/ago 214 r-economy.com r-economy, 2022, 8(3), 208–218 doi: 10.15826/recon.2022.8.3.017 online issn 2412-0731 0 1000 2000 3000 4000 5000 6000 7000 19 95 19 96 19 97 19 98 19 99 20 00 20 01 20 02 20 03 20 04 20 05 20 06 20 07 20 08 20 09 20 10 20 11 20 12 20 13 20 14 20 15 20 16 20 17 20 18 20 19 20 20 transport, us$ million cars, us$ million food, us$ million herbal products, us$ million metals, us$ million figure 3. key imports to angola source: the observatory of economic complexity. retrieved from https://oec.world/en/profile/country/ago (accessed: 14.07.2022) 0 1 000 000 2 000 000 3 000 000 4 000 000 5 000 000 6 000 000 1 99 5 2 00 0 2 00 1 2 00 2 2 00 3 2 00 4 2 00 5 2 00 6 2 00 7 2 00 8 2 00 9 2 01 0 2 01 1 2 01 2 2 01 3 2 01 4 2 01 5 2 01 6 2 01 7 2 01 8 2 01 9 2 02 0 france, mln usd$ portugal, mln usd$ united states, mln usd$ china, mln usd$ figure 4. imports from angola’s key geographic partners source: the observatory of economic complexity. retrieved from https://oec.world/en/profile/country/ago (accessed: 14.07.2022) table 1 angola’s key import partners and their shares in imports, % country 1995 2002 2019 france 23.1 6.1 14.9 portugal 20.6 18.4 11.0 usa 15.3 12.6 4.5 china 1.3 2.1 16.7 source: calculated by the authors by using the data from the observatory of economic complexity. retrieved from https://oec.world/en/profile/country/ago (accessed: 14.07.2022) the 2020–2021 pandemic in angola, like in other countries of the world, proved to be detrimental to trade relationships, which is why for our analysis we have chosen the year 2019 as more representative. the ties between angola and china strengthened during the sanction period as china provided support for angola during the civil war and contributed to its post-war reconstruction. china is interested in energy sources, in the production of the mining industry, and in diamond reserves. as local experts observe, ho wever, china’s activities in angola may also have negative implications due to the latter’s growing http://r-economy.com https://doi.org/10.15826/recon.2022.8.3.017 https://oec.world/en/profile/country/ago https://oec.world/en/profile/country/ago https://oec.world/en/profile/country/ago r-economy, 2022, 8(3), 208–218 doi: 10.15826/recon.2022.8.3.017 215 r-economy.com online issn 2412-0731 dependence on oil exports as the chinese workforce drive out local producers. africa in general and angola in particular hold much promise for chinese goods and maximizing the potential of this market is one of the priorities of china’s foreign policy in africa. the usa put pressure on angola over concerns about lax regulation leading to money laundering and terrorism financing. the u.s. federal reserve suspended the sale of dollars to banks based in angola and in december 2015 the bank of america for the last time closed its us dollar auction. in 2015, 17.4 billion us dollars were sold on the foreign exchange market, which since then has become the largest amount of foreign currency sold to angola. in the following year 2016, the central bank sold 832 million us dollars in an irregular sequence5. these measures led to a major disruption of its banking system. the decision of the u.s. central bank exacerbated the economic and financial crisis in angola as the latter was struggling with foreign currency shortages. at least three banks have margin us-dollar transactions through their offices abroad or via accounts in foreign banks – banco angolano de investimentos (bai), banco de desenvolvimento de angola (bda), and standard bank angola (sba). meanwhile, luanda, the capi tal of angola, has a thriving black market for foreign currency and illegal currency transactions. the country’s oil industry has generated most of the profit in us dollars through oil crude exports. in the face of dollar drought, the central bank had to rehearse a plan to save correspondent banks acting as intermediaries in the sale of dollars to angola. the key reforms conducted in the country since 2017 included anticorruption and anti-money laundering laws, fiscal policy reforms, and the privatization act. financial regulation was strengthened by the adoption of the new financial institutions general regime law in may 2021, which gives more powers to the national bank of angola to settle disputes and introduces more stringent corporate management requirements. moreover, in 2021 the national assembly of angola approved a constitutional amendment conferring independence on the central bank. certain steps were taken to improve the business climate by a one-stop-shop service for financial institutions, businesses, and potential investors. 5 angola24horas. https://angola24horas.com/politica/ item/24157-angola-e-eua-trabalham-para-o-levantamento-da-suspensao-da-venda-de-divisas (accessed: 14.07.2022) the  national bank of angola (bna) goes to great lengths to maintain the flexibility of the currency exchange rate, allowing more and more companies to sell foreign currency directly to commercial banks. as a result, as of february 2022, the year-on-year increase in the currency exchange rate was 23%. the inflation is still high, however: in february 2022 it rose to 27.3% in comparison with 24.9% in the previous year, which can be explained by the impact of the import restrictions, the lockdown during the covid-19 pandemic as well as the rise in the global prices for raw materials. in general, the macro-economic reforms in angola are already bringing about certain positive effects as the non-oil economic activities were expanding both before and after the covid-19 pandemic. this trend is illustrated by the 41%-growth in non-oil exports in 20216. angola has managed to maintain political stability since the end of the civil war in 2002. the constitution of 2010 adopted the presidential-parliamentary system where the president is the leader of the party with the most seats in parliament. at the moment the parliament is discussing a proposal for revision of the constitution. meanwhile the application of the electoral legislation is suspended7. since march 2022, the angolan government and joe biden’s administration have been searching for ways to revoke the decision to halt dollar supply to angola and to ensure fair and free elections in august 2022. the national government is striving to enhance the diversification of the national economy to stimulate economic growth, which is especially necessary in view of the fact that the country is heavily dependent on the exports of crude oil and petroleum products. plano nacional de desenvolvimento 2013–2017 (pnd) – the national development plan – specifies the main strategic goals of angola’s industrialization and priority sectors such as food production, clothing and footwear industry, wood processing, wooden furniture manufacturing, pulp and paper industry, chemical and pharmaceutical industry, construction materials production, metallurgical industry, metal product 6 calculated by the authors by using the data from the observatory of economic complexity. retrieved from https:// oec.world/en/profile/country/ago (accessed: 14.07.2022) 7 angola24horas. https://angola24horas.com/politica/ item/24157-angola-e-eua-trabalham-para-o-levantamento-da-suspensao-da-venda-de-divisas (accessed: 14.07.2022) angola24horas. https://angola24horas.com/politica/ item/24106-eua-e-angola-discutem-reformas-economicas-e-iniciativas-anticorrupcao (accessed: 14.07.2022) https://doi.org/10.15826/recon.2022.8.3.017 http://r-economy.com https://angola24horas.com/politica/item/24157-angola-e-eua-trabalham-para-o-levantamento-da-suspensa https://angola24horas.com/politica/item/24157-angola-e-eua-trabalham-para-o-levantamento-da-suspensa https://angola24horas.com/politica/item/24157-angola-e-eua-trabalham-para-o-levantamento-da-suspensa https://oec.world/en/profile/country/ago https://oec.world/en/profile/country/ago https://angola24horas.com/politica/item/24157-angola-e-eua-trabalham-para-o-levantamento-da-suspensa https://angola24horas.com/politica/item/24157-angola-e-eua-trabalham-para-o-levantamento-da-suspensa https://angola24horas.com/politica/item/24157-angola-e-eua-trabalham-para-o-levantamento-da-suspensa https://angola24horas.com/politica/item/24106-eua-e-angola-discutem-reformas-economicas-e-iniciativa https://angola24horas.com/politica/item/24106-eua-e-angola-discutem-reformas-economicas-e-iniciativa https://angola24horas.com/politica/item/24106-eua-e-angola-discutem-reformas-economicas-e-iniciativa 216 r-economy.com r-economy, 2022, 8(3), 208–218 doi: 10.15826/recon.2022.8.3.017 online issn 2412-0731 manufacturing, manufacture of machine tools, vehicles, and as well as scrap and metal recycling. the plan also includes measures to support small and medium-sized industrial enterprises to create more favourable conditions for the development of production chains. one of the plan’s parts – programa de fomento da pequena indústria rural (profir) or program to foster small agro-industry – is aimed at stimulating more diversified production, which in the long run should bring some improvements in the overall economic situation. regarding the political and historical context of african countries’ development and based on the available statistical data, we can distinguish three stages of the sanction policy in relation to these states: the cold war period, the post-socialist period, and the contemporary period. during the cold war, at the first stage of the sanctions, their effectiveness was low, which made their adoption rather pointless. at the second stage, western countries exerted large-scale pressure on african countries in an attempt to promote democracy and support democratic institutions. at their current stage, the effect of the sanctions is weak in comparison with the declared goals although they have a negative impact on the living standards in the target countries. conclusion our analysis of the empirical data has shown that the economic sanctions imposed by the un and usa affect the economies of the target countries. the un sanctions have a statistically significant influence on the economic growth of the target state. in the given period, the impact of the sanctions on angola led to a significant drop in exports, which caused a decline in gdp. since angola’s economy largely relies on oil exports, the structural reforms have so far failed to provide macro-economic stability. we found that, since 1995, there have been some significant structural changes of angola’s geographical partners. the share of the imports from china grew by 12% in the period between 1995 and 2019 while the share of france, fell by 8.2%, portugal, by 9.6% and the usa, by 10.8%8. the relationship between angola and china during the period of sanctions strengthened significantly. analysis of the data from the global sanctions database (gsdb) has led us to the following conclusions: first, sanctions are becoming an increasingly popular tool of international relations; second, european countries are the most frequent users of sanctions while african countries are their most frequent targets; third, sanctions are beco ming increasingly diverse; and, finally, the share of trade sanctions is decreasing while the share of financial and travel sanctions is growing. africa is the continent most targeted by sanctions from the un and regional organizations. while the un continues to use sanctions to discourage military aggression, regional organizations cite unconstitutional change of government as the main reason for imposing sanctions on african states. the un 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(in russ.) https://doi.org/10.31857/s086919080013575-9 information about the authors inna v. lazanyuk – candidate of economics, department of economic and mathematical modeling, peoples’ friendship university of russia (rudn university), (6 miklukho-maklaya street, moscow, 117198, russia); scopus author id: 57214988996; orcid: 0000-0002-1834-3154; researcher id: aaa-5127-2019; e-mail: lazanyuk-iv@rudn.ru david mambu diu – a fourth year student in economics, faculty of economics, peoples’ friendship university of russia (rudn university), (6 miklukho-maklaya street, moscow, 117198, russia); republic of angola; e-mail: 1032185006@rudn.ru article info: received june 22, 2022; accepted august 23, 2022 информация об авторах лазанюк инна васильевна – кандидат экономических наук, кафедра экономикоматематического моделирования, российский университет дружбы народов (рудн), (ул. миклухо-маклая, 6, москва, 117198, россия); scopus author id: 57214988996; orcid: 00000002-1834-3154; researcher id: aaa-5127-2019; e-mail: lazanyuk-iv@rudn.ru диу давид мамбу – студент 4 курса экономического факультета, экономический факультет, российский университет дружбы народов (рудн), (ул. миклухо-маклая, 6, москва, 117198, россия); республика ангола; e-mail: 1032185006@rudn.ru информация о статье: дата поступления 22 июня 2022 г.; дата принятия к печати 23 августа 2022 г. 作者信息 拉扎纽克·伊娜·瓦西里耶芙娜——经济学博士，经济与数学建模系，俄罗斯人民友谊 大学（米克卢霍-麦克莱街6号，莫斯科，邮编：117198，俄罗斯）；scopus author id: 57214988996; orcid: 0000-0002-1834-3154; researcher id: aaa-5127-2019; 邮 箱：lazanyuk-iv@rudn.ru 吉·戴维·曼布——经济系学士4年级，俄罗斯人民友谊大学（米克卢霍-麦克莱街6号， 莫斯科，邮编：117198，俄罗斯）；安哥拉共和国；邮箱：1032185006@rudn.ru. http://r-economy.com https://doi.org/10.15826/recon.2022.8.3.017 https://doi.org/10.1080/03050629.2010.502436 https://doi.org/10.1080/03050629.2010.502436 https://doi.org/10.31132/2412-5717-2019-48-3-49-63 https://doi.org/10.1111/j.1468-2478.2008.00512.x https://doi.org/10.1111/j.1468-2478.2008.00512.x https://doi.org/10.31857/s086919080013575-9 https://www.scopus.com/authid/detail.uri?authorid=57214988996 https://orcid.org/0000-0002-1834-3154 http://www.researcherid.com/rid/aaa-5127-2019 https://www.scopus.com/authid/detail.uri?authorid=57214988996 https://orcid.org/0000-0002-1834-3154 https://orcid.org/0000-0002-1834-3154 http://www.researcherid.com/rid/aaa-5127-2019 mailto:1032185006@rudn.ru https://www.scopus.com/authid/detail.uri?authorid=57214988996 https://orcid.org/0000-0002-1834-3154 http://www.researcherid.com/rid/aaa-5127-2019 mailto:lazanyuk-iv@rudn.ru mailto:1032185006@rudn.ru r-economy, 2019, 5(3), 103–114 doi: 10.15826/recon.2019.5.3.011 103 www.r-economy.ru online issn 2412-0731 original paper © n.v. shcherbakova, 2019 doi 10.15826/recon.2019.5.3.011 the role of biological and economic factors in urban population growth n. v. shcherbakova scientific research and design institute of territorial development and transport infrastructure, st. petersburg, russia; email: nadshch@mail.ru abstract this paper explores the influence of biological mechanisms in overpopulated territories on urban growth and addresses the question how biological factors correlate with economic factors, such as gdp growth, in this process. the article provides an overview of the approaches in regional economics, ethology and demography to this problem. to analyze the influence of biological and economic factors on urbanization, four hypotheses are formulated. to test these hypothesis, methods of regression analysis are applied to the statistical data of the united nations and the world bank for 132 countries for 1995, 2005, 2015. the analysis shows that the biological mechanisms of population reduction play a significant role in the least and less developed countries. per capita gdp growth leads to an increase in the concentration of population in big cities (with the population of 1 million inhabitants or more). the total fertility rate varies significantly in these countries, but as the population starts to grow, fertility begins to fall gradually. in more developed countries with a high per capita gdp level, the share of urban population tends to shrink, while the total fertility rate stabilizes there at the level of ca. 1.0–2.0 births per woman. keywords urbanization, overpopulation, fertility rate, birth rate, population density, level of economic development for citation shcherbakova n. v. (2019) the role of biological and economic factors in urban population growth. r-economy, 5(3), 103–114. doi: 10.15826/recon.2019.5.3.011 рост численности городского населения: биологический фактор н. в. щербакова научно-исследовательский и проектный институт территориального развития и транспортной инфраструктуры, санкт-петербург, россия; e-mail: nadshch@mail.ru аннотация в статье исследуется, оказывают ли биологические механизмы, вызванные перенаселением территории, существенное влияние на рост городов, и является ли уровень экономического развития страны значимым при влиянии биологических механизмов. с целью анализа влияния биологических и экономических факторов на процессы урбанизации сформулированы четыре гипотезы, основанные на теоретических утверждениях и эмпирических выводах региональной экономики, этологии и демографии. результаты регрессионного анализа статистических данных на национальном уровне, примененные для проверки этих гипотез, показывают, что биологические факторы городского развития следует рассматривать наравне с экономическими, но необходим комплексный анализ. биологические механизмы сокращения численности населения играют важную роль в наименее развитых и развивающихся странах. с  ростом ввп на душу населения в этих странах увеличивается концентрация населения в крупных городах (с населением 1 млн человек и более). общий коэффициент рождаемости в этих странах значительно различается, но с ростом населения он постепенно снижается. в развитых странах с высоким уровнем ввп на душу населения доля жителей крупных городах в общей численности населения страны имеет тенденцию к снижению, и  общий уровень рождаемости стабилизируется на уровне около 1,0–2,0 родов на одну женщину. ключевые слова урбанизация, перенаселение, коэффициент рождаемости, рождаемость, плотность населения, уровень экономического развития для цитирования shcherbakova n. v. (2019) the role of biological and economic factors in urban population growth. r-economy, 5(3), 103–114. doi: 10.15826/recon.2019.5.3.011 http://doi.org/10.15826/recon.2019.5.3.011 http://dx.doi.org/10.15826/recon.2019.5.3.011 mailto:nadshch@mail.ru 104 www.r-economy.ru r-economy, 2019, 5(3), 103–114 doi: 10.15826/recon.2019.5.3.011 online issn 2412-0731 introduction urban economics explains the formation of cities and their growth in terms of endogenous and exogenous factors, which include access to public good, scale and localization economies, product differentiation, multiplicative effect of industrial development, and location advantages (e.g. proximity to transport nodes). at the same time, the biological factors affecting urban development largely remain underexplored in modern research literature. however, the interdisciplinary approach to the problem of urban growth, in particular the one that combines the perspective of human ethology and demography, is also interesting and holds much promise. human ethology studies the behaviour of humans as social animals and, therefore, it looks the growth of urban population in the light of such problems as the scarcity of natural resources and the overpopulation of our planet. the permanently deteriorating conditions of rural life make people move to cities and towns. the biological mechanisms of population decline lead to urbanization, which in a natural way reduces fertility. in their turn, demographers observe lower fertility rates in cities in comparison with less densely populated areas. biological mechanisms often induce people to act against their economic interests and in ways that seem to be contradictory to the common sense. in economic literature, however, biological mechanisms are considered of minor importance, whereas economic incentives, such as the cost-benefit principle, are expected to prevail. thus, the theoretical premises of urban economics can be expanded by adding the biological factor to the analysis of urban development. the overpopulation of a certain territory leads to urban growth, while in cities the fertility rate of population reduces. the aim of this research is to investigate how big is the influence of the biological factor on cities’ growth by using the statistical data for different countries. the key question this study addresses is whether overpopulation of a territory really leads to urbanization, and whether in urban areas the fertility rate decreases. another important question of this research is how biological factors correlate with economic factors, such as gdp growth, in this process. the paper is organized as follows. the second section provides an overview of the main approaches of regional and urban economics, ethology, and demography, which explain urban growth by taking into account biological factors. this section also contains the main hypotheses of this study. the third section describes the statistical data and the main indicators used in the analysis. in the fourth section, the hypotheses are tested by applying methods of regression analysis. the final section contains the conclusions. theoretical framework emergence and growth of cities is explained in regional and urban economics by applying approaches developed within conventional urban economics, the theory of industrial organization, the new economic geography, the theory of endogenous economic growth, and so on (for more detail see, for example, [1]). however, in the context of this research it is worth pointing out that in economic literature, biological factors are mentioned only briefly. natural limitations are sometimes discussed, for example, when considering urban-rural linkages. due to shortages of working places, famines caused by natural crop failure in rural areas and so on, many people have to move to the city in search of better opportunities [2; 3]. this kind of urban growth is especially typical of developing countries. at the same time, the emergence and development of cities was impossible without the rise in agriculture surplus generated by the technological progress [4; 5] nowadays technological and scientific development has made it possible to produce enough food for cities with the help of labour-saving technologies. in the usa, where incomes are especially high in agriculture, farmers with their families make up 1% of the country’s population, but they supply the rest 99% of population with foodstuffs [6]. therefore, it is possible to conclude that redundancies in rural areas contribute to urban development. this idea was mentioned by many theorists of regional economics [4], but, unfortunately, it has not received enough attention in research literature. in ethology, cities, especially big ones, are considered as collapsing gatherings and as a relatively harmless way of decreasing the population size [7]. when the population size reaches its critical level and the territory becomes too densely populated, this activates the biological mechanisms that lead to a decrease in the population density such as epidemics, a rise in interpersonal aggression and violence. other mechanisms, including collapsing http://doi.org/10.15826/recon.2019.5.3.011 r-economy, 2019, 5(3), 103–114 doi: 10.15826/recon.2019.5.3.011 105 www.r-economy.ru online issn 2412-0731 gatherings, have a more gentle effect. it is important to emphasize that the second group of biological mechanisms come into force before the essential resources, in particular food, are exhausted [8–10]. studies on the influence of high population density on animals’ behaviour were carried out on many species, such as the rats [11], insects (for example, the mediterranean fruit fly [12]), and birds [9]. one of the first studies of this kind was john b. calhoun’s experiment on rats. its results were published in 1962 [11]. he discovered that overcrowding among rats lead to pathological behaviours, such as increased aggression, violation of sexual relations (same-sex relations, rapes of female individuals, simplification or total disappearance of marriage rituals), and decrease in care for posterity. the essential consequences of high density were the declining birth rates and rising death rates. at the same time, those males with their females who managed to claim up to the top of the hierarchical ladder had a normal way of life, which means in some sense that hierarchy is able to soften the pressure of overcrowding and to increase environment capacity [9; 13]. calhoun’s work aroused a large resonance in scientific world and inspired many scientists to research the problem of overcrowding from different aspects, including the challenges of living in large, densely populated cities and ways of dealing with these pressures [14]. following calhoun’s research, jonathan freedman began the first laboratory studies of crowding among human beings at stanford university in the late 1960s [15]. he sought the correlation between density and a variety of pathologies similar to those found in calhoun’s laboratory. his concluded that crowding per se did not automatically lead to pathological behaviour. we cannot solve modern urban and environmental problems by merely reducing the density in the areas we inhabit, but we cannot ignore the fact that the population density does contribute to these problems [16]. one of the central questions in these studies is how relevant are the results of animal experiments for humans [10]. there are two opposite views on this problem: one point of view is that these results cannot be applied to human beings, because humans are a social species and, therefore, a high concentration of individuals within one area might not have a negative effect on their behaviour [8]. in other words, unlike rates in calhoun’s experiment, people are able to cope with overpopulation [14]. other scholars, including the author of this paper, consider these results to be applicable to humans, pointing out that biological mechanisms are shared by animals and humans alike since they do not require rational decision-making [7]. each physical contact of individuals of the same species, including human beings, is a stimulus for the release of a small amount of adrenaline, which means that there should be a limit to the load a person can endure [5]. humans did not use to live in huge conglomerations, numbering thousands of individuals. our behaviour is adapted for living in small tribal groups of little less than one hundred individuals [17]. behaviour aimed at avoiding excessive contacts allows us to limit the number of people we interact within the necessary limit. in big cities, where life is stressful, it is problematic to pursue only healthy forms of human behaviour, which causes aggression, isolation and indifference to others, alienation and a loss of individuality [18]. no wonder that the “prevalence of hypertension rose with urbanization” [19]. despite all our technical achievements, we are still an elementary phenomenon in a biological sense [20]. the iron wall of anthropocentrism prevents us from realizing our natural inclinations [10]. no matter how sophisticated we consider ourselves to be, if the population density rises above a certain limit, when the number of people exceeds the number of the available social roles, it might cause violence and destruction of social structures. nevertheless, urban life also holds a number of advantages: interactions within close urban communities enhance people’s mental abilities. another important advantage of the supertribal conditions is that people enjoy relative freedom in their choice of activities [17]. there are also many demographic facts that confirm the arguments that the results of animal experiments indeed are applicable to humans. a lot has been said about the sharp fall in the fertility rates for urban population, accompanied by alienation and indifference to children [10]. two competing hypotheses are elaborated to explain this fact: compositional and contextual [21]. the compositional hypothesis suggests that fertility levels vary between places simply because different people live in different settlements (e.g., more educated people, students, married people live in cities), whereas the contextual hypothesis suggests that factors related to the immediate living environment are of critical importance. the immediate living environment in cities is deterhttp://doi.org/10.15826/recon.2019.5.3.011 106 www.r-economy.ru r-economy, 2019, 5(3), 103–114 doi: 10.15826/recon.2019.5.3.011 online issn 2412-0731 mined by such factors as high costs of raising children, the lack of opportunities to improve their housing conditions, more individual autonomy and self-actualisation, leading to more rational individual choices, which usually results in people having fewer children. there are studies that explore the regional difference in terms of fertility rates and associated factors for specific countries: great britain [22], nigeria [23], finland and other european countries [21], the usa [24], switzerland [25], etc. all these studies indicate that the fertility rate is influenced by a set of factors (female education and employment, age at first marriage, birth control, family structure, housing conditions). these factors (and the population density is among them) also determine the differences between the urban and rural population. the more densely an area is populated, the lower the fertility rate is. all these factors have an objective character and it is hard to control them through state regulation, for example, through birth-control programs [25]. furthermore, studies show that in many countries the urban-rural fertility variation has decreased over time, but significant differences between various settlements still persist [21; 23]. it is worth mentioning that many developing countries are characterized by high fertility rates even in urban areas, which results in rapid population growth. high fertility rates used to be necessary to compensate for high infant mortality rates but now, thanks to humanitarian aid, these countries are experiencing decline in the infant mortality rates, whereas their fertility rates require more time to decrease accordingly. in sustainable populations, the fertility rate normally conforms with the infant mortality rate [7]. dolnik states that there is no strict dependence between poverty and fertility, pointing out that “poverty” and “wealth” are vague concepts even in economy and sociology [7]. there cannot be a strict causal relationship between such subjective and short-term notion as poverty and the long-term population response (fertility rate). our literature review has led us to the following conclusions: 1. although the influence of biological factors on cities’ formation and development is not denied in urban economics, they are considered to be of minor importance while the priority is given to economic factors. however, the behaviour of economic agents can take irrational forms due to the impact of biological factors. 2. the influence of biological mechanisms on the regulation of animals’ population size is an established fact. one of such mechanisms – collapsing gatherings – leads to the concentration of individuals within a limited territory. when the population density becomes high, the fertility rate decreases and the population size starts to shrink as well, which usually happens in the second generation. 3. the possibility of applying the results of animal experiments of high-density living to human beings is still a debatable question, although the fact that the fertility rate decreases due to the growth in population density is widely acknowledged in demography. we have formulated the following hypotheses: hypothesis 1: there is a direct relationship between the population density and urban growth. hypothesis 2: urban population growth is accompanied by a fall in the fertility rate. hypothesis 3: there is no correlation between poverty and fertility. hypothesis 4: population concentration in big cities and the relationship between the birth rates and the infant mortality rates depend on the level of economic development. methods and data to test the above-described hypotheses, this study uses the method of regression analysis. one factor regression is taken into account. multiple regression models are not included in this paper because, as statistical analysis has shown, all of the considered multifactor models can be reduced to one factor regression model. among the types of models under consideration are simple regression models, such as linear, exponential, square root, squared, logarithmic, reciprocal, multiplicative models and polynomial regression models (of the second order). most of the statistical calculations within the scope of regression analysis are made with the help of “statgraphics 18” software. the data of the united nations and the world bank for 132 countries for 1995, 2005, 2015 are selected for the analysis because of their availability and relative sufficiency1. the coverage of the countries is as 1 world bank, world development indicators (https:// data.worldbank.org); united nations, department of economic and social affairs, population division. demographic yearbook 2016, 2011, 2006, 2001, 1996. online editions (https:// unstats.un.org); united nations, department of economic and social affairs, population division (2018). world urbanization prospects: 2018 revision, online edition (https://esa.un.org) http://doi.org/10.15826/recon.2019.5.3.011 https://data.worldbank.org https://data.worldbank.org https://unstats.un.org https://unstats.un.org https://esa.un.org r-economy, 2019, 5(3), 103–114 doi: 10.15826/recon.2019.5.3.011 107 www.r-economy.ru online issn 2412-0731 maximal as possible, but it is limited by the availability of the relevant data. we take the years of 1995, 2005 and 2015 in order to reveal the dynamics in the indicators within a ten-year period. the choice of the years and the interval is determined by the availability of the source data and the aim of this research. the countries are classified according to their level of economic development. the level of gdp per capita in current prices is chosen as the main criteria and, therefore, the countries are divided into three groups: more developed, less developed and the least developed countries. this division of the countries is based on the following relative principles: per capita gdp of more developed countries equals or exceeds the doubled average value of this indicator; per capita gdp of the least developed countries equals or is below the median value of this indicator. these are relative criteria of classification, but they enable us to use the available statistical information. as gdp was gradually growing in all countries of the world, in 1995, 2005 and 2015 the boundary values were different. in 1995, developed countries had per capita gdp of more than 15,400 us dollars. in less developed regions, per capita gdp varied between 2,101 and 15,400 us dollars. the least developed countries had per capita gdp of or less than 2,100 us dollars. in 2005, more developed countries had per capita gdp more than 25,000 us dollars; less developed countries, more than 3,500 but equal or less than 25,000; and the least developed countries, 3,500 or less. in 2015, more developed countries had per capita gdp more than 30,000 us dollars; less developed countries, more than 5,800 but equal or less than 30,000; and the least developed countries, 5,800 or less. in the next section we are going to test the four hypotheses by applying regression analysis and the above-described indicators. results to prove our first hypothesis, we need to show that urban growth is a consequence of high population density. urbanization (urban growth) can be measured as a level of urban population relative to the total population of this area (a static indicator) or as the rate of urban population growth (a dynamic indicator). both indicators can be expressed in percentage terms. we need to look at the relations between the following indicators: the average annual rate of change of urban population in a country and its population density; the share of urban population in the total population of a country and the population density. regression analysis showed that there is no statistically significant relationships between these indicators in all the considered years (see table 1). to test the second hypothesis, we considered the relationship between the fertility rate and the share of urban population in the total population of a country. regression analysis showed that there is a moderately strong relationship between the two variables in all the considered years (see table 2). in 1995 and 2005, the best model fitting table 1 results of regression analysis (first hypothesis test) dependent variable (y) independent variable (x) year correlation coefficient regression model r-squared, % t-statistic (p-value) f-ratio (p-value) durbin watson statistic (p-value) intercept slope average annual rate of change of the urban population, percent population density, inhabitants per square km 1995 –0.14 square root-x model: = −3.06 0.02y x 1.8 15.9 (0.000) –1.9 (0.061) 3.6 (0.061) 1.5 (0.000) 2005 –0.10 square root-x model: = −2.13 0.01y x 1.0 13.7 (0.000) –1.4 (0.160) 2.0 (0.160) 1.6 (0.001) 2015 –0.06 reciprocal-x model: = − 0.04 1.79y x 0.4 12.9 (0.000) –0.8 (0.450) 0.6 (0.450) 1.4 (0.000) urban population, percentage of the total population population density, inhabitants per square km 1995 –0.08 square root-x model: = −54.34 0.35y x 0.7 11.8 (0.000) –0.8 (0.450) 0.6 (0.450) 0.9 (0.000) 2005 0.05 linear model: = −56.35 0.01y x 0.2 19.0 (0.000) 0.4 (0.670) 0.2 (0.670) 0.6 (0.000) 2015 –0.19 logarithmic-x model: = −68.58 2.61lny x 3.6 9.7 (0.000) –1.6 (0.110) 2.6 (0.110) 1.1 (0.000) http://doi.org/10.15826/recon.2019.5.3.011 108 www.r-economy.ru r-economy, 2019, 5(3), 103–114 doi: 10.15826/recon.2019.5.3.011 online issn 2412-0731 this dependence was a linear model in 2015  – a  logarithmic-x model (figure 1)2. the moderately strong relationship between the fertility rate and the percentage of urban population means that as more and more people start living in cities and towns, less children are born in the country. 2 to save space, the graphs are shown for the last considered year. if we divide countries according to their level of economic development in the way described above, we shall see that this relation is more evident in the least developed countries of the world (see table 3). in less developed countries, this correlation between the fertility rate and the percentage of urban population is also observed, but this relationship is weaker. in more developed countries, this dependence is almost absent. table 2 results of regression analysis (second and third hypotheses test) dependent variable (y) independent variable (x) year correlation coefficient regression model r-squared, % t-statistic (p-value) f-ratio (p-value) durbin watson statistic (p-value) intercept slope fertility rate, births per woman urban population, percentage of the total population 1995 –0.60 linear model: = −5.9 0.05y x 36.2 23.5 (0.000) –10.4 (0.000) 108.0 (0.000) 2.10 (0.803) 2005 –0.56 linear model: = −5.2 0.04y x 31.7 21.1 (0.000) –9.5 (0.000) 89.9 (0.000) 2.05 (0.645) 2015 –0.52 logarithmic-x model: = −83.1 27.6 lny x 27.5 25.6 (0.000) –8.5 (0.000) 73.1 (0.000) 2.10 (0.766) fertility rate, births per woman per capita gdp at current prices, us dollars 1995 0.64 reciprocal-x model: = + 594.6 2.7y x 41.1 21.4 (0.000) 11.1 (0.000) 122.2 (0.000) 2.0 (0.534) 2005 0.70 reciprocal-x model: = + 925.6 2.2y x 49.3 21.5 (0.000) 13.5 (0.000) 181.9 (0.000) 2.0 (0.626) 2015 0.75 reciprocal-x model = + 1643.5 2.0y x 56.1 24.6 (0.000) 15.3 (0.000) 233.6 (0.000) 2.1 (0.661) 0 1 2 3 4 5 6 7 8 9 0 10 20 30 40 50 60 70 80 90 100 t ot al fe rt ili ty r at e, b ir th s pe r w om an urban population, % of total population figure 1. dependence between the fertility rate and the share of urban population in the total population of a country in 2015 notes: points denote certain values for countries; the thick solid line denotes a trend line of the logarithmic model http://doi.org/10.15826/recon.2019.5.3.011 r-economy, 2019, 5(3), 103–114 doi: 10.15826/recon.2019.5.3.011 109 www.r-economy.ru online issn 2412-0731 according to our third hypothesis, poverty and fertility are not correlated. to check this hypothesis, we built a dependence between the fertility rate and per capita gdp (see table 2 for the results of regression analysis). we found a moderately strong relationship between these two variables. in all the given years, one of the best-fitted models for this dependence was the reciprocal model (figure  2). a  moderately strong nonlinear relationship between these two indicators means that as per capita gdp grows, the fertility rate tends to fall until the definite level of ca. 1.0 – 2.0 births per woman. table 3 results of regression analysis of the dependence between the fertility rate and the percentage of urban population in the total population of a country, divided by the level of its economic development year level of economic development correlation coefficient regression model r-squared, % t-statistic (p-value) f-ratio (p-value) durbin-watson statistic (p-value)intercept slope 1995 least developed countries –0.44 linear model: = −6.2 0.04y x 19.4 17.4 (0.000) –5.0 (0.000) 24.8 (0.000) 2.1 (0.707) less developed countries –0.38 squared-y square root-x: = −(31.2 2.7 )y x 47.6 5.0 (0.000) –3.3 (0.001) 11.2 (0.001) 1.4 (0.007) more developed countries 0.05 reciprocal-y square root-x: = + 1 (0.5 0.01 ) y x 0.25 1.6 (0.123) 0.2 (0.782) 0.1 (0.782) 2.0 (0.5499) 2005 least developed countries –0.48 square root-y model: = −(2.43 0.01 )y x 23.3 25.3 (0.000) –5.6 (0.000) 30.9 (0.000) 1.81 (0.166) less developed countries –0.21 square root-x model: = −3.36 0.14y x 4.33 4.9 (0.005) –1.7 (0.102) 2.8 (0.102) 2.1 (0.715) more developed countries 0.11 squared-y model: = +(2.59 0.01 )y x 1.3 2.2 (0.035) 0.7 (0.513) 0.4 (0.513) 2.0 (0.451) 2015 least developed countries –0.40 exponential model: = 0,014.72 xy e 15.9 15.7 (0.000) –4.4 (0.000) 19.2 (0.000) 1.6 (0.016) less developed countries 0.09 square root-x model: = +1.55 0.05y x 0.90 2.6 (0.011) 0.7 (0.479) 0.51 (0.479) 1.9 (0.348) more developed countries 0.05 square root-x model: = +1.63 0.02y x 0.25 3.3 (0.003) 0.3 (0.781) 0.1 (0.781) 1.0 (0.001) 0 1 2 3 4 5 6 7 8 0 20000 40000 60000 80000 100000 120000 140000 160000 180000 t ot al fe rt ili ty ra te , b ir th s p er w om an gdp per capita, current us$ figure 2. dependence between the fertility rate and per capita gdp in 2015 notes: points denote certain values for countries; the thick solid line denotes the trend line of the reciprocal-x model http://doi.org/10.15826/recon.2019.5.3.011 110 www.r-economy.ru r-economy, 2019, 5(3), 103–114 doi: 10.15826/recon.2019.5.3.011 online issn 2412-0731 according to the fourth hypothesis, population concentration in big cities and the relationship between the birth rates and the infant mortality rates depend on the level of economic development. to check this hypothesis, we considered the relationships between the following variables: – the share of population of agglomerations with 1 million inhabitants or more in the country’s total population and its per capita gdp; – the ratio of the birth rate to the infant mortality rate and per capita gdp. according to the results of regression analysis (see table 4), for the given years, a polynomial 0 100 200 300 400 500 600 700 800 0 20000 40000 60000 80000 100000 120000 140000 160000 180000 r at io o f t ot al b ir th ra te to to ta l i nf an t m or ta lit y ra te , r el at iv e un it s gdp per capita, current us$ figure 3. dependence between the share of population of agglomerations with 1 million inhabitants or more in the total population of a country and its per capita gdp in 2015 notes: points denote certain values for countries; the thick solid line denotes the trend line of the polynomial model of the second order table 4 results of regression analysis (fourth hypothesis test) dependent variable (y) independent variable (x) year regression model r-squared, % t-statistic (p-value) f-ratio (p-value) durbin watson statistic (p-value) constant parameter x parameter x2 population of agglomerations with 1 million inhabitants or more, percentage of the total population per capita gdp at current prices, us dollars 1995 polynomial model of the second order: −= + − ⋅ 8 214.8 0.002 5.22 10y x x 30.1 7.7 (0.000) 6.0 (0.000) –4.6 (0.000) 22.6 (0,.000) 2.0 (0.415) 2005 polynomial model of the second order: −= + − ⋅ 8 214.53 0.003 4.91 10y x x 33.9 7.5 (0.000) 6.7 (0.000) –5.7 (0.000) 27.4 (0.000) 1.9 (0.224) 2015 polynomial model of the second order: −= + − ⋅ 8 215.21 0.001 1.63 10y x x 28.1 7.1 (0.000) 5.3 (0.000) –3.8 (0.000) 21.0 (0.000) 1.8 (0.156) ratio of the birth rate to the infant mortality rate, relative units per capita gdp at current prices, us dollars 1995 polynomial model of the second order: −= + − ⋅ 7 233.73 0.01 1.92 10y x x 90.5 4.6 (0.000) 8.4 (0.000) –5.9 (0.008) 86.2 (0.000) 2.4 (0.844) 2005 polynomial model of the second order: −= + − ⋅ 8 272.27 0.006 3.00 10y x x 53.5 6.1 (0.000) 6.4 (0.000) –2.5 (0.016) 56.9 (0.000) 2.0 (0.553) 2015 polynomial model of the second order: −= + − ⋅ 8 2100.33 0.007 3.89 10y x x 34.1 4.1 (0.000) 5.9 (0.000) –4.4 (0.000) 19.4 (0.000) 1.7 (0.131) http://doi.org/10.15826/recon.2019.5.3.011 r-economy, 2019, 5(3), 103–114 doi: 10.15826/recon.2019.5.3.011 111 www.r-economy.ru online issn 2412-0731 model of the second order fits the first dependence best of all (figure 3). the polynomial dependence between the considered variables means that the highest concentration of population in big cities is more typical of less developed countries. in the least developed and more developed countries, the share of the population living in urban agglomerations with 1 million inhabitants or more is not as high as in less developed countries. in other words, at first, the concentration of urban population grows together with the economic growth of the country, but after reaching a certain level of per capita gdp (ca.  23000 us dollars in 1995, ca. 25000 us dollars in 2005, and ca. 40000 us dollars in 2015), this concentration gradually declines. the best trend line fitting the dependence between the ratio of the birth rate to the infant mortality rate and per capita gdp is also described by a polynomial model of the second order (figure  4). the polynomial model shows us that at first with per capita gdp growth the ratio of the birth rate to the infant mortality rate also increases, but after a certain value of per capita gdp (ca. 34000 us dollars in 1995, ca. 80000 us dollars in 2005, and ca. 95000 us dollars in 2015), it begins to decrease. in less developed countries, this ratio is higher in comparison with the least and more developed countries. in the least developed countries, this ratio is low because of the high infant mortality rate, and in more developed countries this ratio is comparatively low because of the low birth rate. conclusion the aim of this research was to investigate how strongly the biological factor (acting alongside economic factors) affects urban growth. therefore, we have formulated the following hypotheses: hypothesis 1: there is a direct relationship between the population density and urban growth. hypothesis 2: urban population growth is accompanied by a fall in the fertility rate. hypothesis 3: there is no correlation between poverty and fertility. hypothesis 4: population concentration in big cities and the relationship between the birth rates and the infant mortality rates depend on the level of economic development. to test these hypotheses, we applied methods of regression analysis and found that the second and the fourth hypotheses were partially confirmed. the first and the third hypotheses were refuted. the first hypothesis is refuted, because in the given years no statistically significant relationship between urban growth (urbanization) and population density was discovered. it is worth mentioning one more time that we used the national statistical data and, therefore, population density was considered for a country rather than a region 0 100 200 300 400 500 600 700 800 0 20000 40000 60000 80000 100000 120000 140000 160000 180000 r at io o f t ot al b ir th ra te to to ta l i nf an t m or ta lit y ra te , r el at iv e un it s gdp per capita, current us$ figure 4. dependence between the ratio of the birth rate to the infant mortality rate of a country and its per capita gdp in 2015 notes: points denote certain values for countries; the thick solid line denotes the trend line of the polynomial model of the second order http://doi.org/10.15826/recon.2019.5.3.011 112 www.r-economy.ru r-economy, 2019, 5(3), 103–114 doi: 10.15826/recon.2019.5.3.011 online issn 2412-0731 or a city. therefore, there is a need for further analysis using the data on population density on the level of individual cities. even on a national level, when city states, such as macao or hong kong, are taken into consideration, the existence of these relationships is proved. for example, in the regions with extremely high population density (monaco, singapore and chinese special administrative regions – macao and hong kong), the fertility rate is low – it does not exceed the level of 2.0 births per woman. the second hypothesis is confirmed. we found a moderately strong relationship between the fertility rate and the share of urban population in the total population of a country in the given years. as more and more people start living in cities and towns, less children are born in the country. this relation is more evident in the least developed countries of the world. in more developed countries, this dependence is almost absent. for better understanding of this relationship, analysis of the data on the level of individual cities is needed. the results of regression analysis did not confirm the third hypothesis. we found a moderately strong nonlinear relationship between the fertility rate and per capita gdp. the growth in per capita gdp is accompanied by a decline in the fertility rate until the definite level of ca. 1.0–2.0 births per woman. this observation contradicts the opinion of dolnik [7] cited above. in other words, the level of a country’s economic development directly influences its fertility rate. our analysis has shown that economic growth is not the sole factor affecting fertility but it is among the most important ones. finally, the fourth hypothesis was confirmed. the regression analysis revealed the polynomial form (of the second order) of the dependence between the share of population of agglomerations with 1 million inhabitants or more in the total population of a country and its per capita gdp. it means that in the least developed and more developed countries, the share of population living in urban agglomerations with 1 million inhabitants or more is not as high as in less developed countries. the peak of concentration of the population in big cities is observed at the mean level of economic development of a country. is there an equilibrium between the birth rates and infant mortality rates in more developed countries, which can thus be described as sustainable populations? to answer these questions, we considered the dependence between the ratio of the birth rate to the infant mortality rate and per capita gdp. we found that this relationship is also better described by a polynomial model of the second order. in less developed countries, this ratio is higher in comparison with the least and more developed countries. in the least developed countries, high infant mortality rates compensate for high birth rates. a rapid decline in the infant mortality rate due to humanitarian aid led to the unrestrained population growth in developing countries. only more developed countries have managed to find a new balance between the birth rates and infant mortality rates. therefore, we can conclude that the population of developed countries can be described as sustainable in this sense. the results of this research show that the biological factors of urban development should be considered on a par with economic ones. therefore, a comprehensive analysis of different factors of urban development is needed. biological mechanisms affecting urban population play a significant role in the least and less developed countries, where the fertility rates vary significantly. nevertheless, they start to decrease gradually along with the population growth. in more developed countries with high levels of per capita gdp, less than 60–70% of people live in cities with the population of 1 million inhabitants or more and the fertility rate does not exceed the simple reproduction level of 2.1 births per woman3. as we have pointed out above, this research used the national-level data, so the next step in this direction would be to look at the city-level data. further analysis may also expand the range of socio-economic factors by considering per capita incomes, social security, the level of education, life expectancy, etc. this could be an important contribution to this research, taking into account the current approach to gdp estimation and the fact that service industries, which usually concentrate in urban areas, bring the biggest added value and make a considerable contribution to gdp formation. 3 the level of simple reproduction is an average number of children who should be born in order to numerically substitute active generations who are giving births. the total fertility rate of 2,1 is widely used as a simple reproduction level. http://doi.org/10.15826/recon.2019.5.3.011 r-economy, 2019, 5(3), 103–114 doi: 10.15826/recon.2019.5.3.011 113 www.r-economy.ru online issn 2412-0731 references 1. abdel-rahman, h. m., & anas, a. (2004) theories of systems of cities. in: j. v. henderson, j.-f. thisse (eds.) handbook of regional and urban economics, volume 4: cities and geography (pp. 2293–2339). new york: elsevier science. 2. mabogunje, a. l. (1970) systems approach to a theory of rural-urban migration. geographical analysis, 2(1), pp. 1–18. 3. goldsmith, p. d., gunjal, k., & ndarishikanye, b. (2004) rural-urban migration and agricultural productivity: the case of senegal, agricultural economics, 31(1), pp. 33–45. 4. fujita, m., & thisse, j.-f. (2002) economics of agglomeration: cities, industrial location, and regional growth. cambridge: cambridge university press. 5. lindblad, y. (1991) man – you, me and primeval: human evolution. moscow: progress. (in russ.) 6. sachs, j. (2008) common wealth: economics for a crowded planet. new york: penguin press. 7. dolnik, v. r. (2004) disobedient child of the biosphere. conversations about human behavior in the company of birds, beasts and children. saint-petersburg: chero-na-neve, petroglif. (in russ.) 8. chauvin, r. (1968) animal societies from the bee to the gorilla. new york: hill & wang. 9. wynne-edwards, v. c. (1986) evolution through group selection. oxford: blackwell scientific. 10. kurchanov, n. a. (2012) behaviour: evolutional approach. saint-petersburg: speclit. (in russ.) 11. calhoun, j. b. (1962) population density and social pathology, scientific american, 206(2), pp. 139–150. 12. carey, j. r., liedo, p., & vaupel, j.w. (1995) mortality dynamics of density in the mediterranean fruit fly, experimental gerontology, 30(6), pp. 605–629. 13. chauvin, r. (2009) animals’ behaviour. moscow: urss: librocom. (in russ.) 14. ramsden, e., & adams, j. (2009) escaping the laboratory: the rodent experiments of john b. calhoun & their cultural influence, the journal of social history, 42(3), pp. 761–792. 15. freedman, j. l. (1975) crowding and behaviour. san francisco: w. h. freeman. 16. moore, j. (1999) population density, social pathology, and behavioral ecology, primates, 40(1), special edition: primate socioecology, pp. 1–22. 17. morris, d. (1996) the human zoo: a zoologist’s study of the urban animal. new york: kodansha america, inc. 18. lorenz, k. (1974) civilized man’s eight deadly sins. london: methuen & co. 19. cacioppo, j. t., mcclintock, m. k., berntson, g. g., & sheridan, j. f. (2005) multilevel integrative analyses of human behavior: social neuroscience and the complementing nature of social and biological approaches, psychological bulletin, 126(6), pp. 829–843. 20. morris, d. (2015) the naked ape: a zoologist’s study of the human animal. london: random house. 21. kulu, h. (2013) why do fertility levels vary between urban and rural areas? regional studies, 47(6), pp. 895–912. doi: 10.1080/00343404.2011.581276 22. newell, a., & gazeley, i. (2012) the declines in infant mortality and fertility: evidence from british cities in demographic transition, economics department working paper series, university of sussex, no. 48–2012. 23. ushie, m. a., ogaboh, agba a. m., olumodeji, e. o., & attah, f. (2011) socio-cultural and economic determinants of fertility differentials in rural and urban cross rivers state, nigeria, journal of geography and regional planning, 4(7), pp. 383–391. 24. fox, j., & myrskylä, m. (2011) urban fertility responses to local government programs: evidence from the 1923–1932 u.s., max planck institute for demographic research. 25. bonoli, g. (2008) the impact of social policy on fertility: evidence from switzerland, journal of european social policy, 18(1), pp. 64–78. doi: 10.1177/0958928707081074 http://doi.org/10.15826/recon.2019.5.3.011 http://dx.doi.org/10.1080/00343404.2011.581276 http://dx.doi.org/10.1177/0958928707081074 114 www.r-economy.ru r-economy, 2019, 5(3), 103–114 doi: 10.15826/recon.2019.5.3.011 online issn 2412-0731 information about the author nadezhda v. shcherbakova – chief specialist of socio-economic research department of scientific research and design institute of territorial development and transport infrastructure (4, letter k, fuchika str., 192102, st. petersburg, russia); e-mail: nadshch@mail.ru article info: received june 06, 2019; accepted august 13, 2019 информация об авторе щербакова надежда викторовна – главный специалист департмамента социально экономических исследований научно-исследовательского и проектного института территориального развития и транспортной инфраструктуры (192102, россия, г. санкт-петербург, ул. фучика, 4, литера к); e-mail: nadshch@mail.ru информация о статье: дата поступления 6 июня 2019 г.; дата принятия к печати 13 августа 2019 г. this work is licensed under a creative commons attribution 4.0 international license эта работа лицензируется в соответствии с creative commons attribution 4.0 international license http://doi.org/10.15826/recon.2019.5.3.011 mailto:nadshch@mail.ru 148 r-economy.com r-economy, 2022, 8(2), 148–160 doi: 10.15826/recon.2022.8.2.012 online issn 2412-0731 original paper © sandler, d.g., gladyrev, d.a., kochetkov, d.m., zorina, a.d., 2022 doi 10.15826/recon.2022.8.2.012 udc 378.3 jel i22, i23, h52 factors of research groups’ productivity: the case of the ural federal university d.g. sandler1, d.a. gladyrev1 , d.m. kochetkov1, 2, a.d. zorina1 1 ural federal university, ekaterinburg, russia;  d.a.gladyrev@urfu.ru 2 centre for science and technology studies, leiden university, leiden, netherlands abstract relevance. one of the main goals of state university support programs in russia is to increase the number of scientific publications. in 2021, project 5-100 was replaced by the program priority 2030 (strategic academic leadership program). the new program increased the significance of the factors affecting the number of publications in universities and the issue of the optimal allocation of funding among research groups. research objective. this study examines the factors that affect the productivity of research groups at the university. unlike the majority of other studies on this topic, this study analyzes scientific productivity at the level of research groups. data and methods. the study was possible due to the availability of data for 79 research groups at the ural federal university for the period from 2014 to 2020. the total number of articles and the number of articles in journals with an impact factor of more than two were used as indicators of research groups’ performance. to determine the factors influencing these indicators, we used econometric models for panel data. we used two separate samples: for social sciences and humanities and for other sciences. results. we identified the following factors affecting the performance of research groups: the number of participants, the age of the research group, the supervisor’s scientific age, and the amount of funding (the possibility of obtaining more funds or being denied funds). the most interesting result is the following: the supervisor’s scientific age and increased funding have a negative impact on the group’s performance. the article provides possible explanations for these results. conclusion. since the purpose of creating and funding research groups is primarily to increase their productivity, the results may be in favor of younger supervisors. university managers may also be interested in the ambiguous impact of increased funding: we suppose that research groups are more motivated not by the actual funding but by the prospective amount they may get. keywords research groups, university economics, economics of higher education, science management, scientometrics, econometric analysis acknowledgements the research funding from the ministry of science and higher education of the russian federation (ural federal university program of development within the priority-2030 program) is gratefully acknowledged. for citation sandler, d.g., gladyrev, d.a., kochetkov, d.m., & zorina, a.d. (2022). factors of research groups’ productivity: the case of the ural federal university. r-economy, 8(2), 148–160. doi: 10.15826/recon.2022.8.2.012 факторы продуктивности исследовательских групп: пример уральского федерального университета д.г. сандлер1, д.а. гладырев1 , д.м. кочетков1, 2, а.д. зорина1 1 уральский федеральный университет, екатеринбург, россия;  d.a.gladyrev@urfu.ru 2 центр исследований науки и технологий, лейденский университет, лейден, нидерланды аннотация актуальность. одной из основных целей программ поддержки государственных университетов в россии является увеличение количества научных публикаций. в 2021 году проект 5-100 был заменен программой приоритет 2030 (программа стратегического академического лидерства). новая программа увеличила значимость факторов, влияющих на количество публикаций в университетах, и вопроса оптимального распределения финансирования между исследовательскими группами. цель исследования. в данном исследовании рассматриваются факторы, влияющие на продуктивность исследовательских групп в университете. в отличие от большинства других исследований по этой теме, данное исследование анализирует научную продуктивность на уровне исследовательских групп. ключевые слова исследовательские группы, экономика вуза, экономика высшего образования, управление наукой, наукометрия, эконометрический анализ https://doi.org/10.15826/recon.2022.8.2.012 https://doi.org/10.15826/recon.2022.8.2.012 mailto:d.a.gladyrev@urfu.ru mailto:d.a.gladyrev@urfu.ru r-economy, 2022, 8(2), 148–160 doi: 10.15826/recon.2022.8.2.012 149 r-economy.com online issn 2412-0731 introduction in any economy, universities and research organizations have limited and usually insufficient resources to provide funding for all possible topics and projects. every year, universities and academic institutions have to distribute limited funds between their research groups to maximize the overall research performance. government agencies and scientific foundations are dealing with a similar problem by setting models and rules for funds distribution between organizations, teams, and individual scientists. sometimes the task is different – how to measure the effectiveness of current funding and reallocate funds without negative consequences. there is a need for the data on the factors affecting research groups’ performance to allow for more evidence-based decision-making. in this case, it данные и методы. исследование стало возможным благодаря наличию данных по 79 научным группам уральского федерального университета за период с 2014 по 2020 годы. в качестве показателя работы исследовательских групп используются показатели её общего числа статей и числа статей в журналах с импакт-фактором более двух. для определения факторов, влияющих на эти показатели, использовались эконометрические модели панельных данных. мы использовали две отдельные выборки: по социально-гуманитарным наукам и по прочим наукам. результаты. выявлены следующие факторы, влияющие на результаты работы групп: количество участников, возраст исследовательской группы, научный возраст руководителя группы и объем финансирования. наиболее интересный результат заключается в следующем: научный возраст научного руководителя и увеличение финансирования негативно сказываются на результативности группы. в статье приведены возможные объяснения этих результатов. вывод. поскольку целью создания и финансирования исследовательских групп является прежде всего повышение их научной результативности, результаты могут говорить в пользу назначения более молодых руководителей. университетских управленцев также может заинтересовать неоднозначное влияние увеличения финансирования: мы полагаем, что исследовательские группы больше мотивированы не фактическим финансированием, а будущей суммой, которую они могут получить. благодарности исследование выполнено при финансовой поддержке министерства науки и высшего образования российской федерации в рамках программы развития уральского федерального университета имени первого президента россии б.н. ельцина в соответствии с программой стратегического академического лидерства «приоритет-2030» для цитирования sandler, d.g., gladyrev, d.a., kochetkov, d.m., & zorina, a.d. (2022). factors of research groups’ productivity: the case of the ural federal university. r-economy, 8(2), 148–160. doi: 10.15826/recon.2022.8.2.012 研究小组的科研效率：以乌拉尔联邦大学为例 桑德勒1，格拉德列夫1 ，科切特科夫1, 2，佐丽娜1 1 乌拉尔联邦大学，叶卡捷琳堡，俄罗斯； d.a.gladyrev@urfu.ru 2 莱顿大学科学技术研究中心，莱顿，荷兰 摘要 现实性：俄罗斯大学支持项目的主要目标之一是增加科研成果。2021 年，“5-100大学计划”被“优先2030计划”（战略学术领导力计划） 所取代。新的计划聚焦于大学的科研出版数量，并优化研究小组之间的 科研资金分配。 研究目标：本研究考察了影响大学各研究小组科研效率的因素。与其他 研究相似主题的大多学者不同，我们把目光转向研究小组的科研效率。 数据与方法：本文收集了乌拉尔联邦大学2014–2020年79个研究小组的 数据，这使研究成果具有代表性。数据来源是科研论文的总数和影响因子 大于2的论文数量。为了确定影响科研效率的因素，我们采用了经济面板 数据模式。另外，我们将科研数据分为两块：社会人文学科和其他学科。 研究结果：研究得出了影响科研效率的因素：参与者人数、研究小组的 成立时间、小组组长的科研年龄及研究经费。最有趣的结果如下：研究 小组组长的科研年龄和研究经费的增加对小组的科研结果有消极影响。 本文对这些结果提出了可能的解释。 结论：创建和资助研究小组的目的主要是提高参与者的科研绩效，从而 有利于任命更年轻的组长。大学的管理层可以对科研经费进行多层计 划：我们认为，更能激励研究小组成员的不是实际科研经费，而是未来 可以获得的额度。 关键词 研究小组，大学经济学，高等 教育经济学，科学管理，科学 计量学，计量模型分析 供引用 sandler, d.g., gladyrev, d.a., kochetkov, d.m., & zorina, a.d. (2022). factors of research groups’ productivity: the case of the ural federal university. r-economy, 8(2), 148–160. doi: 10.15826/recon.2022.8.2.012 https://doi.org/10.15826/recon.2022.8.2.012 mailto:d.a.gladyrev@urfu.ru 150 r-economy.com r-economy, 2022, 8(2), 148–160 doi: 10.15826/recon.2022.8.2.012 online issn 2412-0731 is possible to maximize the efficiency of the research funding system. we have chosen research groups as the main actor in knowledge generation. usually the data on research groups are not available and we can find only the data on universities, countries or individual researchers. but since we have access to the performance indicators of research groups at the ural federal university, it is possible to conduct such analysis. the purpose of the study is to determine the factors of research groups’ effectiveness. the number of publications was chosen as the main performance indicator. to achieve this goal, we collected the data on 79 research groups from the ural federal university (ekaterinburg, sverdlovsk region) for the period from 2014 to 2020 and studied its connection with the regio nal economy. another issue to be considered was data representativeness. based on the data from the ural federal university, we have built econometric models to study the influence of different factors on research productivity and analyzed the results. literature review the idea of using econometric methods to study the factors that affect r&d is not new. such studies were conducted in the second half of the 20th century (pakes, 1978; griliches, 1979; hall, griliches and hausman, 1986; pardey, 1989). many scholars studied the impact of university research on economic growth (jaffe, 1989; acs, audretsch and feldman, 1994; jaffe and trajtenberg, 1996; martin, 1998; varga, 1998, 2000, 2001; fischer and varga, 2003; riddel and schwer, 2003). evaluations were made of research teams’ effectiveness based on a combination of econometric and scientometric methods (adams et al., 2005). among other things, these studies raised the question of the size and composition of research groups (perovic et al., 2016). quite illustrative in this respect is the study of the effectiveness of university hospitals in tehran, performed on the basis of a combination of nonparametric ana lysis methods-data envelope analysis (dea) and stochastic frontier analysis (sfa) (rezapour et al., 2015)in tehran, iran. methods: this study was conducted in 2012; the research population consisted of all hospitals affiliated to iran and tehran medical sciences universities of. required data, such as human and capital resources information and also production variables (hospital outputs. there is a substantial body of research that establishes links between scientometric, economic, and other indicators at the university level (zinchenko and yegorov, 2019; geiger, 2004). in particular, for russian universities, it was shown that the number of publications is higher in the universities that: 1) are engaged in research in physics; 2) have a higher share of international collaborations; 3) accept students with a higher entrance score; 4) have a larger share of master’s and phd students; 5) have higher levels of citations; 6) have a higher share of foreign students; 7) have a higher level of salaries in comparison with the region’s average (sandler & gladyrev, 2020). a high positive correlation between the number of publications and their quality (usually measured by the level of citations of these articles or the journal in general) has also been revealed by international studies at the level of individual researchers (michalska-smith and allesina, 2017), at the university level (hayati and ebrahimy, 2009), and at the national level (lawani, 1986). other studies have shown a positive effect of collaboration (landry et al., 1996), especially international (aldieri et al., 2018; aldieri et al., 2019). a j-shaped impact of government funding was also revealed in some sectors, but there was no impact of business funding (beaudry & allaoui, 2012). there is evidence of the positive impact of the long-term university-industry interactions (garcia et al., 2020). in a study based on the university data in leuven (belgium), the authors have shown higher scientific productivity of female researchers and researchers with an academic degree (de witte & rogge, 2010). another study based on the spanish data, on the contrary, demonstrated a higher scientific performance of male researchers (albert et al., 2016). some other studies compared young and older researchers: it was found that the young researchers have a higher level of scientific performance (levin and stephan, 1989; albert et al., 2016). it is also worth noting that all these factors can have a different impact on scientific productivity, depending on the level of the considered journals (jung et al., 2017). data and methods we used the data on the performance of 79 research groups of the ural federal university (ekaterinburg) for the period from 2014 to 2020. the data were provided by the university’s department of strategic development and marketing. due to the fact that not all research groups https://doi.org/10.15826/recon.2022.8.2.012 r-economy, 2022, 8(2), 148–160 doi: 10.15826/recon.2022.8.2.012 151 r-economy.com online issn 2412-0731 were functioning during the entire reviewed period, the total number of observations was 438. from an organizational point of view, a research group (in the university’s documentation it is referred to as a “competence center”) is a team selected on a competitive basis in order to support its members’ research activities. commitments to work on a specific topic formulated by the research team are recorded in the project passport, which also specifies the planned indicators for the number of publications, the amount of r & d, and additional indicators. annually, a special commission of reputable researchers (direct conflicts of interest are exclu ded) evaluates each group’s activities: the dyna mics of the key indicators and correspondence to the obligations taken. these evaluations are used further by the special council that divides research groups into several funding groups. groups with better results receive more funding. every year, from 2 to 5 groups are denied funding for a year or are completely withdrawn from the project. instead, several new research groups are introduced on a competitive basis. one of the signs of the project’s success is a significant increase in the university’s publication activity (see table 1): the total number of publications almost tripled in 6 years and research groups kept more than a half of the university’s articles for almost all of the years (and more than 60% of articles in journals with an impact factor of more than 2). despite these results, we assume that there is still room for improvement in terms of the funding system’s efficiency. in this study, we took all the variables included in research groups’ reports, with the exception of the number of articles in journals with if>5 (as only few research groups have such publications). one variable (the supervisor’s scientific age) was collec ted manually for all research groups from scopus. the original dataset has eight variables: 1) articles is the number of articles of the research group indexed in scopus and web of science in the reporting year. 2) articles in if>2 is the number of articles of the research group in journals with if>2 indexed in scopus and web of science in the reporting year. 3) funding is the amount of funding for the research group in the reporting year, million rubles. 4) participants is the number of participants in the research group at the end of the reporting year. table 1 dynamics of the number of articles published by the university’s researchers indexed in scopus and web of science year total number of articles articles of research groups share of research groups’ articles total articles in if>2 journals articles of research groups in if>2 journals share of research groups’ articles in if>2 journals 2014 1413 836 59.16% 275 201 73.09% 2015 1742 1091 62.63% 387 265 68.48% 2016 2334 1256 53.81% 480 350 72.92% 2017 2930 1482 50.58% 611 391 63.99% 2018 3253 1594 49.00% 710 437 61.55% 2019 3772 1992 52.81% 954 567 59.43% 2020 3946 2001 50.71% 991 639 64.48% source: compiled by the authors table 2 descriptive statistics articles articles in if>2 funding participants project age social-hum supervisor’s scientific age r&d average 23.21 6.507 2.263 19.925 3.753 0.18 23.388 12.969 median 17 2 1,4 15 4 0 0 0 maximum 107 68 15.593 112 7 1 53 398.61 minimum 0 0 0.08 1 1 0 14.76 32.77 standard deviation 20.465 10.383 2.686 16.956 1.967 0.385 23.39 12.97 source: compiled by the authors https://doi.org/10.15826/recon.2022.8.2.012 152 r-economy.com r-economy, 2022, 8(2), 148–160 doi: 10.15826/recon.2022.8.2.012 online issn 2412-0731 5) project age is the number of the year when the research group received funding (starting from 2014, when the program in its current format was launched). 6) social-hum is a binary variable equal to 1 if the research group belongs to social sciences and arts & humanities (there are 15 such groups with 79 observations) and 0 otherwise (there are 64 such groups with 359 observations); 7) supervisor’s scientific age is the number of years since the first supervisor’s scopus-indexed article was published. 8) r & d is the declared amount of r&d income of the research group, million rubles. the main statistical characteristics of the variables are shown in table 2. the econometric models took into account the panel data structure; the tests proved that the best model is a model with fixed effects. the main variable is δ articles; an additional model also uses the variable δ articles in if>2. the analysis of the second model is less interesting, since the selected indicator has a very low deviation (a significant number of research groups do not have any articles in journals with an impact factor higher than two). it should be noted that different subject areas have different average impact factors. the impact of the total time that the research group has been receiving organized funding was considered in variable project age. the model also included variables δ funding and δ r & d. using variables δ articles, δ funding and δ r & d (instead of articles, funding, and r & d directly) helps us overcome endogeneity and outliers. taking into account the fact that the effect of funding growth can be lagged, the models were created with both the current and the previous period value. since many of the considered dependencies are not strictly linear, preference was given to non linear dependencies. for this reason, the model did include natural logarithms of participants and the supervisor’s scientific age. the social-hum variable was used to divide the sample into two and create a separate model for each of them. this is done under the assumption that research groups in social sciences and arts & humanities are significantly different from others. table 3 confirms this assumption: almost all the key indicators differ in comparison with the research groups specializing in social sciences and the humanities. table 3 average values by category of research groups social sciences and humanities (n = 79) other sciences (n = 359) average number of articles 12.48 25.57 average number of articles in journals with if > 2 0.59 7.81 average annual funding, mln 1.45 2.44 average number of participants 16 20.79 source: compiled by the authors thus, the following variables were taken as explanatory variables: 1. project age 2. δgrowth 3. δfunding 4. log (participants) 5. log (scientific age of the supervisor) 6. r & d the issue of representativeness should be also considered. is it possible to use the ural federal university’s data to study the performance factors of research groups in general? there is a number of reasons for considering the university’s research groups as a representative sample: the university has a very high scientific performance (it ranks 10th among all the russian institutions and 7th among universities by the total number of publications in 2015–2020, according to scival); it also boasts a diversity of subject areas. it should, however, be noted that the university’s scientific performance is connected with the structure of sverdlovsk region’s economy (and to some extent to that of other neighboring regions). at the same time, we can assume that the university’s scientific performance also affects the structure of the region’s economy. the impact of research on the economic development of regional economies is one of the tasks of the federal program “priority 2030”1. table 4 shows how the distribution of subject areas at the ural federal university differs from the national-level distribution. these differences include a higher share of articles in physics and astronomy, materials science and chemistry, and a lower share in medicine, environmental science, energy and agricultural and biological sciences. 1 https://priority2030.ru/about https://doi.org/10.15826/recon.2022.8.2.012 https://priority2030.ru/about r-economy, 2022, 8(2), 148–160 doi: 10.15826/recon.2022.8.2.012 153 r-economy.com online issn 2412-0731 table 4 comparison of the share of subject areas of publications of the ural federal university and in russia as a whole subject fields share in russia share of the university physics and astronomy 14.4% 21.4% engineering 12.2% 12.4% materials science 9.7% 16.5% computer science 6.6% 5.9% medicine 6.5% <2% earth and planetary sciences 6.2% 2.6% chemistry 6.0% 8.6% mathematics 5.7% 6.0% social sciences 4.8% 4.3% environmental science 4.6% 2.9% biochemistry, genetics and molecular biology 3.8% <2% energy 3.3% <2% agricultural and biological sciences 2.9% <2% chemical engineering 2.8% <2% arts and humanities 2.6% 2.1% source: scival from 2016 to may 2022 table 5 shows the differences between the economy of sverdlovsk region and the national economy. these differences include a lower share of natural resources in sverdlovsk region and a higher share of manufacturing. the parallels between the deviations in the university’s subject areas from the national ones and between the deviations of the regional economy from the national economy are shown in table  6. the main positive deviations in the university’s subject areas are related to physics, chemistry and materials sciences and these deviations can be connected with the dominance of the most powerful branch of sverdlovsk region’s economy – manufacturing. on the contrary, the subject areas corresponding to earth sciences, energy, environmental economics, and agriculture at the ural federal university are below the national average, which can be explained by the lower (in comparison with the national) share of the region’s economy in mining and agriculture. all of these findings are consistent with the previous studies that noted close links between universities, government, and business in russian regions (vlasova & lyashenko, 2021). table 5 industry structure of gross value added in 2019 in russia branch share in russia share in sverdlovsk region difference between sverdlovsk region and country in general agriculture, forestry, hunting, fishing and fish farming 4.1 2.4 –1.7 natural resources / mining 13.5 2.1 –11.4 manufacturing 16.8 31.9 15.1 provision of electric energy, gas and steam; air conditioning 2.9 3.9 1 water supply; water disposal, organization of waste collection and disposal, activities to eliminate pollution 0.6 1.1 0.5 construction 5.4 4 –1.4 wholesale and retail trade; repair of motor vehicles and motorcycles 14.2 12.7 –1.5 transportation and storage 7.3 7.5 0.2 activities of hotels and public catering 1 1 0 information and communication activities 3 2.4 –0.6 financial and insurance activities 0.5 0.2 –0.3 real estate operations 10 10.4 0.4 professional, scientific and technical activities 4.3 4.2 –0.1 administrative activities and related additional services 2.3 2 –0.3 public administration and military security; social security 5.6 5.7 0.1 education 3 3.1 0.1 health and social services activities 4 4.1 0.1 activities in the field of culture, sports, leisure and entertainment 1 0.7 –0.3 provision of other types of services 0.5 0.6 0.1 activity of households as employers 0 0 0 source: rosstat: https://gks.ru/bgd/regl/b21_14p/main.htm https://doi.org/10.15826/recon.2022.8.2.012 https://gks.ru/bgd/regl/b21_14p/main.htm 154 r-economy.com r-economy, 2022, 8(2), 148–160 doi: 10.15826/recon.2022.8.2.012 online issn 2412-0731 among the factors that speak in favor of the representativeness of the data is the fact that the university was formed relatively recently by merging a classical and technical university (with different cultures of academic activity). the final argument is that the sample includes groups that differ in terms of their research experience and the level of citation. it should be noted that the detected dependencies will be sufficiently reliable only for the ural federal university, and in other universities, due to historical, organizational and subject area differences, the patterns may be different. some variables were not used for our ana lysis because their variation was too low. the most interesting of these variables is the supervisor’s gender. table 7 shows the distribution of research groups by the supervisor’s gender and subject area. of the 79 research groups under review, 60  are supervised by men and 19, by women. at the same time, among the groups in social sciences and the humanities, women lead 9 out of 15 research groups. table 7 statistics of research groups by the supervisor’s gender social sciences and humanities other sciences total male 6 54 60 female 9 10 19 source: compiled by the authors results the correlation matrix (see table 8) gives us a basic understanding of the relationships between the variables and helps us make sure that the resulting models will not have multicollinearity (high correlation between the factors). it should be noted that an increase in the number of articles does not result in a decrease in their quality. the correlation coefficient between an increase in the number of articles and an increase in the number of articles in journals with if>2 is 0.56. thus, the goals of increasing the total number and quality of articles are not contradictory and even accompany each other. previously, a similar link was established for russian universities (sandler & gladyrev, 2020), and now it has been demonstrated at the level of individual research groups. our conclusions, however, cannot be interpreted in such a way that an increase in the number of articles will always be accompanied by an increase in their quality. table 9 shows the results of the first model with fixed effects, where the explained variable is the growth in the number of articles of the research group. the most reliable factor determining the growth in the number of articles is the size of the given research group. this means that an increase in the size of the research group leads to an increase in the number of scientific articles and this result is not as trivial as it may seem. often, estable 6 comparison of the differences in scientific performance between the university and russia and corresponding branches of the regional economy and russia branch difference between russia and sverdlovsk region subject area difference between russia and the university mining russia: 13.5%sr: 2.1% ↓ earth and planetary sciences russia: 6.2% urfu: 2.6%↓ environmental science russia: 4.6%urfu: 2.9%↓ energy russia: 3.3%urfu: <2%↓ manufacturing russia: 16.8%sr: 31.9% ↑ physics and astronomy russia: 14.4%urfu: 21.4%↑ materials science russia: 9.7%urfu: 16.5%↑ chemistry russia: 6.0%urfu: 8.6%↑ agriculture, forestry, hunting, fishing and fish farming russia: 4.1% sr: 2.4% ↓ agricultural and biological sciences russia: 2.9% urfu: <2%↓ source: scival from 2016 to may 2022 and rosstat: https://gks.ru/bgd/regl/b21_14p/main.htm https://doi.org/10.15826/recon.2022.8.2.012 https://unicode-table.com/ru/2191/ https://unicode-table.com/ru/2191/ https://unicode-table.com/ru/2191/ https://unicode-table.com/ru/2191/ https://gks.ru/bgd/regl/b21_14p/main.htm r-economy, 2022, 8(2), 148–160 doi: 10.15826/recon.2022.8.2.012 155 r-economy.com online issn 2412-0731 table 8 correlation matrix δ articles δ articles in if>2 project age δ funding log(participants) log(supervisor’s scientific age) δ r & d δ articles 1.00 δ articles in if>2 0.56 1.00 project age 0.01 0.10 1.00 δ funding –0.09 –0.10 0.44 1.00 log(participants) 0.20 0.11 0.38 0.04 1.00 log(supervisor’s scientific age) –0.02 0.03 0.10 –0.05 0.18 1.00 δ r & d –0.05 –0.03 –0.03 –0.12 0.03 0.03 1.00 table 9 model for the number of the research group’s articles variable explained variable – δ articles other subject areas social sciences and humanities (1) (2) (3) (4) project age –0.456 (0.71) 0.67 (1.01) 2.24 (1.37) 3.83*** (1.2) δ funding –0.22 (0.49) –1.53* (0.73) δ funding(-1) –0.55 (0.55) –0.85** (0.36) log(participants) 6.76*** (2.34) 4.67 (3.31) 7.8* (3.75) 9.48*** (2.75) log(supervisor’s scientific age) –10.85** (5.22) –10.29* (5.56) –14.28** (6.09) –21.1*** (5.17) δ r & d –0.036* (0.02) –0.03* (0.018) –0.072 (0.19) –0.11 (0.16) constant 20.39 (15.68) 18.2 (14.9) –7.59 (7.48) –8.91* (4.95) panel data model with fixed effects robust standard errors are shown in parentheses *** significant at the 1% significance level ** significant at the 5% significance level * significant at the 10% significance level pecially when the recruitment of new members of the research group is limited only to university employees, students, and postgraduates, it may seem that new members of the group will not give a significant increase in articles (or will do it only with a lag); and the main growth potential lies in increasing the productivity of the group’s core. the results show that this is not true. an interesting and even paradoxical result connected with the coefficient of the supervisor’s scientific age is as follows: a negative sign and high statistical reliability indicate that the more experienced is the supervisor, the lower is the group’s rate of publication growth; and vice versa. some reservations, however, should be made regarding the interpretation of this result: it does not mean that groups with an experienced scientific supervisor have a low scientific outcome, but that such groups are less likely to increase their scientific performance, and their potential is already rea lized. since one of the main goals of forming research groups is increasing their scientific productivity by using university funding, this result can be used in favor of appointing younger mana gers. some previous studies have shown the lower scientific performance of more senior researchers in many subject areas (levin and stephan, 1989; albert et al., 2016). https://doi.org/10.15826/recon.2022.8.2.012 156 r-economy.com r-economy, 2022, 8(2), 148–160 doi: 10.15826/recon.2022.8.2.012 online issn 2412-0731 the role of funding growth is also a paradoxical result at first glance. we could expect a reliable direct relationship between increased funding and the growth in the number of articles, but it is not observed both for current and previous funding; moreover, there is some evidence in favor of the inverse relationship. it is fair to note that the statistical reliability of this result is not high. one explanation for this result is the motivation factor: research groups whose funding has been reduced or increased slightly are more motiva ted to achieve high scientific performance in the hope of receiving higher funding for the next year. the groups that have already received substantial funding can be satisfied with merely maintai ning the last year’s level of performance. thus, it is possible that a prospective increase in funding is a stronger motivating factor than maintaining the same level of funding. for the growth in r & d, the results are also interesting: in all the models the dependence is negative (but only in two models this coefficient is significant at the 10% significance level). it means that the higher is the growth in r & d income, the lower is the increase in the number of articles. this may indicate that income-gene rating research work and scientific publications are not complementary activities, but rather substitutes – at least in terms of the dynamics of the indicators. table 10 shows the results of the second model, where the explained variable is the number of articles of the research group in journals with an impact factor of more than two. the results of this model show approximately the same results as it was for the first model. the growth in the number of articles in journals with if>2 is also positively connected with the number of participants in the research group, negatively connected with the supervisor’s scientific age (but this result is statistically significant only for social sciences and arts & humanities), and there is weak evidence of the negative impact of increased funding on the growth in the number of articles. like in the previous model, there is a negative impact of the growth in research volumes for other sciences. we found a significant impact of the project’s period for projects in social sciences and arts & humanities, where the number of publications in high-impact journals tends to be lower (wos arts and humanities citation index doesn’t have if at all). it can be assumed that the accumulated experience and interaction within the team allow research groups to increase their publications in such journals over time. table 10 model for the number of research group articles in journals with if>2 variable explained variable – δ articles in if>2 other subject areas social sciences and humanities (1) (2) (3) (4) project age 0.413 (0.48) 0.83 (0.72) 1.65** (0.73) 2.11** (0.86) δ funding –0.57* (0.32) –0.84 (0.63) δfunding(–1) –0.39 (0.36) 0.04 (0.39) log(participants) 2.63** (1.26) 2.07 (1.52) 2.71* (1.27) 3** (1.33) log(supervisor’s scientific age) –1.67 (2.81) –2.96 (2.6) –5.34** (2.33) –8.43** (3.66) δ r & d –0.017** (0.007) –0.013* (0.007) 0.08 (0.69) 0.08 (0.07) constant term –3.1 (7.2) 0.23 (5.01) –6.95 (3.12) –4.75 (2.57) panel data model with fixed effects robust standard errors are shown in parentheses ** significant at the 5% significance level * significant at the 10% significance level https://doi.org/10.15826/recon.2022.8.2.012 r-economy, 2022, 8(2), 148–160 doi: 10.15826/recon.2022.8.2.012 157 r-economy.com online issn 2412-0731 conclusion this paper contributes to the study of the factors of scientific productivity at the level of research groups. the econometric models based on the data of the ural federal university have brought to light the factors that affect the scientific performance of research groups. the main factor influencing the growth in the number of articles is the number of research group’s participants. the positive effect of this factor turned out to be statistically significant for most of the models. the influence of the next two factors was paradoxical. first, there is a negative influence of the supervisor’s academic age on the growth in the number of articles. although the paper explains this result as well as cautions against its misinterpretation, the main recommendation is that more credit should be given to younger managers. secondly, the negative impact of increased funding on the growth in the number of articles of the research group. this result is explained by the specific motivation of research groups, but it should also be interpreted with great caution, especially because it can affect the university leadership’s decision-making regarding funding allocation. the age of the research group is also one of the factors that positively affects the growth in scientific performance, but only for social sciences and arts & humanities, and especially for high-impact articles. perhaps this is because social sciences and arts & humanities in russia are younger, which is why the effect of the creation of such groups is stronger. in both models for other sciences, a negative relationship between the growth in articles and the growth of r&d income was detected. this suggests that a simultaneous growth in these indicators can be problematic. the value of these results may be influenced by the fact that only research groups of the ural federal university are included in the sample. this was a forced limitation caused by the fact that we had access only to one university’s data on individual research groups while the corresponding data for other universities are closed. it is shown that the structure of the ural federal university’s publications to some extent reflects the specifics of sverdlovsk region, and with a high degree of reliability, the conclusions can be applied only to this university, but the large sample size and variety of subject areas allow us to assess the possibility of applying these conclusions to other universities optimistically. it will be interesting to observe the changes in the performance of research groups in connection with the launch of the new priority 2030 federal program in russia and changes in the target indicators in comparison with the previous program (project 5-100). due to the new emphasis on the number of articles in the first and second quartiles, we should expect an increase in the number of high-quality publications. it is unlikely that this increase will lead to a decrease in the total number of publications (as quality and quantity usually go together), but the growth rate of the total number of publications of research groups is likely to decrease. references acs, z.j., audretsch, d.b., & 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(2019). modeling the effectiveness of russian universities. economic journal of the higher school of economics, 23(1), 143–172. information about the authors daniil g. sandler – phd in economics, associate professor at the department of international economics and management, graduate school of economics and management; leading researcher, research laboratory for university development issues, first vice-rector (economics and strategy), ural federal university (19 mira str., 620002 ekaterinburg, russia); scopus author id: 56581474400; orcid: 0000-0002-5641-6596; e-mail: d.g.sandler@urfu.ru dmitry a. gladyrev – senior lecturer at department of economics, graduate school of economics and management, ural federal university (19 mira str., 620002 ekaterinburg, russia); scopus author id: 57208191401; orcid: 0000-0001-5746-0495; e-mail: d.a.gladyrev@urfu.ru dmitry m. kochetkov – phd in economics, senior researcher at the laboratory for university development, ural federal university (19 mira str., 620002 ekaterinburg, russia); phd candidate at the center for science and technology studies, leiden university (willem einthoven building, kolffpad 1, 2333 bn leiden, netherlands); scopus author id: 57194605735; orcid: 0000-00017890-7532; e-mail: d.kochetkov@cwts.leidenuniv.nl anna d. zorina – deputy of head, department of strategic development and marketing, ural federal university (19 mira str., 620002 ekaterinburg, russia) article info: received april 15, 2022; accepted june 2, 2022 информация об авторах сандлер даниил геннадьевич – кандидат экономических наук, доцент кафедры международной экономики и менеджмента, институт экономики и управления; ведущий специалист научно-исследовательской лаборатории по проблемам университетского развития, первый проректор по экономике и стратегическому развитию, уральский федеральный университет (620002, россия, екатеринбург, ул. мира, 19); scopus author id: 56581474400; orcid: 0000-0002-5641-6596; e-mail: d.g.sandler@urfu.ru гладырев дмитрий анатольевич – старший преподаватель кафедры экономики, институт экономики управления, уральский федеральный университет (620002, россия, екатеринбург, ул. мира, 19); scopus author id: 57208191401; orcid: 0000-0001-5746-0495; e-mail: d.a.gladyrev@urfu.ru кочетков дмитрий михайлович – кандидат экономических наук, старший научный сотрудник научно-исследовательской лаборатории по проблемам университетского развития, уральский федеральный университет (620002, россия, екатеринбург, ул. мира, 19); аспирант центра исследований науки и технологий, лейденский университет (2333 bn, нидерланды, лейден, willem einthoven building, kolffpad 1); scopus author id: 57194605735; orcid: 00000001-7890-7532; e-mail: d.kochetkov@cwts.leidenuniv.nl зорина анна дмитриевна – заместитель директора управления стратегического развития и маркетинга, уральский федеральный университет (620002, россия, екатеринбург, ул. мира, 19); e-mail: a.d.zorina@urfu.ru информация о статье: дата поступления 15 апреля 2022 г.; дата принятия к печати 2 июня 2022 г. https://doi.org/10.15826/recon.2022.8.2.012 https://www.scopus.com/authid/detail.uri?authorid=56581474400 https://orcid.org/0000-0002-5641-6596 mailto:d.g.sandler@urfu.ru https://www.scopus.com/authid/detail.uri?authorid=57208191401 https://orcid.org/0000-0001-5746-0495 mailto:d.a.gladyrev@urfu.ru https://www.scopus.com/authid/detail.uri?authorid=57194605735 https://orcid.org/0000-0001-7890-7532 https://orcid.org/0000-0001-7890-7532 mailto:d.kochetkov@cwts.leidenuniv.nl https://www.scopus.com/authid/detail.uri?authorid=56581474400 https://orcid.org/0000-0002-5641-6596 mailto:d.g.sandler@urfu.ru https://www.scopus.com/authid/detail.uri?authorid=57208191401 https://orcid.org/0000-0001-5746-0495 mailto:d.a.gladyrev@urfu.ru https://www.scopus.com/authid/detail.uri?authorid=57194605735 https://orcid.org/0000-0001-7890-7532 https://orcid.org/0000-0001-7890-7532 mailto:d.kochetkov@cwts.leidenuniv.nl mailto:a.d.zorina@urfu.ru 160 r-economy.com r-economy, 2022, 8(2), 148–160 doi: 10.15826/recon.2022.8.2.012 online issn 2412-0731 作者信息 桑德勒·丹尼尔·根纳季耶维奇——经济学博士，国际经济管理系副教授，经济管 理学院，大学发展研究实验室资深专家，经济与战略发展第一副校长，乌拉尔联邦大 学（邮编：620002，俄罗斯，叶卡捷琳堡，米拉大街19号）；scopus author id: 56581474400; orcid: 0000-0002-5641-6596; 邮箱：d.g.sandler@urfu.ru 格拉德列夫·德米特里·阿纳托利耶维奇——经济系高级讲师，经济管理学院，乌拉尔 联邦大学（邮编：620002，俄罗斯，叶卡捷琳堡，米拉大街19号）；scopus author id: 57208191401; orcid: 0000-0001-5746-0495; 邮箱：d.a.gladyrev@urfu.ru 科切特科夫·德米特里·米哈伊洛维奇——经济系博士，大学发展研究实验室高级研究 员，乌拉尔联邦大学（邮编：620002，俄罗斯，叶卡捷琳堡，米拉大街19号）；莱顿大 学科学技术研究中心博士在读（邮编：2333 bn，荷兰，莱顿，willem einthoven building, kolffpad 1）；scopus author id: 57194605735; orcid: 0000-0001-7890-7532; 邮箱：d.kochetkov@cwts.leidenuniv.nl 佐丽娜·安娜·德米特里耶夫娜——战略发展与市场部副部长，乌拉尔联邦大学（邮 编：620002，俄罗斯，叶卡捷琳堡，米拉大街19号）；邮箱：a.d.zorina@urfu.ru https://doi.org/10.15826/recon.2022.8.2.012 https://www.scopus.com/authid/detail.uri?authorid=56581474400 https://orcid.org/0000-0002-5641-6596 mailto:d.g.sandler@urfu.ru https://www.scopus.com/authid/detail.uri?authorid=57208191401 https://orcid.org/0000-0001-5746-0495 mailto:d.a.gladyrev@urfu.ru https://www.scopus.com/authid/detail.uri?authorid=57194605735 https://orcid.org/0000-0001-7890-7532 mailto:d.kochetkov@cwts.leidenuniv.nl mailto:a.d.zorina@urfu.ru r-economy, 2020, 6(2), 89–99 doi: 10.15826/recon.2020.6.2.008 89 https://journals.urfu.ru/index.php/r-economy online issn 2412-0731 original paper © akberdina, v.v., sergeeva, a.s., 2020 doi 10.15826/recon.2020.6.2.008 strategic priorities for the development of middle regions in russia v.v. akberdina , a.s. sergeeva institute of economics of the ural branch of the russian academy of sciences, ekaterinburg, russia; e-mail: akb_vic@mail.ru abstract relevance. the key factor in the development of any region is its geographical position in the socio-economic and geopolitical space of the country. in this respect, middle regions are of particular interest. unfortunately, their unique qualities remain largely underexplored in research literature, which is the gap this article seeks to address. research objective. the purpose of the study is to provide a definition of the concept ‘middle region’, describe its key characteristics and align them with the strategic priorities in the development of such regions. data and methods. the research methodology centres around the notion of cumulative effect of the middle region and the tools for its assessment. this effect is associated with enhanced socio-economic efficiency of a territorial capital resulting from the advantages of its middle position. among other things, this effect manifests itself through higher economic returns on investment. the empirical part of the study relies on the data on 36 russian middle regions, their missions and priorities of strategic development. results. the article summarizes the russian and international theoretical approaches to the definition of the middle regions, their place and role in the territorial structure of a country and its socio-economic development. it is shown that most authors assign middle regions the role of the country’s epicenter, highlighting their key role in economy, culture, politics and other spheres of life. the approach proposed in this study focuses on middle regions’ position in space, on the one hand, and, on the other, sees them as systems of interactions in the socio-economic space. based on this understanding of the middle region, several groups of russian middle regions are identified: integrators, sustainable middle regions and developing middle regions. conclusions. the mission of middle regions is one of the fundamental concepts of strategic management, comprising a hierarchy of goals. it is shown that although the mission of middle regions should be to become integrators of the country’s socio-economic space through the network of inter-territorial and global interactions, not all russian middle regions are ready to pursue this ambitious goal and prefer to focus on addressing internal goals of their own. keywords middle regions, strategic priorities, mission, economic and geographical position, resonant effect acknowledgements the research was supported by the institute of economics of the ural branch of the russian academy of sciences (research plan for 2019–2021). for citation akberdina, v.v., & sergeeva, a.s. (2020) strategic priorities for the development of middle regions in russia. r-economy, 6(2), 89–99. doi: 10.15826/recon.2020.6.2.008 стратегические приоритеты развития срединных регионов россии в.в. акбердина , а.с. сергеева институт экономики уральского отделения российской академии наук, г. екатеринбург, россия; e-mail: akb_vic@mail.ru аннотация актуальность. ключевым фактором развития любого региона является его географическое положение в социально-экономическом и геополитическом пространстве страны. среди различных типов пространственных позиций региона по отношению к его стране значимо выделяются срединные регионы. цель исследования. целью исследования является формулировка подхода к идентификации срединных регионов и обоснованию стратегических приоритетов их развития. данные и методы. методология исследования сосредоточена вокруг понятия «кумулятивного срединного эффекта» и предлагают методический инструментарий его оценки. данный эффект представляет собой превышение ключевых социально-экономических показателей срединного региона над среднероссийскими показателями. помимо прочего, этот эффект проявляется через более высокую экономическую отдачу от инвестиций. для проведения эмпирического исследования были отобраны 36 регионов российской федерации. все они ключевые слова срединные регионы; стратегические приоритеты; миссия; экономикогеографическое положение, резонансный эффект http://doi.org/10.15826/recon.2020.6.2.008 http://doi.org/10.15826/recon.2020.6.2.008 mailto:akb_vic@mail.ru mailto:akb_vic@mail.ru 90 https://journals.urfu.ru/index.php/r-economy r-economy, 2020, 6(2), 89–99 doi: 10.15826/recon.2020.6.2.008 online issn 2412-0731 классифицируются по географическому положению как средние регионы. результаты. в статье обобщены теоретические подходы российских и зарубежных ученых к определению срединных регионов, их месту и роли в территориальном устройстве страны и ее социально-экономическом развитии. показано, что большинство авторов отводят срединным регионам роль главного эпицентра страны, выделяют его решающее участие в делах государства, сохраняющуюся за ним ключевую роль в экономике, культуре, политике и других сферах жизни. подход, предложенный в этом исследовании, фокусируется на положении срединных регионов в пространстве, с одной стороны, и, с другой стороны, рассматривает их через систему взаимодействий в социально-экономическом пространстве. проведенное исследование позволило авторам выделить такие типы средних регионов, как «интегратор экономического пространства», «устойчивый средний регион» и «развивающийся средний регион». выводы. миссия срединных регионов – одна из фундаментальных концепций стратегического управления, и она включает в себя иерархию целей. показано, что, хотя миссия средних регионов должна состоять в том, чтобы стать интеграторами социально-экономического пространства страны через сеть межтерриториальных и глобальных взаимодействий, не все средние российские регионы готовы преследовать эту амбициозную цель и предпочитают сосредоточиться на решение внутренних задач самостоятельно. благодарности работа выполнена при поддержке института экономики уральского отделения российской академии наук (план исследований на 2019–2021 гг.). introduction the location of a region in socio-economic and geopolitical space is a crucial factor of its development. rodoman (2012) defines spatial position as ‘a set of spatial aspects characterizing the relationship of an object to other objects that are essential for the object in question’ and proves that the properties of objects depend on their position in space. he refers to this set of spatial aspects as the ‘pressure of the place’ or ‘positional pressure’. the position of an object in space is not only its ‘absolute’ position in the geographical system of coordinates but also its position in relation to other objects. in addition, the position of an object in space must be considered and determined within the system of time coordinates. although one can speak of an object’s position in space from different perspectives, such as physical-geographical, political-geographical, cultural-geographical, geopolitical, and so on, the economic-geographical position (egp) is by far the most significant. according to gritsay et al. (2002), the egp can be considered not only as a factor, but also as ‘an important territorial resource that mediates the role of external resources for this object and affects its development along with its own natural and labor resources, as well as scientific and technical potential’. pilyasov (2011) analyzes the egp as a ‘special kind of asset’. some studies place a special emphasis on innovation, i.e. the position of an object in relation to the ways of spreading new knowledge and processes (innovation) of different significance and scale (bulaev & novikov, 2011; leizerovich, 2006). the concept of economic-geographical position is inextricably linked to the concept of economic space, which, on the one hand, is a combination of the territory where economic entities are located and their interactions and, on the other hand, the socio-economic environment where these interactions take place, formed by mechanisms of economic regulation in the given territory. it should be noted that economic space usually comprises such elements as economic entities; relations and interactions between them; regulatory mechanisms determined by the institutional conditions within the territory (norms and rules for regulating relations) (baldwin et al., 2003; bathelt & glückler, 2003; тота et al., 2014). a region can occupy various spatial positions within the country, for example, it can be located in the middle and in this case, it can be referred to as a middle region. the middle region, due to its location, accumulates many functions: production, social, political, and other. the purpose of the study is to describe an approach that can be used to identify middle regions and determine strategic priorities of their development. our study will consider the topological features of middle regions, the effects their position within the country has on their development and their mission in the overall development of the country. our research contributes to the theory of regional economics by clarifying the concept ‘middle region’, describing its topological features, and highlighting its mission. the proposed methodo logy can be of use to regional and federal authoriдля цитирования akberdina, v.v., & sergeeva, a.s. (2020) strategic priorities for the development of middle regions in russia. r-economy, 6(2), 89–99. doi: 10.15826/recon.2020.6.2.008 http://doi.org/10.15826/recon.2020.6.2.008 r-economy, 2020, 6(2), 89–99 doi: 10.15826/recon.2020.6.2.008 91 https://journals.urfu.ru/index.php/r-economy online issn 2412-0731 ties when developing, adjusting and updating spatial development strategies. conceptual framework to understand what distinguishes the middle region as a separate type of regions, it is necessary to look at other types or classes of regions. according to gladkiy & chistobaev (2011), more than 50 categories of regions are identified in research literature. we are going to focus only on the most relevant typologies of regions, for example, the distinctions between central and peripheral regions or such types as coastal regions, border regions and remote regions (golubev, 2011). the concept of middle region is closely connected to that of a ‘central’ region. it should be noted that ‘center’ and ‘middle’ are not synonymous from the perspective of regional economy and economic geography. in the classical sense, these two words have a very close meaning: the center is the middle and main part of something; the core, the place of concentration of something. both notions have been established in regional economics and geography. the term ‘central’ is closer in its meaning to the concept of ‘capital’ than to ‘middle’. in the concept ‘middle region’, one can more clearly trace its main distinctive feature – territorial location in the middle of a country, continent, part of the world or another larger spatial unit. the term ‘center’ as well as other related structural taxonomic elements is defined by alaev (2010) in socio-economic dictionary the following way: the ‘center’ is a point (a geographical object or section) whose connections with the surroun ding area are functional. the center that distri butes flows of matter, energy, and information to the surrounding landscape and generally transmits its characteristics to the landscape should be called the focus (or center of diffusion, distribution); the center towards which there is a contraction, concentration of matter and energy – the focus (or center of attraction). according to alaev (2010), the concepts ‘center’, ‘focus’, and ‘core’ suggest the presence of an opposing, complementary taxon territory, which in this case is called the periphery. the concepts of centrality and middle play an important role in many theories of production organization (losch, 1944; weber, 1909; christaller, 1933; isard, 1960; krugman, 1991; lukermann, 1960). however, middle regions differ from central ones (although theoretically they may coincide) because the former are not necessarily located in the historical center of the country and are not always endowed with all the high capital functions, including administrative and managerial ones. the middle region is a region that is located in the middle of a higher-order territory (country, part of the world, continent, or other larger space). the most important distinctive quality of such a region is that ‘the average distance of movement from this region to any point of the “mother” territory, of which it is a part, will be less than the same average distance to any point of this territory in other regions’ (tatarkin, 2005). the middle region is more accessible to other regions, and other regions are easier accessed from the middle. the contemporary research literature devoted to spatial organization of production and regions of different types highlights the unique economic features and geographical location of all middle (and central) regions, in particular the pheno menon of the middle, which acts as a catalyst for regional development. the concept of the me dian can be considered at different spatial scales – a single country or group of counties, a larger scale region, city, i.e. a middle region can be seen not only as a part of the country but can also be a country itself. we will be more interested in middle regions located within one country. in this respect, the studies of the ural scientific school (a.tatarkin, e. animitsa, e. dvoryadkina, n. novikova, yu. lavrikova, a. glumov and others) are of particular interest (animitsa et al., 2008). the middle region has many functions that are connected to its location. what is important is not only a certain number of roads or highways, but also the benefits that the region receives due to its position at the intersection of the most important transport routes, which, in its turn, has an impact on its economic development. first of all, the development of transport and logistics and tax revenues from companies operating in the transport services market guarantee new jobs and, of course, investment in the deve lopment of transport and logistics infrastructure and other spheres. such economic and geographical location also favours the development of trade and business infrastructure (restaurants, hotels, warehouses, shopping and business centers, offi ces of global companies, etc.), since it is convenient to hold exhibitions and meetings and to open branches and offices in middle regions. http://doi.org/10.15826/recon.2020.6.2.008 92 https://journals.urfu.ru/index.php/r-economy r-economy, 2020, 6(2), 89–99 doi: 10.15826/recon.2020.6.2.008 online issn 2412-0731 another advantage of such location is the development of production functions since it allows enterprises to save on transportation of raw materials and products across the region or to its borders. the concentration of production depends on how actively and effectively the region uses local natural resources and technological achievements. position in the middle makes such regions better protected against ‘unfriendly’ penetration. therefore, these regions often host strategically important facilities for the country – defense enterprises, nuclear power plants, etc. the development and expansion of managerial and organizing functions in the middle region (industrial, social, political, and other) is an important sign of the middle region. various organizational and managerial entities operating in the region contribute to the increasing uniformity and integration of the regional economic space; implement their own regional strategic projects; initiate interactions between economic entities; accelerate decision-making in the economic sphere, thereby helping economic entities to save on transaction costs. one of the key features of the middle region is its participation in state affairs and its role in the economy, culture, politics and other spheres of life. middle regions are often characterized by their own, unique processes of formation and development in different countries. these characteristics are rooted in these regions’ individual history and create a specific socio-economic environment, certain demographic commonality, necessary for the regions’ development through the effective use of natural, economic, social, demographic, and other innovative capabilities and engagement of all internal forces. since the unique characteristics of a middle region to a great extent originate in its history, it is necessary to emphasize the role of the time factor, i.e. implementation and maintenance of the middle region’s functions over a long historical period. the region for many decades and even centuries (the latter is especially typical of russian regions) accumulates traditions, forms a multi-layered economy, developed infrastructure, while remaining in the thick of national events. e. animitsa defines the middle region as a special, state-forming type of a large region which is located in the central, strategically important part of the country and has a set of specific topological features such as a significant number of ‘entrances’ and ‘exits’ to passenger and cargo flows, a high level of concentration of production and population, scientific and technical, intellectual and human potential, historically formed infrastructure, industrial and technological and socio-cultural connectivity, and regional identity. moreover, such regions have a powerful core (or several cores), that is, the largest cities that have the official status of administrative, political, economic, organizational centers of their respective territories. a. glumov’s approach is similar to that of e. animitsa, but it focuses on the concentration of the country’s population, production, capital and resources in middle regions (animitsa & glumov, 2007). tatarkin (2005) interprets the middle region as being located in the middle of the territory of a country, continent, part of the world or other, larger units. in our opinion, these definitions fail to emphasize the role of the middle region as an integrator of space, its special geopolitical, socio-economic, cultural and spiritual mission. the functional features of any middle region can be determined by forecasting the economic effect of its development. taking into account the conceptual characteristics discussed above (central location, developed transport and business infrastructure, concentration of population, industry and other sectors), it is also necessary to highlight a number of topological qualities (properties) that distinguish this type of regions. these are objectivity, multi-dimensionality, scale, which determines their role in the development of the country, openness, contacts with other regions, transit potential, attractiveness for capital and people. in addition, it should be noted that middle regions play an important creative and integrative role in the sphere of production, financial, social and business spheres, in maintaining the interconnectedness of regions, in the formation of a single economic and political space of the country. thus, the middle region can be defined through its territorial position, on the one hand, and through its connection to the system of interactions in the socio-economic space of the state, on the other. the middle region is understood here as a complex hierarchical system in the multi-level territorial structure of the country, whose unique features are determined both by its central geographical position and the set of relationships and dependencies arising as a result of http://doi.org/10.15826/recon.2020.6.2.008 r-economy, 2020, 6(2), 89–99 doi: 10.15826/recon.2020.6.2.008 93 https://journals.urfu.ru/index.php/r-economy online issn 2412-0731 the region’s strategically important role in national socio-economic development and security. it should be emphasized that the distinctive features of such understanding of the middle region is, firstly, the rejection of the idea of equidistance from the geographical borders of the state, and secondly, the disclosure of the median factor not only through geographical location, but also through the totality of relations between economic entities, integrated structures and authorities at various levels. our understanding of the middle is directly related to the etymology of this word, namely, being in the middle of something or between two objects. this is what distinguishes this concept from the concept of geographical center, which is equidistant from the borders. thus, our approach relies on the definition of the middle region is a set of features, connections and relations and the more general notion of region as a relatively stable part of the socio-economic and poli tical space of the country. there can be several middle regions in a country. the middle region as an integral system of interactions and interdependencies that, on the one hand, provide connectivity within the region and, on the other, make it to the outside world. from the morphological point of view, one of the key characteristics of the middle region is its ‘polystructuredness’, which is a specific feature of the russian space, where administrative and political centers appear to be superior in status to their territories. as table 1 illustrates, we supplemented the topological features that are traditionally emphasized in the definitions of the middle region such as spatial location, administrative component, socio-economic component, and interactions with some new ones. methodology and data the methodological framework of our study centres around the concept of cumulative effect and comprise tools for its assessment. the cumulative effect of the middle region, in our view, is created by its unique topological features, advantages and disadvantages of its geographical position. the cumulative effect of the middle region is understood here as the socio-economic efficiency of a territorial capital resulting from the advantages of its middle position. the cumulative effect leads to the region’s enhanced socio-economic performance in comparison with the national average, in particular a high economic return on investment (hanson, 2005; oerlemans, 2001; head, 2010). in this regard, to estimate the cumulative effect, we need to look at the indicators corresponding to such spheres as economy, regional budget, innovation, industry, trade, construction, transport, and social sphere (education and health). the methodology for calculating the cumulative effect of the middle region comprises a system of indicators and a procedure for their integration. the most successful way to assess the cumulative table 1 topological features of middle regions classification group of features traditional features additional features territory spatial scale location in the ‘middle’ transitivity historical infrastructure cargo and passenger traffic resources gravity administrative openness population concentration one core or multiple cores regional identity polystructuredness role in ensuring national security territorial ‘frame’ (p. george’s term) financial self-sufficiency multiple pilot projects relationships socio-economic component multidimensionality play a defining role in the national economy concentration of industries, trade and services concentration of intellectual and human potential low risk of doing business high investment and innovation potential investment climate interactions multiple contacts with neighboring territories attractiveness for capital and people connectedness space integration interrelated regional development resonance effect network interactions clustering http://doi.org/10.15826/recon.2020.6.2.008 94 https://journals.urfu.ru/index.php/r-economy r-economy, 2020, 6(2), 89–99 doi: 10.15826/recon.2020.6.2.008 online issn 2412-0731 effect is to determine the value of the integral index. in doing so, we can, for example, rank the regions under consideration based on individual indicators and integrated assessment; such ranking can be easily updated by using the current values of indicators for calculations. in addition, the methodology has significant potential for scaling – it can be applied to an increasing number of research objects (for example, countries) without extra adjustment. it is important to identify the indicators that characterize the metrics of the region’s middle position. the choice of the indicators that should be taken into account in the calculation process largely depends on the researchers’ goals, their expertise, and the availability of information that can be used in the calculations. special attention, as it was noted earlier, should be paid to the reliability of the proposed indicators as well as the access to the necessary data. the data about the development of territories and industries can be obtained from official government statistics; corporate reports; surveys and research conducted by private companies. it is very important at this stage to check the tightness of the regression relationship between the selected indicators: if any indicators related to the same area closely correlate with each other, it is necessary to exclude one (or more) of them from the set of indicators used in the analysis. to calculate the cumulative effect, we are going to use the power function from the product of partial indicators of the effects of the middle position of the regions (table 2): 1 , n nmp i i r r = = ∏ rmp is the cumulative effect of the region’s middle position and ri signifies the effects that occur in certain areas (table 2). to conduct an empirical study, we selected 36 russian regions classified as middle regions. these regions are homes to 43.7% of the country’s population. they also account for 38.9% of russia’s gdp; 64.2% of the volume of mineral production; 41.5% of investment in fixed assets; and 44.7% of the volume of innovative production. table 2 indicators for calculating the cumulative effect of the region’s middle position n effects by location key indicator formula for calculating the effect r1 economy value added per 1 unit of investment grp investment in the region 100% gdp investment in the country ⋅ r2 budget regional budget per 1 unit of investment consolidated budget investment in the region 100% country budget investment in the country ⋅ r3 innovation volume of innovative products per 1 unit of investment innovative products of the region investment in the region 100% innovative products in the country investment in the country ⋅ r4 industry added value in industry per 1 unit of investment added value in industry of the region investment in the region 100% added value in industry in the country investment in the country ⋅ r5 trade added value of trade per 1 unit of investment added value in trade of the region investment in the region 100% added value in trade in the country investment in the country ⋅ r6 construction added value in construction per 1 unit of investment added value in construction of the region investment in the region 100% added value in construction in the country investment in the country ⋅ r7 transport added value in transport per 1 investment unit added value in transport of the region investment in the region 100% added value in transport in the country investment in the country ⋅ r8 health care added value in healthcare per 1 unit of investment added value in healthcare of the region investment in the region 100% added value in healthcare in the country investment in the country ⋅ r9 education added value in education per 1 unit of investment added value in education of the region investment in the region 100% added value in education in the country investment in the country ⋅ http://doi.org/10.15826/recon.2020.6.2.008 r-economy, 2020, 6(2), 89–99 doi: 10.15826/recon.2020.6.2.008 95 https://journals.urfu.ru/index.php/r-economy online issn 2412-0731 results and discussion our study has showed that the cumulative effect differs significantly across russian middle regions. therefore, it seems reasonable to distinguish between such types of middle regions as an ‘integrator of economic space’, ‘sustainable middle region’ and ‘developing middle region’. middle regions of the first type – integrators – have the following quantitative characteristics: a high value of the cumulative effect of the middle position; high turnover; high value of gravity on interregional trade; a high proportion of neighboring territories in the balance of interregional trade; and a high coefficient of clustering. based on the above-described methodology, the follo wing territories of russia can be described as ‘integrator regions’: moscow, tatarstan, bashkortostan and komi republics, sverdlovsk and tomsk regions. these regions have a cumulative effect value of more than 150%. a stable middle region is characterized by a high value of the cumulative effect of the middle; a significant role in the country’s overall econo mic performance; considerable potential for investment and innovation; substantial budget capacity; low risks for doing business; and a large number of national ‘pilot projects’ operating in their areas. based on the authors’ calculations, this group of regions includes moscow, novgorod, lipetsk, irkutsk, vologda, nizhny novgorod, kaluga, ryazan, samara and yaroslavl regions, perm region, khanty-mansiysk autonomous district and the udmurt republic. the value of the cumulative median effect is between 101.6 and 148.2%. the second type – developing middle region – is characterized by low values of the cumulative effect of the middle; lower levels of investment, innovation and budget capacity; and high risks of doing business. these regions in the short term can potentially move into the category of ‘sustainable middle regions’, and in the long-term, ‘integrators’. this group includes the following regions: vladimir, kostroma, tula, oryol, tambov, tver, kemerovo, penza, ulyanovsk, kirov and ivanovo regions, khakassia, mari el, mordovia, chuvashia, adygea republics, and stavropol region. the value of the cumulative middle effect is between 62.1 and 98.9%. the assessment of the effect of the middle position allowed the authors to test their hypothesis about the special mission of the middle regions. in the context of globalization and global competition (wang, 2020), regions become more oriented towards strategic management, which includes the mission of the region, scenarios and concepts of development (barnes, 2003; combes 22 1, 3 20 1, 8 19 8, 6 18 6, 4 17 9, 6 17 4, 5 14 8, 2 13 6, 9 13 6, 4 13 6, 1 13 5, 9 13 4, 9 13 4, 8 13 4, 3 13 0, 6 13 0, 3 12 8, 7 11 7, 1 10 1, 6 98 ,9 98 ,7 98 ,2 97 ,2 96 ,4 95 ,7 89 ,2 87 ,6 87 ,1 86 ,1 85 ,3 84 ,3 82 ,1 81 ,3 79 ,9 75 ,3 62 ,1 0 50 100 150 200 250 m os co w r ep ub lic o f t at ar st an sv er dl ov sk re gi on r ep ub lic o f b as hk or to st an to m sk re gi on r ep ub lic o f k om i m os co w re gi on pe rm re gi on n ov go ro d re gi on h m a o li pe ts k re gi on ir ku ts k re gi on v ol og da re gi on k al ug a re gi on sa m ar a re gi on ya ro sl av l r eg io n n iz hn y n ov go ro d re gi on u dm ur t r ep ub lic r ya za n re gi on v la di m ir re gi on k os tr om a re gi on tu la re gi on o re l r eg io n ta m bo v re gi on tv er re gi on k em er ov o re gi on pe nz a re gi on u ly an ov sk re gi on k ir ov re gi on r ep ub lic o f k ha ka ss ia st av ro po l t er ri to ry r ep ub lic o f m ar i e l r ep ub lic o f m or do vi a c hu va sh r ep ub lic iv an ov o re gi on r ep ub lic o f a dy ge a figure 1. value of the cumulative middle position effect of russian regions source: the authors’ calculations based on data from the statistical yearbook ‘regions of russia published by the federal state statistics service (rosstat) https://www.gks.ru/folder/210/document/13204 (accessed data: march 25th, 2020) http://doi.org/10.15826/recon.2020.6.2.008 https://www.gks.ru/folder/210/document/13204 96 https://journals.urfu.ru/index.php/r-economy r-economy, 2020, 6(2), 89–99 doi: 10.15826/recon.2020.6.2.008 online issn 2412-0731 et al., 2008; cairncross, 2001), socio-economic forecasting (zhao & fan, 2019; chen, 2020), targeted integrated programs, and mechanisms for implementing the goals of regional strategic management (wiberg, 2019; chen, 2019; qiu et al, 2020). the mission of the region is one of the fundamental concepts of strategic management; it should be unique in each case and formulated by taking into account the region’s specific characteristics. the scenario of socio-economic development of a region should be aligned with the mission and include the strategic goal and tools for achieving it. the tools for implementing the regional strategy rely on organizational, legal, financial and monitoring mechanisms (zemtsov & baburin, 2016). the organizational mechanism includes a set of strategic development and planning documents; the legal mechanism corresponds to the socio-economic sphere, business activities, strategic planning system, etc.; the financial mechanism includes budget strategies, financial plans, etc. the control mechanism is of vital importance; it comprises assessment and expertise, monitoring, etc. monitoring results help to adjust the short-, mediumand long-term forecasts. the mission of a region should capitalize on its competitive advantages and helps it survive through the periods of recession by prioritizing certain areas of development. by and large, it could be expected that any middle region should strive to integrate the country’s socio-economic space through the network of inter-territorial and global interactions based on the strategic polystructure of the territory and to ensure the socio-economic growth and security of the country. we analyzed the strategies of 36 middle regions in russia, paying special attention to their missions, goals and strategic priorities of development. the study showed that not all regions today position themselves as integrators of the country’s space. out of 36 middle regions, only 6 regions, in view of their unique position, connect their missions with spatial development of russia. in the modern globalized world, success is achieved by those regions that find the right balance between globality and identity, skillfully fitting into the national and world economy, capitalizing on their unique qualities to succeed in interregional competition. such middle regions include sverdlovsk, samara and tomsk regions, tatarstan, komi and udmurt republics. sverdlovsk region defines its mission not only in the national context, but also in the context of global economy, focusing on a new quality of life and new industrialization. the goals of the social and economic policy of sverdlovsk region for 2016-2030 are enhance its competitiveness in global economy and to improve the quality of life as the region is envisioned to become an attractive territory for human life and development. the strategy highlights three key priorities: 1) in the social sphere, to provide a new quality of life, that is, creation of optimal conditions for accumulation and preservation of human potential; 2) in the economic sphere, to promote new industrialization, that is, creation of conditions for increasing the region’s industrial, innovative and entrepreneurial potential; and 3) territory for life and business – to ensure balanced development of the region. the republic of tatarstan positions itself as the growth pole of a large region. its strategy puts forward the main strategic goal: by 2030, to turn tatarstan into a globally competitive and sustainable region, a driver of the so-called volga-kama growth pole. tatarstan is a leader in terms of the quality of interconnected development of human capital, institutions, infrastructure, economy, external integration (‘axial’ eurasian region of russia) and internal space. it is a rapidly developing region with high involvement in the internatio nal division of labor. the strategy centres around three interrelated strategic priorities: 1) formation and accumulation of human capital; 2) creation of a comfortable space for the development of human capital; and 3) creation of economic relations and public institutions for the development of human capital. samara region, with its powerful potential, can become a significant point of economic growth in the volga federal district. this region holds significant potential for the development of science, education and industry, especially in the aerospace sector and petrochemicals; it is also one of the largest transport and logistics hubs. its strategic goals of socio-economic development for the period up to 2030 are to ensure economic growth and increase the competitiveness of the regional economy; improve the quality of life; and improve the efficiency of regional management. the mission of tomsk region emphasizes a better quality of life in siberia, which is planned to be achieved by implementing an intensive development model. priorities of socio-economic development of tomsk region are the new technologies; human capital; conditions for investhttp://doi.org/10.15826/recon.2020.6.2.008 r-economy, 2020, 6(2), 89–99 doi: 10.15826/recon.2020.6.2.008 97 https://journals.urfu.ru/index.php/r-economy online issn 2412-0731 governmental, organizational and managerial structures. the middle region, due to its location, accumulates many industrial, social, political and other functions. the review of international and russian research literature on this topic has revealed a certain knowledge gap regarding the theory of development of large middle regions. it was this gap that this article sought to address: we strove to clarify the theoretical and methodological aspects of the concept ‘middle region’ based on the gravitational theory, cluster theory, and methodology for evaluating innovation potential. in particular, we substantiated the approach that reveals the unique nature of middle regions: focusing on their location and at the same time describing them as systems of interactions in the socio-economic space of the state. we have added some important topological features of the middle region to the already established understanding of this type of region. our analysis of russian regions’ missions has demonstrated that middle regions can play an important role in ensuring the country’s long-term growth and security as integrators of the country’s social and economic space through the network of inter-territorial and international connections on the basis of strategic polystructural areas. the quantitative assessment of the cumulative effect of middle regions can be used in policy making on regional and national levels. ment and business development; effective territorial policy; and effective management. the mission of the republic of komi emphasizes the region’s role in the country’s prosperity and prioritizes comfortable conditions for residents and their families, which includes a good living environment, education and health care, opportunities for personal growth and social security. the high quality of life in the region should be based on sustainable economic growth and attraction of investors. the mission of the udmurt republic is to become a developed industrial region supplying high-tech products to national and world markets. the main goal of social and economic development of the udmurt republic in the long term is to increase the efficiency and stability of the economy and improve the quality of life. unfortunately, the missions of the other middle regions in this group are not so ambitious. most of the missions largely focus on the regions’ internal development, building a sustainable economy, improving the quality of life and addressing the problem of population decline. conclusions russia occupies a vast territory with regions as the main structural elements. among the regions, the middle regions play a significant role – they serve as integrators and enhance interactions between the territories through various business, references alaev, e.b. 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(2014). the european spatial structure. lap lambert academic publishing, 285. http://doi.org/10.15826/recon.2020.6.2.008 http://ezproxy.urfu.ru:2077/outboundservice.do?sid=e5krrz1kyu84ajatqhx&mode=rrcauthorrecordservice&action=go&product=wos&lang=ru_ru&daisids=12312361 http://ezproxy.urfu.ru:2077/outboundservice.do?sid=e5krrz1kyu84ajatqhx&mode=rrcauthorrecordservice&action=go&product=wos&lang=ru_ru&daisids=35641602 http://ezproxy.urfu.ru:2077/outboundservice.do?sid=e5krrz1kyu84ajatqhx&mode=rrcauthorrecordservice&action=go&product=wos&lang=ru_ru&daisids=30972859 http://ezproxy.urfu.ru:2077/outboundservice.do?sid=e5krrz1kyu84ajatqhx&mode=rrcauthorrecordservice&action=go&product=wos&lang=ru_ru&daisids=660120 http://ezproxy.urfu.ru:2077/outboundservice.do?sid=e5krrz1kyu84ajatqhx&mode=rrcauthorrecordservice&action=go&product=wos&lang=ru_ru&daisids=35636076 http://ezproxy.urfu.ru:2077/outboundservice.do?sid=e5krrz1kyu84ajatqhx&mode=rrcauthorrecordservice&action=go&product=wos&lang=ru_ru&daisids=8287108 r-economy, 2020, 6(2), 89–99 doi: 10.15826/recon.2020.6.2.008 99 https://journals.urfu.ru/index.php/r-economy online issn 2412-0731 information about the authors victoria v. akberdina – dr. sc. (econ.), corresponding member of the ras, deputy director institute of economics of the ural branch of the russian academy of sciences, head of regional industrial policy and economic security dept. (29 moskovskaya st., yekaterinburg, 620014, russia); e-mail: akb_vic@mail.ru alena s. sergeeva – postgraduate student, institute of economics of the ural branch of the russian academy of sciences (29 moskovskaya str., yekaterinburg, 620014, russia); e-mail: zabr0dina@mail.ru article info: received december 15, 2019; accepted february 12, 2020 информация об авторах акбердина виктория викторовна – доктор экономических наук, член-корреспондент ран, врио заместителя директора института экономики уральского отделения ран, заведующий отделом региональной промышленной политики и экономической безопасности, профессор уральского федерального университета (620014, россия, г. екатеринбург, ул. московская, 29); e-mail: akb_vic@mail.ru сергеева алёна сергеевна – аспирант института экономики уральского отделения ран (620014, россия, г. екатеринбург, ул. московская, 29 информация о статье: дата поступления 15 декабря 2019 г.; дата принятия к печати 12 февраля 2020 г. http://doi.org/10.15826/recon.2020.6.2.008 mailto:zabr0dina@mail.ru mailto:akb_vic@mail.ru r-economy, 2019, 5(4), 155–167 doi: 10.15826/recon.2019.5.4.016 155 www.r-economy.ru online issn 2412-0731 original paper © ju. g. lavrikova, a. v. suvorova, 2019 doi 10.15826/recon.2019.5.4.016 spatial aspects of regional infrastructure distribution (the case of sverdlovsk region) ju. g. lavrikova1 , a. v. suvorova1, 2 1 institute of economics, ural branch of the russian academy of sciences, ekaterinburg, russia; e-mail: lavrikova_ug@mail.ru 2 ural state university of economics, ekaterinburg, russia abstract the article discusses the correlation between the localization of specific infrastructure objects within a region and characteristics of this region’s territorial development. conceptually the study is grounded in the theory of regional economics, spatial analysis and modelling and uses the tools of spatial autocorrelation analysis, such as the global and local moran’s i, and map-based spatial analysis. the settlement system of sverdlovsk region (russia) is considered as a key characteristic of its territorial development and the analysis shows the correlation between settlement patterns and the distribution of certain objects of social infrastructure (places of attraction) across the region’s territory. access to infrastructure is an important factor which attracts people to this or that municipality. however, the key parameter that determines the spatial aspects of infrastructure distribution in the region is the emergence and development of the factors underlying this process. the article demonstrates that the localization of infrastructure objects built to generate economic effects and bring profit to their developers to a greater extent correlates with the prospective transformations of the settlement system (primarily agglomeration processes) rather than with its current characteristics (such correlation is more typical of the infrastructure objects specifically intended to address social issues). these research findings can be used by policy-makers for setting priorities of regional development, which would shape the spatial transformations of the territory. keywords space, settlement system, distribution, social infrastructure, region, spatial autocorrelation, moran’s i, map-based spatial analysis, sverdlovsk region acknowledgements the research was supported by the institute of economics, ural branch of the russian academy of sciences in accordance with the plan for 2019–2021. for citation lavrikova ju. g., suvorova a. v. (2019) spatial aspects of regional infrastructure distribution (the case of sverdlovsk region). r-economy, 5(4), 155–167. doi: 10.15826/recon.2019.5.4.016 пространственные аспекты инфраструктурного обустройства региона: пример свердловской области ю. г. лаврикова1 , а. в. суворова1, 2 1 институт экономики уральского отделения российской академии наук, г. екатеринбург, россия; e-mail: lavrikova_ug@mail.ru 2 уральский государственный экономический университет, г. екатеринбург, россия аннотация статья посвящена оценке степени соответствия характера размещения в  пространстве региона элементов инфраструктуры особенностям его территориального развития. теоретическую и методологическую основу исследования составляет совокупность научных представлений в  области региональной экономики, пространственного анализа и моделирования. на основе оценки пространственной автокорреляции (с помощью определения величин как глобального, так и локального индекса морана) и осуществления картографического анализа выделены и сопоставлены друг с другом особенности сложившейся в свердловской области системы расселения (как одной из ключевых характеристик ее территориального развития) и взаиморасположения в регионе элементов инфраструктуры мест проживания и мест притяжения. показано, что размещение объектов социальной инфраструктуры в целом соответствует характеру расположения на территории ее основных потребителей – жителей региона. однако ключевым параметром, определяющим пространственные аспекты инфраструктурного обустройства территории, является генезис факторов, лежащих в основе данного процесса. доказано, что локализация инфраструктурных объектов, главной целью создания которых ключевые слова пространство, система расселения, размещение, социальная инфраструктура, регион, пространственная автокорреляция, индекс морана, картографический анализ, свердловская область благодарности работа выполнена при поддержке института экономики уральского отделения российской академии наук в соответствии с планом на 2019–2021 гг. http://doi.org/10.15826/recon.2019.5.4.016 http://doi.org/10.15826/recon.2019.5.4.016 mailto:lavrikova_ug@mail.ru mailto:lavrikova_ug@mail.ru 156 www.r-economy.ru r-economy, 2019, 5(4), 155–167 doi: 10.15826/recon.2019.5.4.016 online issn 2412-0731 introduction the distribution of infrastructure elements across space is one of the main topics not only in regional economics and economic geography but also in policy-making on different levels of the territorial hierarchy. the principal difficulty is to determine the parameters for the optimal location of such infrastructure objects. it seems obvious that the key criterion should be the ability of infrastructure objects to meet the needs of the main stakeholders, regardless of the level of the territory – cities, regions or the country as a whole. it means that the distribution of infrastructure should correlate with the concentration of its users, that is, the latter should be provided with a convenient access to these objects. developed infrastructure, in its turn, attracts more residents to the area, which is conducive to socio-economic growth and turns infrastructural development into a powerful tool of regional policy-making. irrespective of whether the infrastructure is going to be developed in accordance with the already existing settlement patterns and distribution of productive forces across the territory or with the view to future transformations of the socio-economic space, decision-making in this sphere is based primarily on the analysis of the current situation: before building new objects of infrastructure, it is necessary to assess different parameters of the region’s development, in particular the already existing infrastructure, and identify the gaps and disproportions that need to be addressed. this study is aimed at analyzing the characteristics of territorial development of a region and revealing their correlation with the localization of infrastructure objects in the given area. it should be noted that such analysis should take into account different types of infrastructure. our study focuses on the discrepancies between settlement patterns of a region (characteristics of its territorial development) and localization of some elements of social infrastructure in the same region (infrastructure necessary for maintaining and improving the living conditions). theoretical framework spatial aspects of economic development now attract considerable scholarly attention in russia, especially after the adoption of the federal law ‘on strategic planning in the russian federation’1 in 2014. this law identifies the strategy of spatial development as one of the key strategic planning documents. however, it should be noted that the research on the relationship between the distribution of economic entities across space and specific parameters of territorial development goes back to the nineteenth century. the classical location theory developed by j. h. von thünen [1], a. weber [2], a. lösch [3], w. christaller [4], and c. w. f. launhardt [5] described the factors that determine the localization of industries in space. spatial aspects of territorial development were also considered by the growth poles theory and the theory of polarized development, theories and concepts of urban development [8; 9], and so on. questions related to distribution of productive forces were also discussed by soviet economists, such as n. n. nekrasov [10], i.  g.  alexandrov [11], a. e. probst [12] and others. interestingly enough, as a. i. tatarkin and e. g. animitsa point out in their article on the paradigm theory of regional economy, seminal works written by western authors had little impact on the theoretical views of soviet scholars in what concerned the distribution of industrial enterprises and regional development. nevertheless, the development of territorial studies in the ussr, which dealt primarily with the radical shifts in the location of productive forces, theory and practice of economic zoning, factors that determine the location of industries, to some extent coincided with the international trends. the research of the role played by spatial factors in the development of socio-economic systems requires a methodological approach that would not rely exclusively on evaluating the dy1 federal law no. 172-fz of 06.26.2014 ‘on strategic planning in the russian federation’. retrieved from: http:// www.consultant.ru/document/cons_doc_law_164841 выступает генерация экономических эффектов и получение прибыли, в большей степени коррелирует не с текущими особенностями системы расселения (что характерно для объектов, создание которых призвано способствовать решению социальных проблем), а  с  перспективами ее преобразования, проявляющимися тенденциями (в  первую очередь, с агломерационными процессами). полученные результаты могут найти применение при определении приоритетов осуществления региональной политики, пространственных преобразований территорий. для цитирования lavrikova ju. g., suvorova a. v. (2019) spatial aspects of regional infrastructure distribution (the case of sverdlovsk region). r-economy, 5(4), 155–167. doi: 10.15826/recon.2019.5.4.016 http://doi.org/10.15826/recon.2019.5.4.016 http://www.consultant.ru/document/cons_doc_law_164841 http://www.consultant.ru/document/cons_doc_law_164841 r-economy, 2019, 5(4), 155–167 doi: 10.15826/recon.2019.5.4.016 157 www.r-economy.ru online issn 2412-0731 namics of certain objects in time but consider the specific parameters of these objects’ distribution across space, that is, the proximity of objects to each other, their concentration within one area and the scale of the systems they form. therefore, such studies prioritize methods of spatial analysis and modelling. without going into a detailed discussion of the history of spatial analysis, we need to mention that this methodology goes back to the 1940s and 1950s, when the first papers on spatial modelling were published [14; 15]. at the subsequent stages [16; 17], more new methods for estimating the spatial effects produced by the transformations on different levels were proposed. these methods provided sufficient foundation for a vast number of empirical studies, including the studies based on russian data. spatial autocorrelation analysis has been gaining popularity among russian scholars [18–22]. spatial autocorrelation can be defined the following way: for set s containing n geographical units, spatial autocorrelation is a correlation between the variable observed in each of the  n  localities and a measure of geographical proximity defined for all n (n − 1) pairs chosen from s [23]. in other words, spatial autocorrelation analysis shows the strength of correlation between the parameters characterizing the development of territories located in close proximity to each other. one of the most widely applied (and relatively easy to use) parameters is moran’s i. the test for spatial autocorrelation proposed by patrick moran is used in most russian studies of patterns of spatial dependence between neighbouring territories. various indicators can be used to describe the situation in the given territories: for example, y. v. pavlov and e. n. koroleva analyzed territorial clusters in samara region by looking at the population data of its municipalities [18]. a. a. grigoriev estimated the scale of spatial autocorrelation in russian regions by using such parameters as education, crime rates, birth rates, infant mortality rates, urbanization, migration, urbanization and household income [19]. o. a. demidova focused on the level of unemployment [20]; o. s.  balash, on the grp per capita [21]; e. s. inozemtsev and o. v.  kochetygova, on birth rates and life expectancy [22]. if we look at the theoretical and methodological foundations of russian and international studies of economic space, we can see that spatial analysis methods hold enormous potential as they help us search for correlations between various parameters of territorial development and the localization of infrastructure within this territory. methodology and data this study focuses on the case of sverdlovsk region in russia, which comprises 73 municipalities – 68 urban districts and 5 municipal districts. the choice of indicators was determined by the fact that any area can be seen from the perspective of its potential users as a place to live and work in and as a place of attraction, that is, as a source of opportunities for leisure and recreation. elements of social infrastructure can be classified the same way: amenities and benefits for living and work; infrastructure for sport and leisure. in this study, we decided to focus on the social infrastructure used by people in their daily lives (we use the supply of new housing as an indicator) and the infrastructure that turns certain spots into places of attraction (for example, the number of stadiums with terraces). we did not consider infrastructure objects that are necessary for creating a comfortable working environment, although the proposed methodology would make it possible to consider those as well. moreover, this methodological approach can be applied to analyze the spatial distribution of infrastructure elements of other types, for instance, those unrelated to the social sphere or linked to other indicators such as cultural facilities, public improvements and so on. as an indicator characterizing settlement patterns, we took the number of permanent residents in the municipalities of the region. in order to obtain the necessary data on the population, new housing supply and the number of stadiums with terraces for specific municipalities, we used the database2 of the federal state statistics service. the study period was one year – 2017. the study comprised several stages: at the first stage, we focused on the settlement patterns in the region and searched for correlations between the population size of neighbouring municipalities. thus, we were able to identify clusters within the regional settlement system. at the second stage, we investigated the distribution of specific elements of infrastructure across the region and its correlation with the settlement patterns. methodologically, this study relies on calculations for moran’s i and map-based analysis. 2 official website of the federal state statistics service. database of municipal indicators. retrieved from: http://www. gks.ru/dbscripts/munst/ http://doi.org/10.15826/recon.2019.5.4.016 http://www.gks.ru/dbscripts/munst/ http://www.gks.ru/dbscripts/munst/ 158 www.r-economy.ru r-economy, 2019, 5(4), 155–167 doi: 10.15826/recon.2019.5.4.016 online issn 2412-0731 we calculated the parameters of spatial autocorrelations (based on moran’s test) by following the procedure described below. first, a distance matrix was generated. the matrix shows the distances between all the given territorial units. entries for the matrix can be determined in different ways: for example, an entry may be equal to 0 (if the territories do not share a border) or 1 (if they do). entries can be also determined by using aerial distance data, the length of the roads or railways between the territories in question. we built the distance matrix by using the data on the length of the roads connecting administrative centres of the municipalities. the region has three municipalities whose administrative centres are located outside their borders and, therefore, coincide with the administrative centres of the neighbouring municipalities (kamensky and krasnoufimsk urban districts, kamyshlovsky municipal district). the distance between these municipalities and the neighbours which they share their ‘capital’ with was taken as 0. second, we calculated the global moran’s i and looked for the spatial autocorrelation or its absence. the formula for the global moran’s i (1) looks the following way: = = = − − = − ∑ ∑ ∑ 1 1 2 0 1 ( )( ) , ( ) n n ij i j i j n i i n w x x x x i s x x (1) where i is the global moran’s i, x is the given parameter, s0 is the sum of spatial weights ( = = = ∑ ∑0 1 1 ij i j s w ), and n is the number of territories. the index values may vary between –1 and 1. we need to compare the actual value with the expected value (2) to make a conclusion about the presence or absence of spatial autocorrelation and its character. − = − 1 ( ) , 1 e i n (2) where e(i) is the expected value and n is the number of territories. these values can be interpreted the following way. if the calculated value of moran’s i exceeds the expected value, we observe a positive spatial autocorrelation (the values of the given indicator for neighbouring areas are similar or close to each other); if the expected value exceeds the value of moran’s i, it means that there is a negative spatial autocorrelation (the values of the given indicator for neighbouring areas are different). if the expected value of moran’s i coincides with the actual value, it means the absence of spatial autocorrelation [21]. to test for significance of moran’s i, we use a z-test – a traditional procedure for hypothesis testing in econometrics. the z-score for moran’s global i is calculated by applying the following formula: − = −2 2 ( ) , ( ) ( ) i e i z score e i e i (3) where i is the global moran’s i and e(i) is the expected value. the z-score thus obtained is the measure of how many standard deviations above or below the expected value the actual value of moran’s i is. if the above value is sufficiently high, it means that the actual distribution did not occur by chance. third, we calculate the local moran’s i and find the strength of correlation between the territories. the local moran’s i shows the interdependence between the territories and its strength [25, p. 147]. the local moran’s i can be calculated by applying formula (4): = ∑ ,il i ij ji z w z (4) where ili is the local moran’s i for the ith territory, wij is the standardized distance between the ith and jth territories, zi and zj are the standardized values of the given indicator for the ith and jth territories. the values we obtain may be negative (minimum –1) or positive (maximum 1) and can be interpreted by following the same logic as for the global moran’s i. it is also interesting to look at the separate components of local index (5), whose values characterize the strength of interdependence between the two territories [18]: = ,ij i j ijlisa z z w (5) where lisaij is the strength of interdependence between the ith and the jth areas, wij is the standardized distance between the ith and jth areas, zi and zj are the standardized values of the given indicator for the ith and jth areas. fourth, the territories are grouped according to the correlation between the standardized values of the given indicators and the values of the spatial factor. if we combine the standardized values of the given indicator (z) with its spatial centred weights (wz) for each given territory within one system of http://doi.org/10.15826/recon.2019.5.4.016 r-economy, 2019, 5(4), 155–167 doi: 10.15826/recon.2019.5.4.016 159 www.r-economy.ru online issn 2412-0731 axes, we can notice that the points (corresponding to the territorial units) concentrate in one of the four quadrants [24, p. 50]. if values z and wz are positive (quadrant hh), it means that territories characterized by high values in the given indicator are clustered with adjacent territories, which also demonstrate high values. if values z and wz are negative (quadrant ll), it means that the territories are located near other areas with similar values in the given parameter, but in both cases the territories demonstrate a low level of performance in the given indicator. if value z is positive while value wz is negative (quadrant hl), the territory is different from its neighbours – it is ahead of the adjacent territories in this indicator. if value z is, on the contrary, negative, while value wz is positive (quadrant lh), the territory lags behind its neighbours. thus, territories with a positive autocorrelation fall within the quadrants hh and ll, with negative autocorrelation – quadrants hl and lh. such grouping demonstrates the place of each territorial unit in this spatial system, shows its leaders (extrema) and peripheral areas and allows us to make spatial clustering. the map helps us display the results of spatial data analysis and complements other research methods. maps can be used as spatial models of real-life situations, illustrating the already existing or planned structures and relationships in a socio-economic space. if we add new information to the map (symbols and pictograms characterizing the localization of the objects, lines in different thicknesses to show the strength of interdependence between the specific territories, different colours to highlight some parts of the map, and so on), we can show subtle trends, relationships and correlations. results and discussion the population density in sverdlovsk region (the map of the region with its municipalities is shown in figure 1) is uneven, with 34.7% of the population living in the region’s administrative centre – ekaterinburg. the population of the urban agglomeration of ekaterinburg (its boundaries are defined by the territorial planning scheme of sverdlovsk region3) is over 2,242 thousand people or 51.8% of the total population of the region. 3 decree of the government of sverdlovsk region no. 1000-pp of august 31, 2009 ‘on the approval of the territorial planning scheme of sverdlovsk region’. retrieved from: http:// docs.cntd.ru/document/895218020 it should be noted that the size of the area of the region’s constituent municipalities is only 6.8% of the total area of sverdlovsk region4. in order to estimate spatial autocorrelation, we analyzed the data on the population of municipalities in sverdlovsk region and found that there is an inverse relationship between the values of this indicator for nearby localities: the actual value of the global moran’s i (–0.021) is smaller than the expected value, which means that there is a negative autocorrelation. the significance of this result is confirmed by the z-test. this means that the population size varies significantly from municipality to municipality. it should be noted, however, that negative values of moran’s i can be explained by the sheer size of the largest municipality – ekaterinburg: it differs considerably not only from the region’s average but also from its nearest neighbours, even though many nearby territories have quite large populations. the local moran’s i for ekaterinburg is –0.010, which means that if we exclude this municipality from our calculations, the value of the global moran’s i (for the whole region) will exceed the expected value. the values of local indices calculated with the help of formula (4) show that large municipalities, such as ekaterinburg, nizhny tagil, and kamensk-uralsky, differ significantly from their neighbours. the same applies to the municipalities located in closest proximity to these cities (see table 1). thus, we can suppose that ekaterinburg, nizhny tagil and kamensk-uralsky concentrate most population in the region (extrema) and that they are the leaders of their respective territorial clusters. table 1 municipalities characterized by negative values of the local moran’s i municipality ili municipality ili ekaterinburg –0.010 degtyarsk –0.001 kamensky –0.003 closed settlement ‘uralsky’ –0.001 kamensk-uralsky –0.002 nizhny tagil –0.002 verkhnee dubrovo –0.001 gornouralsky –0.002 verkh-neyvinsky –0.001 sredneuralsk –0.001 aramilsky –0.001 the table does not include the data on those municipalities whose values of the local moran’s i are negative but are closer to 0 than to –0.001. 4 official website of the federal state statistics service. database of municipal indicators. retrieved from: http://www. gks.ru/dbscripts/munst/ http://doi.org/10.15826/recon.2019.5.4.016 http://docs.cntd.ru/document/895218020 http://docs.cntd.ru/document/895218020 http://www.gks.ru/dbscripts/munst/ http://www.gks.ru/dbscripts/munst/ 160 www.r-economy.ru r-economy, 2019, 5(4), 155–167 doi: 10.15826/recon.2019.5.4.016 online issn 2412-0731 in order to make a more solid conclusion about the spatial characteristics of the settlement system in sverdlovsk region, we need to group the territories according to the correlation between the standardized values of the indicator and the values of the spatial factor. moran’s diagram of spatial dispersion (figure 2) illustrates the distribution of z points in the system of axes z and w. each point corresponds to one of the municipalities. the three points located to the right of the vast majority of points are the obvious leaders we have already identified above. nevertheless, along with the easily identified extrema, there are other municipalities in the ivdelsky ud pelym ud garinsky ud severouralsky ud 1 2 krasnoturyinsk ud karpinsk ud novolyalinsky ud sosvinsky ud verkhotursky ud alapaevskoye md 3 4 5 6 7 kushvinsky ud gornouralsky ud nozhneturinsky ud kachkanarsky ud lesnoy ud verkhnyaya tura ud nizhny tagil taborinsky md turinsky ud tavdinsky ud slobodo-turinsky md 18 rezhevskoy ud 19 20 artemovsky ud irbitskoye md 8 39 krasnou�msk ud shakinsky ud 11 21 9 10 1312 14 1516 17 2425 27 2622 23 30 31 32 34 revda ud 35 33 28 36 kamensk-uralsky ud kamyshlovsky ud kamyshlovsky md 37 38 40 41 42 29 1 – volchansky urban district; 2 – serovsky urban district; 3 – krasnouralsk urban district; 4 – verkhnesaldinsky urban district; 5 – closed settlement svobodny; 6 – nizhnyayasalda urban district; 7 –alapaevsk municipal district; 8 – irbit municipal district; 9 – kirovgradsky urban district; 10 – nevyansky urban district; 11 – staroutkinsk urban district; 12 – nizhny tagil urban district; 13 – verkh-neyvinsky urban district; 14 – novouralsky urban district; 15 – verkhnyaya pyshma urban district; 16 – sredneuralsk urban district; 17 – berezovsky urban district; 18 – malyshevsky urban district; 19 – reftinsky urban district; 20 – asbestovsky urban district; 21 – bisertsky urban district; 22 – degtyarsk urban district; 23 – ekaterinburg urban district; 24 – verkhnee dubrovo urban district; 25 – zarechny urban district; 26 – beloyarsky urban district; 27 – closed settlement uralsky; 28 – aramilsky urban district; 29 – baikalovsky municipal district; 30 – аchitsky urban district; 31 – krasnoufimsky municipal district; 32 – artinsky urban district; 33 – pervouralsk urban district; 34 – nizhneserginsky municipal district; 35 – polevskoy urban district; 36 – sysertsky urban district; 37 – kamensky urban district; 38 – bogdanovich urban district; 39 – sukhoy log urban district; 40 – pyshminsky urban district; 41 – talitsky urban district; 42 – tugulymsky urban district figure 1. municipalities of sverdlovsk region http://doi.org/10.15826/recon.2019.5.4.016 r-economy, 2019, 5(4), 155–167 doi: 10.15826/recon.2019.5.4.016 161 www.r-economy.ru online issn 2412-0731 hl group (areas with a higher population concentration than their neighbours) such as serov, novouralsk and krasnoturyinsk (table 2). their values of spatial autocorrelation are too close to zero, which means that their impact on the surrounding territories is insignificant. one more group of municipalities with relatively large populations (and positive autocorrelation values) includes seven territories (group hh). these municipalities do not qualify as centres of the settlement system and, therefore, they do not dominate the surrounding territories. at –0.010 –0.005 0.000 0.005 0.010 0.015 0.020 –1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 w z z figure 2. moran’s diagram of spatial dispersion (parameter – ‘resident population size’) table 2 groups of municipalities with different positions in the regional settlement system municipality ili municipality ili lh hh kamensky urban district –0.0029 pervouralsk urban district 0.0015 gornouralsky urban district –0.0016 verkhnyaya pyshma urban district 0.0013 sredneuralsk urban district –0.0014 berezovsky urban district 0.0006 closed settlement ‘uralsky’ –0.0012 polevskoy urban district 0.0002 verkhneedubrovo urban district –0.0011 sysertsky urban district 0.0001 aramilsky urban district –0.0011 revda urban district 0.0001 degtyarsk urban district –0.0007 asbestovsky urban district 0.0000 verkh-neyvinsky urban district –0.0006 zarechny urban district –0.0003   staroutkinsk urban district –0.0003   bysertsky urban district –0.0003   beloyarsky urban district –0.0003   malyshevsky urban district –0.0002   closed settlement ‘svobodny’ –0.0002   verkhnytagil urban district –0.0002   reftinsky urban district –0.0002   kirovgradsky urban district –0.0001   nizhneserginsky municipal district –0.0001   nevyansk urban district –0.0001   shalinsky urban district –0.0001   rezhevskoy urban district –0.0001   bogdanovich urban district –0.0001   artinsky urban district –0.0001   nizhnyayasalda urban district –0.0001   sukhoy log urban district 0.0000   achitsky urban district 0.0000   alapaevskoye municipal district 0.0000   makhnevskoye municipal district 0.0000   alapaevsk urban district 0.0000   artemovsky urban district 0.0000   verkhnesaldinsky urban district 0.0000   ll hl other municipalities ekaterinburg –0.0104 http://doi.org/10.15826/recon.2019.5.4.016 162 www.r-economy.ru r-economy, 2019, 5(4), 155–167 doi: 10.15826/recon.2019.5.4.016 online issn 2412-0731 the same time, they have large populations, which means that we cannot consider them simply as peripheral areas. it would be more appropriate to refer to them as constituent parts of agglomerations, elements of the area of population concentration. these also include those urban districts (pervouralsk, verkhnyaya pyshma, and berezovsky) which have closer relations with their neighbours than other municipalities in this group (their values of the local moran’s i are the highest). the lh group includes municipalities with comparatively low values in the given indicator, located in proximity with densely populated territories and thus inevitably influenced by these neighbours. eight of these municipalities (placed at the top of the corresponding part of the table) are more closely connected with the neighbouring municipalities (these municipalities are the most influential ones) than with others. all other municipalities in the region (not included in any of the groups) have a positive autocorrelation (which means a certain similarity to their neighbours) and have relatively low values of the population size. these are included into the ll group: they are neither influenced by their neighbours nor influence their neighbours themselves. the map in figure 3 illustrates these results. the four groups of municipalities are highlighted by different colours and the saturation of the colour depends on how closely these municipalities interact with their neighbours: red, dark green or dark yellow are used for municipalities with the highest values of the local moran’s i in their respective groups. the territories with strongest interdependence are connected by lines (we used formula 5 to assess the strength of influence between the two possible pairs of territories). territories signi�cantly in�uenced by the leaders territories insigni�cantly in�uenced by the leaders territories unin�uenced by the leaders kamensk-uralsky krasnoturyinsk serov nizhny tagil novouralsk ekaterinburg centres of the regional settlement system centres of local settlement systems densely populated areas with a positive spatial autocorrelation with theirneighbours densely populated areas with a negative spatial autocorrelation with their neighbours strongest interterritorial relations figure 3. spatial autocorrelation between municipalities in sverdlovsk region (parameter – ‘resident population size’) http://doi.org/10.15826/recon.2019.5.4.016 r-economy, 2019, 5(4), 155–167 doi: 10.15826/recon.2019.5.4.016 163 www.r-economy.ru online issn 2412-0731 these results confirm our previous conclusion that the population distribution across sverdlovsk region is uneven: the region has three extrema with large populations and these municipalities are surrounded by other territories, which are also quite densely populated (areas of population concentration). the centres of the regional settlement system (and the surrounding areas of influence) are located in the south-western part while the rest of the region looks like a ‘desert’, comprising scarcely populated municipalities. although some researchers expect the city of serov in the north of the region to evolve into a full-fledged urban agglomeration [26; 27], it is still too early to speak of it as a newly emerged centre in the regional settlement system. serov and krasnoturyinsk have much larger populations than the surrounding territories, which turns them into local leaders, although their resources are not sufficient for scaling up their activities and for creating an agglomeration effect. parameters of spatial autocorrelation identified through the analysis of infrastructure localization are slightly different from the previously identified strength of correlations between the resident populations of the given municipalities. the value of the global moran’s i (0.025) exceeds its expected value: we observe a positive spatial autocorrelation, which means that in general there are no significant disparities between the development of the neighbouring territories. what we see is a gradual change in the given indicators. an undisputed leader in terms of new housing supply is ekaterinburg. the neighbouring territories are behind ekaterinburg but they still tend to perform above the average level in the region. therefore, ekaterinburg together with the adjacent territories (group hh) form an area characterized by intensive construction of new housing (see table 3). as table 3 illustrates, the strongest correlations between the values of this indicator for this area are observed for ekaterinburg, berezovsky, sysert and verkhnyaya pyshma. table 3 leaders in new housing supply group municipality ili hh verkhnyaya pyshma 0.0065 berezovsky 0.0061 ekaterinburg 0.0059 sysert 0.0044 beloyarsky 0.0010 pervouralsk 0.0009 sredneuralsk 0.0006 kamensk-uralsky 0.0000 hl nizhny tagil –0.0001 in the hl group (territories whose rates of new housing supply are considerably higher than in the neighbouring municipalities), only one municipality – nizhny tagil – can be considered to be a local leader, able to compete (though not very successfully) with ekaterinburg and its surroundings. the majority of municipalities in these groups are characterized by a negative autocorrelation (group lh) since their performance in this indicator is not very high while their proximity to the top municipalities means that they are influenced by these leaders. the ll group again includes those municipalities which account for over a half of the region’s total area, primarily, its northern and eastern parts (figure 4). if we compare the results shown in figure 3 and figure 4, we shall see that in general municipalities with positive spatial autocorrelation in the two given parameters demonstrate the following trend: areas with a high concentration of population and objects of infrastructure (including the zones of influence surrounding these objects) are located in the south-western part of the region while its northern and eastern parts are maximally remote (not only geographically but also regarding the specific aspects of territorial development) from the regional leaders. at the same time our analysis of spatial autocorrelation has brought to light a significant difference between the spheres in question. the adjacent municipalities may differ considerably in terms of the population size while the difference between their rates of new housing supply is usually not that substantial, which can be explained by the differences inherent in the nature of the phenomena in question. the population size results from the impact of a whole set of complex socio-economic processes while the data on new housing (characterizing the process as such) correlate with the economic parameters of territorial development and are driven by market factors. the demand in the housing market is to a great extent determined by the number of potential buyers – local residents. nevertheless, housing developers’ decision-making depends even more on the trends in the sphere of land use planning and development. those who build infrastructure for this or that residential space seek to maximize their profits and occupy new market niches. in doing so, they try to predict in what direction the transformation of the settlement system in this territory will be heading and at the same time http://doi.org/10.15826/recon.2019.5.4.016 164 www.r-economy.ru r-economy, 2019, 5(4), 155–167 doi: 10.15826/recon.2019.5.4.016 online issn 2412-0731 adjust this transformation to their needs. transformations of agglomerations mostly involve the development of the territories surrounding the centre, which means that new living spaces tend to emerge within the boundaries of these territories rather than beyond them. in their turn, the territories which do not play a significant role in the settlement system and hold little potential in this respect continue to rank low in the regional system of living spaces. analysis of the data on places of attraction (for example, stadiums with terraces) built in the region shows a negative spatial autocorrelation (there are differences in the given indicators between the adjacent territories): the global moran’s i is 0.058. we have thus arrived at some interesting results (see figure 5). first, the distribution of the given infrastructure objects across the region cannot be called even, although fewer municipalities are uninfluenced by the regional leaders (in comparison with the distribution of population and new housing considered above). second, the number of centres (mostly local) where stadiums are built (hl group) is quite large (23). the factor that influenced the results of this study is that the number of stadiums in the region (or equivalents thereof ) is insignificant. centres of the local system of distribution of infrastructure objects areas of infrastructure concentration with a positive spatial autocorrelation with their neighbours areas of infrastructure concentration with a negative spatial autocorrelation with their neighbours territories signi�cantly in�uenced by the leaders territories insigni�cantly in�uenced by the leaders territories unin�uenced by the leaders territories with no open statistical data on the amount of new housing supply nizhny tagil ekaterinburg kamensk-uralsky figure 4. spatial autocorrelation between municipalities in sverdlovsk region (parameter – ‘new housing supply’) http://doi.org/10.15826/recon.2019.5.4.016 r-economy, 2019, 5(4), 155–167 doi: 10.15826/recon.2019.5.4.016 165 www.r-economy.ru online issn 2412-0731 third, the proximity of certain municipalities without stadiums of their own to the areas with stadiums enabled them to join the zone of influence created by the leaders (that is, municipalities which have at least one stadium), which means that inhabitants of the former can enjoy access to the infrastructure of the latter. if we look at the maps in figure 3 and figure 5, we can notice that, despite the perceived differences in the distribution of infrastructure across municipalities (location of stadiums), there are certain correlations in terms of infrastructure concentration (concentration areas are located in the south-western part of the region), location of hubs in urban districts, such as nizhny tagil and kamensk-uralsky, and the settlement system. the difference between the spatial characteristics of the infrastructure in residential areas and places of attraction (figure 4 and figure 5) is even more significant. this can be explained by the fact that it is usually the local authorities who initiate the building of such objects as stadiums and their further development, because these projects are not considered profitable by local businesses (except for large stadiums in big cities) and, therefore, do not attract much private investment. thus, the distribution of such objects in space is determined not so much by the economic factors centres of the local systems of distribution of infrastructure objects areas of infrastructure concentration with a positive spatial autocorrelation with their neighbours areas of infrastructure concentration with a negative spatial autocorrelation with their neighbours territories signi�cantly in�uenced by the leaders territories insigni�cantly in�uenced by the leaders territories unin�uenced by the leaders territories with no open statistical data on the number of stadiums with terraces centres of the regional system of distribution of infrastructure objects nizhny tagil ekaterinburg kamensk-uralsky – 7 – 5 – 3 – 2 – 1 number of sports facilities (stadiums with terraces), units figure 5. spatial autocorrelation between municipalities in sverdlovsk region (parameter – ‘number of stadiums with terraces’) http://doi.org/10.15826/recon.2019.5.4.016 166 www.r-economy.ru r-economy, 2019, 5(4), 155–167 doi: 10.15826/recon.2019.5.4.016 online issn 2412-0731 but by social factors such as the standards of infrastructure provision (determined by the current demographic characteristics of the area), residents’ needs and expectations. conclusion scholarly interest in spatial socio-economic systems of different levels and their dynamics as well as the need for efficient regional policy-making has led to the development of a comprehensive system of analytical methods. these methods are applied for analysis of the localization of objects and its characteristics, spatial aspects of territorial transformations, and problems of spatial development. characteristics of regional settlement systems, infrastructure distribution and the relationship between them can be studied with the help of spatial autocorrelation analysis combined with map analysis. in our study we revealed a correlation between the patterns of distribution of different social infrastructure elements in sverdlovsk region and the region’s settlement patterns, which can be explained by the fact that these objects of infrastructure attract their potential users, thus increasing the population concentration in these areas. distribution and concentration of infrastructure of different types is determined by various factors, and, therefore, the infrastructural systems can meet the needs of local residents to a greater or lesser extent. for example, the spatial organization of the regional infrastructure, its emergence and further transformations stem from the need to generate economic effects and, therefore, correlate to a greater extent with the prospective transformations of the settlement system rather than with its current characteristics. since it is regional and local authorities who are in charge of building places of attraction, the localization of such infrastructure correlates more with the current settlement system. formation and transformation of the region’s infrastructural framework can contribute to levelling the differences between the territories and thus enhance the shrinkage of space and its defragmentation (provided that the key factor of such transformation is the agglomeration processes and the changes they cause). territorial infrastructure should be able to respond promptly to the region’s needs in spatial development, which makes monitoring of the qualitative and quantitative characteristics of the infrastructure vitally important. references 1. thünen, j. 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(in russ.) information about the authors julia g. lavrikova – doctor of economics, associate professor, director of the institute of economics, ural branch of russian academy of sciences (29 moskovskaya st., 620014, ekaterinburg, russia); e-mail: lavrikova_ug@mail.ru arina v. suvorova – candidate of economics, deputy director for research of the institute of economics, ural branch of russian academy of sciences, associate professor, department of regional, municipal economy and management, ural state university of economics (29 moskovskaya st., 620014, ekaterinburg, russia); e-mail: av_suvorova_av@mail.ru article info: received july 2, 2019; accepted september 10, 2019 информация об авторах лаврикова юлия георгиевна – доктор экономических наук, доцент, директор, институт экономики уральского отделения российской академии наук (620014, россия, г. екатеринбург, ул. московская, 29); e-mail: lavrikova_ug@mail.ru суворова арина валерьевна – кандидат экономических наук, врио зам. директора по научной работе, институт экономики уральского отделения российской академии наук, доцент, кафедра региональной, муниципальной экономики и управления, уральский государственный экономический университет (620014, россия, г. екатеринбург, ул. московская, 29); e-mail: av_suvorova_av@mail.ru информация о статье: дата поступления 2 июля 2019 г.; дата принятия к печати 10 сентября 2019 г. this work is licensed under a creative commons attribution 4.0 international license эта работа лицензируется в соответствии с creative commons attribution 4.0 international license http://doi.org/10.15826/recon.2019.5.4.016 http://doi.org/10.17323/1813-8918-2018-1-164-173 http://doi.org/10.18500/1994-25402018-18-3-314-321 http://doi.org/10.1111/j.1538-4632.1981.tb00731.x mailto:av_suvorova_av@mail.ru mailto:av_suvorova_av@mail.ru 252 r-economy.com r-economy, 2022, 8(3), 252–267 doi: 10.15826/recon.2022.8.3.020 online issn 2412-0731 original paper © belik, i.s., starodubets, n.v., yachmeneva, a.i., prokopov, k.a., 2022 doi 10.15826/recon.2022.8.3.020 udc 338.054.23:502.3 jel f18, q56 border carbon adjustment: implications for russian companies and regions in the context of the russia sanctions (the case of magnitogorsk iron and steel works and chelyabinsk region) i.s. belik1 , n.v. starodubets1, a.i. yachmeneva2, k.a. prokopov1 1 ural federal university, ekaterinburg, russia;  irinabelik2010@mail.ru 2 pjsc rostelecom, ekaterinburg, russia abstract relevance. there are at least two serious challenges that russian exporting companies are now facing: first, in 2021, the eu introduced the carbon border adjustment mechanism (cbam), which will come into force in 2026, and, second, since february 2022, many exporters have been subject to the eu sanctions as part of the russia sanctions regime. there is much uncertainty surroun ding the duration of the current sanctions episode as well as the introduction of the carbon tax in the middle eastern and asian countries. research objective. the study aims to assess potential economic losses resulting from the cbam introduction and the pressure of sanctions on the russian exporters of metallurgical products and their home regions. the study focuses on the case of magnitogorsk iron and steel works (mmk) and chelyabinsk region. data and methods. methodologically, the study relies on scenario analysis. two scenarios are considered: the eu sanctions against russian steel companies will be lifted after 2024–2025 and the sanctions will not be lifted in the near future. for each scenario, two variations are analyzed and the annual economic losses are calculated both for mmk and for chelyabinsk region. the data for the study was taken from ммк official reports. results. if the eu sanctions are lifted in the nearest future, at the initial stages of the carbon tax introduction, the economic consequences for russian exporters will be insignificant. in the future, however, carbon regulation can create serious threats to the financial condition of such enterprises even if exports account for a small share of their revenue. if the eu sanctions stay in place, russian enterprises are likely to search for trade partners in the middle east and asia. if the latter introduce a carbon tax, russian companies can enjoy a competitive edge due to the comparatively low carbon intensity. conclusions. to ensure russian steel companies’ competitive edge, it is necessary to stimulate them to reduce their carbon footprint and create a national carbon regulation system. not only will this measure help to reduce the loss of export income and regional governments’ tax revenues but it will also enable companies to stay competitive and deal more effectively with the sanctions pressure. keywords carbon border adjustment mechanism, carbon regulation, regional tax revenue, sanctions, scenario analysis, iron and steel industry, carbon intensity acknowledgments the research was supported by the grant from the russian science foundation and the government of sverdlovsk region (project no. 22-28-20453 “integrated approach to the processes of economy decarbonization: the formation of regional policy”). for citation belik, i.s., starodubets, n.v., yachmeneva, a.i., & prokopov, k.a. (2022). border carbon adjustment: implications for russian companies and regions in the context of the russia sanctions (the case of magnitogorsk iron and steel works and chelyabinsk region). r-economy, 8(3), 252–267. doi: 10.15826/recon.2022.8.3.020 пограничная углеродная корректировка: последствия для российских компаний и регионов в контексте санкций против россии (на примере магнитогорского металлургического комбината и челябинской области) и.с. белик1 , н.в. стародубец1, а.и. ячменева2, к. а. прокопов1 1 уральский федеральный университет, екатеринбург, россия;  irinabelik2010@mail.ru 2 пао ростелеком, екатеринбург, россия аннотация актуальность. есть как минимум две серьезные проблемы, с которыми сейчас сталкиваются российские компании-экспортеры: во-первых, в 2021 г. европейский союз (ес) принял резолюцию о введении трансграничного углеродного регулирования (тур), которая начнет действовать ключевые слова трансграничное углеродное регулирование, экономические потери от углеродного регулирования, https://doi.org/10.15826/recon.2022.8.3.020 https://doi.org/10.15826/recon.2022.8.3.020 mailto:irinabelik2010@mail.ru r-economy, 2022, 8(3), 252–267 doi: 10.15826/recon.2022.8.3.020 253 r-economy.com online issn 2412-0731 с 2026 г., и, во-вторых, с февраля 2022 г. многие российские экспортеры попали под санкции, запрещающие ввоз продукции на территорию ес. существует большая неопределенность в отношении продолжительности текущего эпизода санкций, а также введения налога на выбросы углерода в странах ближнего востока и азии. цель исследования. целью исследования является оценка возможных экономических потерь в результате введения трансграничного углеродного регулирования и санкционного давления на российских экспортеров металлургической продукции и регионы их базирования. исследование сосредоточено на примере магнитогорского металлургического комбината (ммк) и челябинской области. данные и методы. методологически исследование опирается на сценарный анализ. рассматриваются два сценария: санкции ес в отношении российских металлургических компаний будут сняты после 2024–2025 гг. и санкции не будут сняты в ближайшее время. для каждого сценария анализируются два варианта и рассчитываются годовые экономические потери как для ммк, так и для челябинской области. данные для исследования были взяты из официальных отчетов ммк. результаты. если санкции ес будут сняты в ближайшее время, то на начальных этапах введения налога на выбросы углерода экономические последствия для российских экспортеров будут незначительными. однако в будущем углеродное регулирование может создать серьезные угрозы для финансового положения таких предприятий, даже если экспорт составляет небольшую долю их доходов. если санкции ес останутся в силе, российские предприятия, скорее всего, будут искать торговых партнеров на ближнем востоке и в азии. если последние введут налог на выбросы углерода, российские компании смогут получить конкурентное преимущество за счет сравнительно низкой углеродоемкости. выводы. для обеспечения конкурентоспособности российских металлургических компаний необходимо стимулировать их к сокращению углеродного следа и созданию национальной системы углеродного регулирования. эта мера не только поможет сократить потери доходов от экспорта и налоговых поступлений региональных правительств, но также позволит компаниям оставаться конкурентоспособными и более эффективно справляться с санкционным давлением. экономические потери регионального бюджета, санкционное давление, сценарии, сценарный анализ, металлургия, углеродоемкость благодарности исследование выполнено при поддержке гранта рнф и правительства свердловской области (проект № 22-2820453 «комплексный подход к процессам декарбонизации экономики: формирование региональной политики»). для цитирования belik, i.s., starodubets, n.v., yachmeneva, a.i., & prokopov, k.a. (2022). border carbon adjustment: implications for russian companies and regions in the context of the russia sanctions (the case of magnitogorsk iron and steel works and chelyabinsk region). r-economy, 8(3), 252–267. doi: 10.15826/recon.2022.8.3.020 制裁背景下的跨境碳调整对俄罗斯公司和地区的影响 （马格尼托哥尔斯克钢铁联合企业和车里雅宾斯克州为例） 别利克1 ，斯塔罗杜贝茨1，亚赫梅内娃2，普罗科波夫1 1 乌拉尔联邦大学，叶卡捷琳堡，俄罗斯；  irinabelik2010@mail.ru 2 俄罗斯电信公司，叶卡捷琳堡，俄罗斯 摘要 现实性：现在俄罗斯出口商至少面临两个严重的问题：首先，2021年欧 盟（eu）通过了跨境碳监管(tur)决议，该法规将从2026年开始生效； 其次，许多俄罗斯出口商自2022年2月以来一直受到制裁，他们被禁止 向欧盟输送货品。当前制裁的持续时间以及中东和亚洲国家是否引入碳 税存在很大的不确定性。 研究目的：评估跨境碳监管和制裁压力对俄罗斯冶金产品出口商及其家 乡造成的潜在经济损失。研究的重点是马格尼托哥尔斯克钢铁联合企业 （mmk）和车里雅宾斯克州。 数据与方法：该研究基于情景分析，其中考虑了两种可能：欧盟对俄罗 斯钢铁公司的制裁将在2024-2025年后解除，以及制裁在近期内不会解 除。文章对于每种可能，都列举了两种情况，并计算了钢铁联合企业和 车里雅宾斯克州的年度经济损失。研究数据来自马格尼托哥尔斯克钢铁 联合企业的官方报告。 关键词 跨境碳监管、碳监管经济损 失、区域预算经济损失、制裁 压力、情景、情景分析、冶 金、碳强度 致謝 該研究得到了俄羅斯科學基金 會和斯維爾德洛夫斯克州政 府的資助（項目編號 22-2820453“經濟脫碳過程的綜合方 法：區域政策的形成”）。 https://doi.org/10.15826/recon.2022.8.3.020 mailto:irinabelik2010@mail.ru 254 r-economy.com r-economy, 2022, 8(3), 252–267 doi: 10.15826/recon.2022.8.3.020 online issn 2412-0731 introduction most of the paris agreement countries, which account for more than a half of global greenhouse gas (ghg) emissions, are planning to introduce a  carbon management system in the nearest future or, alternatively, are considering the possibility of participating in other countries’ carbon management systems. russia is no exception: even under the pressure of sanctions, the government is planning to introduce carbon regulation. there is a national system to account for ghg emissions by sector, described in the methodology of the intergo vernmental panel on climate change (ipcc). large companies also have their own corporate accounting systems for ghg emissions. in 2021, the low-carbon development strategy until 2050 was adopted by the russian government1. the ministry of economic development has set forth a set of criteria for climate projects2, which can be used as a guidance by companies and citizens implementing such projects. to obtain state funding, they need to record their ghg emission reductions in a carbon registry system. it should be noted, however, that such important elements of carbon regulation as co2 pricing and emissions trading have not yet been developed in russia and will not begin to function soon. meanwhile, after years of discussions, in july 2021, the eu introduced the carbon border adjustment mechanism (cbam) as part of the comprehensive “fit for 55” climate package. the cbam is essentially aimed to ensure that eu importers should pay a price for their carbon emissions that would be comparable to the price paid 1 decree of the government of the russian federation dd. october 29, 2021 no. 3052-r 2 decree of the government of the russian federation. march 24, 2022 no. 455 “on approval of the rules for verifying the results of the implementation of climate projects” https://www.garant.ru/hotlaw/federal/1535164/ (accessed: 19.06.2022). by european domestic producers3. the tax is calculated by using the volume of direct ghg emissions that occurred during the production process and the price of co2 emissions equal to the market price of mandatory carbon certificates of the eu ghg emissions trading system (eu ets). this fee is paid by the importer, who must register with a special regulatory body, provide information on the volume of ghg emissions and purchase certificates to offset them. the tax applies to five commodity groups: cement, fertilizers, iron and steel, aluminum, and electricity. moreover, for electricity, there are rules for calculating emissions that differ from other goods. the cbam is planned to be introduced in several stages, starting from 2023, and then in full, including the purchase of cbam certificates, from 2026. initially, the cbam will cover direct emissions of selected sectors (scope 1). for complex products, tax calculations will also take into account ghg emissions from natural resources extraction and materials production (scope 1 + scope 3). the system of carbon regulation traditionally relies on efficient administrative management methods such as technical regulation, consumption rates for fossil fuels and electricity used, building energy efficiency standards, compiling lists of the best available technologies, quantitative limitation of emissions, etc. we believe, however, that by relying on administrative methods alone, the government will be unable to create a comprehensive carbon regu lation system. it is clear that if the system of carbon regulation does not include economic incentives (e.g. setting a market price per ton of ghg; introducing a carbon tax), its effectiveness will be 3 proposal for a regulation of the european parliament and of the council establishing a carbon border adjustment mechanism. https://eur-lex.europa.eu/legal-content/en/ txt/?uri=celex:52021pc0564 (accessed: 22.06.2022) . 研究结果：如果欧盟的制裁很快被解除，那么碳税在初始阶段对俄罗斯 出口商的经济影响将很小。然而，在未来，即使出口占其收入的一小部 分，碳监管也可能对这些企业的财务状况构成严重威胁。如果欧盟制裁 将持续存在，俄罗斯企业可能会在中东和亚洲寻找贸易伙伴。如果后者 引入碳税，俄罗斯公司可以通过其相对较低的碳强度获得竞争优势。 结论: 为确保俄罗斯冶金公司的竞争力，有必要鼓励它们减少碳足迹并建 立国家碳监管体系。这一措施不仅有助于提高出口收入、减少地区政府 税收损失，而且还能使公司保持竞争力，更好地应对制裁压力。 致謝 belik, i.s., starodubets, n.v., yachmeneva, a.i., & prokopov, k.a. (2022). border carbon adjustment: implications for russian companies and regions in the context of the russia sanctions (the case of magnitogorsk iron and steel works and chelyabinsk region). r-economy, 8(3), 252–267. doi: 10.15826/recon.2022.8.3.020 https://doi.org/10.15826/recon.2022.8.3.020 https://www.garant.ru/hotlaw/federal/1535164/ https://eur-lex.europa.eu/legal-content/en/txt/?uri=celex:52021pc0564 https://eur-lex.europa.eu/legal-content/en/txt/?uri=celex:52021pc0564 r-economy, 2022, 8(3), 252–267 doi: 10.15826/recon.2022.8.3.020 255 r-economy.com online issn 2412-0731 low. in addition, economic methods such as capand-trade systems with baselines and emissions reduction subsidies (including subsidizing the use of renewable energy) allow the governments to set a more “objective” price for carbon because the cost of production should, among other things, depend on the external costs of overcoming the consequences of emissions (the so-called monetization of environmental damage). thus, econo mic instruments for ghg emissions reduction, including carbon taxes and cbam systems simi lar to the one implemented in the eu, can be applied in other countries, including the countries of the middle east and southeast asia (tagliapietra, & wolff (2021); morgan, & patomäki (2021)). since february 2022, russian iron and steel enterprises have been under sanctions from various countries, including the eu. the fourth package of the eu restrictive measures bans iron and steel imports from russia to the eu4. if these sanctions are not lifted by 2024–2025, domestic metallurgical enterprises are likely to search for trade partners in asian and middle eastern countries and reorient their production toward these markets5. this circumstance will increase the transportation costs of exporting enterprises. it is also conceivable that in the designated countries carbon payments will be introduced, similar to those included in the european cbam system, which will mean extra costs for exporters. at present, the actual price of carbon for more than half of all the emissions in the world remains at a very low level and does not exceed $10 per ton of co2-eq., which does not stimulate the decarbonization of the economy. however, according to the international energy agency, the price of co2-eq. can be set at around 75–100 us dollars per ton of co2. to date, this price level has been set for only 5% of the emissions covered by the carbon adjustment, the source of these emissions being mainly the eu countries. russia is not included in this group. therefore, in the absence of the national carbon adjustment system, when the carbon tax is introduced in the eu, russian exporters to the eu and other countries may lose their competitive edge and/or incur significant losses. 4 council regulation (eu) 2022/428 of 15 march 2022. https://eur-lex.europa.eu/legal-content/en/txt/pdf/?uri=oj: l:2022:087i:full&from=en (accessed: 05.06.2022). 5 ferrous metallurgy is predicted to stagnate under sanctions until 2030. https://www.vedomosti.ru/business/ articles/2022/08/07/934909-chernoi-metallurgii-stagnatsiyusanktsiyami (accessed: 08.06.2022). the purpose of this article is to estimate russian exporters’ potential economic losses caused by the introduction of the cbam, taking into account the sanctions pressure on the russian exporters of metallurgical products and their home regions. to this end, we are going to use the case of one of the largest facilities in russia’s metallurgical sector – pjsc “magnitogorsk iron and steel works” (mmk) situated in chelyabinsk region. mkk is a group of companies, which includes both manufacturing facilities and trade companies operating in russia and abroad. to achieve this goal, the following tasks have been set, which, in their turn, determined the structure of the article: first, we are going to build an organizational chart for the cbam and calculate the amount of the carbon tax; second, since there is much uncertainty surrounding the duration of the current sanctions episode, we are going to consider two possible scenarios – the first scenario proceeds from the assumption that the eu sanctions will be lifted after 2024–2024 and the second, that it won’t happen in the near future; third, we are going to apply both of these scenarios to the case of magnitogorsk iron and steel works (mmk) and its home region; finally, for each scenario, we intend to estimate the losses incurred by the facility and chelyabinsk region and give our recommendations as to how these losses can be handled. theoretical framework a border adjustment instrument is introduced to encourage exporters to reduce the carbon intensity of their products as well as enhance the competitiveness of european producers, who bear higher environmental costs due to the eu legislation. european companies adhere to the carbon neutral policy, and it is believed that in this respect they are less competitive than manufacturers from countries such as the united states, china and russia, which use carbon fuels and carbon-intensive technologies, since these countries do not have any serious restrictions on co2 emissions (krivorotov, belik et al., 2019). according to ailor et al. (2020), china, russia and the united states rank high among the main countries in terms of carbon dioxide emissions in europe (fig. 1). russia is the second largest exporter to the eu after china in terms of co2 volumes (approximately 150-200 million tons annually for all goods and services). the eu countries account for 42% of russian exports, including metals. https://doi.org/10.15826/recon.2022.8.3.020 https://eur-lex.europa.eu/legal-content/en/txt/pdf/?uri=oj:l:2022:087i:full&from=en https://eur-lex.europa.eu/legal-content/en/txt/pdf/?uri=oj:l:2022:087i:full&from=en https://www.vedomosti.ru/business/articles/2022/08/07/934909-chernoi-metallurgii-stagnatsiyu-sanktsi https://www.vedomosti.ru/business/articles/2022/08/07/934909-chernoi-metallurgii-stagnatsiyu-sanktsi https://www.vedomosti.ru/business/articles/2022/08/07/934909-chernoi-metallurgii-stagnatsiyu-sanktsi 256 r-economy.com r-economy, 2022, 8(3), 252–267 doi: 10.15826/recon.2022.8.3.020 online issn 2412-0731 china has already joined the carbon trading system, and in july 2022 held the first online trading of ghg quotas, while the cost of quotas did not exceed $10 (in the european market, the price exceeds 60 euros per ton). thus, we can assume that the market for trading carbon units in china has already been created. it would make sense, therefore, to consider the group of studies dealing with the problem of china’s transition to carbon neutrality. ren et al. (2021) explored the ways for china’s transition to a low-carbon model in the sphere of iron and steel manufacturing to achieve carbon neutrality by 2050. iron and steel production in china accounts for 14% of total energy-related co2 emissions, which means that the decarbonization of this industry plays an important role in achieving carbon neutrality. ren et al. (2021) apply an integrated approach combining a general equilibrium model and a bottom-up technology choice modu le to show that in the long term it is necessary to focus on the introduction of advanced technologies, for example, carbon capture and storage and hydrogen-based direct reduction. the latter could be an effective option to reduce co2 emissions in scenarios where carbon capture and storage is not available, increasing its share to 23–25% by 2050. xiao et al. (2021) proposed a decarbonization model that takes into account the technological progress in china and inter-regional power transmission for china’s energy sector. demetriou & hadjistassou (2021) note that china’s electricity sector can only achieve net zero emissions by phasing out coal. thus, it should be expected that the development of a low-carbon economy will not only minimize the costs associated with more stringent regulation but the products with a low carbon footprint will become more competitive, which will create extra benefits (favorable borrowing conditions, reduced trade barriers, etc.) for exporting companies and will ensure their sustainable presence in international markets. belik et al. (2016, 2017) explore the concept of low-carbon economic development and propose a mechanism for its implementation for russia. chernenko et al. (2022) identified regional determinants of the low-carbon transition in russian companies and found that this transition is becoming an essential component of the national deve lopment strategy, and that there are two types of factors that influence the implementation of ma nagement practices for the low-carbon transition: human capital and the digitalization of regions. schiffer (2021) explains that an international agreement on the floor price for co2 within the g20, which is superior to the cbam advocated by the eu commission, should be the “cornerstone” for the cbam introduction. hájek et al. (2018) investigated the effectiveness of the carbon tax in the energy sectors of individual eu countries and concluded that an increase in the carbon tax rate can help reduce ghg emissions. frischmuth & härtel (2022) examined the structure of low-carbon energy markets and energy markets and demonstrated that achieving climate neutrality in europe will require transformations in all sectors of the economy, including energy, construction, industry and transport. andersson et al. (2021) discuss industrial decarbonization processes and argue that energy imported emissions, million tons figure 1. sources of co2 emissions for the european union source: ailor et al., 2020 https://doi.org/10.15826/recon.2022.8.3.020 r-economy, 2022, 8(3), 252–267 doi: 10.15826/recon.2022.8.3.020 257 r-economy.com online issn 2412-0731 management is the most important means of improving energy efficiency. since production processes in the manufacturing industries differ significantly, andersson et al. (2021) conclude that it is essential to develop sector-specific models for devising the necessary indicator systems. lopez et al. (2021) modified carbon analysis approaches to determine the minimum renewable energy target for a group of countries with an electricity trade agreement. the efficiency of this carbon-contained energy planning approach is illustrated by three case studies, including those involving the countries of the association of southeast asian nations. sotiriou and zachariadis (2021) have developed a multi-objective approach to optimize decarbonization pathways in a dynamic policy context. although the modeling framework was developed and adapted to the specific political conditions of the eu, the proposed methodology is fully applicable to other regions of the world and includes the development of a decarbonization roadmap. there is a growing consensus in research literature that decarbonization is a major economic trend and that it is achieved through the development of clean technologies, governmental support of the projects for the creation of an appropriate infrastructure and policy-makers’ efforts to eliminate the barriers to investment in such projects. there is substantial research evidence pointing to the potential of the carbon tax as a source of funding for the upcoming moder nization of european industry and the fuel and energy complex (parry, 2019). a number of studies discuss the implications of the cbam introduction, including the consequences for russia (see, for example, sulin et al. (2021), kolpakov (2021), and sokolov (2021)). stepanov (2021)6 developed a methodology for calculating the implied price of carbon, the aggregate price of a ton of emissions, which includes both the direct price of emissions, set through carbon taxes and the eu ets, and the indirect price, presented in taxes on the use of fossil fuels (including motor fuel taxes). a separate group of studies deal with the problems of decarbonization in russia in the context of specific industries (see, for example, gru6 stepanov, i.a. (2021). economic instruments for regulating greenhouse gas emissions in european countries. summary of thesis. … cand. of economic sciences. moscow, 27 p. (in russ.) shevenko et al. (2021), usov et al. (2017), vetrova et al. (2021), iktisanov & shkrudnev (2021), lukin (2021) on the oil and gas industry7; gaida et al. (2021), golyashev et al. (2021) on the energy industry; plakitkina et al. (2021) on the coal industry; klepcha (2021) on the iron and steel industry)8. lebedev (2022), kaisina & kustikova (2022), balashov (2020) and mitrofanova (2021) provide a more comprehensive perspective on the decarbonization processes in russian industry the cbam may provide a stimulus for russia to introduce its own carbon regulation system: in order to be granted an exemption from paying the carbon tax, an exporter has to have a similar carbon payment mechanism in its home country (gaida et al, 2021; golyashev et al, 2021; sokolov, 2021). to date, the strategy for the socio-economic development of russia with low ghg emissions until 2050 (dated october 29, 2021) considers two scenarios: the inertial (“no change”) scenario and target scenario, with different sets of measures to decarbonize the economy (table 1). table 1 mass indicators for ghg emissions and uptake name actual – 2019 plan – 2030 plan – 2050 “no change” scenario ghg emissions 2119 2253 2521 absorption –535 –535 –535 net emissions 1584 1718 1986 target scenario ghg emissions 2119 2212 1830 absorption –535 –539 –1200 net emissions 1584 1673 630 source: strategy for socio-economic development of the russian federation with low ghg emissions until 2050. http://static.government.ru/media/files/adkkczp3fwo32e2ya0bhtipyzwfhaiua.pdf (accessed: 27.05.2022). another big step for russia in the development of carbon regulation is the so-called sakhalin experiment (no. 34-fz “on conducting an experi ment to limit ghg emissions in certain regions of the russian federation”), which will run from september 1, 2022 to december 31, 2028. the goal of the experiment is to achieve carbon neutrality in sakhalin region by december 31, 2025. 7 lukin, v. (2021). decarbonization: industry risks and opportunities. neftegaz.ru, 7(115), 54–59. retrieved from https://magazine.neftegaz.ru/articles/ekologiya/689023dekarbonizatsiya-otraslevye-riski-i-vozmozhnosti-/ (in russ.). (accessed: 15.06.2022). 8 klepcha, к. (2021). pioneers of the low carbon footprint. expert, 23. https://expert.ru/expert/2021/23/pionerynizkouglerodnogo-sleda/ (in russ.) (accessed: 17.06.2022). https://doi.org/10.15826/recon.2022.8.3.020 http://static.government.ru/media/files/adkkczp3fwo32e2ya0bhtipyzwfhaiua.pdf http://static.government.ru/media/files/adkkczp3fwo32e2ya0bhtipyzwfhaiua.pdf https://magazine.neftegaz.ru/articles/ekologiya/689023-dekarbonizatsiya-otraslevye-riski-i-vozmozhno https://magazine.neftegaz.ru/articles/ekologiya/689023-dekarbonizatsiya-otraslevye-riski-i-vozmozhno https://expert.ru/expert/2021/23/pionery-nizkouglerodnogo-sleda/ https://expert.ru/expert/2021/23/pionery-nizkouglerodnogo-sleda/ 258 r-economy.com r-economy, 2022, 8(3), 252–267 doi: 10.15826/recon.2022.8.3.020 online issn 2412-0731 data and methods the carbon tax and emissions trading systems are the most applicable economic tools in the world. as of 2021, the world bank counted 64 active or launch date carbon pricing initiatives9 covering 46 national and 35 subnational jurisdictions, covering approximately 22.3% of global ghg emissions (22gt co2-eq.). regarding russia, according to experts’ preliminary estimates (gaida, 2021), the introduction of a carbon tax could affect about 42% of all the exports, since the carbon intensity of domestic products is very high. the following diagram (see fig. 2 below) gives a visual representation of the dynamics of emissions by sector. the structure of the country’s emissions is dominated by the energy sector, whose share in total emissions volume is 78.9%. analysis of the intra-industry structure indicates that the largest contribution is made by the extraction, transportation, processing and use of various types of fossil fuels (with the exception of their use as raw materials). the associated emissions are classified as emissions from the energy sector since they are produced by the combustion and processing of extracted natural fuel (oil, natural and associated gas, coal, peat and oil shale). the most important source of the country’s emissions in the industrial sector is the iron and steel industry. its contribution to the total ghg 9 the world bank. state and trends of carbon pricing. https://openknowledge.worldbank.org/handle/10986/35620 (accessed: 16.06.2022). emissions in this sector in 2017 amounted to 46.3%. another significant source of emissions is the chemical industry – 29.6%; emissions from the production of mineral materials account for 15.9% (see table 2). as noted, an important export market for russia is the european union. the key russian exports are the products of the oil and gas industry and metallurgical sector. the share of the russian exports to the eu in 2021, according to the federal customs service, was approximately 36%; metallurgy ranks second in this structure10. experts from boston consulting group (ailor, gilbert, & kosach, et al. (2020) and kpmg, one of the big four accounting firms11, in their study on the impact of a carbon border tax on global trade found that regulation will mainly affect exporters of carbon fuels of oil and gas and coal industries as well as the iron and steel industry. for example, if the tax is charged at $30 per ton of co2 emissions for producers of flat steel products, the losses from the fall in exports to the eu could be up to 40%. a positive side of the situation for russian companies is that in terms of global competitive advantages they look much more attractive than manufacturers from china, whose steel carbon intensity is much higher. 10 rosstat. https://rosstat.gov.ru/storage/mediabank/ 26_23-02-2022.html (accessed: 20.06.2022). 11 kpmg. summary of the cbam regulation. https:// home.kpmg/xx/en/home/insights/2021/07/summary-of-thecbam-regulation.html (accessed: 25.06.2022). waste industry agriculture energy 1990 1995 2000 2005 2010 2011 2012 2013 2014 2015 2016 2017 years 3500 3000 2500 2000 1500 1000 500 0 em is si on s, m t c o 2eq . figure 2. amount of ghg emissions in russia, excluding land use changes in land use and forestry source: 4th biennial report of the russian federation submitted in accordance with decision 1/cp.16, the conference of the parties to the united nations framework convention on climate change. https://unfccc.int/sites/default/files/resource/10469275_russian%20federation-br4-1-4br_rus.pdf (accessed: 27.05.2022) https://doi.org/10.15826/recon.2022.8.3.020 https://openknowledge.worldbank.org/handle/10986/35620 https://rosstat.gov.ru/storage/mediabank/26_23-02-2022.html https://rosstat.gov.ru/storage/mediabank/26_23-02-2022.html https://home.kpmg/xx/en/home/insights/2021/07/summary-of-the-cbam-regulation.html https://home.kpmg/xx/en/home/insights/2021/07/summary-of-the-cbam-regulation.html https://home.kpmg/xx/en/home/insights/2021/07/summary-of-the-cbam-regulation.html https://unfccc.int/sites/default/files/resource/10469275_russian%20federation-br4-1-4br_rus.pdf r-economy, 2022, 8(3), 252–267 doi: 10.15826/recon.2022.8.3.020 259 r-economy.com online issn 2412-0731 according to the management of the association of russian metallurgists “russian steel”12, the business may suffer significant losses due to the loss of its position in a highly competitive market, and over time, the cross-border tax factor will put more pressure on the business, since the cost of co2 linked to the eu ets prices, will keep growing every year12: kpmg predicts the eu ets price for  the period of 2023–2030 within the range from 56 to 89 euros/t co2-eq. the cbam resolution proposes to calculate the cross-border carbon tax by using the following formula: carbon tax = (cf – cf ∙ ss) × × (cco2eu – cco2 country of origin), (1) where сf is the carbon footprint of the impor ted product in tons of co2-eq. per unit of production; ss is the sectoral share of free emission quotas in the eu ets, units; cco2eu is the cost of cbam-certificate in the eu, eur/t co2-eq.; cco2 country of origin of the product is the payment for the 1 ton of co2-eq. in the product’s country of origin, eur/tco2-eq. the methodology for calculating the components of the carbon tax raises many questions as it relies on approaches that are not verified by practice, including some issues that have not been worked out procedurally, containing data that are 12 metallurgists urge authorities to protect them from eu carbon tax. https://www.rbc.ru/business/15/07/2021/60f01ab4 9a79479e896d2e64 (accessed: 20.06.2022). not reflected in current reporting. thus, our calculations are based on certain assumptions and extrapolation methods. in 2021, the price in the eu ets has almost doubled compared to the level before the pandemic and reached 50 euros per 1 tonne of greenhouse gases13. in this regard, the authors rely on the weighted average price, which is 55 euros per ton of co2-eq.. the payment for ghg emissions in the country of origin of the goods is assumed to be zero, since the national regulatory mechanism in russia has not yet been formed. at the moment, there is also uncertainty related to the procedure for calculating the non-taxable part of the carbon footprint of products imported by the eu. the existing ets benchmark system in the european union, which establishes the number of free quotas for ghg emissions issued to enterprises in various sectors of the economy, is not directly applicable to the cbam. this discrepancy is explained by the fact that in the eu ets, emission benchmarks are introduced for production processes, while in the cbam the carbon footprint is estimated for individual products, not processes. it is likely that in the future, emission benchmarks for individual products will be introduced specifically for the cbam, and these two benchmark systems will be harmonized. for this reason, when determining the 13 trading economics. https://tradingeconomics.com/ commodity/carbon (accessed: 20.06.2022). table 2 ghg emissions associated with industrial processes and product use, mln tons of co2-eq. source categories gas 2010 2011 2012 2013 2014 2015 2016 2017 mineral materials mining co2 37.14 40.11 42.10 43.52 43.07 40.01 36.51 37.12 chemical industry co2 35.09 36.64 36.08 37.62 37.61 39.24 41.31 43.37 ch4 0.39 0.41 0.41 0.45 0.43 0.45 0.45 0.48 n2o 5.40 5.65 5.50 5.76 5.56 6.01 6.32 6.57 f-gases 8.21 4.42 9.08 11.50 13.13 9.46 9.16 17.99 iron and steel industry co2 99.21 100.34 103.82 101.22 103.17 104.13 103.75 104.82 ch4 0.13 0.13 0.13 0.13 0.13 0.14 0.13 0.13 f-gases 3.49 3.15 3.18 3.28 2.90 3.36 3.49 3.01 use of solvents and non-energy fuel products co2 1.12 1.18 1.30 1.20 1.50 1.59 1.69 1.39 use of fluorinated substitutes (ods) f-gases 5.39 7.07 8.92 10.47 11.85 13.05 14.63 16.43 source: 4th biennial report of the russian federation submitted in accordance with decision 1/cp.16, the conference of the parties to the united nations framework convention on climate change. https://unfccc.int/sites/default/files/resource/10469275_ russian%20federation-br4-1-4br_rus.pdf (accessed: 27.05.2022). https://doi.org/10.15826/recon.2022.8.3.020 https://www.rbc.ru/business/15/07/2021/60f01ab49a79479e896d2e64 https://www.rbc.ru/business/15/07/2021/60f01ab49a79479e896d2e64 https://tradingeconomics.com/commodity/carbon https://tradingeconomics.com/commodity/carbon https://unfccc.int/sites/default/files/resource/10469275_russian%20federation-br4-1-4br_rus.pdf https://unfccc.int/sites/default/files/resource/10469275_russian%20federation-br4-1-4br_rus.pdf 260 r-economy.com r-economy, 2022, 8(3), 252–267 doi: 10.15826/recon.2022.8.3.020 online issn 2412-0731 share of free quotas for emissions, the assumption is made that in 2019 in all sectors that produce products subject to the cbam, the sectoral shares of free quotas were 80–90% and that they will remain so until 2026. subsequently, with the start of the second stage of the cbam, all these shares will be reset to zero by 2035. therefore, the data obtained through the extrapolation over a tenyear period were taken into account. the shares of free sectoral emission quotas issued by the eu ets, as stipulated by the amendments to the law on the eu ets, should be reduced by 10% annually, starting from 2026. table 3 presents the values of the free quotas by sector. we estimated the potential losses from the carbon tax introduction for domestic exporting enterprises and for regional budgets by using the case of one of the largest facilities in the metallurgical sector – magnitogorsk iron and steel works (mmk) and chelyabinsk region. the company occupies the first place in the esg-transparency ranking of companies and banks of the “expert ra” rating agency and is included in the top four ratings of openness of mining and metallurgical companies in russia in the field of environmental responsibility compiled by the wildlife fund (wwf) of russia. the data on gross and specific ghg emissions at mmk (scope 1, 2 and 3) are taken at the 2020 level and are presented in fig. 3 and 4. as follows from fig. 4, in 2020, mkk released 2.18 tons of co2-eq. per ton of steel. to date, there is no exact understanding of how the situation with the sanctions against russia will develop. therefore, in the face of the uncertainty about the duration of these sanctions, we propose to consider two scenarios: the eu sanctions against russian iron and steel companies will be lifted after 2024–2025 and the eu sanctions against russian iron and steel companies will not be lifted in the near future, which will require companies to reorient themselves to new markets. table 3 shares of free quotas for ghg emissions in the sectors that manufacture cbam-targeted products, in 2019, 2026–2035, % sector actual forecast 2019 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 aluminum production 85 77 68 60 51 43 34 26 17 9 0 pig iron and steel production 74 66 59 51 44 37 29 22 15 7 0 ammonia production 82 74 66 57 49 41 33 25 16 8 0 production of nitric and sulfonitric acids 87 78 70 61 52 43 35 26 17 9 0 cement production 99 89 79 69 60 50 40 30 20 10 0 power generation 0 0 0 0 0 0 0 0 0 0 0 source: khomutov et al., 2021; cross-border carbon regulation in the eu: how to turn it in favor of russia? http://www. petromarket.ru/upload/iblock/306/cbam_petromarket_08_2021.pdf (accessed: 27.06.2022). 26.09 27.49 29.49 11.17 12.42 0.71 0.81 scope 1 scope 2 scope 3 0 10 20 30 40 50 2020 2019 2018 figure 3. gross ghg emissions of mmk, in mln tons of co2-eq. source: mmk integrated report 2020. https://mmk.ru/upload/iblock/c5f/t80bjab1uofvi6fjvfr1i26w23xtape8/integrated%20 annual%20report_rus.pdf (accessed: 27.05.2022) https://doi.org/10.15826/recon.2022.8.3.020 http://www.petromarket.ru/upload/iblock/306/cbam_petromarket_08_2021.pdf http://www.petromarket.ru/upload/iblock/306/cbam_petromarket_08_2021.pdf https://mmk.ru/upload/iblock/c5f/t80bjab1uofvi6fjvfr1i26w23xtape8/integrated%20 annual%20report_rus. https://mmk.ru/upload/iblock/c5f/t80bjab1uofvi6fjvfr1i26w23xtape8/integrated%20 annual%20report_rus. r-economy, 2022, 8(3), 252–267 doi: 10.15826/recon.2022.8.3.020 261 r-economy.com online issn 2412-0731 2.5 2.0 1.5 1.0 0.5 0 2019 2020 target until 2025 2.13 2.18 1.80 figure 4. ghg emissions of mmk, t со2-eq./t of steel source: compiled by the authors the paper considers the following scenarios for the development of the situation for mmk and chelyabinsk region. scenario 1 the first variation of this scenario considers two options: a) there is a company affiliated with mmk that buys products from russia while being a resident of the eu. in this case, when metal products are exported to the eu, this company will bear the burden of the carbon tax, which means losses for the whole mkk group. b) an importer of the cbam-targeted products will pay the full carbon tax. in this case, when concluding a contract with a counterparty from russia for the supply of products, it may set a condition for including a  discount in the contract, the amount of which will be determined by the amount of the paid carbon fee. the second variation of this scenario is the loss of a part of export revenues because of the decrease in the export volume of metal products due to the reduction in the size of preferential quotas for the eu producers and, as a result, an increase in the amount of carbon tax paid for imports of those products that fall under the cbam. calculations based on the case of mmk will assume that the decline in sales will be gradual and will amount to 10% of the total sales to europe (proportionate to the volume of the reduction in preferential quotas in the european union). scenario 2 the first variation of this scenario is related to russian companies’ reorientation to the middle east and asian markets. in this case, there are additional costs associated with an increase in the transportation leg. according to the estimates of the association “russian steel”, about 4 million tons of steel products per year can be redirected by russian metallurgical companies to the east, while the distance of cargo delivery will increase by more than three times – from 2300 to 7900 km, which will lead to additional companies’ expenses of 17 billion rubles a year, or, in terms of a ton of products, additional costs will amount to 4.25 thousand rubles per ton14. the second variation repeats the conditions of the previous one, an additional assumption being that the countries of the middle east and asia will also introduce a carbon tax on the import of carbon-intensive products, while, since the conditions for its calculation in the given countries are not known today, it is proposed to calculate it by using the eu parameters (formula (1)). the introduction of carbon payments for exporting companies, a decrease in revenue from the export of goods falling under the cbam, and an increase in transport costs will also have an impact on regional tax revenues. mmk is the largest taxpayer in chelyabinsk region, and in the following section we are going to consider the potential losses of the regional budget arising from the shortfall in income tax. according to the tax code of the russian federation, today 17% of the corporate income tax goes to the regional budget. results according to our calculations, the amount of the carbon tax for importers of metal products to the eu will be 40.766 euros/per ton of steel (2.18 – 2.18 · 0.66) · (55 – 0). now we are going to calculate the potential losses of mkk and chelybinsk region for the two scenarios and their variations described above: 1st scenario variation (1a). the assessment of mkk’s potential losses will take into account the annual volume of exports to the eu (an average of 2.9% or 280,000 tons in 2021, according to the financial statements of mmk). the losses in this case will amount to 11,414.48 thousand euros (280,000 · 40.766) or 993,972.9 thousand rubles (for the exchange rate we used the average annual rate of the central bank of the russian federation 14 metallurgists estimated the costs of redirecting russian steel from europe to the east. https://www.forbes.ru/ biznes/461239-metallurgi-ocenili-zatraty-na-perenapravleniestali-iz-evropy-na-vostok (accessed: 25.06.2022). https://doi.org/10.15826/recon.2022.8.3.020 https://www.forbes.ru/biznes/461239-metallurgi-ocenili-zatraty-na-perenapravlenie-stali-iz-evropy-na https://www.forbes.ru/biznes/461239-metallurgi-ocenili-zatraty-na-perenapravlenie-stali-iz-evropy-na https://www.forbes.ru/biznes/461239-metallurgi-ocenili-zatraty-na-perenapravlenie-stali-iz-evropy-na 262 r-economy.com r-economy, 2022, 8(3), 252–267 doi: 10.15826/recon.2022.8.3.020 online issn 2412-0731 in 2021 – 87.08 rubles). these losses will be borne by the entire mmk holding. losses of the regional budget in this case will amount to 168,975 thousand rubles per year (993,972.9 thou. rubles · 0.17). 1st scenario variation (1b). in this case, mmk will face a decrease in its export revenue by the amount of carbon tax paid in the amount of 993,972.9 thousand rubles. losses of the regional budget in this case will also amount to 168,975 thousand rubles per year. 1st scenario variation (2). according to mmk’s annual report, in 2021, the company’s revenue from exports to the eu amounted to 18,952,542 thousand rubles. in this case, the sales volume will be 252 thousand tons, and the carbon tax will be equal to 10,273 thousand euros (252,000 · 40.766) or 894,575.6 thousand rubles. export proceeds from sales to the eu will decrease by 18,952,542 thousand rubles · 0.1 = 1,895,254 thousand rubles or by 21,764.5 thousand euros (mkk’s revenue from exports to the eu for 2021 are taken as the basis for calculations). thus, the total losses of mmk in this scenario will amount to 894,575.6 thousand rubles + 1,895,254.0 thousand rubles = = 2,789,829.6 thousand rubles or 32,038.3 thousand euros. losses of the regional budget will amount to 474,271 thousand rubles per year. 2nd scenario variation (1). due to the reorientation to the middle eastern and asian markets, additional transportation costs for mmk will amount to 4.25 thousand rubles · 280,000 tons = =  1,190,000 thousand rubles per year. losses of the regional budget in the form of the lost income tax in this case will amount to 202,300 thousand rubles per year. 2nd scenario variation (2). if the middle eastern and asian countries introduce a carbon tax similar to the eu, mmk will incur costs equal to 11,414.48 thousand euros (280,000 · 40.766) or 993,972.9 thousand rubles. thus, the total losses of mmk, together with additional transportation costs, in this case will amount to 1,190,000 thousand rubles + 993,972.9 thousand rubles = = 2,183,972.9 thousand rubles tax losses of the regional budget in this scenario variation will amount to 371,275 thousand rubles per year. in both variations of scenario 2, there are risks associated with the loss of a part of export earnings due to a likely decrease in the price of export metal products. it should be noted, however, that the carbon intensity of domestic metal products is at the global average and is significantly lower than in the countries of the asian and middle eastern segments (fig. 5). the latter is very important to determine the amount of the carbon tax and it can also be used as a leverage in price negotiations. if we consider the situation in relation to the mmk group, whose position is the most vulnerable (fig. 6) in terms of the carbon intensity of products compared to the top russian companies, an important observation should be made: since 2016 the company has been accounting for its ghg emissions. and now, mmk’s top goal is to reduce specific ghg emissions (co2-eq./t of steel) by more than 20% by 2025 (compared to 2018). 2.5 2.0 1.5 1.0 0.5 0 2017 2018 2019 2020 2025 world average –wsa mc “metalinvest” pjsc “nlmk” “evraz” group (steel segment) pjsc “severstal” pjsc “mmk” t c o 2eq ./t s te el figure 5. russian companies’ co2 emissions per ton of steel source: bashmakov i. benchmarking of specific ghg emissions in industrial production. cenef-xxi. https://cenef-xxi.ru/uploads/session_2_i_bashmakov_benchmarking_of_greenhouse_gas_ emissions_in_industrial_ production_dfe5178e68.ppt (accessed: 27.05.2022) https://doi.org/10.15826/recon.2022.8.3.020 https://cenef-xxi.ru/uploads/session_2_i_bashmakov_benchmarking_of_greenhouse_gas_%20emissions_in_industrial_production_dfe5178e68.ppt https://cenef-xxi.ru/uploads/session_2_i_bashmakov_benchmarking_of_greenhouse_gas_%20emissions_in_industrial_production_dfe5178e68.ppt r-economy, 2022, 8(3), 252–267 doi: 10.15826/recon.2022.8.3.020 263 r-economy.com online issn 2412-0731 to achieve this goal, mmk is actively implementing projects to increase its energy efficiency and improve its technological processes, which means cutting the amount of ghg emissions. moreover, in the future, the company plans to implement even more such projects, including a converter gas utilization project, starting in 2025, which will significantly reduce the carbon intensity of its products and strengthen its competitive position worldwide. a summary of the four scenarios is presented in table 4. if the sanctions are lifted in 2024–2025, the annual losses of both mmk and the regional budget will be the highest in the second variation of the first scenario, 2.8 times higher than in the first variation. in this case mmk will incur losses both due to the profits lost as a result of a drop in eu exports revenue due to the company’s high carbon intensity and falling competitiveness and due to payments under the cbam. proportionately, the government of chelyabinsk region will also lose a part of its tax revenue. we believe that the events described in the second variation of the first scenario are more likely since a gradual decrease in the value of free quotas in the eu by 2035, as the cbam is introduced, appears unavoidable (see sato, rafaty, calel, & grubb, (2022); ellerman, marcantonini, zaklan (2016)). if the eu sanctions against metallurgical enterprises are not lifted, then the second variation of the second scenario will mean the maximum losses for mkk and its home region – here the carbon tax is added to the additional transport costs. we believe, however, that it is less likely to happen in the near future, since so far there have been no official statements from the asian and middle eastern countries about the extension of intra-country carbon payments to third countries. in any case, russian steel manufacturers’ low carbon intensity compared to their counterparts in these regions as well as mkk’s planned decarbonization activities give us hope that carbon tax payments will be lower. in this regard, the implementation of projects aimed at reducing the carbon footprint is of particular importance. such targets should also be reflected in regional investment programs. the planned reduction in the specific carbon intensity of mmk’s products to 1.8 tons of co2-eq. per ton of steel (see fig. 6) will bring this figure in line with the global average and allow the company to compete more confidently in the global market in terms of the carbon intensity of its products (see fig. 5). –14% 2.40 2.30 2.13 2.18 2.00 1.80 31.1 29.5 28.3 26.8 26.5 22.9 2017 2018 2019 2020 2021 2022 co2, thousand t. emission factor t co2/t sreel greenhouse gases figure.6. reducing mkk’s impact on the environment source: pjsc mmk’s presentation for private investors bcs. https://mmk.ru/upload/iblock/234/vmanww0oq260mjt0n mvpnq63ca9igizz/mmk_bcs_retail_investors_conference_final.pdf (accessed: 27.05.2022) table 4 the estimation of economic losses of mmk and chelyabinsk region facility annual economic losses, thousand rubles scenario 1 (the eu sanctions are lifted in 2024–2025) scenario 2 (reorientation to new markets) 1а 1b 2 1 2 mmk 993,972.9 993,972.9 2,789,829.6 1,190,000.0 2,183,972.9 chelyabinsk region 168,975.0 168,975.0 474,271.0 202,300.0 371,275.0 total 1,162,948.0 1,162,948.0 3,264,101.0 1,392,300.0 2,555,247.9 source: authors’ estimations https://doi.org/10.15826/recon.2022.8.3.020 https://mmk.ru/upload/iblock/234/vmanww0oq260mjt0nmvpnq63ca9igizz/mmk_bcs_retail_investors_conference_final.pdf https://mmk.ru/upload/iblock/234/vmanww0oq260mjt0nmvpnq63ca9igizz/mmk_bcs_retail_investors_conference_final.pdf 264 r-economy.com r-economy, 2022, 8(3), 252–267 doi: 10.15826/recon.2022.8.3.020 online issn 2412-0731 conclusions the scenarios considered for mmk and chelyabinsk region related can be extrapolated to the whole russian market. of course, while the organizational structure of the mechanism remains unclear, there is also high uncertainty surrounding the national carbon regulation system. whether it will be similar to the mechanisms of the eu ets and the eu cbam, and the russian regulator will be guided by similar principles or whether it will develop more serious regulatory measures is still unclear. this situation indicates that if at the initial stages of the introduction of the cbam the risks for export-oriented companies are small, then in the near future carbon regulation in the european union and other countries may create serious threats to financial stability of enterprises, even those with a small share of exports in their sales. after the abolition of the free emission quotas in the eu and the global increase in ghg prices, enterprises will incur significant costs from the carbon tax. companies with an uncertain environmental policy and unclear plans for its implementation will lose out against their competitors, as evidenced by various indices, both russian and international, which determine the level of environmental friendliness of a particular corporation and product. an increase in the level of environmental friendliness is achieved through the implementation of so-called “green” projects. the decree of the government of the russian federation of september 21, 2021 no. 1587 establishes the criteria for sustainable (including green) development projects and the requirements for the verification system for sustainable (including green) deve lopment projects. such environmental projects should meet the criteria of the national taxonomy of adaptation (or transition) projects. in the world such projects are not recognized as “green” in the full sense of this word, but they are very important for the russian economy, as their goals are related to ghg reduction. green financing provides such financial instruments as debt securities or loans. these funds, however, can be used exclusively for capital expenditures and operating expenses necessary for the implementation of the project and financing the portfolio of sustainable development projects. funds raised through financial instruments can be used both for future projects of an enterprise, and for refinancing and reimbursement of the costs of ongoing projects. active stimulation of metallurgical companies to reduce their emissions, for example, through regional programs, will help regional governments avoid losses in export earnings and regional budget revenues in the future, while complete inaction is fraught with losses, both in the share of export profits and in the domestic market. the russian system of target indicators for reducing ghg emissions by sector is rapidly evolving. the russian legislation also provides for the gradual introduction of carbon reporting: the largest emitters of ghg emissions (more than 150 thousand tons of co 2 at the first stage until 2024) will have to provide mandatory carbon reporting while for other enterprises carbon reporting will be optional. russian regions should take an active part in the development of carbon policy tools. while the regulatory framework for non-financial corporate reporting is still beginning to take 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(2021). decarbonizing china’s power sector by 2030 with consideration of technological progress and cross-regional power transmission. energy policy, 150, number of article: 112150. https://doi.org/10.1016/j.enpol.2021.112150 information about authors irina s. belik – doctor of economics, professor of the department of economic security of industrial complexes, ural federal university (19 mira str., yekaterinburg 620002, russia); e-mail: irinabelik2010@mail.ru natalya v. starodubets – candidate of economic sciences, associate professor of the department of economic security of industrial complexes, ural federal university (19 mira str., yekaterinburg 620002, russia); e-mail: n.v.starodubetc@urfu.ru alena i. yachmeneva – leading economist of the financial and economic block of pjsc rostelecom (134b lunacharskogo str., yekaterinburg 620110, russia); e-mail: alena.yachmenewa@yandex.ru konstantin a. prokopov – student, ural federal university (19 mira str., yekaterinburg 620002, russia); e-mail: prokopovk333@gmail.com article info: received may 29, 2022; accepted september 7, 2022 информация об авторах белик ирина степановна – доктор экономических наук, профессор кафедры «экономическая безопасность производственных комплексов», уральский федеральный университет (россия, 620002, г. екатеринбург, ул. мира, 19); e-mail: irinabelik2010@mail.ru https://doi.org/10.15826/recon.2022.8.3.020 https://doi.org/10.32339/0135-5910-2021-8-902-912 https://doi.org/10.1016/j.apenergy.2021.117209 https://doi.org/tps://doi.org/10.1002/wcc.796 https://doi.org/tps://doi.org/10.1002/wcc.796 https://doi.org/10.1007/s10273-021-2982-6 https://doi.org/10.1007/s10273-021-2982-6 https://doi.org/10.48137/2687-0703_2021_15_3_84 https://doi.org/10.48137/2687-0703_2021_15_3_84 https://doi.org/10.1016/j.jclepro.2021.128623 https://www.ey.com/ru_ru/tax/tax-alert/2021/07/ey-mehanizm-transgranichnogo-uglerodnogo-regulirovani https://www.ey.com/ru_ru/tax/tax-alert/2021/07/ey-mehanizm-transgranichnogo-uglerodnogo-regulirovani https://doi.org/10.1038/d41586-021-00736-2 https://doi.org/10.1016/j.enpol.2021.112150 r-economy, 2022, 8(3), 252–267 doi: 10.15826/recon.2022.8.3.020 267 r-economy.com online issn 2412-0731 стародубец наталья владимировна – кандидат экономических наук, доцент кафедры «экономическая безопасность производственных комплексов», уральский федеральный университет (россия, 620002, г. екатеринбург, ул. мира, 19); e-mail: n.v.starodubetc@urfu.ru ячменева алена игоревна – ведущий экономист финансово-экономического блока пао ростелеком (россия, 620110, г. екатеринбург, ул. луначарского, 134б); e-mail: alena. yachmenewa@yandex.ru прокопов константин алексеевич – студент, уральский федеральный университет (россия, 620002, г. екатеринбург, ул. мира, 19); e-mail: prokopovk333@gmail.com информация о статье: дата поступления 29 мая 2022 г.; дата принятия к печати 7 сентября 2022 г. 作者信息 别利克·伊琳娜·斯捷潘诺夫娜 —— 经济系全博士，教授，生产经济安全系教授，乌拉 尔联邦大学（俄罗斯，邮编：620002，叶卡捷琳堡市，米拉大街19号）；邮箱：irinabelik2010@mail.ru 斯塔罗杜贝茨·纳塔利娅·弗拉基米洛夫娜 —— 经济学博士，副教授，生产经济安全系 副教授，乌拉尔联邦大学（俄罗斯，邮编：620002，叶卡捷琳堡市，米拉大街19号）； 邮箱：n.v.starodubetc@urfu.ru 亚赫梅内娃·阿莱娜·伊戈列夫娜 —— 俄罗斯电信公司财经部首席经济师（俄罗斯，邮 编：620110，叶卡捷琳堡市，卢纳察尔斯基街134б街）；邮箱：alena.yachmenewa@ yandex.ru 普罗科波夫·康斯坦丁·阿列克谢耶维奇 —— 本科学生，乌拉尔联邦大学（俄罗斯，邮 编：620002，叶卡捷琳堡市，米拉大街19号）；邮箱：prokopovk333@gmail.com https://doi.org/10.15826/recon.2022.8.3.020 mailto:alena.yachmenewa@yandex.ru mailto:alena.yachmenewa@yandex.ru mailto:prokopovk333@gmail.com mailto:irinabelik2010@mail.ru mailto:irinabelik2010@mail.ru mailto:n.v.starodubetc@urfu.ru mailto:alena.yachmenewa@yandex.ru mailto:alena.yachmenewa@yandex.ru mailto:prokopovk333@gmail.com r-economy, 2022, 8(3), 237–251 doi: 10.15826/recon.2022.8.3.019 237 r-economy.com online issn 2412-0731 original paper © bozhko, l.l., 2022 doi 10.15826/recon.2022.8.3.019 udc 3.339.545 jel f63, e65, l53 challenges of anti-russia sanctions for metals and mining enterprises in kazakhstan l.l. bozhko  rudny industrial institute, rudny, kazakhstan;  bogkoll@rii.kz, bozhkoll70@gmail.com abstract relevance. the new challenges for kazakhstan’s economy have emerged in the aftermath of current geopolitical tensions, especially after kazakhstani businesses have found themselves under the threat of the us and eu secondary sanctions. the industries of the export-oriented metals and mining sector were hit the hardest. kazakhstani enterprises in their attempts to navigate the sometimes contradictory trends in world trade responded in a variety of ambivalent ways. this situation clearly requires more research. while the lack of large data volumes makes qualitative diagnostics and scenario-based forecasting extremely difficult, the proposed approach may prove to be a viable solution. research objective. this study aims to identify and describe the main models of behaviour demonstrated by kazakhstani companies that seek to manage the risk of secondary sanctions and mitigate their export losses. data and methods. to study the responses of kazakhstani companies to the risk of secondary sanctions, the case study method was used, which provides us with a broader view on the companies of different sizes and territorial presence. the cases are then systematized to identify the key types of corporate responses to se condary sanctions. the study relies on the observations and data gathered from the documentations of kazakhstani companies, media publications, reviews, the list of items prohibited for export and import in russia and the republic of belarus pursuant to sanctions, and the normative legal acts of the republic of kazakhstan. results. the study has brought to light the models of behaviour demonstrated by large enterprises and junior companies in kazakhstan’s metals and mining industry. seeking to minimize the risk of secondary sanctions, kazakhstani enterprises choose different behaviour models. a comprehensive in-depth content-analysis has revealed the basic trends in the development of kazakhstan’s metals and mining sector. conclusions. the analysis of the resulting portfolio of cases has shown diffe rences in the responses of large companies affiliated with tncs and small and medium-sized juniors. the study also brought to light the sanctions’ negative impact on the development of kazakhstan’s economy. keywords sanctions, metals and mining sector, restrictions, companies, new challenges, target markets, exports, state regulation, secondary sanctions for citation bozhko, l.l. (2022). challenges of anti-russia sanctions for metals and mining enterprises in kazakhstan. r-economy, 8(3), 237–251. doi: 10.15826/recon.2022.8.3.019 проблемы антироссийских санкций в отношении металлургических и горнодобывающих предприятий казахстана л.л. божко  рудненский индустриальный институт, рудный, казахстан;  bogkoll@rii.kz, bozhkoll70@gmail.com аннотация актуальность. новые вызовы для казахстанской экономики возникли в связи с текущей геополитической напряженностью, особенно после того, как казахстанский бизнес оказался под угрозой вторичных санкций сша и ес. больше всего пострадали отрасли экспортоориентированной металлургии и горнодобывающего сектора. в этих условиях казахстанские предприятия демонстрируют высокую степень неопределённости, пытаясь учесть разнонаправленную динамику мировых товарных рынков. эта ситуация явно требует дополнительных исследований. хотя отсутствие больших объемов данных делает качественную диагностику и прогнозирование на основе сценариев чрезвычайно сложными, предлагаемый подход может оказаться жизнеспособным решением. ключевые слова санкции, горно-металлургическая отрасль, ограничения, компании, новые вызовы, рынки сбыта, экспорт, государственное регулирование, вторичные санкции https://doi.org/10.15826/recon.2022.8.3.019 https://doi.org/10.15826/recon.2022.8.3.019 https://e.mail.ru/compose/?mailto=mailto%3abogkoll@rii.kz https://e.mail.ru/compose/?mailto=mailto%3abozhkoll70@gmail.com https://e.mail.ru/compose/?mailto=mailto%3abogkoll@rii.kz https://e.mail.ru/compose/?mailto=mailto%3abozhkoll70@gmail.com 238 r-economy.com r-economy, 2022, 8(3), 237–251 doi: 10.15826/recon.2022.8.3.019 online issn 2412-0731 introduction for businesses in kazakhstan, especially for those that have long-standing commercial ties with russia, one of the major concerns now is to avoid the risk of falling under the eu or us secondary sanctions. to avoid any potential penalties, companies opt for overcompliance, that is, take more extensive actions than strictly necessary, including severing financial and economic ties with their trade partners from the sanctioned country. the current situation is fraught with other political risks for kazakhstan. these risks, however, are minimized by the ongoing moderni zation reforms of the country’s political system. as a result of the republican referendum on constitutional amendments held in june 2022, цель исследования. данное исследование направлено на выявление и  описание основных моделей поведения казахстанских компаний, стремящихся управлять рисками вторичных санкций и минимизировать свои экспортные потери. данные и методы. для изучения реакции казахстанских компаний на риск вторичных санкций был использован метод кейс-стади, который дает нам более широкое представление о компаниях разного размера и территориального присутствия. затем кейсы систематизируются для выявления основных типов реакции корпораций на вторичные санкции. исследование опирается на наблюдения, документы казахстанских компании, статьи в прессе, обзоры, а также сервис проверки санкционных товаров, запрещённых для экспорта и импорта в россию и беларусь, нпа республики казахстан. результаты. в ходе исследования выявлены модели поведения крупных предприятий и молодых компаний горно-металлургической отрасли казахстана. стремясь минимизировать риск вторичных санкций, казахстанские предприятия выбирают разные модели поведения. комплексный глубокий контент-анализ позволил выявить основные тенденции развития горно-металлургического комплекса казахстана. выводы. анализ полученного портфеля кейсов показал различия в реакциях крупного бизнеса и юниорских компаний гмо. исследование также выявило негативное влияние санкций на развитие экономики казахстана. для цитирования bozhko, l.l. (2022). challenges of anti-russia sanctions for metals and mining enterprises in kazakhstan. r-economy, 8(3), 237–251. doi: 10.15826/recon.2022.8.3.019 哈萨克斯坦冶金与采矿公司的反制裁问题 博日科  鲁德尼工业学院，哈萨克斯坦； bogkoll@rii.kz, bozhkoll70@gmail.com 摘要 现实性：当前的地缘政治紧张局势给哈萨克斯坦经济带来了新的挑战，尤 其是在哈萨克斯坦企业受到美国和欧盟二次制裁的威胁之后。以出口为导 向的冶金和采矿业受到的冲击最大。在这种环境下，哈萨克斯坦企业表现 出高度的不确定性，并试图考虑到全球商品市场的多向动态。这种情况显 然需要进一步研究。尽管缺乏大量的数据使得高质量诊断和情景预测极其 困难，但文章所提出的方法可能被证明是一种可行的解决方案。 研究目标：本研究旨在识别和描述哈萨克公司寻求管理二级制裁风险和 尽量减少出口损失的主要行为模式。 数据和方法：为了研究哈萨克斯坦公司对二级制裁风险的反应，文章使 用了案例研究方法，这让我们对不同地域和规模的公司有了更广泛的了 解。然后这些案例被系统化，以确定公司对二级制裁的主要反应类型。 该研究基于观察法，哈萨克斯坦公司文件、新闻报道、调查，俄罗斯和 白俄罗斯出口与进口的制裁货物名单，以及哈萨克斯坦共和国的国家行 动计划都为文章提供了研究基础。 研究结果：该研究揭示了哈萨克斯坦采矿和冶金行业的大型企业和年轻 公司的行为模式。为了尽量减少二次制裁的风险，哈萨克斯坦企业选择 了不同的行为模式。 通过全面深入的内容分析，可以确定哈萨克斯坦采 矿和冶金综合体发展的主要趋势。 结论：案例组合的分析表明，大型企业和初级中小企业的反应存在差 异。该研究还揭示了制裁对哈萨克斯坦经济发展的负面影响。 关键词 制裁、采矿和金属、限制、公 司、新挑战、销售市场、出 口、政府监管、二次制裁 致謝 bozhko, l.l. (2022). challenges of anti-russia sanctions for metals and mining enterprises in kazakhstan. r-economy, 8(3), 237–251. doi: 10.15826/recon.2022.8.3.019 https://doi.org/10.15826/recon.2022.8.3.019 https://e.mail.ru/compose/?mailto=mailto%3abogkoll@rii.kz https://e.mail.ru/compose/?mailto=mailto%3abozhkoll70@gmail.com r-economy, 2022, 8(3), 237–251 doi: 10.15826/recon.2022.8.3.019 239 r-economy.com online issn 2412-0731 56 amendments to 33 articles of the constitution were approved. the changes to the constitution signal that the transition from the super-presidential model to the presidential republic will be finally completed. the amendments also signify the devolution of powers to the regional or local level; increased political participation; revision of the role and status of the parliament; modernization of electoral law and electoral process; and strengthening of the mechanisms for protecting the constitutional rights of citizens. the amendments provide for the reorganization of the constitutional court.  the president is prohibited from having an affiliation with any political party during his or her tenure; his or her relatives are prohibited from holding government and quasi-government positions. the amendments are intended to stimulate the decentralization of powers by making akimats and maslikhats more politically and economically independent from the head of state and central government. the constitutional amendments mean the creation of the second republic and are expected to pave the way for a radical change of the entire paradigm of national development, which was announced by kassym-jomart tokaev at the celebration of the 30th anniversary of kazakhstan’s police1. the constitutional amendments in fact transform the relationship between the government and citizens of kazakhstan and introduce signi ficant adjustments to the legislative process. in the nearest future, the laws will be adopted on the level of the mazhilis (the lower house of the parliament) and then passed over to the senate (the upper house), which can either approve or reject them. in general, this practice corresponds to the international standards. there is reason to hope that the above-described liberalization reforms will significantly reduce the risk of social and political unrest in the country. the level of uncertainty in the country is much higher regarding the effects of the sanctions. a proactive approach is needed in order to manage this situation effectively. historically, exports of oil and metals provided over 80% of the country’s hard-currency income. in his interview to tv channel “rossiya 24”, the president of kazakhstan kassym-jomart tokayev said: “sanctions are sanctions, they should not be violated, 1 official web-site of the president of the republic of kazakhstan. https://www.akorda.kz/ru/prezident-prinyal-uchastie-v-torzhestvennom-meropriyatii-po-sluchayu-30-letiya-kazahstanskoy-policii-235228 (accessed: 01.07.2022) particularly because we are getting warnings that any attempt to bust the sanctions will lead to the so-called secondary sanctions from the west targeting our economy”2. kazakhstan already faced eu restrictions following a lengthy dispute with moldovan entrepreneur anatolie stati. as a result, assets of the kazakhstan national fund and shares of kmg b.v.  kashagan were frozen in the west, which led to a shrinkage of liquid assets of kazakhstan’s government and the country’s gdp growth fell from 45% in 2016 to 22% in 2017. moreover, this situation also negatively affected the country’s oil sector3. secondary sanctions are measures administered or enforced against legal entities engaging in commercial activity involving a party under primary sanctions. the application of sanctions by the us government is regulated by the countering america’s adversaries through sanctions act (caatsa), which came into force in 2018. according to this law, non-us persons (foreign persons and foreign financial institutions) may be subject to sanctions if they engage in the dealings with russian legal and physical persons targeted by the primary sanctions. while being subject to penalties is unlikely to severely destabilize the economy of kazakhstan, the secondary sanctions may have serious implications for certain companies and projects. faced with the risk of doing business with russia, companies demonstrate a variety of behaviours and strategies: they have to halt their business with their long-term partners, rebuild their supply and logistics chains, and search for new markets for their products. thus, the main focus of this study is on the ways kazakhstani enterprises are dealing with the situation at hand, in particular the models of behaviour these companies adopt under the threat of secondary sanctions and the key factors that dominate their decision-making. this aim determines the following research objectives: – to analyze the trade structure of kazakhstan-russia exports and imports in the period prior to the introduction of sanctions; 2 tadtaev g. (2022). tokaev has promised to comply with the western sanctions against russia. https://www. rbc.ru/politics/15/06/2022/62a9badd9a79473847ccadb6?ysclid=l4pynyfi2512114905 (accessed: 04.07.2022) 3 ishekenova b. (2018). kazakhstan vs. stati: a billion-dollar dispute. https://lsm.kz/stati (accessed: 01.07.2022) https://doi.org/10.15826/recon.2022.8.3.019 https://www.akorda.kz/ru/prezident-prinyal-uchastie-v-torzhestvennom-meropriyatii-po-sluchayu-30-let https://www.akorda.kz/ru/prezident-prinyal-uchastie-v-torzhestvennom-meropriyatii-po-sluchayu-30-let https://www.akorda.kz/ru/prezident-prinyal-uchastie-v-torzhestvennom-meropriyatii-po-sluchayu-30-let https://www.rbc.ru/politics/15/06/2022/62a9badd9a79473847ccadb6?ysclid=l4pynyfi2512114905 https://www.rbc.ru/politics/15/06/2022/62a9badd9a79473847ccadb6?ysclid=l4pynyfi2512114905 https://www.rbc.ru/politics/15/06/2022/62a9badd9a79473847ccadb6?ysclid=l4pynyfi2512114905 https://lsm.kz/stati 240 r-economy.com r-economy, 2022, 8(3), 237–251 doi: 10.15826/recon.2022.8.3.019 online issn 2412-0731 – to identify the role played by the state in the development of one of the key export-oriented segments in kazakhstan’s economy; – to construct a portfolio of cases of kazakhstani enterprises and conduct content-analysis of their models of behaviour when faced with the risk of secondary sanctions. theoretical framework in the contemporary research literature, the effects of sanctions are discussed from different viewpoints and angles. a group of scholars (bapat & kwon, 2009; drezner, 2003; drury, 1998; morgan & schwebach, 1997; whang and kim, 2015) subscribe to the view that by inflicting pain on the people of the target country, sanctions could foment popular anger against the country’s lea dership and thus pressure them into changing the state policy and make them more willing to negotiate meaningful concessions. alfred-maurice de zayas (2022), kramarenko (2022), and kortunova (2022) discuss the “collateral damage” of sanctions and financial blockades. a view shared by a number of scholars (bapatetal, 2013; cox & drury, 2006; jeong & peksen, 2019; lektzian & souva, 2003) is that the effectiveness of sanctions correlates with the level of democratic development in a target country. in other words, in comparison with an authoritarian state, a mature democracy is much more capable of minimizing the negative impact of sanctions. democratic leaders are more interested in mobilizing a larger amount of resources during the sanction episode as they are aware of the fact that exogeneous shocks negatively affect the level of trust citizens have in their leaders, resulting in the latter’s electoral defeat (bueno de mesquita, 1999). peterson (2013) examined how sanction threats affected the sender’s reputation by looking at us sanction threats spanning 1971–2000 and concluded that “the target is less likely to acquiesce when the united states recently backed down from a sanction threat”. bapat and kwon (2015) demonstrated that imposing sanctions creates a strategic dilemma for sanctioning states because the restrictions on the economic transactions with targeted states may undermine their companies’ competitiveness. bapat and kwon’s model indicates that sanctions are more likely to succeed when the sender’s firm retains a moderate share of the target’s market relative to its foreign competitors. the model also demonstrates, however, that sanctions are likely to be imposed only when the conditions do not favor their success. ang and peksen (2007), drury and li (2006), li and drury (2004), morgan et al. (2014) discuss a broad spectre of questions regarding the effectiveness of economic sanctions and their role in overcoming major foreign-policy crises. shokhin (2022) offers a somewhat different perspective on the topic: he explores the possibility that sanctions will stimulate import substitution and technolo gical development of the targeted country. jin mun jeong (2019) proposes a typology of sanctions based on the effects that different types of sanctions have on the duration of sanction episodes. morgan, bapat, and kobayashi (2014) believe that multilateral economic sanctions are more effective than unilateral as they have a potential to produce a broader spectrum of effects. gress (2018), travnickova et al. (2015) focus on sanctions in the form of nontariff barriers to trade operations, their impact on exports and imports and the specifics of secondary sanctions. morozov (2021) considers other sanctions regimes and secondary sanctions by looking at the cases of princeton university, american company bitpay, inc. and american animal health company zoetis (new jersey). voinikov (2022) discusses the political and legal aspects of the possible eu visa sanctions against russian citizens with an emphasis on targeted measures. an earlier study by kazakhstani scholars analyzes the impact of sanctions on the integration processes within the eurasian economic union, the possible threats to the import/export transactions between the member states, scenarios of further development of the union’s foreign trade with eu countries, and russia’s countersanctions (khitakhunov et al, 2016). sukharev and voronchikhina (2021) demonstrate the differences between the national models of economic growth by analyzing the eaeu members’ responses to the crises of 2009 and 2015, arguing that these differences are largely determined by the specific economic policies the countries adopt. aituar (2022) makes a special emphasis on the impact of anti-russia sanctions on kazakhstan’s economy. as this literature review shows, there is a considerable body of research dealing with the economic aspect of sanctions, especially their effect on countries' economic development. despite the vast body of research on sanctions and their effects, little is written about secondary sanctions and on companies' responses. other perceived https://doi.org/10.15826/recon.2022.8.3.019 https://www.tandfonline.com/doi/full/10.1080/03050629.2021.1860034?src=recsys https://www.tandfonline.com/doi/full/10.1080/03050629.2021.1860034?src=recsys https://www.tandfonline.com/doi/full/10.1080/03050629.2021.1860034?src=recsys https://www.tandfonline.com/doi/full/10.1080/03050629.2021.1860034?src=recsys https://www.tandfonline.com/doi/full/10.1080/03050629.2021.1860034?src=recsys https://www.tandfonline.com/doi/full/10.1080/03050629.2021.1860034?src=recsys https://www.tandfonline.com/doi/full/10.1080/03050629.2021.1860034?src=recsys https://www.webofscience.com/wos/author/record/2430256 https://link.springer.com/article/10.1007/s10644-016-9182-1#auth-azimzhan-khitakhunov r-economy, 2022, 8(3), 237–251 doi: 10.15826/recon.2022.8.3.019 241 r-economy.com online issn 2412-0731 research gaps are the development of specific industry segments under sanctions pressure and the impact of sanctions on kazakhstan's economy. the lack of large data volumes impedes empirical research and creates difficulties for scenario-based forecasting of national economic development. the threat of secondary sanctions and the divergent dynamics of the world trade markets complicate the picture even more. data and methods in recent years, the case study method has become an increasingly popular tool among qualitative researchers, especially in studies dealing with complex organizational problems. one of the advantages of this method is that it can generate an in-depth, multi-faceted understanding of the processes or phenomena of interest. the case study method is defined as a method of empirical inquiry into contemporary phenomena in their real-life setting in situations where the boundaries between the phenomenon and context are blurred and where multiple sources of evidence are employed (khachatryan, 2018). the case study method allows for detailed analysis of the chronology, causes and consequences of events. moreover, this approach encourages researchers to develop or reconsider their initial conceptual framework, enabling them to come to robust conclusions in the end (miles & matthew, 2014). this research uses the case study method to examine the responses of kazakhstani companies to the risk of secondary sanctions. the choice of this method was determined by the following: – the complexity of the problem in question, which requires a comprehensive and in-depth content analysis; – a wide range of behaviours of companies of different sizes and territorial scope, which need to be analyzed and systematized; – the need to gain a better understanding of the strategies and behaviour models of kazakhstani enterprises in the absence of large quantitative data sets. it should be noted that by its nature, the case study method is not linear, meaning that unlike the methodology where the chosen tools and data collection protocols remain unchanged, it implies an iterative research procedure where data collection is performed simultaneously with analysis and adjustment of the following stages. the study was conducted in the following three logically related stages: at the first stage, the focus was made on the trade structure of kazakhstan-russia imports and exports in the period prior to the adoption of economic sanctions; at the second stage, the emphasis was made on the role of the state in the development of the mining sector; at the third stage, a portfolio of cases was constructed reflecting the responses of kazakhstani enterprises to the sanctions. the sources of data are observations, documents of kazakhstani companies, media publications, and reviews. the study relies on the official data of the bureau of national statistics of the agency for strategic planning and reforms of the republic of kazakhstan; list of items prohibited for export and import in russia and the republic of belarus pursuant to sanctions; legal acts of the republic of kazakhstan regulating industrial development; and policy documents issued by the national and regional governments of kazakhstan. research polygon as a polygon for this study, transnational corporations (tncs) and juniors companies in the metals and mining sector of kazakhstan were chosen. the choice of enterprises in this segment was determined by the following considerations: first, the metals and mining sector ranks second in kazakhstan’s economy in terms of production volume and the number of enterprises. the total reserves of iron ore exceed 35 billion tons; 29.2 billion tons are in the state balance sheet, including 17.1 billion tons of ore in а + в + с1 + с2 categories. in the cis, kazakhstan ranks third after russia and ukraine in terms of the amount of iron ore reserves4; second, the metals and mining industry is highly vulnerable to the fluctuations of the global financial and trade markets: in the first quarter of 2022, the manufacturing and extractive industry demonstrated a 6.5 and 6.1% growth respectively, but in the second quarter the indicators in both industries went down. the world steel association forecast that in 2021 the steel demand would grow by 2.7% and in 2022, by only 0.4%5; 4 nurbek s. (2021). atlas of emerging jobs and competencies in kazakhstan: metals and mining sector. https:// www.kazenergy.com/upload/document/atlas/gmk_ru.pdf (accessed: 06.07.2022) 5 distorted world. russian and world steel markets: 26 june – 3 july 2022. https://www.metalinfo.ru/ru/news/138446 (accessed: 07.07.2022) https://doi.org/10.15826/recon.2022.8.3.019 https://www.kazenergy.com/upload/document/atlas/gmk_ru.pdf https://www.kazenergy.com/upload/document/atlas/gmk_ru.pdf ttps://www.metalinfo.ru/ru/news/138446 242 r-economy.com r-economy, 2022, 8(3), 237–251 doi: 10.15826/recon.2022.8.3.019 online issn 2412-0731 third, the metals and mining industry has strong traditions but also suffers from considerable inertia. moreover, companies in this segment need to keep up with the latest technology trends due to the high level of competition on the international level; fourth, large mining and metallurgical enterprises of kazakhstan are mostly located in monotowns and have a huge impact on the socio-economic development of these territories. a  drop in production, curtailed operations or shutdowns of these businesses will exacerbate regional disparities, which present a serious problem for the development of kazakhstan’s economy (kireyeva et al., 2022); fifth, the development of this sector is subject to state regulation. kazakhstan has been quite successful in attracting foreign investment to its extractive industries, especially large-scale oil extraction projects and basic processing of raw materials. direct foreign investment to kazakhstan is much higher in comparison with other countries with a similar economic structure. it should, however, be noted that over 40% of investment is concentrated in the extractives sector6. transnational corporations tncs make an excellent polygon for research because such companies usually have a  long history and a wide network of branches and subsidiaries, which means that they have already accumulated a large amount of data re6 macroeconomic overview. of kazakhstan, june 2022. https://www.aerc.org.kz (accessed: 05.07.2022) sulting from multiyear observations. being international in terms of their policies and vision, a tnc can pursue coordinated policies and realize general strategies through its single center for strategic decision-making. what makes tncs particularly worthy of interest is that their capital movement is relatively independent from what is happening within the national boundaries. tncs’ long-standing presence in kazakhstan makes them major players in the country’s economy. one of such companies is eurasian resources group (erg), a leading diversified natural resources producer. in its current form, erg was established in 2013 after it acquired the eurasian natural resources corporation, which was de listed from the london stock exchange and kazakhstan stock exchange. erg is operating across 15  countries of the world on 4 continents. the company’s product portfolio comprises such divisions as ferroalloys, iron ore, alumina and aluminium, other non-ferrous metals, energy, and logistics. the company’s production indicators demonstrate its strong operational performance. in 2020, despite the pandemic, the company managed to prevent a significant decline in its operational efficiency and enhanced its production potential in the majority of divisions (table 1). in 2020, standard & poor’s global ratings raised its corporate credit ratings on erg to “b-/b” level while the outlook was stable, which demonstrated the company’s improved financial performance and stability. table 1 dynamics of erg’s key production indicators in 2019–2020 key host countries divisions production volumes, ths tons name specialization 2019 2020 relative deviation, % kazakhstan ferroalloys ferroalloys 1 639 1 653 100.8 kazakhstan, brazil iron ore iron ore concentrate and pellets 13 195 13 114 99.3 kazakhstan alumina and alu-minium alumina 1 393 1 383 99.2 alumunium 263 265 100.7 democratic republic of congo (drc), zambia other non-ferrous metals metallic copper 59 80 136 copper concentrate 83 103 124 cobalt metal 1.5 0.1 6.7 cobalt hydroxide 7 17 2.5 times kazakhstan energy coal 27 503 28 871 102.8 energy production, gwh 14 460 14 793 102.3 kazakhstan logistics volume of freight, ths tons 53 836 53 076 98.6 source: compiled by the author by using the data from: ensuring sustainable development in a difficult time. eurasian resources group s.à r.l.: sustainable development report 2020. https://www.erg.kz/ru/news/2344 (accessed: 05.07.2022) https://doi.org/10.15826/recon.2022.8.3.019 https://www.aerc.org.kz https://www.erg.kz/ru/news/2344 r-economy, 2022, 8(3), 237–251 doi: 10.15826/recon.2022.8.3.019 243 r-economy.com online issn 2412-0731 another tnc of interest to this study is arcelormittal, which was formed in 2006 from the merger of luxembourg company arcelor and mittal steel owned by indian businessman lakshmi mittal. the company’s headquarters are in luxembourg. the group’s structure comprises 6 operation segments: flat carbon americas, flat carbon europe, long carbon americas and europe, asia, africa and cis (aacis), distribution solutions, and mining. each enterprise belongs to one of these segments. the company operates on four continents, covers all of the key steel markets, from emerging to mature. about 35% of steel is produced in america; 47%, in europe; and 18% in other regions, including kazakhstan, south africa and ukraine7. the company’s iron ore mining operations are located in the united states, canada, mexico, brazil, liberia, bosnia, ukraine and kazakhstan. the company is now also developing mining projects in australia, mauritania, mozambique, senegal, and south africa. in 2020, due to the covid-19 pandemic restrictions, steel production declined in all of the company’s divisions (see table 2). table 2 dynamics of arcelormittal’s key performance indicators key host countries steel production, ths tons 2019 2020 relative deviation, % north america 21897 17813 81.3 brazil 11001 9539 86.7 europe 43913 34003 77.4 cis and africa 12997 10172 78.3 source: compiled by the author by using the data from: 2020 annual financial report of arcelor mittal group. https://bf.arsagera.ru/arcelormittal_mt/itogi_2020_g/?ysclid=l574ch9s7235975622 (accessed: 06.07.2022) junior companies kazakhstan holds much promise for businesses operating in the sphere of subsurface and mineral resources use, metal manufacturing and high-value manufacturing. junior companies or simply juniors are commonly understood as companies engaging in early stage exploration projects (small companies and start-ups). over 50 to 65% of all the new deposits in the world were discovered and explored by junior companies. modern juniors can be rough7 blogoforum. fundamental analytics (2021). https://bf.arsagera.ru/arcelormittal_mt/itogi_2020_g/?ysclid=l574ch9s7235975622 (accessed: 06.07.2022) ly divided into three main groups depending on the stages of the mining project – exploration, development, and production. each stage is determined by the yield-risk balance of the project. it should be noted that an important trend in the non-ferrous metals industry is that enterprises plan their manufacturing and marketing activities in coordination with their clients. these enterprises supply not only materials but also the appropriately sized products tailored to the needs of specific clients, which makes the establishment and maintenance of close relationships with clients is one of the priorities in the creation of junior companies. the strategy for the developing of the mining industry in the republic of kazakhstan until 2030 explains that one of the main conditions for economic stabilization and growth is active pursuit of foreign capital, increase in the number of juniors for geological exploration, and creation of new enterprises and ‘small metallurgy’ (the production of metal products at machine-building enterprises (non-ferrous, precious, rare and rare earth metals)). results and discussion 1. kazakhstan-russia exports and imports in the pre-sanction period quite obviously, in their export and import transactions, russia and kazakhstan pursued their own goals determined by the national and regional agenda. each country, however, had its own priorities and interests: for example, while the russian side was predominantly interested in kazakhstan’s raw materials, kazakhstan was in need of modern technologies, machinery and equipment. as table 3 illustrates, in the pre-sanction period, the structure of russia’s imports from  kazakhstan was dominated by mineral products, metals and metal products (51.7%), chemicals (12.8%), and energy products (9.3%). russia was one of the main markets for kazakhstan’s metals & mining industry. external demand was mainly oriented towards low added-value production due to the exporter’s need to ensure stable development of its own metals and mining sector and related industries. kazakhstani enterprises and organizations bought products made of ferrous and non-ferrous metals, reactors, atomic piles, equipment and machinery, polymers, metal structures, rail https://doi.org/10.15826/recon.2022.8.3.019 https://bf.arsagera.ru/arcelormittal_mt/itogi_2020_g/?ysclid=l574ch9s7235975622 https://bf.arsagera.ru/arcelormittal_mt/itogi_2020_g/?ysclid=l574ch9s7235975622 https://bf.arsagera.ru/arcelormittal_mt/itogi_2020_g/?ysclid=l574ch9s7235975622 https://bf.arsagera.ru/arcelormittal_mt/itogi_2020_g/?ysclid=l574ch9s7235975622 244 r-economy.com r-economy, 2022, 8(3), 237–251 doi: 10.15826/recon.2022.8.3.019 online issn 2412-0731 locomotives and land transport vehicles. in some product categories, the imports were dominated by the equipment imported by the russian investors to develop mineral deposits, including the caspian shelf. the analysis of the composition and structure of imports show that industrial and consumer goods are represented in equal measure. unfortunately, technological equipment and manufacturing machinery remain somewhat underrepresented. it should be noted that in kazakhstan, russian companies have been mainly competing with asian and american manufacturers. in the pharmaceuticals market, russia’s main rival is india; in the car market, japan, korea, the usa, and china; in the confectionery market, turkey. specific market segments more and more get dominated by china and korea. many markets see the growing presence of chinese manufacturers offering quality products at a reasonable price. analysis of kazakhstan’s imports has shown the country’s vast potential in the creation of joint ventures. this is especially true of ferrous metals production, manufacturing of metal structures, plastics, and chemicals. the economic sanctions against russia, however, brought significant changes to the structure of imports/exports between the two countries. kazakhstani enterprises responded to the challenge differently. table 3 commodity structure of kazakhstan-russia exports and imports prior to the imposition of economic sanctions goods exported by kazakhstan share in total exports, % goods imported by kazakhstan share in total imports, % ores, concentrates, and metals: iron ore, chrome ore, manganese ore, zinc ore, precious metals, rolled metal, alumina, zinc 51.7 products made of ferrous and non-ferrous metals, ferrous metals, metal structures 14.3 mineral fuel, oil and products of their distillation 9.3 ores, slag and ash 12.0 cement and lime 2.1 reactors, atomic piles, equipment and ma-chinery 9.7 inorganic chemicals, organic chemical compounds 12.8 organic chemical compounds, inorganic chemicals 1.9 vehicles 1.0 electrical machinery, tools and optical equip-ment 7.2 rail locomotives and associated transport equipment 2.0 rail locomotives and land transport vehicles 8.4 agricultural products and food 5.0 aircraft and spacecraft 1.3 cotton 0.2 textiles, footwear and leather goods 4.0 pharmaceutical products 0.9 pharmaceutical products 1.2 fertilizers 0.4 fertilizers 0.8 plastics and plastic products 1.2 polymers and polymer products 4.4 other 13.4 wood, wooden products and furniture 3.3 rubber and rubber products 1.9 ceramic products 1.0 pulp and paper 2.1 glass and glassware 0.8 tobacco and tobacco substitutes 1.4 grains and grain products 2.0 alcoholic and non-alcoholic beverages 1.0 sugar, sugar confectionery, and other sugar preparations 1.3 other food products 7.5 soap and detergents 1.5 other 11 source: compiled by the author by using the data from: international trade of the republic of kazakhstan. statistical yearbook. 277 p. (in kazakh and russian). https://stat.gov.kz/edition/publication/collection (accessed: 01.07.2022) https://doi.org/10.15826/recon.2022.8.3.019 https://stat.gov.kz/edition/publication/collection r-economy, 2022, 8(3), 237–251 doi: 10.15826/recon.2022.8.3.019 245 r-economy.com online issn 2412-0731 2. the role of the state in the development of the metals and mining sector in kazakhstan taking into account the fact that some companies and industrial sectors struggle to manage their risks under the threat of secondary sanctions, they should be provided with sufficient risk management advice and assistance. in this situation, the state needs to coordinate companies’ efforts to adapt to the new reality and avoid being hit by secondary sanctions. the go vernment, business and expert communities need to work together to devise specific measures that could help companies overcome the negative consequences of the sanctions imposed by the usa, uk, eu and other parties as well as to minimize the adverse effects of overcompliance. for several years, the metals and mining industry in kazakhstan was subject to state regulation. the national government sought to increase the sector’s competitiveness and create a favou rable legal and business climate. the state program of industrial and innovative development of the republic of kazakhstan for 2010–2014 adopted in february 2010 became the main strategic document in the sphere of economic development for the following five years. the aim of the second stage of industrialization was to stimulate diversification and make the manufacturing sector more competitive. the state program of industrial and innovative development for 2015–2019 set 14 priority sectors with a high potential for development in 6 industries, including ferrous and non-ferrous metallurgy. thus the state signaled to businesses and foreign investors which priority industry niches will be supported in the first place and which thus will hold the most promise. the second program also listed over 100 tools the government was planning to use to support economic activity. the third program for 2020–2025 was largely aimed at ensuring the transition from disparate tools of state support to a single comprehensive system of measures. it also described the reciprocal obligations of industrial enterprises and set for them the task to enter global value chains by attracting foreign investors. the state geological exploration program for 2021–2025 is aimed at ensuring geological exploration of kazakhstan’s territory, replenis hing the mineral resource base, and attracting investors to the industry. it is expected that the development of geological exploration will ge nerate a multiplier effect through the influx of highly skilled workers and technologies and rapid development of service providers. to reduce the geological and operational risks, tau-ken samruk offers comprehensive one-window assistance to exploration-oriented junior companies, which includes financial, expert, and marketing support. to make kazakhstan’s small metallurgy more attractive for investors, astana international financial centre (aifc) organized a special online exchange platform. moreover, the transparency of the procedures that will enable mining companies to enter the aifc stock market was ensured and there were introduced mechanisms for settling disputes between landowners and mining companies in the international arbitration centre or the aifc court. the regulation of the junior market is mostly aimed at ensuring compliance with the international reporting standards and with the feasibility study requirements in the sphere of geological exploration and mining. 3. portfolio of cases of enterprises operating in the metals and mining sector of kazakhstan the following analysis encompasses the cases of the enterprises from kazakhstan’s metals and mining industry by making a special focus on these companies’ strategies to reduce sanctions risk exposure and their corresponding behaviour models. the case of erg is a good illustration of the overcompliance strategy. in kazakhstan, erg has the following manufacturing assets: tnc kazchrome jsc, sokolov-sarybai mining production association (ssgpo) jsc, aluminium of kazakhstan jsc, kazakhstan aluminium smelter jsc, eurasian energy corporation jsc, shubarkol komir jsc, transportation group transcom llp, 3-energoortalyk jsc, and erg service, llp (fig. 1). the sokolov-sarybai mining production association (ssgpo), one of the giants of kazakhstan’s mining industry, specializes on iron ore mining and beneficiation. the facility manufactures over 13,114 thousand tons of iron-ore concentrate and pellets8. the ssgpo’s main clients are russia’s magnitogorsk iron and steel works (mmk), arcelormittal temirtau steelworks, and chinese companies. previously, the company’s strategy provided 8 ensuring sustainable development in a difficult time/ eurasian resources group s.à r.l.: sustainable development report 2020. https://www.erg.kz/ru/news/2344 (accessed: 05.07.2022) https://doi.org/10.15826/recon.2022.8.3.019 https://www.erg.kz/ru/news/2344 246 r-economy.com r-economy, 2022, 8(3), 237–251 doi: 10.15826/recon.2022.8.3.019 online issn 2412-0731 ferroalloys assets: transcom kostanay region pavlodar astana ekibastuz aksu kazakhstan erg’s main assets are located in kazakhstan and their operations rely on the integrated energy and transport infrastructure erg assets in kazakhstan coal/energy logistics alumina and aluminium production: bauxite, alumina, aluminium assets: shubarkol komir, eurasian energy corporation production: coal, semi-coke, electricity assets: donskoy ore-mining and processing plant, aksu and aktobe ferroalloys plants production: fecr, fesi, fesicr, fesimn assets: ssgpo production: iron ore, concentrate and pellets iron ore almaty karaganda region khromtau aktobe rudny figure 1. erg’s assets in kazakhstan source: ensuring sustainable development in a difficult time. eurasian resources group s.à r.l.: sustainable development report 2020. 120 p. https://www.erg.kz/ru/news/2344 (accessed: 05.07.2022) for the possibility to diversify its target markets of iron ore, for example, to enter the iranian and turkish markets. mmk has been the ssgpo’s most long-standing customer, their partnership going back over 70 years, and its manufacturing process heavily relies on the ssgpo’s production. it should be noted that the changing situation in the iron ore market has had a huge impact on this sector. for example, in 2005, in the russian market, iron ore production exceeded demand nearly twofold, which led to a crisis that could bring damage to the production chains. after the russian federation lifted the import duty on iron ore, mkk tried to negotiate a substantial price reduction, by 40% at the minimum. after the request was declined by the ssgpo, the management of the russian plant took decision to stop sourcing from kazakhstan and look for a better deal elsewhere. the alternative suppliers were russian enterprises karelsky okatysh jsc and stoilensky mining and beneficiation plant (sgок), ukrainian enterprises central iron ore enrichment works (cgok) and ferrexpo poltava mining (poltava gok)9. the situation repeated itself in 2008, when the management of mkk informed the ssgpo about 9 metallurgical bulletin (2005). https://www.metalbulletin.ru/publications/1743/ (accessed: 25.06.2022) its intention to cut the amount of ore sourced from the latter, which had a destabilizing effect on the kazakhstani company’s operations. only after the conclusion of a 4-year contract for the supply of more than 30 million tons of iron ore to mkk in 2016, the ssgpo managed to stabilize its exports. on average, the iron ore supplies from kazakhstan met about 70% of mkk’s needs. it was, therefore, a justified decision to introduce a unified customs tariff framework and non-tariff regulation measures, particularly in the light of such factors as supplier-customer geographical proximity (the distance is about 300 km). thus, during the episode of the us sanctions against iran’s metals and mining industry (executive order 13871), the ssgpo managed to ensure a market for its products. in the first half of 2020, china’s imports of iron ore rose to 445.3 million tons, which is 5.1% higher compared with the same period in 2019. china’s mega infrastructure projects and booming construction industry have created a large iron ore demand. in the first half of 2020, iron ore prices on the dalian commodity exchange increased to $89,98/ton (on average by $2,87/ton compared with the same period in 2019)10. 10 china increased iron ore imports from kazakhstan (2022). https://kz.kursiv.media/2020-06-12/kitay-narastil-import-zheleznoy-rudy-iz-kazakhstana/ (accessed: 28.06.2022) https://doi.org/10.15826/recon.2022.8.3.019 https://www.erg.kz/ru/news/2344 https://www.metalbulletin.ru/publications/1743/ https://www.metalbulletin.ru/publications/1743/ https://kz.kursiv.media/2020-06-12/kitay-narastil-import-zheleznoy-rudy-iz-kazakhstana/ https://kz.kursiv.media/2020-06-12/kitay-narastil-import-zheleznoy-rudy-iz-kazakhstana/ r-economy, 2022, 8(3), 237–251 doi: 10.15826/recon.2022.8.3.019 247 r-economy.com online issn 2412-0731 there are, however, significant constraints to iron ore exports from kazakhstan to china caused by the limited capacity of the railways as well as the limited freight traffic capacity of the mountain pass dzungarian gate. in 2021, the supplies from kazakhstan to russian metallurgical enterprises, including mkk, dropped when the pandemic restrictions forced russian car manufacturers to halt their operations, causing a decline in steelmakers’ production. the dipping exports of iron ore to russian metallurgical factories were compensated by the growing exports to chinese manufacturers, which explains the slight decrease in kazakhstan’s exports. in the first half of 2022, after the beginning of russia’s special military operation in ukraine, erg’s management decided to terminate its contracts with mkk to avoid secondary sanctions. in this case, it may be said that erg literally followed the request to suspend “all transactions of a certain type with a specific person, group, sector or country”. thus, since 2005, the ssgpo has repeatedly faced problems with its target markets. the lack of a viable market diversification strategy has impeded the company’s efficient adaptation to the sanctions-induced situation. in light of the fact that the exports to mkk accounted for over 25% of the iron ore that the ssgpo produced while the exports to china are limited by the capacity of railways, the company is now struggling to find alternative markets for its production, which has become a particularly challenging task after the decrease in world steel demand. a high degree of uncertainty due to sanction-induced problems is also faced by companies from the arcelormittal group. arcelormittal ranks second largest ferrous metals company after erg in kazakhstan and owns the following production assets: arcelormittal temirtau steel works, arcelormittal temirtau coal division, iron ore division (llp “orken”), arcelormittal tubular products aktau, power networks llp, “energougol” production division (fig. 2). arcelormittal temirtau steel works’s production capacity is 6–6.5 million tons of steel a year. the factory specializes on manufacturing flat and long steel products, including polymer, aluminium and zinc coated products. arcelormittals’ assets in kazakhstan kostanay region akmola region temirtau karaganda region aktau iron ore division (llp “orken”) likasovsky branch (kostanay region) “orken kentobe” (karaganda region) “orken atasu” (karaganda region) “orken atansor” (akmola region) arcelormittal tubular products aktau specializes in the manufacturing of welded steel pipes for oil and gas industry, water mains, district heating lines, slurry pipelines used in mining industry “energougol” production division specializes in electrical power transmission and distribution to the division’s enterprises and outside consumers on a contractual basis, electrical power network management power networks llp provides electricity in temirtau power generation hub (karaganda region), ensuring uninterrupted power supply to enterprises. comprises 3 substations: “kms”, “zapadnaya”, “yuzhnaya” coal division abayskaya coal mine saranskaya coal mine kazakhstanskaya coal mine shakhtinskaya coal mine tentekskaya coal mine kuzembayeva coal mine lenin coal mine kostenko coal mine ore-processing plant ‘“cwp vostochnaya” auxiliary facilities in karaganda region (cities karaganda, saran, abay, and shakhtinsk) “arcelormittal temirtau” metallurgical complex – coke chemical production; – sinter production; – steelmaking; – rolling production; – uni�ed repair and installation management; – department of the chief power engineer; – transport management figure 2. arcelormittal’s assets in kazakhstan source: compiled by the author based on arcelormittal temirtau: sustainable development report 2020. https://www.arcelormittal.kz/reports/cr/csr_2020.pdf (accessed: 05.07.2022) https://doi.org/10.15826/recon.2022.8.3.019 https://www.arcelormittal.kz/reports/cr/csr_2020.pdf 248 r-economy.com r-economy, 2022, 8(3), 237–251 doi: 10.15826/recon.2022.8.3.019 online issn 2412-0731 previously almost the total volume of the facility’s output (98%) was exported to 65 countries of the world. the main export destinations were china, russia, turkey, the usa, and iran. due to the us sanctions, however, the company suffered lost one of its key markets: arcelormittal halted all trade with iran after president trump issued executive order on may 8, 201911, imposing sanctions on the physical and legal persons operating in iran’s iron and steel industry as well as in aluminium and copper industry. two thirds of all the secondary sanctions imposed by the usa encompassed organizations that had ties with iran. the secondary sanctions included the following: 1) blocking the assets of legal entities from the iranian sector of ferrous metallurgy, alumi nium and copper production; 2) blocking sanctions against third-country persons engaging in or facilitating “significant transactions” involving this sector of the iranian economy as well as physical persons and legal entities exporting iranian iron, steel, copper and aluminium to third-country markets; 3) the imposition of blocking sanctions on physical persons and legal entities providing material and/or technical assistance to identified targets, technology transfer and supply of goods and services to person listed in item 1; 4) sanctions against legal entities directly or indirectly controlled by the sanctioned persons listed in item 112. as a result, arcelormittal completely lost this market and several hundred million dollars of net profit. before that, the annual exports of hot-rolled steel coils from kazakhstan to iran exceeded 1 billion ton. in 2021, arcelormittal temirtau steel works produced 3.4 million tons of steel, out of which 2.6 million was exported (76.5%), including 1.6 million tons (61.5%) of steel exported to russia. hot-rolled steel accounted for over 50% of sales to russia: 60% of products were sold to siberia and russia and 27%, to the central regions and the volga region. after the introduction of 11 morozov v. (2021). overview of international sanction policy (2019, august). https://russiancouncil.ru/analyticsand-comments/columns/sanctions/obzor-mezhdunarodnoysanktsionnoy-politiki-avgust-2019/ (accessed: 11.06.2022) 12 timofeev i., morozov v., sokolshchik y. (2020). sanctions against russia: a look into the year 2020. https:// russiancouncil.ru/activity/publications/sanktsii-protiv-rossiivzglyad-v-2020-g / (accessed: 21.06.2022) the sanctions in may 2022, arcelormittal halted all exports to russia. in june 2022, the company resumed its steel sales to russia at dumping prices. exports of flat products intensified on 10 june 2022. in the second half of june, the company shipped 77 thousand tons of steel, including 50 thousand tons of hot-rolled steel (71%) and 15 thousand tons of coated rolled steel (21%). it is estimated, however, that due to the differences in prices in the russian and world markets, arcelormittal is unlikely to continue its exports to russia because world markets, in the absence of russian production, will become more attractive13. arcelormittal temirtau steel works, which already has some prior negative experience of losing its market in iran under the threat of secondary sanctions, now demonstrates considerable ambivalence in its decision-making. in the current situation, the risks of losing target markets exceed the risks of being subjected to secondary sanctions, which is why the company decided not to halt its supplies to russia altogether. junior companies operating in kazakhstan demonstrate more consistent behaviour strategies in their responses to the anti-russian sanctions. there are over 500 junior companies currently operating in kazakhstan. by experts’ estimates, these companies account for 600 to 800 billion tenge of investment and 10–15 thousand jobs14. central asia metals plс is a junior mining company which in recent years has been rapidly expanding its production. in kazakhstan, central asia metals launched the solvent extraction– electrowinning copper recovery plant in 2012 at the kounrad mine site, 15 km north of the city of balkhash. this facility recovers copper from waste dumps that originated from the kounrad open-pit copper mine. recently not only has the company expanded its production at the kounrad mine but it has also increased its stake in copper bay project in chile from 50% to 75%15. junior company discovery ventures kazakhstan specializes on exploration of gold, copper, 13 zeynullin ye. (2020). arcelormittal rolled to russia. https://www.kommersant.ru/doc/5446717 (accessed: 0.07.2022) 14 nurzhanov g. (2021). junior companies should be supported. https://kapital.kz/economic/99563/galymnurzhanov-yuniorskiye-kompanii-nuzhno-podderzhivat. html (accessed: 21.06.2022) 15 cataloxy (2022). https://dzhezkazganskaya-oblast. cataloxy-kz.ru/firms/balhash/centralasiametals.com.htm (accessed: 6.07.2022) https://doi.org/10.15826/recon.2022.8.3.019 https://russiancouncil.ru/analytics-and-comments/columns/sanctions/obzor-mezhdunarodnoy-sanktsionnoy https://russiancouncil.ru/analytics-and-comments/columns/sanctions/obzor-mezhdunarodnoy-sanktsionnoy https://russiancouncil.ru/analytics-and-comments/columns/sanctions/obzor-mezhdunarodnoy-sanktsionnoy https://russiancouncil.ru/activity/publications/sanktsii-protiv-rossii-vzglyad-v-2020-g / https://russiancouncil.ru/activity/publications/sanktsii-protiv-rossii-vzglyad-v-2020-g / https://russiancouncil.ru/activity/publications/sanktsii-protiv-rossii-vzglyad-v-2020-g / https://www.kommersant.ru/doc/5446717 https://kapital.kz/economic/99563/galym-nurzhanov-yuniorskiye-kompanii-nuzhno-podderzhivat.html https://kapital.kz/economic/99563/galym-nurzhanov-yuniorskiye-kompanii-nuzhno-podderzhivat.html https://kapital.kz/economic/99563/galym-nurzhanov-yuniorskiye-kompanii-nuzhno-podderzhivat.html https://dzhezkazganskaya-oblast.cataloxy-kz.ru/firms/balhash/centralasiametals.com.htm https://dzhezkazganskaya-oblast.cataloxy-kz.ru/firms/balhash/centralasiametals.com.htm r-economy, 2022, 8(3), 237–251 doi: 10.15826/recon.2022.8.3.019 249 r-economy.com online issn 2412-0731 zinc and accompanying metals. it is expected that the minerals exploration project will be completed in 6 years. the total contract area is about 1,500 sq.km.16 mining and processing plant “massalsky gok llp” realizes the project “construction of a mining and metallurgical complex on the basis of massalskoye iron ore deposit in akmola region”. massalskoye deposit is located in zharkain district of akmola region, 16 km east of priishimskaya railway station of yessil-arkalyk railway, in the north-western part of central kazakhstan. the total operational reserves of ore in c1 and c2 categories (included in the state balance sheet by the protocol no. 1327-13-у of 02.09.2013 of the state material reserves committee of the ministry of national economy of the republic of kazakhstan) amount to 729,156,000 tons with an average iron content of 15.82%17. northern katpar llp specializes in combined exploration and production of tungsten-molybdenum ores at northern katpar and upper kairakty fields18. kemin resources limited specializes in exploration and mining of molybdenum, copper, lithium and tungsten at the drozhilovskoye and smirnovskoe deposits in kostanay region. both of these projects hold a large potential for the development of non-ferrous metals industry in kazakhstan19. content-analysis has shown that when dealing with the threat of secondary sanctions, junior companies are more resilient than larger companies. juniors are oriented at the early stages of mining projects (exploration and development) and their main asset is usually the mining license. juniors are not involved in import/export transactions and, therefore, they are more adaptive and can respond more promptly to changes in the market. juniors are more flexible in their decision-making, they have relatively low administra16 kudaybergen k. (2020). tau-ken samruk, jsc in partnership with a junior company start geological exploration in three areas in kazakhstan. https://www.vnedra. ru/novosti/ao-tau-ken-samruk-somestno-s-yuniorskojkompaniej-nachinayut-geologorazvedku-v-treh-oblastyahkazahstana-12392/ (accessed: 08.07.2022) 17 information websitemasalsky mining and processing plant llp. http://mgok.kz/ru/o-kompanii/ (accessed: 03.07.2022) 18 information website of national mining company “tau-ken samruk” jsc. https://tks.kz/subsidiaries/toosevernyj-katpar/ (accessed: 01.07.2022) 19 information website kemin resources limited. https://keminresources.com/about-us/company.html (accessed: 09.07.2022) tion costs, and are able to maximize the efficiency of their small working capital, technologies and human resources. these companies’ resilience can also be explained by the effective state support aimed at stimulating the development of the metals and mining sector and reproduction of the country’s mineral reserve base. conclusions the metals and mining sector in kazakhstan has proven to be quite vulnerable to the fluctuations in the global financial and trade markets. the market of ferrous metals, which is one of the key elements of industrial production, followed the dynamics of world economy. the unstable economic and political environment, fraught with contradictory trends, in particular the shocks triggered by the sanctions, has had a disruptive effect on the supply and demand balance. continuing sanctions pressure together with fractured supply chains are now the main threats to kazakhstan’s foreign trade. the risks kazakhstani enterprises face in connection with the secondary sanctions include banks and other lending institutions’ denial of service, prohibition of us dollar transactions, and foreign counterparts ending or suspending their dealings. disruptions of the long-standing logistics and supply chains caused due to overcompliance may result in shrinking production volumes/supplies, lower corporate profits and, therefore, reductions in the tax base and possible job cuts. affiliates of tncs in kazakhstan demonstra ted various and sometimes ambivalent responses to the risk of secondary sanctions. for example, during the active phase of the us sanctions against iran, the ssgpo managed to ensure a virtually guaranteed sale market for its products by signing a long-term contract with mkk. meanwhile, arcelormittal totally lost its market in iran after suspending all its trade relations with iranian partners. in 2022, large metals and mining companies operating in kazakhstan initially demonstrated fairly uniform responses to the anti-russia sanctions by suspending their exports to russia. in june 2022, arcelormittal resumed its supplies to russian pipe manufacturing plants. in the future, there is likelihood that there will be a growing demand for metal products from almost all of the industries in kazakhstan, https://doi.org/10.15826/recon.2022.8.3.019 https://www.vnedra.ru/novosti/ao-tau-ken-samruk-somestno-s-yuniorskoj-kompaniej-nachinayut-geologora https://www.vnedra.ru/novosti/ao-tau-ken-samruk-somestno-s-yuniorskoj-kompaniej-nachinayut-geologora https://www.vnedra.ru/novosti/ao-tau-ken-samruk-somestno-s-yuniorskoj-kompaniej-nachinayut-geologora https://www.vnedra.ru/novosti/ao-tau-ken-samruk-somestno-s-yuniorskoj-kompaniej-nachinayut-geologora http://mgok.kz/ru/o-kompanii/ https://tks.kz/subsidiaries/too-severnyj-katpar/ https://tks.kz/subsidiaries/too-severnyj-katpar/ https://keminresources.com/about-us/company.html 250 r-economy.com r-economy, 2022, 8(3), 237–251 doi: 10.15826/recon.2022.8.3.019 online issn 2412-0731 references aituar, a. 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(2022, july 4). 25 principles of international order: a roadmap to peace. russian international affairs council. https://russiancouncil.ru/en/analytics-and-comments/analytics/25-principles-of-international-order-a-roadmap-to-peace/ information about the author larissa bozhko – vice-rector. rudny industrial institute (38, 50 let oktyabrya str., rudny, kostanay region, kazakhstan); e-mail: bogkoll@rii.kz, bozhkoll70@gmail.com article info: received july 13, 2022; accepted september 6, 2022. информация об авторе божко лариса леонидовна – проректор по академическим вопросам, рудненский индустриальный институт (республика казахстан, костанайская область, г. рудный, ул. 50 лет октября, 38); e-mail: bogkoll@rii.kz, bozhkoll70@gmail.com информация о статье: дата поступления 13 июля 2022 г.; дата принятия к печати 6 сентября 2022 г. 作者信息 博日科·拉里萨·列奥尼多夫娜 —— 负责学术事务的副校长，鲁德尼工业学院（哈萨 克斯坦共和国，科斯塔奈州，鲁德内市，五十年十月街，38号）；邮箱：bogkoll@rii. kz, bozhkoll70@gmail.com https://doi.org/10.15826/recon.2022.8.3.019 https://doi.org/10.1111/j.1528-3577.2004.00185.x https://doi.org/10.1177/0738894213520379 https://doi.org/10.1111/0020-8833.00032 https://russiancouncil.ru/analytics-and-comments/columns/sanctions/obzor-mezhdunarodnoy-sanktsionnoy-politiki-fevral-2021-g/ https://russiancouncil.ru/analytics-and-comments/columns/sanctions/obzor-mezhdunarodnoy-sanktsionnoy-politiki-fevral-2021-g/ https://doi.org/10.1111/isqu.12017 https://russiancouncil.ru/analytics-and-comments/comments/sanktsii-sposob-obespecheniya-tekhnologicheskoy-nezavisimosti/?sphrase_id=93046696 https://russiancouncil.ru/analytics-and-comments/comments/sanktsii-sposob-obespecheniya-tekhnologicheskoy-nezavisimosti/?sphrase_id=93046696 https://doi.org/10.15826/ recon.2021.7.4.022 https://doi.org/10.15826/ recon.2021.7.4.022 https://www.webofscience.com/wos/author/record/2430256 https://www.webofscience.com/wos/author/record/24434163 https://www.webofscience.com/wos/author/record/4457455 https://www.webofscience.com/wos/woscc/general-summary?queryjson=%5b%7b%22rowboolean%22:null,%22rowfield%22:%22cf%22,%22rowtext%22:%22international conference of the czech republic%27s strategy for competitiveness 2015%22%7d%5d&eventmode=oneclicksearch https://russiancouncil.ru/en/analytics-and-comments/analytics/legal-and-political-aspects-of-eu-s-po https://russiancouncil.ru/en/analytics-and-comments/analytics/legal-and-political-aspects-of-eu-s-po https://russiancouncil.ru/en/analytics-and-comments/analytics/legal-and-political-aspects-of-eu-s-po https://doi.org/10.1080/03050629.2015.1024242 https://russiancouncil.ru/en/analytics-and-comments/analytics/25-principles-of-international-order-a https://russiancouncil.ru/en/analytics-and-comments/analytics/25-principles-of-international-order-a https://e.mail.ru/compose/?mailto=mailto%3abogkoll@rii.kz https://e.mail.ru/compose/?mailto=mailto%3abozhkoll70@gmail.com https://e.mail.ru/compose/?mailto=mailto%3abogkoll@rii.kz https://e.mail.ru/compose/?mailto=mailto%3abozhkoll70@gmail.com mailto:bogkoll@rii.kz mailto:bogkoll@rii.kz https://e.mail.ru/compose/?mailto=mailto%3abozhkoll70@gmail.com r-economy, 2019, 5(4), 189–197 doi: 10.15826/recon.2019.5.4.019 189 www.r-economy.ru online issn 2412-0731 original paper © i. k. lebedeva, 2019 doi 10.15826/recon.2019.5.4.019 public-private partnerships and their role in enhancing the cargo handling efficiency of container lines in the black sea i. k. lebedeva admiral ushakov state maritime university, novorossiysk, russia; e-mail: lebedeva.irene69@gmail.com abstract the article discusses the current situation in the container shipping market and the terminal infrastructure in the black sea region. the analysis is based on the container fleet database accumulated by the author. these data are used for making observations and predictions and drawing conclusions about the dynamics of the marine transportation market. the methodological framework comprises theoretical, empirical and mathematical methods. the comparative analysis of container services of different russian terminals and ports has shown that the market is now undergoing major transformations and suffers from a considerable imbalance due to the rapid growth in deadweight tonnage and the insufficient capacity of the infrastructure, which means that it is unable to keep up with the rising demand. the excess of deadweight tonnage and the shortage of the necessary equipment leads to chronic bottlenecks in cargo handling, cargo clearance and so on. to address these problems, it is proposed to explore the opportunities provided by the integration of public-private partnerships into the service structure of maritime transport. by focusing on the case of the russian port of novorossyisk, the article demonstrates that public-private partnerships are able to enhance the efficiency  of  cargo-handling operations of container lines in the black sea region. keywords public-private partnership, logistics, maritime transport, world fleet, container ships, container lines, black sea for citation lebedeva i. k. (2019) publicprivate partnerships and their role in enhancing the cargo handling efficiency of container lines in the black sea. r-economy, 5(4), 189–197. doi: 10.15826/recon.2019.5.4.019 государственно-частное партнерство – как инструмент повышения интенсивности терминальной обработки контейнерных линий черноморского региона и. к. лебедева осударственный морской университет им. адм. ф.ф. ушакова, г. новороссийск, россия; e-mail: lebedeva.irene69@gmail.com аннотация в данной статье рассмотрено состояние рынка контейнерных перевозок и инфраструктуры терминального сервиса на сегодняшний день. проведенное исследование и собранная информация позволили проанализировать нынешнее состояние рассматриваемого сегмента рынка. база данных контейнерного флота, накопленная автором статьи для дальнейшего определения уровня рынка и расчетов показателей флота и последующее наблюдение, предоставляет возможности для дальнейшего развития исследования. в рамках статьи автором были применены теоретические, эмпирические и математические методы. основной целью данной статьи является проведение аналитического исследования рынка контейнерных услуг и управления флотом; сбор актуальных данных; проведение компаративного анализа сервиса контейнерного флота различных терминалов и определение уровня сервиса на терминалах российских морских портов. состояние рынка контейнерных перевозок претерпевает масштабные изменения и приводит к дисбалансу отрасли в связи со стремительным ростом тоннажа и неподготовленности сервиса к созданному грузообороту. в современных экономических условиях при избытке тоннажа и дефиците оборудования, соответствующими последствиями ожидается возникновение узких мест на этапах терминальной обработки и оформлении груза в контейнерных перевозках и т.д. в поисках решения проблем в этой связи автором предлагается рассмотреть возможность привлечения государственно-частного партнерства в сервисную структуру морского транспорта, как инструмент повышения интенсивности терминальной обработки контейнерных линий рассматриваемого черноморского региона с последующими выводами. ключевые слова государственно-частное партнёрство, логистика, морской транспорт, мировой флот, контейнерные суда, контейнерные линии, черноморский регион для цитирования lebedeva i. k. (2019) publicprivate partnerships and their role in enhancing the cargo handling efficiency of container lines in the black sea. r-economy, 5(4), 189–197. doi: 10.15826/recon.2019.5.4.019 http://doi.org/10.15826/recon.2019.5.4.019 http://doi.org/10.15826/recon.2019.5.4.019 mailto:lebedeva.irene69@gmail.com mailto:lebedeva.irene69@gmail.com 190 www.r-economy.ru r-economy, 2019, 5(4), 189–197 doi: 10.15826/recon.2019.5.4.019 online issn 2412-0731 introduction the russian national economy is now becoming more and more open and integrated into the global economic system, which means that it has come to rely more heavily on transport infrastructure. therefore, it is crucial to analyze the work of maritime transport infrastructure, in particular container terminals and ports. as the international division of labour grows deeper and the international trade relations expand, the container segment in the international logistics supply chain also grows in importance. interactions between international container lines and container terminals are determined by the current trends in the development of trade fleet and regional transport hubs. it is necessary to consider further stages and prospects of development of the russian port infrastructure and the related strategic decisions. in this respect, it would be interesting to assess the potential of public-private partnerships in the sphere of maritime transport development. maritime transport plays a special role in the development of the global trade infrastructure. the structure of maritime transport is determined by a set of factors, including the demands of the market. in their turn, trade organizations face financial risks when trying to create a certain transport and logistics relationships on the basis of the already existing infrastructure. their attempts to minimize these risks lead to an increase in the demand for container shipping services. in addition to the risks, container transportation also allows us to minimize transportation costs and time intervals for cargo handling at terminals. cargo stored in containers does not require additional storage facilities, since the site is used as a warehouse. introduction of public-private partnerships (ppp) in this segment of maritime transport will let us attract more suppliers to the russian market, expand the range of export and import and accelerate the processing of ships at a terminal. ppp has different forms of organization and can be used in a range of investment deals and infrastructure industry complexes1. the main forms of ppp are as follows: – bot (build, operate, transfer) is a form of project financing, wherein a private entity receives a concession from the private or public sector to finance, design, construct, own, and operate a facility stated in the concession contract; 1 guidelines for project realization of public-private partnership in russian regions (2013). the ppp development center, moscow – boo (build, own, operate) means that a private entity builds, owns and operates some facility or structure receiving some financial incentives from the government; – boot (build, own, operate, transfer) means that a private organization conducts a large development project under contract to a public-sector partner, such as a government agency; – dbfm (design, build, finance, maintain) means that the private sector is responsible for the design, building, finance and maintenance of an asset, which incentivises the private sector to design the asset taking into account the long-term maintenance required. in this article we are going to look at the current state of the sea container fleet and container terminals in the black sea region, in order to identify the bottlenecks and opportunities to eliminate them with the help of ppp. the black sea plays an important role in russian economy with novorossiysk ranking first in terms of cargo turnover in russia and third in europe2. we believe that the ppp holds most potential for the development of the regional transport industry. taking into account this consideration, we are going to research the condition of the world container market and compare it with the situation in the black sea region, in particular the ways of enhancing the cargo handling efficiency of container lines. theoretical framework ppp means cooperation between public and private entities primarily for infrastructure provision within a certain area or region. ppp and its role in regional economies was discussed by g. p. hasaev, s. a. martishkin [1], d. i. shabunin and others. container shipping management was studied by malcolm mclean, e. l. limonov [2], v.  v.  vinnikov [3], o. n. baburina [4; 5], v. k. tsygankov [6] and others. other authors researching the problems of container shipping include l. edirisinghe, zhihong jin, a. w. wijeratne [7], i. rekik, s. elkosantini [8]. lalith edirisinghe, zhihong jin, and a. w. wijeratne focus on the practical aspects of container exchange and its potential for addressing the problem of imbalance in world trade. ines rekik and sabeur elkosantini also analyze the container market and seaport terminals service levels as well as the storage area. eugene korovyakovsky 2 retrieved from source or supplier information. retrieved from: https://www.vestifinance.ru/articles/108278?page=1 http://doi.org/10.15826/recon.2019.5.4.019 https://www.vestifinance.ru/articles/108278?page=1 r-economy, 2019, 5(4), 189–197 doi: 10.15826/recon.2019.5.4.019 191 www.r-economy.ru online issn 2412-0731 and yulia panova [9] provide an overview of the dynamics of russian dry ports. in this article, we are going to analyze the available data on the market of container services, compare the services provided by different terminals, assess the current level of terminal services in russian black sea ports, and discuss the ways of optimizing them. methodology the methodological framework of this research includes empirical, theoretical and mathematical methods: data collection, structuring, comparative analysis and mathematical calculations. our analysis relies on the data on the world merchant marine fleet and follows the procedure described below. first, to get a clear picture of the current situation in the container market, we need to collect the data such as the vessel types, sizes, tonnage and capacity, age range and container liner operators. these data can be obtained from the ‘review of maritime transport’ of 2016 and 2017 [10; 11] and the data on the russian sea ports found in dispatchers’ daily reports. second, we are going to structure and visualize the results of our calculations. third, it is necessary to systemize the results of research for further comparative analysis of the world port practices and the practices of black sea ports and terminals. finally, we are going to formulate recommendations concerning the ways to enhance the efficiency of cargo handling in the terminals of the black sea region. discussion the structure of the world trade fleet reflects the demand for container shipping, as the total deadweight of the fleet and its share in the total tonnage increases. in 2017, the fleet of dry cargo vessels accounted for 43.2% of the world fleet by deadweight and 17.2% by value. the analysis of the structure of the maritime transport market has shown the market share of standard vessels by deadweight and the share of the total fleet [10, p. 25]. as part of the analysis of the structure of the world fleet in terms of deadweight, the dry cargo fleet occupies the leading position of the world fleet. the tanker fleet is in the second place, and container ships are in the third place. vessels for the transportation of general cargo rank fourth (table 1). the growth of the fleet is reflected in the comparative figures of the total tonnage for the period from 2015 to 2017, in which it increased by 6.69%. with the decline in the share of the typical vessels of the total fleet, the total tonnage over the period from 2015 to 2016 increased by 3.47%, and in the period from 2016 to 2017, it grew by 3.06%. therefore, when considering the structure of the model fleet, it becomes apparent that the share of tankers and container ships among the total deadweight increased in comparison with 2015 and 2017. in 2017, the average age of the commercial fleet exceeded the ones in 2016 by 0.7 age units and was 20.6 years in total (table 2) [10, p. 27]. the age segmentation of the world fleet varies from the indicators of newly built ships to the number of decommissioned or obsolete ships. in comparison with the established opinion about the average age of the world fleet, the indicators of 2017 indicate a fairly ‘young’ age of ships, especially those in the segment of dry cargo and container ships. the fleet of countries with developing economies is on average 10 years older than ships of countries with developed economies (see table 2). therefore, it makes sense to indicate that vessels of various types, such as tankers, general vessels and others, are considerably older in terms of the average age of a fleet than the youngest fleet of dry cargo and container ships [12, p. 91]. it also becomes evident that over the past 15–19 years, ship sizes have undergone some significant changes. prior to that, the largest types by deadweight were dry cargo ships and tankers, but over the past few years, the container fleet has table 1 structure of the world trade fleet, 2015–2017 vessel type deadweight, thous. tons share, % 2015 2016 2017 2015 2016 bulkers 761,776 778,890 796,581 43.6 43.1 oil tankers 488,308 503,343 534,887 28 27.9 container ships 228,224 244,274 245,609 13.1 13.5 general cargo vessels 74,158 75,258 74,823 4.2 4.2 others 193,457 204,886 209,984 11.1 11.5 subtotal 1,745,923 1,806,651 1,861,884 100 100 source: uncnad secretariat calculations, based on the data from clarksons research. http://doi.org/10.15826/recon.2019.5.4.019 192 www.r-economy.ru r-economy, 2019, 5(4), 189–197 doi: 10.15826/recon.2019.5.4.019 online issn 2412-0731 caught up with the leaders in this indicator. the previously mentioned dimensions and capacity of container ships are currently being brought to the maximum level, and further growth is not being planned in terms of potential opportunities and the bandwidth of channels and straits. in the past five years, the market of sea container transportation of linear type has been characterized by rigorous competition [13], which required enormous expenses on the part of the carriers. they had to invest in the new fleet consisting of larger ships (container ships), which lead to a decrease in freight rates for the container on average in affordable areas; a decrease in the frequency of servicing; increase in port charges for ship handling; and shortages of container equipment. the specificity of chartering a container fleet lies in the cellular-like structure of the onboard/ bilge space used to store containers [14]. a fully-cellular container vessel is a cellular type of a container carrying ship. this type of container ship makes up 98% of the world container fleet. if, in the market of bulk cargo, loading depends primarily on the calculation of the cargo capacity of the vessel according to its specific weight, capacity and carrying capacity, then in linear container transportation the calculation is made for each container, according to its capacity and carrying capacity [15]. this kind of loading can be compared with chartering ‘part cargo’. in this case, the hold and freight are divided between charterers, and, as a rule, this type of chartering is common, both in the general cargo market and in the beam market. the organization and management of the container fleet within the line depend on intertable 2 age and quantitative distribution of the world fleet by vessel types and economic affiliation for 2016–2017 economic grouping and vessel type 0–4 years average age % change 5–9 10–14 15–19 20+ 2017 2016 2016–2017 world fleet bulk carriers % of total ships 35.77 33.8 12.05 9.33 9.05 8.8 8.8 0.00 % of deadweight tonnage 38.66 34.88 11.91 7.55 7.01 7.95 7.94 0.01 average vessel size (dwt) 79,099 75,525 72,283 59,244 56,673       container ships % of total ships 18.63 30.5 22.72 15.66 12.5 11.55 11.1 0.45 % of deadweight tonnage 31.51 32.57 20.82 10.17 4.92 8.72 8.39 0.33 average vessel size (dwt) 80,624 50,891 43,679 30,961 18,751       general cargo ships % of total ships 7.68 16.5 10.20 7.54 58.08 25.21 24.44 0.76 % of deadweight tonnage 14.98 24.7 12.23 10.24 37.85 18.29 17.83 0.46 average vessel size (dwt) 8,118 6,081 5,086 5,630 2,561       oil tankers % of total ships 16.03 22.51 15.46 7.74 38.26 18.76 18.36 0.4 % of deadweight tonnage 22.07 34.74 24.44 12.67 6.09 9.9 9.54 0.36 average vessel size (dwt) 73,274 82,242 84,610 89,498 8,777       other % of total ships 14.37 18.65 10.60 8.43 47.96 22.73 22.25 0.48 % of deadweight tonnage 19.4 26.43 14.21 10.29 29.67 15.58 15.65 0.07 average vessel size (dwt) 7,777 7,907 8,004 7,144 3,954       all ships % of total ships 11.75 17.97 10.13 7.00 53.15 20.57 19.92 0.65 % of deadweight tonnage 29.8 33.16 16.95 9.78 10.31 9.9 9.55 0.34 average vessel size (dwt) 42,207 34,948 32,847 25,991 5,917       all ships – developing economies % of total ships 16.92 21.01 11.29 7.92 42.86 29.03 28.33 0.7 % of deadweight tonnage 31.4 30.6 12.74 9.75 15.5 16.72 15.91 0.81 average vessel size (dwt) 34,624 27,025 22,137 23,195 6,733       all ships – developed economies % of total ships 16.15 23.86 14.08 10.76 35.15 19.05 18.51 0.54 % of deadweight tonnage 29.25 35.13 19.73 9.76 6.12 9.15 9.04 0.11 average vessel size (dwt) 53,396 43,538 42,708 28,695 6,589       all ships – transition economies % of total ships 6.32 8.82 6.02 3.19 75.66 29.39 28.93 0.46 % of deadweight tonnage 12.58 28.76 21.23 11.2 26.22 15.59 16.03 –0.43 average vessel size (dwt) 14,835 24,533 26,714 25,028 2,447       source: uncnad secretariat calculations, based on the data from clarksons research. http://doi.org/10.15826/recon.2019.5.4.019 r-economy, 2019, 5(4), 189–197 doi: 10.15826/recon.2019.5.4.019 193 www.r-economy.ru online issn 2412-0731 nal and external factors of the market economy: coordination of terminal service and line representation at the local level, stable cargo flow (export/import), schedule of port calls, loading and unloading operations rates, etc. [16]. the structure of the world market of liner transportation distributes service offers by regions of demand (table 3). in mid-2018, the cargo capacity of the linear container fleet was 21.9 million teu, and in 2016 – 19.8 million teu. the growth of cargo capacity of the container fleet is 2.1 million teu for a partial period of 1.5 years. in 2016, 127 new container ships were launched, which is 70% lower than in the peak year, 2008. in addition, significant changes in the average size of new ships were revealed. prior to this, the size of the new fleet had exceeded the size of the existing one, especially in the container segment. this trend, observed until 2016, complicated the relations with port authorities in terms of setting up and handling ships not only in small ports in all regions, but also in large ports in asia and europe. the rapid increase in tonnage and cargo capacity of the container fleet resulted in lower rates on the freight of a container, increased costs of the use of containers outside the port and a reduction in the period of free use. the shortage of container equipment means that reorganization of service centers and regional divisions of container lines is required [17]. public-private partnerships may be used to accelerate the process of cargo and ship handing at marine terminals. planning is one of the most significant tools used for the reduction of risks in the management of the fleet and container line as a whole. it is necessary for a container line to plan the routes and ways to navigate regions in order table 3 top 30 major container shipping line operator companies, 2018 rank line operator cargo capacity, teu market share,% 1 apm-maersk 4,118,975 18.7 2 msc 3,241,555 14.7 3 cma cgm group 2,518,195 1.5 4 cosco shipping co ltd 1,949,516 8.9 5 hapag-lloyd 1,611,772 7.3 6 one (ocean network express) 1,522,005 6.9 7 evergreen line 1,088,509 5 8 oocl 694,597 3.2 9 yang ming marine transport corp. 662,625 3 10 pil (pacific int. line) 427,624 1.9 11 zim 367,566 1.7 12 hyundai m.m. 358,981 1.6 13 wan hai lines 251,108 1.1 14 x-press feeders group 144,399 0.7 15 kmtc 128,698 0.6 16 zhounggu logistics corp. 126,182 0.6 17 antong holdings (qasc) 126,119 0.6 18 sitc 104,071 0.5 19 irisl group 96,383 0.4 20 ts lines 80,761 0.4 21 arkas line/emes 72,717 0.3 22 sinotrans 61,925 0.3 23 sm line corp. 57,992 0.3 24 sinokor 56,382 0.3 25 salam pasific 53,712 0.2 26 rcl (regional container l) 49,687 0.2 27 heung-a shipping 48,051 0.2 28 simatech 47,008 0.2 29 unifeeder 45,775 0.2 30 grimaldi (napoli) 44,773 0.2   total for the top 30 20,201,606 81.7   other companies 1,785,690 18.3   subtotal 21,987,296 100 source: https://alphaliner.axsmarine.com/publictop100/ http://doi.org/10.15826/recon.2019.5.4.019 https://alphaliner.axsmarine.com/publictop100/ 194 www.r-economy.ru r-economy, 2019, 5(4), 189–197 doi: 10.15826/recon.2019.5.4.019 online issn 2412-0731 to improve its services, to control cargo flow and meet the needs of customers in a particular market segment. results the seasonality of the work of many directions of line service is determined by the specifics of the cargo and requirements of the market. taking into account the specifics of the cargo of certain segments of the market and the calculation of the fleet from the cargo base, a regional representative of the container line has the opportunity to avoid downtime of ships and non-profitable trips with incomplete loading of the vessel. therefore, while devising a plan for the future operation of the container lines, the representative works together with regional representatives, considering all options, including the use of ppp, and taking into account the technical capabilities of the port. thus, a plan of anchoring the vessel is formed; the volume of the processed cargo, the capacity of the terminal, the intensity of the ppp, the rates of terminal and ship fees, etc. are calculated [6]. the recommended period of ppp agreement should be no less than three years, with the minimal investment amount of 200 mln. rub.3 let us now focus on the case of the russian port of novorossyisk. in terms of cargo traffic, novorossiysk is the third largest port in europe4. we calculated the average speed of container handling in pjsc ‘ncsp’ on the basis of the available terminal group data – 24.4 containers per hour. this indicator reflects the average value for the varying degrees of vessel capacity and size of container ships making port calls to the port of novorossiysk to the terminal of pjsc “ncsp” in the first quarter of 2018. the processing speed is directly dependent on the cooperation of the staff of the terminal, freight forwarders, ship agents, stevedores and ship’s crew, speed of execution and submission of applications for loading/unloading, preparation of tally sheets, design and supply of rolling stock, warehousing, connection (in case of perishable goods), etc. the container line ‘zim russia’, in the first quarter of 2018, has an average ship processing speed that is higher than ‘maersk line’ and ‘lider line’. the most stable speed of container handling is observed in maersk, which is 29.9 containers per hour. 3 guidelines for project realization of public-private partnership in russian regions (2013). the ppp development center, moscow. 4 retrieved from: http://www.nmtp.info/holding/about/ to compare the performance indicators of novorossiysk with the world average value of the container ship processing speed, we can look at the average value of the vessel berthing in the port for cargo operations and paperwork. table 4 average container processing speed in pjsc ‘ncsp’ (container/hour) month/ container line zim lider line standart-f maersk avg speed, container per hr january 33.8 16.5 13.8 – 21.4 february 26.7 13.8 – 29.9 23.4 march 37.5 18 – 29.9 28.5 average speed, container per hr 32.6 16.1 13.8 29.9 24.4 the average time a ship spends in a port is determined by the average speed and the average number of containers for loading and unloading during the given period. the average processing time of the vessel in pjsc ‘ncsp’ is 22.8 hours or 0.95 days. the indicator of global average processing time of a ship in a port is 0.87 days or 20.9 hours, the difference being 1.9 hours (table 5) [11, p. 69]. table 5 average port time: container ships, 2016, [11] country port time, days total port calls, units china 0.83 60,795 japan 0.29 38,415 south korea 0.49 23,545 usa 0.97 19,844 taiwan 0.4 16,895 singapore 0.8 16,159 malaysia 0.93 15,678 germany 0.46 14,784 spain 0.51 14,018 holland 1.14 12,264 average world difference 0.87 445,990 conclusion as the strategy of port infrastructure development until 2030 indicates, it is planned to improve the processing speed of ships through the construction of new storage spaces; improvement of the existing berthing areas, improvement of the technical characteristics of the lifting base of the port; deepening of the mooring lines; and so on5. nevertheless, the interaction of the port/terminal 5 strategy of developing marine port infrastructure of russia until 2030 (adopted by the marine congress of the russian government on 28.09.2012) retrieved from: http:// www. rosmorport.ru/ http://doi.org/10.15826/recon.2019.5.4.019 http://www.nmtp.info/holding/about/ http:// www.rosmorport.ru/ http:// www.rosmorport.ru/ r-economy, 2019, 5(4), 189–197 doi: 10.15826/recon.2019.5.4.019 195 www.r-economy.ru online issn 2412-0731 and container line with other contractors forms the order of ship handling [3]. this sequence of relationships reflects the basic principle of supply chains – minimizing transport, time and financial costs throughout the entire cycle of linear service. the real issue, in this case, is the specific characteristics of organization of the container line at the terminal, which can be illustrated by the case of the container terminal of pjsc ‘ncsp’. regarding the line service for container fleet maintenance, the shipowner, as in the case of tramp shipping, can delegate management functions of the company to the regional representative of the line or its operator6. the parent company distributes responsibilities to countries/ports of call, which allows the company to respond promptly to changes in operation and tariffs of the port/terminal and control the process of port call service. the interaction of the line operator with the shipowner, in this case, is limited to the contract of freight, the contract of intermediary services and the corresponding document circulation [2; 18]. a contract for the provision of services is necessary if the line operator is located in russia, in which case it is required to sign a bilingual contract approved by the monetary control of the bank of the line operator. thus, the shipowner deals with the operational issues of the vessel, while the line operator organizes the operation of the service on the line. let us look at this situation in more detail by using the case of pjsc ‘ncsp’ as an illustration: a line operator at the terminal of pjsc ‘ncsp’ performs the following functions and responsibilities: 1. cargo towing (chartering)7. the chartering department or chartering manager can be found through outsourcing. the panel broker or line operator independently organizes the work of the chartering department. it needs, however, to coordinate its plans of loading, trips and ship calls with the owner. the costs of ship calls account for most of the transportation expenses, which means that the preliminary calculation of the flight is required at the planning stage. 2. port operations. as a rule, each port/country/region has its own line representative. the line operator interacts with the commercial depart6 a line operator is an organization that manages and interacts with contractors on behalf of the shipowner, which preforms the functions of chartering (booking), organization, accounting and control of the line within the terminal service. 7 chartering is the conclusion of the contract of carriage, specifying the specific conditions, mode of transport, terms and periods of shipment, rates per ton or lot. ment of the port/terminal, forms the required contractual relationship, building a chain of financial obligations to the port/terminal, and devises a work schedule based on the capabilities of the port and the schedule of the line’s ship calls. 3. sales and customers. when the container line is being organized, it is important to create a customer base and demand for the carrier’s services. the competitive environment in the container transportation market is gaining momentum every year. if there is a demand for the carrier’s services, the line operator forms the main customer base and informs the customers about the creation or renewal of the service. at the initial stage, the cost of container freight should not exceed the average value in the region, and, while the customer based is still being formed, the cost of freight can be seasonally reduced. a productive relationship with customers is one of the key success factors in the shipping market. a problem which has to be addressed in russia is the terms of payment for services. terms of payment, which is an integral part of the contractual relationship, allow the company to describe in advance the required sequence of money transfers for rendered services, or specify whether a prepayment for services needs to be provided. it is particularly important to build a clearly defined sequence of mutual settlement if the company is working with numerous contractors and intermediaries. for instance, if, according to the schedule of ship calls formed by the port manager, a container ship arrived at the port of discharge, a container was loaded onto the ship, and the freight of the aforementioned container was not paid for. in this situation, there are two scenarios: the operator may be allowed to unload the container and place it in the warehouse, with a ban on its export/release from the territory of the port until the debts have been payed to the line or, after the container has been fully unloaded, in the absence of payment and any counteractions on the part of the cargo owner/ forwarder/charterer of the container, the line has the full right to continue using its own equipment (container) with the goods at its discretion (if the contract does not specify other conditions). the line operator pays for the storage of containers that are located on the territory of the port/ terminal and has the right to decide whether or not they should load the unpaid container together with empty ones, i.e. issue it as re-export. such an operation may be cheaper for the line than http://doi.org/10.15826/recon.2019.5.4.019 196 www.r-economy.ru r-economy, 2019, 5(4), 189–197 doi: 10.15826/recon.2019.5.4.019 online issn 2412-0731 paying for a simple container in the port, until it is required, especially if the container is refrigerated and the cargo is perishable. such situations are common. the cost of storage, including the costs related to its utilization and maintenance, usually ends up having a price range that starts from usd 50 per day8. therefore, if it is possible to use ppp at this terminal with the possibility of signing an individual draft contract for each container line, which will result in the following advantages: an increase in the capacity and turnover of the port/ terminal; acceleration of ship handling; expansion of the range of export/import cargoes and goods; reduction in the risk of cargo downtime at the port, delays in ship handling and inappropriate use of port facilities; reduction of the risk of financial indebtedness to the port/terminal, which would eliminate the potential situation of service delay in case of non-payment; and, finally, enhancement of the efficiency of container lines, created by accelerating the turnover of container equipment inside the cycle. 8 port dues, charges and tariffs for service and regulations of their application in the sea port of russian federation (black and azov sea ports), (2014). llc ‘maritime tariffs center’. saint-petersburg: cnimt publisher. thus, the use of ppps may well prove to be a feasible solution to the above-described problems. operation of a container terminal can be affected by unique configurations of internal and external factors. the regional feature allows you to debug the processes of port facilities depending on the cargo situation, weather conditions, tonnage and other features not applicable to ports and terminals in other regions. the world’s merchant fleet is characterized by the rapid growth of deadweight (cargo capacity) tonnage of container ships. this trend contributes to lower transport costs due to economies of scale. however, the amount of container equipment is insufficient. the growth rate of container tonnage (2.1 million teu) is higher than the growth rate of container equipment. one of the ways to solve the problem is to increase the speed of container handling at port terminals with the help of ppps the average speed of container handling at the terminal of pjsc ‘ncsp’ is 24.4 containers per hour. it is proposed to increase the processing speed of container ships by optimizing business processes on container lines through the centralization of container service at the terminal and the consolidation of ppp in the sphere of maritime transport. references 1. lapteva n. v., martyshkin s. a. 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(2017). specification of tonnage research in grain cargo deliveries from azov-black marine sea ports/scientifics view. scientific view, 19, 90–94. (in russ.) 13.  stopford m. (2009). maritime economics. london: routledge. 3rd ed. doi: 10.4324/9780203891742 14. wilson f. j. (2010). carriage of goods by sea. london: longman. 7th ed. 15. over p. c. (2017). dry cargo chartering. london: institute of chartered shipbrokers. 16.  prokofyev v. a., veprinskay t. a. (2010). the management of marine fleet maintenance and operation. st petersburg: admiral makarov state academy of maritime and inland shipping publisher. (in russ.) 17. geerlings h., kuipers b., zuidwijk r. (2018). ports and networks. london: routledge. london: routledge. 18. ivanova s. e., ivanov m. u. (2004). maritime fleet management and commercial service. novorossiysk: nsma publisher. (in russ.) information about the author irina k. lebedeva – phd student and lecturer at “admiral ushakov state maritime university” (93, lenin’s avenue, novorossiysk, 353918, russia); director of “konstanta” llc, e-mail: lebedeva. irene69@gmail.com. article info: received june 25, 2019; accepted october 15, 2019 информация об авторе лебедева ирина константиновна – аспирант и преподаватель гму им. ф.ф. ушакова (353918, россия, новороссийск, проспект ленина 93); директор ооо «константа», e-mail: lebedeva.irene69@gmail.com. информация о статье: дата поступления 25 июня 2019 г.; дата принятия к печати 15 октября 2019 г. this work is licensed under a creative commons attribution 4.0 international license эта работа лицензируется в соответствии с creative commons attribution 4.0 international license http://doi.org/10.15826/recon.2019.5.4.019 http://doi.org/10.4324/9780203891742 mailto:lebedeva.irene69@gmail.com mailto:lebedeva.irene69@gmail.com mailto:lebedeva.irene69@gmail.com 207 r-economy.com r-economy, 2023, 9(2), 207–225 doi 10.15826/recon.2023.9.2.013 online issn 2412-0731 © a. e. sudakova, d.m.s. dahel, 2023 doi 10.15826/recon.2023.9.2.013 udc 378 jel i22, i28, h52 funding the higher education system: international experience and russian practice a. e. sudakovaa) , d.m.s. dahelb)  a)ural federal university, ekaterinburg, russia;  ae.sudakova@gmail.com b)al-furat al-awsat technical university;  mustafaaladli@gmail.com abstract relevance. education is a significant factor in economic growth. however, the discussion about the principles for distributing higher education funding is still open, and the cases of individual countries are not sufficiently covered in research literature. research objective. the study aims to determine the principles of financing based on the case studies of russian universities. foreign financing mechanisms are analyzed and compared with russian practice that has similar foundations. financing mechanisms are classified according to their distribution principle. data and methods. the statistical base for the study is the data of a large-scale higher education monitoring project of 2019-2021. the study was conducted in more than 650 russian universities. in order to determine the principles of financing, a correlation analysis is carried out to identify the correlation between the indicators. universities are grouped by regions with different socio-economic characteristics, subgroups of universities within the regional division were identified. results. the distribution of funding among russian universities is based on the principles of quasi-competition and equalization. universities located in regions with low indicators of socio-economic development are mainly financed to achieve equalization of educational activities, and, as the socio-economic situation in the region improves, funding is channeled into equalization of research activities. another more obvious conclusion is that research activities of universities that participate in state programs are funded based on competition, while other universities have lower correlation between indicators, which leads us to the assumption that other universities’ research activities are funded based on the principles of equalization. conclusions. the novelty of the study is the results that enrich the understanding of the principles for funding distribution in the russian higher education system. contrary to most studies of the concentration of resources around a limited number of institutions, the study concludes that resources and funding are distributed based on equalization, supporting the less competitive units of the system, and directing funding to regions with less stable socio-economic characteristics. keywords higher education, financing higher education; competition; equalization; development of universities, funding universities acknowledgements the research funding from the ministry of science and higher education of the russian federation (ural federal university program of development within the priority-2030 program) is gratefully acknowledged for citation sudakova, a. e., & dahel, d. m. s. (2023). funding the higher education system: international experience and russian practice. r-economy, 9(2), 207–225. doi: 10.15826/recon.2023.9.2.013 финансирование системы высшего образования: международный опыт и российская практика а. е. судаковаa) , м. с. д. дахелb)  a)уральский федеральный университет, екатеринбург, россия;  ae.sudakova@gmail.com b)аль-фурат аль-авсат технический университет, наджаф, ирак;  mustafaaladli@gmail.com аннотация актуальность. образование является значимым фактором экономического роста. при этом открытой остается дискуссия в части принципов распределения финансирования высшего образования, и в то же время менее изученным вопросом с точки зрения освещения кейсов отдельных стран. цель исследования. исследование направлено на определение принципов финансирования на примере кейсов российских вузов. проанализированы зарубежные механизмы финансирования и представлено их сравнение с российской практикой, которая имеет схожие основы. механизмы финансирования классифицированы по принципу их распределения. ключевые слова высшее образование, финансирование высшего образования; конкуренция; выравнивание; развитие университетов, финансирование университетов original paper http://r-economy.com https://doi.org/10.15826/recon.2023.9.1.003 mailto:ae.sudakova@gmail.com mailto:mustafaaladli@gmail.com mailto:ae.sudakova@gmail.com mailto:mustafaaladli@gmail.com 208 r-economy.com r-economy, 2023, 9(2), 207–225 doi 10.15826/recon.2023.9.2.013 online issn 2412-0731 данные и методы. статистической базой исследования служат данные мониторинга высшего образования за 2019-2021 гг. исследование проведено более чем по 650 российским вузам. с целью определения принципов финансирования проводится корреляционный анализ на предмет выявления взаимосвязи между показателями. произведена группировка вузов по регионам с различными социально-экономическими характеристиками, выделены подгруппы вузов внутри регионального деления. результаты. распределение финансирования среди вузов рф основывается на принципах квазиконкуренции и выравнивания. вузы, расположенные в регионах с низкими показателями социально-экономического развития, финансируются преимущественно по принципу выравнивания в большей части относительно образовательной деятельности, по мере улучшения социально-экономического состояния региона, финансирование на условиях выравнивания направлено на научную деятельность вузов. другой вывод, более очевидный, научная деятельность вузов-участников государственных программ финансируется на условиях конкуренции, в то время как остальные вузы имеют меньшую зависимость между показателями, в результате чего, можем предположить, что финансирование научной деятельности остальных вузах основывается на принципах выравнивания. выводы. новизной исследования являются результаты, расширяющие представление о принципах распределения финансирования в системе российского высшего образования. в противовес большинству исследований о концентрации ресурсов в кругу ограниченного количества вузов, в исследовании делается вывод, что распределение также осуществляется на условиях выравнивания, поддерживая менее конкурентоспособные единицы системы, и направляя финансирование в регионы с менее устойчивыми социально-экономическими характеристиками. благодарности исследование выполнено при финансовой поддержке министерства науки и высшего образования российской федерации в рамках программы развития уральского федерального университета имени первого президента россии б.н. ельцина в соответствии с программой стратегического академического лидерства «приоритет-2030» для цитирования sudakova, a. e., & dahel, d. m. s. (2023). funding the higher education system: international experience and russian practice. r-economy, 9(2), 207–225. doi: 10.15826/recon.2023.9.2.013 高等教育融资：国际经验与俄罗斯实践 苏达科娃a) 、达赫尔b)  a)乌拉尔联邦大学，叶卡捷琳堡，俄罗斯，邮箱：  ae.sudakova@gmail.com b) al-furat al-awsat技术大学，纳杰夫，伊拉克，邮箱：  mustafaaladli@gmail.com 摘要 现实性：教育是经济增长的一个重要因素。然而，关于高等教育资金分配原则的 辩论仍未结束，同时学术界在个别国家的相关案例研究也较少。 研究目标：本研究旨在以俄罗斯大学为例确定融资原则。文章对国外的融资机制 进行分析，并将其与具有类似基础的俄罗斯案例进行比较。融资机制将根据其分 配原则进行分类。 数据与方法：该研究的统计基础是2019-2021年的高等教育监测数据。研究对象 是650多所俄罗斯高等教育机构。为了确定融资原则，文章进行了相关分析，以 确定各指标之间的关系。高等教育机构按区域不同社会经济特征进行分组，并确 定区域中的高等教育机构子群。 研究结果：俄罗斯大学之间的经费分配遵循准竞争和均等的原则。位于社会经济 发展指标较低地区的高等院校在教育活动方面主要按照均衡化原则获得经费，随 着该地区社会经济状况的改善，均衡化融资被导向高等院校的科学活动。另一个 更明显的结论是，参与专项国家计划的学校的研究活动资金是通过竞争获得的， 而其他大学对该项目的依赖性较小，因此我们可以假设其他大学的研究活动资金 是基于均衡化原则。 结论：该研究的新颖之处在于扩大了对俄罗斯高等教育系统资金分配原则的理 解。与大多数关于资源集中在有限数量的高等教育机构圈子的研究相反，该研究 的结论是，分配是在均衡的基础上进行的，国家项目支持系统中竞争力较弱的单 位，并将资金引向社会经济特征不那么持久的地区。 关键词 高等教育、高等教育经费；竞赛； 均衡性; 大学发展、大学融资 致谢 衷心感谢俄罗斯联邦科学和高等教 育部（2030 年优先计划——乌拉 尔联邦大学发展计划）的研究经费 供引用 sudakova, a. e., & dahel, d. m. s. (2023). funding the higher education system: international experience and russian practice. r-economy, 9(2), 207–225. doi: 10.15826/recon.2023.9.2.013 introduction education is a significant factor in economic growth. many studies have proven a positive correlation between investment in a country’s human capital and its economic development (hanushek, 2015). countries that recognize the importance of knowledge, flourish, whereas those that do not hinder their own socio-economic development. however, these conclusions are not unanimous, worth noting are studies that give other arguments (benos, 2013). nevertheless, many national (kolosnitsyna, 2021) and foreign (maneejuk, 2021) researchers have come to the conclusion that investment in education has a positive effect http://r-economy.com mailto:ae.sudakova@gmail.com mailto:mustafaaladli@gmail.com 209 r-economy.com r-economy, 2023, 9(2), 207–225 doi 10.15826/recon.2023.9.2.013 online issn 2412-0731 on developed countries. developing and maintaining regional higher education systems allows regions to develop and prevent the outflow of the younger generation (maneejuk, 2021). conversely, increased public spending on higher education in developing countries with low levels of primary education does not have a positive effect. at the same time, the discussion about the principles for distributing higher education funding in different types of economy is still open. on the one hand, there are arguments for basing funding on competition and quasi-competition (agasisti, 2020), leading to differentiation of universities within the system. on the other hand, it is noted that “in poorer developing countries, competition and market mechanisms will not work, and it is necessary to invest in higher education as a public good” (marginson, 2006: 36). musgrave r.a. drew attention to this much earlier (musgrave, 1969): he advocated higher levels of public investment in higher education for countries with lower levels of economic development, and lower levels of public investment for countries with higher levels of economic development. yonezawa a. and kaiser f. also support the idea of state control, arguing that “only through actions taken at the state level, specific recommendations set out in the corresponding documents of the 1998 world conference on higher education, are implemented” (yonezawa, 2003 ). figure 1 shows public spending on higher education in relation to gdp. total public and private expenditure on higher education in russia is about 1% of gdp, which is 2.5 times less than the maximum value shown in the figure. if these costs are recalculated per student, the gap is even wider: it is twice less than the average for the eurozone countries, 2.1 times less than in germany; 2.3 times less than in japan; 3 times less than in great britain; and 3.5 times lower than in the usa (figure 2). within the framework of this study, we will outline the following challenges for the higher education system: the need to invest in education as a factor in the development of the country’s and the region’s economy, the dependence of higher education in many countries on state funding, and for the russian federation in particular, we can note the lack of financing in comparison to international practice. figure 1. higher education spending as a share of gdp worldwide 2019 source: data on russia taken from form № vpo-2 (2021). url: https://minobrnauki.gov.ru/action/stat/highed/; oecd (2022). resourcing higher education in portugal. oecd publishing, paris. 170 р. https://doi.org/10.1787/a91a175e-en. http://r-economy.com https://minobrnauki.gov.ru/action/stat/highed/ https://doi.org/10.1787/a91a175e-en 210 r-economy.com r-economy, 2023, 9(2), 207–225 doi 10.15826/recon.2023.9.2.013 online issn 2412-0731 the objective of the study is to analyze foreign and russian experience in financing the higher education system, to identify the principles of financing in the russian higher education system. based on their experience in the field of higher education research, the authors hypothesize that the mechanisms for distributing funding are based on two principles: on the principle of competition and on the principle of supporting less competitive units of the system. theoretical basis the main sources of funding for higher education are: public, private and foreign funds. however, this list can be detailed further. thus, chernova e. (chernova, 2017) distinguishes 8 sources, identifying subgroups in each main group (private funds: donations, funding received from companies, self-financing, etc.). for a long time, public expenditure was the main source of funding for universities in most countries (us universities (geiger, 2004; becker, 1993 ), except for countries in south and east asia and latin america (varghese, 2021). however, public funding still plays an important role: based on surveys, it can be noted that “in europe, public expenditure is much more significant than in the us (varghese, 2015: 209)”, and remains the dominant source of funding, accounting for 50 to 90 % of university income (estermann, 2013). thus, in germany core funding from state grants accounts for about 80% of the universities’ institutional income (estermann, 2022: 33); french universities receive 80% of their income as public funding (foret, 2021), portuguese universities this figure reaches an average of 64%, including r&d grants from public funds (oecd, 2022b: 711) (figure 3). higher education institutions in russia, including private universities, receive 61% of their finances from public funds, (public universities – 63%). this distribution of funding between private and public sources reflects the position of marginson s., musgrave r. in developing economies, public funding gives a positive return. until recently, state programs of financing science and higher education brought positive effects an increase in publication activity (prakhov, 2021; matveeva, 2021), a change in the researchers’ migration trajectory, an increase in their mobility (sudakova, 2021), higler positions of universities in international rankings etc. however, the latest destructive geopolitical events allow us to 1 oecd (2022b). oecd statistics – education and training, oecd. stat, https://stats.oecd.org/ figure 2. total expenditure on tertiary educational institutions per full-time equivalent student, 2019 source: data on russia taken from form № vpo-2 (2021). url: https://minobrnauki.gov.ru/action/stat/highed/; oecd (2022). total expenditure on educational institutions per full-time equivalent student (2019): in equivalent usd converted using ppps for gdp, direct expenditure within educational institutions, by level of education, in education at a glance 2022: oecd indicators, oecd publishing, paris, https://doi.org/10.1787/80998d78-en. http://r-economy.com https://minobrnauki.gov.ru/action/stat/highed/ https://doi.org/10.1787/80998d78-en 211 r-economy.com r-economy, 2023, 9(2), 207–225 doi 10.15826/recon.2023.9.2.013 online issn 2412-0731 form only evaluative conclusions about the new challenges brought by these changes. so, despite the fact that almost all countries have the same sources of funding, in different countries they are, firstly, presented in different proportions, and secondly, there are different mechanisms for distributing this funding (table 1). ). table 1 mechanisms for distributing higher education funding mechanisms for distributing funding characteristic countries block grants, including: include three components: on a historical basis, via a funding formula or through a performance contract european countries 1) performance-based funding distribution of a fixed amount of money among institutions based on their relative performance. performance or development contracts, and goal-setting agreements whereby certain goals are agreed between the sponsor and the university, also related to performance-based funding, although they do not always have a direct impact on funding and vary in nature. 2) funding formula input indicators are used (the number of students enrolled); in addition, other indicators, with less weighting, are used in the formula, and they differ between countries (doctoral degrees, international activities, etc.) 3) performance contracts the amount allocated for a specific purpose as a result of negotiations between universities and distributed by the university. in some countries (germany 2% and 5%, the netherlands 7%, denmark 1%, the netherlands, austria, finland, latvia up to 100%), the legislation sets the minimum percentage of the total university funding. evaluation of the achievement of results is not always strict, sometimes it serves as a tool for regulating the university management policy. 13 counties-members of oecd, some states of the usa (oecd, 2019a) 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% united kingdom australia united states canada new zealand russia* russia* st uni korea israel italy ireland japan estonia portugal slovak republic hungary netherlands greece czech republic spain denmark france germany belgium sweden poland finland türkiye mexico austria norway central govt. state govt. local govt. international other private households total private figure 3. expenditure on higher education institutions by source (share of expenditure on public and government-dependent heis by source, 2018) source: data on russia taken from form № vpo-2 (2021). url:https://minobrnauki.gov.ru/action/stat/highed/; oecd (2022): oecd indicators – education at a glance 2022. 462 p. https://doi.org/10.1787/3197152b-en http://r-economy.com https://minobrnauki.gov.ru/action/stat/highed/ https://doi.org/10.1787/3197152b-en 212 r-economy.com r-economy, 2023, 9(2), 207–225 doi 10.15826/recon.2023.9.2.013 online issn 2412-0731 mechanisms for distributing funding characteristic countries excellence programs funding is channeled into research and supporting large initiatives. the amount of allocated funds and directions are much wider than with research grants (research initiatives, campus construction, establishing doctoral schools, regional integration of universities, etc.). the standard is the programs of germany and france. similar programs exist in china, russia, and other countries. itemized distribution of funding funds are allocated strictly according to the items of expenditure, there is a tight restriction on the redistribution of funds between budget items. such a mechanism results in a high level of financial control and transparency for the central budgetary authorities, but drastically limits the ability of institutions to take responsibility for resource management and make strategic decisions on resource prioritization. rarely in european countries; remain the main mechanism in greece (oecd, 2018), korea, state universities in mexico (oecd, 2019), public universities of the russian federation (agasisti, 2020) competition-based (grants, projects) funds are allocated on a competitive basis, as a rule, from research foundations, for a limited period, aimed at supporting research, human resources, and infrastructure. the majority of countries, including russia source: budget code of the russian federation no. 145-fz of july 31, 1998 (as amended on december 28, 2022), article 161; oecd (2018). education for a bright future in greece, reviews of national policies for education, oecd publishing, paris. https://dx.doi.org/10.1787/9789264298750-en; oecd (2019). the future of mexican higher education: promoting quality and equity, reviews of national policies for education, oecd publishing, paris. https://dx.doi.org/10.1787/9789264309371-en; oecd (2019a). university-industry collaboration: new evidence and policy options, oecd publishing, paris, https://dx.doi. org/10.1787/e9c1e648-en. figure 4 shows the relationship between mechanisms and classification characteristics. this study distinguishes three principles for financing higher education: • competition/quasi-competition-based: the more competitive units of the system are financed. however, the mechanisms for distributing finances based on competition lead to high differentiation within the system and compression of the number of units of the system; • based on equalization: all units of the system are financed, including the less competitive ones; the principle can be carried out through allocating places at universities paid for by state subsidies, maintaining competitive wages, developing infrastructure in order to preserve and evenly distribute human capital across regions; • based on investment: funding can be used to develop the infrastructure of higher education, to enhance universities’ competitiveness, and to develop promising areas of training. in european countries, funding is a block grant (pruvot, 2015; oecd, 2020) 2 (table 1) which 2 oecd (2020). resourcing higher education:  challenges, choices and consequences. higher education. oecd publishing, paris, https://doi.org/10.1787/735e1f44-en. includes three components; the ratio between these three components is different in different universities, and funding in some european countries is long-term, i.e. the funding budget is set for up to four years (pruvot, 2017). the considered mechanisms correlate with the mechanisms of financing higher education in the russian federation. performance-based funding and funding formula are represented in the russian federation by subsidies provided to universities as part of the implementation of the government assignments3. the founders determine the volume of public services for organizations when devising the state assignment for the provision of public services for the next financial year and planning period, and when assessing the achievement of indicators of the volume of public services in the reporting financial year. permissible deviations from the target indicators of the state 3 order of the ministry of science and higher education of the russian federation of october 28, 2021 no. 989 “on approval of the methodology for the formation of the government assignment for the provision of educational services in the field of higher and secondary vocational education for the next financial year and planning period” http://r-economy.com https://dx.doi.org/10.1787/9789264298750-en https://dx.doi.org/10.1787/9789264309371-en https://dx.doi.org/10.1787/e9c1e648-en https://dx.doi.org/10.1787/e9c1e648-en https://doi.org/10.1787/735e1f44-en 213 r-economy.com r-economy, 2023, 9(2), 207–225 doi 10.15826/recon.2023.9.2.013 online issn 2412-0731 assignment are set5. funding formula manifests itself in the cost of providing one unit of service and achieving absolute values. for example, the target admission figures determine the number of places (hereinafter referred to as taf) for which the university can attract students with the appropriate exam scores; later on, the university receives state funding based on the number of enrolled students, but not more than the taf. excellence programs are implemented not only in european countries, but are also a tool for supporting universities’ development in china (the “211” and “985” projects, etc.), and russia (5/100 program, priority 2030, campus construction programs). in the russian federation, programs are implemented based on competition, on achieving roadmap indicators, i.e. set target indicators with certain funding: funding for the next financial year is distributed based on the achievement of the current year indicators. with regard to the distribution of funding through research foundations, the distribution mechanism is also based on competition, with the focus on achieving the set targets. 4 the figure was updated on august 16, 2023 (the content remained unchanged). 5 order of the ministry of education and science of the russian federation of march 15, 2021 no. 172 “on approval of the procedure for determining and applying the permissible (possible) deviations of the values of quality indicators and (or) volume from the established values of quality indicators and (or) the volume of public services when devising government assignments for the provision of public services for a federal state budgetary or autonomous for which the ministry of science and higher education of the russian federation exercises the functions and powers of the founder” higher education in the russian federation is funded through the students’ (their households’) finances as follows: • targeted funding a small share in the structure of russian universities’ income (4% of all funds for educational activities in general for universities of the russian federation6): tuition is paid by an organization in which a university graduate must work for a predetermined period (3 years, as a rule) after graduation. financing is provided by agreement between households and the organization, to a specific university or a university of their choice, the choice of the degree field is carried out in the same way; • household funds (private funding) are the main source of funding in some areas of training; • public funds through the provision of the number of “state-funded” places which are determined by the admission targets and represent a complex mechanism7. this mechanism can 6 vpo-2 form “information on the material, technical and information base, financial and economic activities of an educational organization of higher education” // ministry of education and science of russia. 2022. 7 order of the ministry of science and higher education of the russian federation of november 1, 2021 no. 996 “on approval of the procedure for conducting the competition for the distribution of target admission figures by areas of training and (or) enlarged groups of specialties and areas of training for studying in educational programs of higher education, and also by groups of research specialties and (or) research specialties for training programs for the training of research and pedagogical personnel in post-graduate school in state-funded places financed from the federal budget” // official internet portal of legal information. url: http://publication.pravo.gov.ru/ document/view/0001202111250038 (accessed on 05.02.2023) figure 4. correlation between mechanisms for financing higher education and principles of distribution source: compiled by the authors4 http://r-economy.com http://publication.pravo.gov.ru/ document/view/0001202111250038 http://publication.pravo.gov.ru/ document/view/0001202111250038 214 r-economy.com r-economy, 2023, 9(2), 207–225 doi 10.15826/recon.2023.9.2.013 online issn 2412-0731 combine all the three principles (figure 4). we assume that the equalization principle manifests itself when state-funded places are provided to remote regions with less competitive units of the system in order to preserve human capital in the regions, and investment principle is used for developing promising areas of training, or those that are important for the socio-economic sphere, but are less popular with applicants. thus, different mechanisms for financing higher education form different systems and their characteristics: increasing the gap between universities (agarkov, 2019; abankina, 2013), monopolizing the units of the system (sudakova, sandler, 2022), creating competitive universities and world-class universities, ensuring equal opportunities for higher education (allocating quotas for applicants from low-income families (dill, 1997), developing infrastructure. building a full picture of the state of higher education will make it possible to respond to the socio-economic, technological and global challenges of our time in a timely manner. despite the fact that there are a large number of studies focused on diagnosing the state of higher education (sandler, 2020; sandler, 2021), on assessing the degree of differentiation of the units within the system (kuzminov, 2014), in our opinion, they overlook an important characteristic of the higher education system principles for the distribution of funding. methods and data the principles of distribution of resources, in particular public funding in the russian higher education system, are identified through economic and statistical analysis methods. the statistical base for the study is the data of a largescale higher education monitoring project of 2019-2021 (education in russia, 2021)8,9. the database has statistical information for the period of 2019-2021, consisting of indicators for more than 650 public and private russian universities (2019 681, 2020 670, 2021 662 universities). the indicators used for the study include the number of students, the university’s income, the number of faculty members, and publication activity. all indicators are detailed by funding sources, mode of education, etc. the study tests the hypothesis about the distribution of funding shown in figure 4, assuming that universities located in regions with less competitive socio-economic characteristics, are funded according to the principle of equalization, i.e. universities in these regions are financed with less reference to qualitative indicators (for example, a decrease in the average use score; number of students in state-funded places; funding is equal to that of more competitive universities), in order to enhance their competitiveness. universities were divided into groups and subgroups for the analysis. to assess the socio-economic state of the region, the following indicators for express analysis were selected: the share of gratuitous revenues 8 information and analytical materials based on the results of monitoring the activities of educational institutions of higher education // mirea russian technological university. the main information and computing center. url: www.miccedu.ru 9 education in russia 2021. statistical bulletin. moscow: mirea russian technological university, 2021. 363 p. figure 5. the share of public funds for educational activities in the total income of public and private universities source: compiled by the authors based on the «data on russia taken from form № vpo-2 (2021). url: https://minobrnauki.gov.ru/action/stat/highed/» http://r-economy.com url: www.miccedu.ru https://minobrnauki.gov.ru/action/stat/highed/ 215 r-economy.com r-economy, 2023, 9(2), 207–225 doi 10.15826/recon.2023.9.2.013 online issn 2412-0731 in the structure of budget income shows how independent the budget is; grp per capita – shows how rich the region is; migration growth we assume that the negative value of this indicator evidences the unattractiveness of the region. in order to identify the equalization mechanism, it seems relevant to analyze revenues from budgets of all levels, since income from educational activities accounts for 66% of the total income of universities (2021), while the volume of finances for educational activities from the budgets of all levels accounts for 43% of the total income of universities. figure 5 shows the grouping of universities according to the share of public funds for educational activities in their total income, the intersection of the x and y values shows how many universities have a similar share. for example, in 2019, one university was 100% funded from the state budget, and all funding was directed to educational activities; the share of public funding for educational activities of 35 universities was 0. the graph for the share of federal funds in the structure of university income looks similar. since the study reveals that university financing is based on equalization, of interest are only those universities that have a share of federal funding in their budget structure. one of the first objectives of the study is to distinguish groups of regions according to their socio-economic characteristics: grp per capita; migratory inflow; income structure of the consolidated budget; priority regions for development10. the regions of the russian federation are highly differentiated, and the support of some regions is already reflected in the level of distribution of inter-budgetary transfers (sudakova, agarkov, 2022). thus, the indicators allow us to rank the objects of study, and categorise them into several groups. using the spss software application, the subjects of the russian federation are divided into 4 clusters figure 6 shows data visualization in three-dimensional space. table 2 presents the quantitative description in each group. 10 if we focus on the state program “balanced regional development”, then it covers a relatively small number of the constituent entities/subjects of the russian federation: the kaliningrad region, the north caucasian region, the far eastern federal district, the republic of crimea and the city of sevastopol. universities located in these subjects of the russian federation will be analyzed separately. table 2 characteristics of subjects (regions) by groups group number migration inflow, thousands of people average value minimum value maximum value number of subjects negative value positive value 1 10,7 2,9 23,9 2 4 2 9,4 4,3 113,0 10 23 3 1,0 7,6 15,4 19 21 4 2 -1,5 9,3 2 2 group number grp per capita, thousand rubles/person average value minimum value maximum value number of subjects * below the average value in the rf above the average value in the rf 1 1 112 9542 1 568 0 5 2 555 454 757 3 30 3 325 142 425 40 0 4 2 790 1 994 5 072 0 4 group number share of gratuitous receipts (subsidies, donations), % average value minimum value maximum value number of subjects** under 10% 11-39% over 40% 1 18,9 2,7 52 2 3 1 2 23 5,8 48 2 29 1 3 47 17 87 0 16 24 4 13 4,5 35 3 1 0 note: * to indicate the boundaries of the indicator, the average value for the russian federation is used, however, the indicators of the super-rich subjects of the russian federation (moscow, ynao, khmao, magadan, sakhalin regions) are excluded; average value 467 thousand rubles (2021); ** the boundaries of the level of gratuitous receipts are presented in accordance with paragraph 3 and paragraph 4 of article 130 of the budget code, the designated boundaries provide for a different level of authority of the subjects. source: compiled by the authors based on the gks.ru http://r-economy.com http://gks.ru 216 r-economy.com r-economy, 2023, 9(2), 207–225 doi 10.15826/recon.2023.9.2.013 online issn 2412-0731 table 3 shows the regions included in the group, and the characteristics of each group. thus, in terms of the identified socio-economic characteristics, the regions of groups 4 and 1 are the most favorable, and the subjects of group 3 have the worst characteristics. table 3 characteristics of groups of regions group group description number of subjects in the group, representatives 1 most subjects are characterized by a positive migration balance (for 4 out of 6), grp per capita is several times higher than the average level in the russian federation, while the share of gratuitous receipts has a different value in the group, but mostly no more than 39%. 6 subjects moscow, krasnoyarsk territory, st. petersburg, murmansk region, republic of sakha, kamchatka territory 2 most of the subjects in the group have a positive migration balance (23 out of 33), the average grp per capita is slightly higher than the average for the russian federation, the share of gratuitous receipts is in the range of 11-39%. 33 subjects, belgorod region, republic of tatarstan, perm territory 3 grp per capita is the lowest in the country, and the value is below the average for the russian federation; 50% of the subjects in the group have a negative balance; for 50% of the subjects the share of gratuitous receipts is mainly in the range of 11-39%, for the rest it is more than 39%. 40 subjects, pskov region, republic of kalmykia, dagestan, chechnya 4 positive balance of migration growth (with the exception of yamalnenets autonomous okrug and the magadan region), a low share of gratuitous receipts, grp per person is several times higher than the average the highest values in the russian federation. 4 subjects, khanty-mansi autonomous okrug, yamal-nenets autonomous okrug *, sakhalin region, magadan region note. * yamalo-nenets autonomous okrug is included in group 4; however, the region is excluded from further analysis, as it does not include universities that have students studying in state-funded places. source: compiled by the authors figure 7 shows a cartographic visualization of the distribution of regions (subjects) by groups. figure 6. visualization of groups in 3d space source: compiled by the authors based on the gks.ru in spss http://r-economy.com 217 r-economy.com r-economy, 2023, 9(2), 207–225 doi 10.15826/recon.2023.9.2.013 online issn 2412-0731 figure 7. groups of russian federation regions according to socio-economic characteristics source: compiled by the authors further analysis is based on the values of university performance indicators; the average values in subgroups are determined, the correlation between indicators is calculated, and a data reliability test is carried out. results first, 4 groups of regions were identified based on their socio-economic characteristics. further analysis is carried out within these groups, with universities divided into subgroups: (1) all universities within the group, (2) universities located in regions with positive migration (pm), (3) universities located in regions with negative migration (nm), (4) universities located in regions with negative migration and a share of gratuitous receipts of more than 40% (nm gr >40). the analysis for (2), (3), (4) is presented in the context of universities with a “special” status (hereinafter “_s”), i.e. those that are program participants (5/100, priority-2030) and/or those that have been assigned a status (national research university nru, federal university fu, etc.) and universities without a status and/or not participating in programs (hereinafter “_w”). in addition, data are presented separately for all universities, without dividing them into groups of regions. universities in group 1 are represented by heterogeneous characteristics: thus, along with more attractive regions and universities in moscow and st. petersburg, the group includes universities in the murmansk region, the republic of sakha, and the kamchatka territory. the calculation of average values showed (table 4) that as the region’s socio-economic indicators deteriorate, the share of income from the federal budget increases, mainly due to students studying in state-funded places, and so does the share of such students, while the average use score of students in state-funded places lowers (figure 8a). the situation with the indicators of research activity is different: they increase as the region’s socio-economic indicators improve, and universities with and without special status show the same trend, but universities that participate in state programs and/or those with a special status have higher indicator values (figure 8b). despite these two divergent trends, it should be noted that the university’s total income per academic staff member increases as the socioeconomic characteristics become worse, and participating universities and/or universities with status have higher values (figure 8b). http://r-economy.com 218 r-economy.com r-economy, 2023, 9(2), 207–225 doi 10.15826/recon.2023.9.2.013 online issn 2412-0731 ta bl e 4 a ve ra ge v al ue s fo r th e in di ca to rs o f u ni ve rs it ie s by g ro up s of r eg io ns g ro up 1 2 3 4 a ll un iv er si ti es su bgr ou ps a ll un ive rs iti es in th e gr ou p 1_ s 1_ w a ll un ive rs iti es in th e gr ou p 2_ s pm 2_ w p m 2_ s n m 2_ w n m a ll un ive rs iti es in th e gr ou p 3_ s pm 3_ w p m 3_ s n m 3_ w n m 3_ s n m g r >4 0 a ll un ive rs iti es in th e gr ou p pm n m al l_ s/ _w p m al l_ s/ _w n m n um be r of re gi on s 6 4 6 33 18 20 7 9 40 12 20 11 18 5 11 4 50 33 35 6 18 46 n um be r of u ni ve rs iti es 15 3 46 10 7 21 1 38 12 9 9 35 15 4 18 59 12 65 5 33 6 39 8 12 6 10 3 11 4 21 29 5 a ve ra ge n um be r of un iv er si tie s in th e re gi on , un iv er si ty /o ne re gi on 25 12 17 ,8 6 2 6, 5 1 3, 9 4 2 3 1 3, 6 1 3 2 8 4 3 19 1 6, 4 sh ar e of s tu de nt s st ud yi ng in s ta te -f un de d pl ac es , % 60 64 56 53 48 50 57 59 57 54 60 52 58 55 60 61 55 58 52 50 54 55 a ve ra ge u se s co re fo r st ud en ts s tu dy in g in s ta te fu nd ed p la ce s, u ni ts 64 71 62 65 71 63 69 64 62 66 59 66 62 57 56 40 62 63 69 51 67 60 a ve ra ge u se s co re fo r st ud en ts p ay in g fo r th ei r tu iti on th em se lv es 55 60 54 57 62 56 60 56 56 59 55 56 57 57 56 35 55 56 61 47 59 54 sh ar e of in co m e fr om th e fe de ra l b ud ge t, % 67 67 64 60 58 56 62 67 65 61 62 61 67 69 69 54 59 69 59 46 63 58 sh ar e of in co m e fr om ed uc at io na l a ct iv iti es , % 72 78 69 67 63 63 69 74 70 63 68 69 73 68 76 74 66 74 66 61 69 65 in co m e fo r ac ad em ic s ta ff, ru bl es /p er so n 46 50 51 50 44 87 33 09 34 57 29 80 39 11 34 94 26 76 27 24 25 07 28 22 28 25 28 76 28 59 54 95 31 58 32 06 34 11 49 17 32 46 30 36 in co m e fr om r & d fo r ac ad em ic s ta ff, r ub le s/ pe rs on 30 9 68 1 23 5 23 8 45 2 16 7 34 3 13 0 16 4 24 1 14 4 24 0 15 0 20 0 13 4 21 2 23 6 15 8 39 8 25 7 28 0 17 1 http://r-economy.com 219 r-economy.com r-economy, 2023, 9(2), 207–225 doi 10.15826/recon.2023.9.2.013 online issn 2412-0731 g ro up 1 2 3 4 a ll un iv er si ti es su bgr ou ps a ll un ive rs iti es in th e gr ou p 1_ s 1_ w a ll un ive rs iti es in th e gr ou p 2_ s pm 2_ w p m 2_ s n m 2_ w n m a ll un ive rs iti es in th e gr ou p 3_ s pm 3_ w p m 3_ s n m 3_ w n m 3_ s n m g r >4 0 a ll un ive rs iti es in th e gr ou p pm n m al l_ s/ _w p m al l_ s/ _w n m n um be r of c ita tio ns in w os p er 1 00 a ca de m ic s ta ff m em be rs , u ni t/ pe rs on 19 2 45 8 13 3 15 5 34 5 16 3 17 5 87 86 14 3 90 12 5 70 14 6 56 36 14 1 86 28 0 17 9 14 4 12 4 n um be r of c ita tio ns in sc op us p er 1 00 a ca de m ic st aff m em be rs , u ni t/ pe rs on 25 3 62 2 16 8 20 2 43 3 19 2 27 7 11 6 12 7 22 0 11 9 20 0 11 1 21 3 96 74 18 3 13 3 37 2 21 6 23 0 15 3 n um be r of fu lltim e st ud en ts fo r ac ad em ic s ta ff, st ud en t/ on e st aff m em be r 10 11 10 11 12 11 12 11 11 12 10 13 10 13 10 11 11 11 12 11 13 10 n um be r of s tu de nt s fo r ac ad em ic s ta ff, s tu de nt /o ne st aff m em be r 16 14 17 19 19 20 18 19 19 17 18 22 19 24 20 24 18 20 17 20 21 19 sh ar e of fu lltim e st ud en ts , % 67 78 59 62 66 56 68 61 59 70 56 59 57 58 57 48 62 58 69 53 62 56 sh ar e of s tu de nt s in ba ch el or ’s de gr ee p ro gr am s, % 68 63 69 66 62 69 68 65 69 59 72 66 65 67 67 83 69 67 61 75 67 71 n ot e: “ 1_ s” (2 _s ; 3 _s ) ca lc ul at io n fo r u ni ve rs iti es w ith a sp ec ia l s ta tu s, i.e . p ar tic ip at in g in th e pr og ra m s ( n u /f u , l ea di ng e ng in ee ri ng s ch oo ls le s, 5 /1 00 , p ri or ity 2 03 0) a nd “ 1_ w ” (2 _w ; 3 _w ; 4 _w ) – u ni ve rs iti es w ith ou t a sp ec ia l s ta tu s. n m a nd p m ca lc ul at io n fo r un iv er si tie s l oc at ed in re gi on s w ith n eg at iv e an d po si tiv e va lu es o f m ig ra tio n flo w s, n m g r > 40 ca lcu la tio n fo r u ni ve rs iti es lo ca te d in re gi on s w ith n eg at iv e va lu es o f m ig ra tio n flo w s a nd w ith a sh ar e of g ra tu ito us re ce ip ts o f m or e th an 4 0% (c al cu la tio n ac co rd in g to p ar ag ra ph 4 , a rt ic le 1 30 of th e r f bu dg et c od e) . 1 , 2 , 3 , 4 un iv er si tie s l oc at ed in re gi on s o f g ro up s 1 , 2 , 3 , 4 . so ur ce : c om pi le d by th e au th or s b as ed o n th e «d at a on r us si a ta ke n fr om f or m № v p o -2 (2 02 1) . u r l: h tt ps :// m in ob rn au ki .g ov .r u/ ac tio n/ st at /h ig he d/ » http://r-economy.com https://minobrnauki.gov.ru/action/stat/highed/ 220 r-economy.com r-economy, 2023, 9(2), 207–225 doi 10.15826/recon.2023.9.2.013 online issn 2412-0731 ta bl e 5 c oe ffi ci en t o f v ar ia ti on b y gr ou ps , % g ro up 1 2 3 a ll un iv er si ti es su bgr ou ps a ll un ive rs it ie s in th e gr ou p 1_ s a ll un ive rs it ie s in th e gr ou p 2_ s p m 2_ s n m a ll un ive rs it ie s in th e gr ou p 3_ s p m 3_ s n m 3_ s n m g r > 40 p m n m al l_ s p m al l_ s n m al l_ w g r > 40 sh ar e of s tu de nt s st ud yi ng in s ta te -f un de d pl ac es 9 7 11 13 9 10 11 14 14 11 8 13 12 15 a ve ra ge u se s co re fo r st ud en ts s tu dy in g in s ta te fu nd ed p la ce s 5 10 5 5 3 5 4 4 5 11 4 5 4 5 a ve ra ge u se s co re fo r st ud en ts p ay in g fo r th ei r tu iti on th em se lv es 8 7 7 4 4 7 3 3 2 11 6 4 4 2 sh ar e of in co m e fr om th e fe de ra l b ud ge t 13 11 11 7 8 11 11 13 12 13 8 10 11 17 sh ar e of in co m e fr om ed uc at io na l a ct iv iti es 11 7 19 13 16 10 10 12 9 20 17 19 22 33 in co m e fo r ac ad em ic s ta ff 10 16 14 16 26 11 10 11 13 20 17 19 22 13 in co m e fr om r & d fo r ac ad em ic s ta ff 49 46 44 40 26 32 41 32 37 43 31 47 32 37 n um be r of c ita tio ns in w os p er 1 00 a ca de m ic s ta ff m em be rs 42 35 65 78 38 64 46 72 91 67 51 79 56 91 n um be r of c ita tio ns in sc op us p er 1 00 a ca de m ic st aff m em be rs 40 37 59 71 38 46 47 64 91 59 42 70 52 91 n um be r of fu lltim e st ud en ts p er a ca de m ic s ta ff m em be r 6 8 7 8 7 9 11 11 13 8 8 9 10 13 n um be r of s tu de nt s pe r ac ad em ic s ta ff m em be r 14 6 10 14 11 13 12 11 12 11 11 13 13 12 sh ar e of fu lltim e st ud en ts 7 3 7 14 11 8 10 10 14 8 8 11 11 14 sh ar e of b ac he lo r’s d eg re e st ud en ts 8 8 7 14 11 9 23 10 11 8 10 17 10 11 so ur ce : c om pi le d by th e au th or s b as ed o n th e «d at a on r us si a ta ke n fr om f or m № v p o -2 (2 02 1) . u r l: h tt ps :// m in ob rn au ki .g ov .r u/ ac tio n/ st at /h ig he d/ » http://r-economy.com https://minobrnauki.gov.ru/action/stat/highed/ 221 r-economy.com r-economy, 2023, 9(2), 207–225 doi 10.15826/recon.2023.9.2.013 online issn 2412-0731 8a) 8b) figure 8. comparison of average values in university sub-groups source: compiled by the authors based on the «data on russia taken from form № vpo-2 (2021). url: https://minobrnauki.gov.ru/action/stat/highed/» table 5 shows the coefficient of variation for groups and sub-groups, the deviation of the data from the average value in the sample is within 10. however, if the average use score in groups 2 and 3 is within 5, then the variation of specific indicators (“income from r&d per academic staff member” and citation rates) exceed the allowable values (more than 30%), which indicates the heterogeneity of the sample according to these indicators. in order to clarify the mechanisms for distributing funding, we conducted a correlation analysis of research-related indicators (table 6): a positive correlation between the indicators will allow us to conclude that funding is distributed based on competition, while the absence of such correlation means distributions based on equalization. table 6 indicators of correlation coefficients by indicators of universities coefficients 2_s pm 2_s nm 3_s, pm, gr < 40 _s pm _s, pm, gr < 40 _s nm university income from r&d and the number of citations in wos** 0,4 0,3 0,6 0,5 0,4 0,3 university income from r&d and the number of citations in scopus** 0,4 0,4 0,7 0,5 0,5 0,4 university income from r&d and the number of publications in wos*** 0,6 0,5 0,7 0,6 0,6 0,4 university income from r&d and the number of publications in scopus*** 0,6 0,7 0,6 0,6 0,5 0,5 data validity (calculated in spss, 95% confidence interval) 100% 100% 100% 100% 100% 100% cronbach’s alpha reliability coefficient based on standardized items α>0,7 α>0,8 α>0,75 α>0,7 α>0,7 α>0,6 cronbach’s alpha reliability coefficient based on standardized items α>0,6 α>0,5 α>0,6 α>0,6 α>0,5 note: *the number of students admitted for full-time studies in bachelor’s and specialist’s degree programs in state-funded places based on the results of the unified state examination; **the number of citations of papers published over the past 5 years, indexed in the information and analytical system web of science core collection (or scopus), per 100 faculty members; ***the number of publications indexed in the web of science core collection (or scopus) per 100 faculty members. source: compiled by the authors based on the «data on russia taken from form № vpo-2 (2021). url: https://minobrnauki. gov.ru/action/stat/highed/» http://r-economy.com https://minobrnauki.gov.ru/action/stat/highed/ https://minobrnauki.gov.ru/action/stat/highed/ https://minobrnauki.gov.ru/action/stat/highed/ 222 r-economy.com r-economy, 2023, 9(2), 207–225 doi 10.15826/recon.2023.9.2.013 online issn 2412-0731 there is a correlation between the following indicators: (*) income from r&d and (*) the number of publications (table 6), with the value of the correlation coefficient decreasing as the region’s socio-economic characteristics deteriorate. it should be noted that the correlation coefficient between similar indicators for universities without a status is below 0.4. the presented data allow us to make a conclusion about a possible difference in the mechanism for distributing funding among different groups of regions. thus, regions with less favorable socioeconomic conditions receive budget funding with a lesser focus on university performance indicators. another pattern was identified: as the socioeconomic characteristics of the region improve (in our case, universities in group 3), funding is directed to the development of research activity based on the principles of equalization. the correlation between the indicators of the universities’ educational activities allows us to draw a conclusion regarding the mechanism for distributing funding: less correlation between indicators related to research activities is observed among universities in group 3, as well as among universities without a special status in group 2. our study comes to a slightly different conclusion than that presented in the work of abankina i.v., which states that “foreign countries try to increase financial support for higher education and the system’s flexibility, and not pursue a policy of focusing efforts solely on supporting leaders, like in russia” (abankina, 2019). conclusion the study is aimed at determining the principles for the distribution of funding among russian universities. the significance of the study is justified by the fact that the importance of financing higher education as a means of investing in the public good has been proved more than once. thus, the study analyzed foreign funding mechanisms and compared them with russian practice, which has similar foundations: competition-based funding (mainly grants from research foundations), development programs, funding by formula (government assignments), etc. the analyzed funding mechanisms are classified according to the principle of distribution. based on the accumulated experience, the study puts forward a hypothesis about the possible existence of two principles for financing russian higher education. the hypothesis was partially confirmed. however, the additional findings obtained, expand the understanding of higher education funding. first, as the region’s socio-economic characteristics deteriorate, there is an increase in the value of some indicators (for example, an increase in the share of income from the federal budget; the share of students studying in statefunded places, the number of students per 1 teaching staff member) and a significant decrease in other indicators (for example, the average use score, the share of full-time students). these data do not allow us to make an unambiguous conclusion that the hypothesis was confirmed, since the change in indicators may be due to lower competition among university applicants (as a result, there is a decrease in the average use score, and an outflow of applicants with higher scores to other regions); the increase in the share of federal funding and the share of students studying in state-funded places may be due to lower demand for non-state-funded (“commercial”) places. however, an important addition to these conclusions is the increase in the indicator of income per academic staff member as the socio-economic characteristics of the region where the universities (within the group) are located, deteriorate. secondly, one more conclusion related to scientific activity was made during the study. as the region’s socio-economic characteristics improve, the values of indicators related to research activity also improve. the analysis carried out allows us to make the following conclusions: the distribution of funding among russian universities is based on the principles of quasi-competition (analysis of data on universities with a special status) and equalization (as the region’s socio-economic characteristics deteriorate). universities located in regions with low indicators of socio-economic development are financed mainly based on the principle of equalization, for the most part, with respect to educational activities, and, as the socio-economic situation in the region improves, funding based on equalization affects the universities’ research activities. universities in group 4 stand out from the general trend (the socalled “wealthy northern regions”). another more obvious conclusion is that research activities of universities that participate in state programs are funded on competitive basis, http://r-economy.com 223 r-economy.com r-economy, 2023, 9(2), 207–225 doi 10.15826/recon.2023.9.2.013 online issn 2412-0731 while other universities have less correlation between the indicators, as a result of which we can assume that research activities of other universities are funded based on the principles of equalization. and a less obvious conclusion is that the correlation between the indicators of educational activities in universities-participants of state programs is low and in some cases negative (with high use scores, the share of students in state-funded places is different). the results of the study expand the understanding of the principles of funding distribution in the russian higher education system: in contrast to most studies on the concentration of resources in a limited number of universities, the study concludes that resources are also distributed based on equalization, supporting less competitive units of the system, and also that funding is sent to regions with unstable socio-economic characteristics. the study can be expanded by detailing the indicators for ranking regions, as well as adding an analysis of the areas of training in the regions to identify the principle of financing based on investment. references abankina, i., aleskerov, f., belousova, v., gokhberg, l., zinkovsky, k., kiselgof, s.&shvydun, s. (2013) tipologiya i analiz nauchno-obrazovatel’noy rezul’tativnosti rossiyskikh vuzov [a typology and analysis of russian universities’ performance in education and research]. foresight russia, 7(3), 48-63 abankina, i.v. (2019). financing of education: trend on personalization. journal of the new economic association, 1(41), 216-225. doi: 10.31737/2221-2264-2019-41-1-11. agarkov, g. a., sandler, d. g., sudakova, a. e. & sushchenko, a. d. (2019). differentiation of universities by the level of teaching staff income: correlation with the quality of education and research productivity. perspektivy nauki i obrazovania = perspectives of science and education, 42 (6), 456-472. doi: 10.32744/pse.2019.6.38. agasisti, t. (2011). performances and spending efficiency in higher education: a european comparison through non-parametric approaches. education economics, 19, 199–224. doi: 10.1080/09645290903094174. agasisti, t.& shibanova, e. 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(2015). the knowledge capital of nations: education and the economics of growth. cambridge, ma: mit press, 262. becker, w. e.& lewis, d. r. (1993). higher education and economic growth. springer science, business media. new york, 184. doi: 10.1007/978-94-015-8167-7 kolosnitsyna, m.g. & ermolina, yu.e. (2021). public spending on education and economic growth: cross-country analysis. voprosy statistiki, 28(3), 70-85. doi: 10.34023/2313-6383-202128-3-70-85 kuzminov, ya., semyonov, d.& froumin, i. (2013). university network structure: from the soviet to the russian ‘master plan’. voprosy obrazovaniya = educational studies moscow, 4, 8-69. doi: 10.17323/1814-9545-2013-4-8-69. maneejuk, p. & yamaka, w. (2021). the impact of higher education on economic growth in asean-5 countries. sustainability, 13, 520. doi: 10.3390/su13020520 marginson, s. (2017). the public good created by higher education institutions in russia. voprosy obrazovaniya = educational studies moscow, 3, 9-36. doi: 10.17323/1814-9545-2017-3-8-36. matveeva, n., sterligov, i.& yudkevich, m. m. (2021). the effect of russian university excellence initiative on publications and collaboration patterns. journal of informetrics, 15(1), article 101110. doi: 10.1016/j.joi.2020.101110. musgrave, r.a. (1969). fiscal systems. new haven and london: yale university press. 397. pruvot, e. b., claeys-kulik, a.l.& estermann, t. (2015) designing strategies for efficient funding of universities in europe. define project paper. brussels: european university association, a. curaj et al. (eds.), the european higher education area. doi: 10.1007/978-3-319-20877-0_11. p. 153-168. pruvot, e.& estermann, t. (2017). university autonomy in europe iii: the scorecard, eua. 76 p. sandler, d. g. (2021). analyzing the state of regional higher education systems. socium and power, 4 (90), 20-37. doi 10.22394/1996-0522-2021-4-20-37. sandler, d. g., sudakova, a. e.& tarasyeva, t. v. (2020). drivers for development in regional higher education. economy of region, 16(4), 1087-1103, doi: 10.17059/ekon.reg.2020-4-6 sudakova, a.e.& agarkov, g.a. (2022). budget centralization and decentralization of the russian federation’s public finances: approaches to the definition. surgut state university journal, 2 (36), 60-69. doi: 10.34822/2312-3419-2022-2-60-69 sudakova, а. е.& sandler, d.g. (2022). institutional monopoly of the higher education system: national and regional level. economy of regions, 18(4), 1135–1152. doi: 10.17059/ekon.reg.2022-4-12 sudakova, a.e., tarasyev, a.a.& koksharov, v.a. (2021). trends in the migration of russian scholars: the regional dimension. terra economicus 19(2): 91–104. doi: 10.18522/2073-66062021-19-2-91-104 curaj a., matei l., pricopie r., salmi j.& scott p. (2015). the european higher education area between critical reflections and future policies. springer, 906. doi: 10.1007/978-3-319-20877-0 varghese n.v. (2021). financing of higher education in india. quality mandate for higher education institutions in india. university grants commission: chandu press, 223-235. varghese n.v.& panigrahi j. (2023). innovations in financing of higher education: an overview. in: varghese, n., panigrahi, j. (eds) financing of higher education. springer, singapore. doi: 10.1007/978-981-19-7391-8_1 yonezawa, a. & kaiser, f. (2003). system-level and strategic indicators for monitoring higher education in the twenty-first century, studies on higher education series, unesco, bucharest. information about the authors anastasia e. sudakova – candidate of economics, associate professor, senior researcher, ural federal university (19 mira street, 620002, russia, yekaterinburg,); e-mail: ae.sudakova@gmail.com, https://orcid.org/0000-0002-3791-1129 dahel mustafa saleh dahel lecturer, al-furat al-awsat technical university (54003, iraq, najaf, babylon-najaf street, 1); e-mail: mustafaaladli@gmail.com, orcid 0000-0002-3610-5088 article info: received february 13, 2023; accepted june 16, 2023 http://r-economy.com http://dx.doi.org/10.1007/978-3-319-20877-0_11 https://orcid.org/0000-0002-3791-1129 225 r-economy.com r-economy, 2023, 9(2), 207–225 doi 10.15826/recon.2023.9.2.013 online issn 2412-0731 информация об авторах судакова анастасия евгеньевна – к.э.н., доцент, старший научный сотрудник, уральский федеральный университет (620002, россия, г. екатеринбург, ул. мира, 19); e-mail: ae.sudakova@gmail.com, orcid: 0000-0002-3791-1129 дахел мустафа салех дахел – лектор, аль-фурат аль-авсат технический университет (54003, ирак, г. наджаф, ул. вавилон-наджаф, 1); e-mail: mustafaaladli@gmail.com, orcid: 0000-0002-3610-5088 информация о статье: дата поступления 13 февраля 2023 г.; дата принятия к печати 16 июня 2023 作者信息 苏达科娃·阿纳斯塔西娅·叶夫根涅夫娜——经济学博士，高级研究员，乌拉尔联邦大 学（邮编：620002，俄罗斯，叶卡捷琳堡市，米拉大街19号）；邮箱：ae.sudakova@ gmail.com, orcid: 0000-0002-3791-1129 达赫尔·穆斯塔法·萨利赫·达赫尔——讲师，al-furat al-awsat技术大学（邮 编：54003，伊拉克，纳杰夫市，巴比伦纳杰夫大街1号）；邮箱：mustafaaladli@ gmail.com, orcid: 0000-0002-3610-5088 http://r-economy.com mailto:ae.sudakova@gmail.com mailto:ae.sudakova@gmail.com mailto:ae.sudakova@gmail.com mailto:ae.sudakova@gmail.com r-economy, 2020, 6(1), 5–13 doi: 10.15826/recon.2020.6.1.001 5 www.r-economy.ru online issn 2412-0731 original paper © zinovyeva, e.g., balynskaya, n.r., koptyakova, s.v., akhmetzianova, o.o., 2020 doi 10.15826/recon.2020.6.1.001 analysis of the residential mortgage market in the ural federal district e.g. zinovyeva1 , n.r. balynskaya1, s.v. koptyakova1, o.o. akhmetzianova2 1 nosov magnitogorsk state technical university, magnitogorsk, russia; e-mail: ekaterina_7707@mail.ru 2 university of science and technology of china, hefei, anhui, china abstract the relevance of this study stems from the fact that it analyzes the current situation on the mortgage market in russia: the influence of macro-economic factors causes a fall in collateral value, dramatic increase in mortgage default and poor performance of the agency for housing mortgage lending (ahml). the study is aimed at investigating the current state of residential mortgage lending on the regional level in russia by focusing on the case of the ural federal district. the study considers the interests of all the participants of this market: individual borrowers, state authorities, financial and credit institutions engaged in mortgage lending. the study analyzes statistical data on the primary residential mortgage market in the ural federal district provided by the central bank of the russian federation, federal state statistics service and the ahml. results. modern approaches to mortgage system evaluation are compared in order to identify and systematize the key criteria and statistical indicators characterizing the current state of this form of lending relationships. the analysis also brings to light the negative trends in mortgage lending in the ural federal district. as a part of our further research, we are going to develop a procedure for evaluating the performance of a mortgage system. keywords residential mortgage, primary mortgage market, lenders, balanced autonomy model, single-tier and two-tiered models, mortgage institutions, lending market анализ состояния рынка ипотечного жилищного кредитования в уральском федеральном округе е.г. зиновьева1 , н.р. балынская1, с.в. коптякова1, о.о. ахметзянова2 1 магнитогорский государственный технический университет им. г.и. носова, магнитогорск, россия; e-mail: ekaterina_7707@mail.ru 2 научно-технический университет китая, хэфэй, китай аннотация актуальность статьи обусловлена тем, что макроэкономическая ситуация последних лет оказала самое серьезное влияние на быстроразвивающуюся систему ипотечного кредитования в российской федерации, обнажив целый комплекс проблем – падение стоимости залога, резкий рост просроченной задолженности по выданным ипотечным кредитам, низкая эффективность работы агентства по ипотечному и жилищному кредитованию. цель исследования – проанализировать состояние ипотечного жилищного кредитования в региональном разрезе на примере уральского федерального округа, учитывая интерес всех участников: населения, государства и финансово-кредитных институтов, имеющих в распоряжении временно свободные денежные средства и предоставляющие их во временное пользование. исследование базируется на аналитическом обзоре статистической информации, характеризующей первичный рынок ипотечного жилищного кредитования в уральском федеральном округе. информационно-эмпирическую базу исследования составили статистические материалы центрального банка российской федерации, федеральной службы государственной статистики, официальные отчетные данные агентства по ипотечному и жилищному кредитованию. результаты. по итогам сравнительного анализа многообразия подходов к оценке эффективности функционирования системы ипотечного кредитования определены и систематизированы основополагающие критерии и статистические показатели, характеризующие качество данной формы кредитных отношений; выявлены негативные тенденции, характерные для системы ипотечного кредитования уральского федерального округа. в  рамках дальнейшего исследования будет предложен алгоритм функционирования системы ипотечного кредитования. ключевые слова ипотечное жилищное кредитование, первичный рынок ипотечного жилищного кредитования, кредитные организации, модель сбалансированной автономии, одноуровневая и двухуровневая модель, ипотечные институты, кредитный рынок for citation zinovyeva, e.g., balynskaya, n.r., koptyakova, s.v., & akhmetzianova, o.o. (2020). analysis of the residential mortgage market in the ural federal district. r-economy, 6(1), 5–13. doi: 10.15826/recon.2020.6.1.001 для цитирования zinovyeva, e.g., balynskaya, n.r., koptyakova, s.v., & akhmetzianova, o.o. (2020). analysis of the residential mortgage market in the ural federal district. r-economy, 6(1), 5–13. doi: 10.15826/recon.2020.6.1.001 http://doi.org/10.15826/recon.2020.6.1.001 http://10.15826/recon.2020.6.1.001 mailto:ekaterina_7707@mail.ru mailto:ekaterina_7707@mail.ru 6 www.r-economy.ru r-economy, 2020, 6(1), 5–13 doi: 10.15826/recon.2020.6.1.001 online issn 2412-0731 introduction the recent macro-economic situation has had a considerable effect on the rapidly growing mortgage lending system in russia, causing a fall in collateral value, a dramatic increase in mortgage default and poor performance results of the agency for housing mortgage lending (ahml). nevertheless, despite these negative conditions, the experience of developed countries shows that in a market economy, this form of credit relationships is one of the key instruments to handle socio-economic problems and ensure the affordabi lity of housing. mortgage market contributes to the development of a competitive economy, its stabilization and modernization, it also helps decrease inflation and social tension by proving people with housing and stimulating construction and other industries, by stabilizing the financial market and enhancing investment. mortgage lending can differ from country to country due to differences in their socio-economic development, financial and credit systems, legislation regulating mortgage relationships and the corresponding models of such relationships. in denmark, most mortgages have been provided by one of the major  mortgage banks for 150 years. in germany, loans are offered not only by mortgage banks but also by building societies (bausoarkassen)1. in the usa, although mortgages are issued by commercial banks, savingsand-loan associations, and credit unions, it is the government sponsored enterprises (gses) established by the us congress which hold a significant part of the national mortgage portfolio2. in the process of building a comprehensive residential mortgage system of its own, russia can benefit from the experience of mortgage lending services accumulated by foreign banks. compa rative analysis of international models of mortgage lending can provide us with insights about the model that may hold most promise for russia. in this article, we are also going to explore the current state of mortgage lending in russian regions by focusing on the case of the ural federal district, in particular by looking at the interests of the key participants of the mortgage market: indi1 getting a mortgage in germany. expatica site. retrieved from: http://www.expatica.com/de/housing/how-toget-amortgage-in-germany_740222.html (19.04.2017). 2 compare mortgage options. u.s. bank national association site. retrieved from: https://www.usbank.com/homeloans/mortgage/compare-mortgage-options.aspx (19.04.2017). vidual borrowers, state authorities, financial and credit institutions engaged in mortgage lending. this general aim comprises the following specific objectives: we are going to consider the existing models of mortgage lending in different countries (usa, canada, uk and germany); investigate the main challenges faced by the mortgage lending system in russia; and conduct a comprehensive analysis of the primary mortgage market and its efficiency by using the case of the ural federal district. as for the practical implications of this study, the described model of mortgage lending can be used by regional authorities in strategizing and decision-making in the sphere of socio-economic development of their respective regions. our findings can also be useful for devising ways of stimulating housing construction through policy-making and legislation. our research can be of interest to housing construction companies seeking to enhance their cooperation with the regional authorities. the results of this study can be used for rationalization of the use of funds in russian regions and municipalities and their reallocation to address issues in the sphere of housing construction as a part of regional socio-economic policies. conceptual and methodological framework the conceptual and methodological framework of this study is based on classical and contemporary, theoretical and applied research works on mortgage lending written by russian and international scholars. it also relies on the main legal acts regulating lending relationships in general and mortgage lending in particular. at the centre of our study is the category ‘model of mortgage lending’, which corresponds to specific aspects of mortgage lending in diffe rent countries determined by their socio-economic development, financial and credit systems, and laws governing mortgage lending. it should be noted that the model of mortgage lending is usually understood as a set of characteristics and relationships within the system of mortgage lending in a specific country [1]. in international practice, there are two basic models of attracting funds to the sphere of mortgage lending: these are single-tier (european countries) and two-tiered (usa, uk and canada) models [2]. in both models funds are attrac ted by means of refinancing of mortgage markets http://doi.org/10.15826/recon.2020.6.1.001 http://www.expatica.com/de/housing/how-to-get-amortgage-in-germany_740222.html http://www.expatica.com/de/housing/how-to-get-amortgage-in-germany_740222.html https://www.usbank.com/homeloans/mortgage/compare-mortgage-options.aspx https://www.usbank.com/homeloans/mortgage/compare-mortgage-options.aspx r-economy, 2020, 6(1), 5–13 doi: 10.15826/recon.2020.6.1.001 7 www.r-economy.ru online issn 2412-0731 through assignment of home loans by secondary market operators and securitization3. for all the local variations, mortgage lending tends to follow some general patterns, which can be described as three basic models: contractual-savings, se condary market model (or american model) and mortgage bank model [3; 4]. as the experience of developed countries shows, rational state policy in the sphere of mortgage lending may ensure the transformation of this sphere into a self-financing sector, capable of providing stable development of a housing market. mortgage serves as a catalyst of the real estate market and interconnected spheres since growth in effective demand for housing stimulates construction, manufacturing of building materials and equipment as well as innovation in architecture. it also contributes to growth of retail industry and enhances employment rates [5]. in developed countries, the mortgage mechanism of housing acquisition is prioritized by the state socio-economic policy due to its efficiency: it helps attract considerable investment to the real sector of economy by encouraging housing construction. moreover, affordable mortgages help the state meet the housing needs of its citizens. a long history of mortgage lending has resulted in the appearance of three classical models [6; 7]: truncated-open, balanced-autonomous and expanded-open. let us consider them in more detail: 1. the balanced autonomous model (contractual savings system) is a model of mortgage lending based on the loan and savings principle similar to private building societies such as german bausparkasse, french livret epargne logement, and american savings and loans. the total portfolio of credit resources is formed not from the funds attracted on the open capital market but from the savings of future borrowers following the same principle as mutual funds [8]. in this model, lenders are not only mortgage banks, but also specialized savings banks such as building societies and savings banks [9]. an essential element of this model is the housing contractual savings, exceedingly wide spread in germany, france, and australia. recently, they have also come in use in the new eu member states such as the czech 3 want a mortgage? forbes site. retrieved from: https:// www.forbes.com/sites/nickclements/2016/09/30/want-amortgagethe-credit-score-used-by-mortgage-companies-willsurprise-you (19.04.2017). republic, croatia, slovakia and hungary4. apart from europe, this model is also applied in angola, indonesia, morocco, thailand, tunisia, and chile. we believe, however, that the balanced autonomous model is not well-suited for russia for the following reasons: first, it limits the amount of attracted funds to the savings of contributors interested in obtaining credits for buying or building homes and does not include savings and resources of other economic entities; and second, inflation makes it impossible to set acceptable mortgage rates [10]. 2). the truncated-open model (traditional, single-tier) is limited to the primary market of mortgage lending where lenders receive mortgage bonds from their clients and use them as security to attract external investment. this model is typical of western europe (the uk, france, denmark, and spain), eastern europe (bulgaria, poland and hungary), israel, australia and some latin american countries. in eu countries, however, mortgage rates vary significantly (the difference can be more than two times) [11; 12]). in spain, the terms and conditions of a mortgage credit are the most liberal in europe: a buyer can borrow up to 100% of the property’s value for up to 35 years, with the mortgage origination fee of 1.5% of the property value. however, if a buyer decides to use a construction mortgage, they could save up to a half of the origination fee [13]. in france, a typical mortgage allows a buyer to borrow up to 80% of the property’s value for up to 25 years. french banks’ lending standards are generally more conservative than in some other european countries and the recent cuts to subsidized interest-free loans for home purchasing have changed the situation as banks started to raise their mortgage lending standards [14]. in the uk, the loan to value ratio is up to 70% while the mortgage rates continue falling and at the moment are at the level of 3.14%. the minimum down payment is about 15% of the property’s value [15]. although the truncated-open (traditional, single-tier) model of mortgage lending is a prototype of the market model of lending relationships, we believe that it would not be a good fit to the russian national context. a key characteristic of the truncated-open model is the direct dependence of mortgage rates on the general state and stability of the country’s economy, which also affects mortgage banking 4 top 5 countries with the lowest mortgage rates. tranio site. retrieved from: https://tranio.com/switzerland,japan,finland,germany,luxembourg/analytics/top_5_countries_with_ the_lowest_mortgag e_rates_5108/ (19.04.2017). http://doi.org/10.15826/recon.2020.6.1.001 https://www.forbes.com/sites/nickclements/2016/09/30/want-a-mortgagethe-credit-score-used-by-mortgag https://www.forbes.com/sites/nickclements/2016/09/30/want-a-mortgagethe-credit-score-used-by-mortgag https://www.forbes.com/sites/nickclements/2016/09/30/want-a-mortgagethe-credit-score-used-by-mortgag https://www.forbes.com/sites/nickclements/2016/09/30/want-a-mortgagethe-credit-score-used-by-mortgag https://tranio.com/switzerland,japan,finland,germany,luxembourg/analytics/top_5_countries_with_the_l https://tranio.com/switzerland,japan,finland,germany,luxembourg/analytics/top_5_countries_with_the_l https://tranio.com/switzerland,japan,finland,germany,luxembourg/analytics/top_5_countries_with_the_l 8 www.r-economy.ru r-economy, 2020, 6(1), 5–13 doi: 10.15826/recon.2020.6.1.001 online issn 2412-0731 activities in specific favourable and unfavourable periods. in practice, within this model, there are no universal standard parameters of mortgages, instead such parameters as the costs and terms of home loans are usually set by each individual mortgage bank depending on specific conditions. while the scope of mortgage service is limited in russia, the mortgage rates tend to be higher and the mortgage terms are shorter than in its european counterparts. 3. the expanded open model (model of the secondary mortgage market, two-tiered) is also commonly referred to as the ‘american mortgage model’ because it is the most popular in the us5 [16]. the primary mortgage market is where borrowers can obtain home loans directly from primary lenders while the secondary market deals with sales of securities or bonds collateralized by the value of mortgage loans. the expanded open model means that a person with a certain annual income purchases a move-in ready home paying in cash only an insignificant part of its value (10–20%) while the rest is borrowed from a specialized mortgage bank with the borrower’s property (either already owned or being purchased) used as a collateral (at the interest rate of 7–9%). as a rule, it takes about 15–30  years to repay such mortgage loans depending on the borrower’s annual income and the mortgage type. within this model, the primary lender can refinance the issued mortgages either by selling them directly to investors or specialized institutions of the secondary market (secondary market operators) or by exchanging them for mortgage-backed securities [17; 18]. the expanded open model is more suitable for the russian context since, unlike the contractual savings system, it does not require much time for the accumulation of natural persons’ funds in the initial period [19]. this means that the expanded open model can be implemented much faster and on a massive scale. our analysis of different models of mortgage lending has led us to the conclusion that the expanded open model is optimal for russia (figure  1) and that it will help make housing more affordable and accessible for russian citizens. since this model is open and oriented towards obtaining resources from the free market, it is quite 5 homebuying step by step. canada mortgage and housing corporation site. retrieved from: https://www.cmhcschl. gc.ca/en/co/buho/step-by-step/index.cfm (19.04.2017). susceptible to changes in the financial and credit market. the stability of the system, however, is ensured by the government through legal, financial and licencing regulation. the government can also give guarantee and insurance against risks, provide tax preferences and offer targeted subsidies. it should be noted that the structure of the current legal framework for mortgage lending in russia is oriented towards building a secondary mortgage market, that is, it relies on the expanded open model. this becomes obvious if we look at chapters 3 and 8 of the federal law ‘on mortgage (pledges of immovable property)’, describing the mortgagee’s rights to the obligation secured by mortgage, assignment of rights under mortgage agreement, transfer and pledge of encumbrance. the two-tiered scheme of mortgage lending in russia was officially adopted in the ‘concept of the development of the residential mortgage system’6, which launched the implementation of a consistent government policy aimed to ensure the rights of lenders and investors on the mortgage market and at the same time to make housing and mortgages more affordable and accessible for creditworthy citizens. the two-tiered model of mortgage lending underpinning the russian residential mortgage system holds considerable potential for state regulation of this market and, consequently, the real estate market, securities market and macro-economic regulation in general [1]. results and discussion the main focus of this study is the financial, economic, institutional and legal relationships in the residential mortgage market in russia. at the key stage of this study we analyzed the available statistical data on the primary mortgage market in russian regions [20; 21]. the data we used at this and the following stages of analysis were provided by the central bank of the russian federation, federal state statistics service (rosstat) and ahml in 2014–2018. 6 the decree of the government of the russian fede ration of 11.01.2000 № 28 (amended as of 08.05.2002) ‘on the measures for the development of the residential mortgage system in the russian federation’ (together with the ‘concept of the development of the residential mortgage system in the russian federation’ and the ‘plan of preparation of the drafts of regulatory acts for the development of the residential mortgage system in the russian federation’). retrieved from: http://www.consultant.ru/cons/cgi/online. cgi?req=doc&base=law&n=36649&fld=134&dst=10000 00001,0&rnd=0.8203381367685081#049319826734995775 (02.03.2020). http://doi.org/10.15826/recon.2020.6.1.001 https://www.cmhcschl.gc.ca/en/co/buho/step-by-step/index.cfm https://www.cmhcschl.gc.ca/en/co/buho/step-by-step/index.cfm http://www.consultant.ru/cons/cgi/online.cgi?req=doc&base=law&n=36649&fld=134&dst=1000000001,0&rnd=0 http://www.consultant.ru/cons/cgi/online.cgi?req=doc&base=law&n=36649&fld=134&dst=1000000001,0&rnd=0 http://www.consultant.ru/cons/cgi/online.cgi?req=doc&base=law&n=36649&fld=134&dst=1000000001,0&rnd=0 r-economy, 2020, 6(1), 5–13 doi: 10.15826/recon.2020.6.1.001 9 www.r-economy.ru online issn 2412-0731 if we look at the statistics on the number of lenders on the primary mortgage market in the ural federal district, we see the following picture: in the given period, the central bank’s policy led to a decline in the number of lenders, including mortgage lenders; falling national currency value on the global market; and reduced demand for banking products (see table 1). table 1 number of lending institutions on the mortgage market of the ural federal district in 2014–2018 year number of lenders, total including: mortgage lenders mortgage investors mortgage refinance lenders lenders attracting secondary market investors 2014 35 34 9 1 6 2015 32 31 8 0 3 2016 29 28 8 1 1 2017 26 26 9 4 3 2018 23 23 10 8 3 compiled by the authors based on the ahml data. retrieved from: https://cbr.ru/statistics/pdko/mortgage/ (accessed: 02.03.2020) in 2014–2018, 11 lenders left the primary mortgage market, that is, the number of participants fell by 32.3%, from 35 to 23. according to figure 2, sverdlovsk region had the maximum number of lenders on the mortgage market in 2014 (15 participants). in 2016, this region accounted for the largest share (45%) in the total number of lenders in the ural federal district. in 2014–2018, kurgan region had the smallest number of lenders on the mortgage market. 100 80 60 50 20 0 2014 2015 2016 2017 2018 kurgan region tyumen region sverdlovsk region chelyabinsk region figure 2. structure of the mortgage market in the ural federal district in 2014–2018 compiled by the authors based on the ahml data. retrieved from: https://cbr.ru/statistics/pdko/mortgage/ (accessed: 02.03.2020) the regional distribution pattern of issued mortgages in the given period remained practically the same. borrowers in tyumen region accounted for the largest volume of issued mortgages and, accordingly, the highest percentage in the overall volume of operations on the mortgage insurance company valuation company borrower property seller commercial bank regional operator ahml investor property as mortgage security health insurance, title insurance, and homeowners insurance market valuation purchase and sale transaction mortgage real estate purchase agreement sale of loans mortgage sale re�nancing of the regional operator mortgage re�nancing placement of mortgage-backed securities guarantees for mortgage-backed securitiesnational government real estate agent figure 1. expanded open model (secondary, 2-tiered) of mortgage lending in russia [3] http://doi.org/10.15826/recon.2020.6.1.001 https://cbr.ru/statistics/pdko/mortgage/ https://cbr.ru/statistics/pdko/mortgage/ 10 www.r-economy.ru r-economy, 2020, 6(1), 5–13 doi: 10.15826/recon.2020.6.1.001 online issn 2412-0731 market in 2014–2018. the lowest figures were supplied by kurgan region and the yamalo-nenets autonomous district (figure 3). 2014 2015 2016 2017 2018 kurgan region tyumen region sverdlovsk region chelyabinsk regionincl. yamalo-nenets ar incl. khanty-mansiysk ar figure 3. volume of mortgage loans given to natural persons in 2014–2018 in the ural federal district compiled by the authors based on the ahml data. retrieved from: https://cbr.ru/statistics/pdko/mortgage/ (accessed: 02.03.2020) the dynamics of the volume of mortgage lending shown in figure 3 determined the dynamics of mortgage debt, which grew steadily in 2014–2018. as of the end of 2018, the amount of mortgage debt in roubles increased by 18,743 roubles (by 117.5%) in comparison with 2014 and reached 125,792 roubles. this situation to a significant extent was determined by per capita income in the region (table 2). in the ural federal district, per capita income increased from 28.7 thousand roubles a month in 2013 to 34.9 thousand roubles a month in 2018. according to rosstat, the yamalo-nenetsk autonomous region ranked first among other ural regions in 2018 in terms of per capita income and its dynamics (79.3 thousand roubles a month) while the poorest region, lagging behind the rest, is kurgan region with per capita income of 20.3 thousand roubles a month. table 2 per capita income in the ural federal district, rbs regions 2013 2014 2015 2016 2017 2018 ural federal district 28719 29997 32794 32907 33643 34955 kurgan region 17076 18315 20310 20175 20660 20334 sverdlovsk region 30459 31538 34113 34718 35210 36735 tyumen region 36167 37783 41893 42657 44241 46124 khanty-mansiysk autonomous region – yugra 39882 40811 46221 46934 48834 50717 yamalo-nenets autonomous region 58829 62020 67624 72358 76027 79398 tyumen region without autonomous regions (khanty-mansiysk and yamalo-nenets) 23169 25142 27448 27044 27672 29162 chelyabinsk region 21971 23070 24654 23657 23719 24386 compiled by the authors on the basis of rosstat data. retrieved from: https://www.gks.ru/free_doc/new_site/population/urov/ urov_11sub.htm (accessed: 02.03.2020) table 3 weighted average period and rate of mortgages in roubles given to natural persons in 2014–2018 in the ural federal district region 2014 2015 2016 2017 2018 weighted average mortgage period, months weighted average rate, % weighted average mortgage period, months weighted average rate, % weighted average mortgage period, months weighted average rate, % weighted average mortgage period, months weighted average rate, % weighted average mortgage period, months weighted average rate, % ural federal district 187.3 12.39 189.8 12.41 183.4 13.42 186.4 12.73 187.3 10.65 kurgan region 215.0 11.61 205.5 12.26 199.9 13.19 195.3 12.60 194.3 10.58 sverdlovsk region 180.2 12.48 184.4 12.46 182.0 13.53 186.2 12.71 189.0 10.66 tyumen region 200.9 12.31 203.6 12.33 192.2 13.35 197.3 12.71 194.7 10.62 including khanty-mansiysk autonomous region – yugra 220.1 12.31 203.5 12.33 188.5 13.30 190.5 12.83 190.4 10.67 including yamalo-nenets autonomous region 217.0 11.83 211.3 11.91 193.5 13.52 196.3 12.58 194.7 10.50 chelyabinsk region 159.6 12.68 163.8 12.55 156.7 13.60 159.9 12.83 165.6 10.75 compiled by the author based on rosstat data. retrieved from: https://cbr.ru/statistics/pdko/mortgage/ (accessed: 02.03.2020) http://doi.org/10.15826/recon.2020.6.1.001 https://cbr.ru/statistics/pdko/mortgage/ https://www.gks.ru/free_doc/new_site/population/urov/urov_11sub.htm https://www.gks.ru/free_doc/new_site/population/urov/urov_11sub.htm https://cbr.ru/statistics/pdko/mortgage/ r-economy, 2020, 6(1), 5–13 doi: 10.15826/recon.2020.6.1.001 11 www.r-economy.ru online issn 2412-0731 in the given period, the weighted average rate in roubles for the ural federal district fell by 1.74 percentage points and the weighted average mortgage period in 2014–2018 remained virtually unchanged – 187.3 months (15.6 years) (table 3). in the given period, the weighted average rate decreased in all the regions – in kurgan region, by 1.03%; in sverdlovsk region, by 1.82%; in tyumen region, by 1.69%; and in chelyabinsk region, by 1.93%. as for the mortgage period, in some regions it became longer (sverdlovsk region, by 7.2 months and in chelyabinsk region, by 6 months) while in kurgan and tyumen regions, it, on the contrary, shortened – by 20.7 months and 6.2 months respectively. conclusion the study of theoretical principles and aspects of mortgage lending has led us to the following conclusions. our analysis of the problems and prospects of the russian mortgage system centred around the model of mortgage lending [1]. analysis of the three key models (balanced autonomous model or contractual savings system; truncated open model or traditional single-tier model; and expanded open model or secondary mortgage model, twotiered), characteristic of international practices of mortgage lending [22; 23], in their relation to the russian context has brought to light the follo wing priorities in the development of the national system of lending relationships: first, it is essential to safeguard the interests of both lenders and borrowers; second, to enhance affordability of mortgages for average consumers and assign a priority role to mortgage lenders in the credit sector; and, finally, to enhance state regulation of mortgage lending relationships [24; 25]. the comprehensive analysis of the primary mortgage market in the ural federal district has revealed the following problems. first, in the given period, the number of participants of this market fell dramatically, in particular the number of lenders (by 32.3%). at the end of the period, there were 23 participants. it is expected that this negative trend will have negative long-term repercussions such as a decline in competition in the banking sector and tiering of the banking system, reduced number of market niches where the right lenders could be found for investment projects (borrowers) of different risk levels. second, in 2014–2018, there was a steady growth of mortgage debt, which increased by 18,743 roubles (or 117.5%). another trend was the ageing of mortgage debt due to poor asset ma nagement, unstable financial and economic situation of borrowers caused by the changing macro and microeconomic conditions in the country. third, in the given period, there was a drop in the mortgage rates from 12.41% in 2014 to 10.65% in 2018, which significantly affected the real estate prices and made housing more attractive in terms of investment opportunities. overall, our analysis of the financial, economic, institutional and legal relations on the primary mortgage market in the ural federal district has demonstrated that at its current stage, the research in this sphere lacks consistency, parti cularly in the evaluation of the mortgage system’s efficiency on the regional level. in our further studies we intend to bridge the existing gaps in research literature by developing a methodology for systematizing the criteria and indicators of the mortgage system’s efficiency. the procedure will include the following stages: creating a ranking system based on the mortgage system’s efficiency criteria and the corresponding set of statistical indicators; analysis of the influence that specific statistical indicators have on the system; and, finally, developing an integral indicator for evaluation of the system’s efficiency on the regional level. references 1. zinovieva, e.g., vasilieva, a.g., & usmanova, e.g. (2018). contemporary issues and trends in the development of the russian national mortgage system. st petersburg: info-da. 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(2017). bank ownership and cost efficiency: new empirical evidence from russia. economic systems, 41(2), 305–319. doi: 10.1016/j.ecosys.2016.08.001. 21. zinovieva, e.g., & usmanova, e.g. (2017). the analysis of effectiveness of the primary market of mortgage loan system functioning under the russian federation conditions. ekonomika i politika = economics and politics, 2, 13–20. (in russ.) 22. zinovieva, e.g., & kuznetsova, m.v. (2017). evaluation of the effectiveness of the primary mortgage market in the regional context. ekonomika i predprinimatelstvo = journal of economy and entrepreneurship, 12-1, 222–227. (in russ.) 23. wood, j.d.g. 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(in russ.) available at: https://elibrary.ru/item.asp?id=36334806. http://doi.org/10.15826/recon.2020.6.1.001 https://ssrn.com/abstract=2005895 https://ssrn.com/abstract=2005895 http://doi.org/10.1016/j.jhe.2005.07.003 http://doi.org/10.1111/jmcb.12620 http://doi.org/10.1016/j.ijindorg.2003.07.002 http://doi.org/10.1016/j.regsciurbeco.2013.12.004 http://doi.org/10.1016/j.regsciurbeco.2013.12.004 http://doi.org/10.1007/s11146-018-9683-y http://doi.org/10.1016/j.econmod.2012.08.004 http://doi.org/10.1016/j.econmod.2012.08.004 http://doi.org/10.1016/j.jhe.2014.01.002 http://doi.org/10.1016/j.jhe.2014.01.002 http://doi.org/10.1016/j.jimonfin.2018.06.013 http://doi.org/10.1016/j.jhe.2009.10.003 http://doi.org/10.1016/j.jhe.2009.10.003 http://doi.org/10.1016/j.ecosys.2016.08.001 http://doi.org/10.1080/13563467.2018.1545755 https://elibrary.ru/item.asp?id=36334806 r-economy, 2020, 6(1), 5–13 doi: 10.15826/recon.2020.6.1.001 13 www.r-economy.ru online issn 2412-0731 information about the authors ekaterina g. zinovyeva – associate professor, nosov magnitogorsk state technical university (38 lenina av., magnitogorsk, 455000, russia); e-mail: ekaterina_7707@mail.ru natalya r. balynskaya – associate professor, nosov magnitogorsk state technical university (38 lenina av., magnitogorsk, 455000, russia); e-mail: balynskaya@list.ru svetlana v. koptyakova – associate professor, nosov magnitogorsk state technical university (38 lenina av., magnitogorsk, 455000, russia); e-mail: svetlana.cop@yandex.ru oksana o. akhmetzianova – researcher, university of science and technology of china (96, jinzhai road baohe district, hefei, anhui, 230026, china); e-mail: oksanochka-star@mail.ru article info: received december 7, 2019; accepted march 05, 2020 информация об авторах зиновьева екатерина георгиевна – доцент, магнитогорский государственный технический университет им. г.и. носова (455000, россия, магнитогорск, пр. ленина, 38); e-mail: ekaterina_7707@mail.ru балынская наталья ринатовна – доцент, магнитогорский государственный технический университет им. г.и. носова (455000, россия, магнитогорск, пр. ленина, 38); e-mail: balynskaya@list.ru коптякова светлана владимировна – доцент, магнитогорский государственный технический университет им. г.и. носова (455000, россия, магнитогорск, пр. ленина, 38); e-mail: svetlana.cop@yandex.ru ахметзянова оксана олеговна – исследователь, научно-технический университет китая, хэфэй, китай (230026, кнр, хэфэй, ул. цзиньчжай, 96); e-mail: oksanochka-star@mail.ru информация о статье: дата поступления 7 декабря 2019 г.; дата принятия к печати 5 марта 2020 г. http://doi.org/10.15826/recon.2020.6.1.001 mailto:ekaterina_7707@mail.ru mailto:balynskaya@list.ru mailto:svetlana.cop@yandex.ru mailto:oksanochka-star@mail.ru mailto:ekaterina_7707@mail.ru mailto:balynskaya@list.ru mailto:svetlana.cop@yandex.ru mailto:oksanochka-star@mail.ru r-economy, 2020, 6(2), 65–73 doi: 10.15826/recon.2020.6.2.006 65 https://journals.urfu.ru/index.php/r-economy online issn 2412-0731 original paper © ignatieva, e.d., mariev, o.s., serkova, a.ye., 2020 doi 10.15826/recon.2020.6.2.006 impact of infrastructure on socio-economic development of russian regions: methodology and analysis e.d. ignatieva1 , o.s. mariev1, 2, a.ye. serkova1 1 institute of economics of the ural branch of the russian academy of sciences, yekaterinburg, russia; e-mail: elen_i99@mail.ru 2 ural federal university, yekaterinburg, russia abstract relevance. regional infrastructure development directly affects economic growth, social development and the quality of life. to identify the key areas of infrastructure development in russian regions, it is necessary to develop a methodological approach to the analysis of the impact of infrastructure on socio-economic development, which determines the relevance of this study. research objective. this study aims to improve the methodology of assessment of the role infrastructure plays in the socio-economic development of russian regions. data and methods. the analysis relies on a system of general and integral, static and dynamic indicators used to assess the current state and dynamics of infrastructure in regions. the analysis takes into account the structural and functional features of infrastructure. the proposed methodology comprises methods for obtaining comparative estimates of regional infrastructure development, which can be applied to compile regional rankings. the study also uses methods of econometric and k-means cluster analysis. results. a comparative analysis of the infrastructure development of russian regions allowed us to assess the infrastructural potential of these regions, the discrepancies in infrastructure development and compare the infrastructure-related characteristics of the leading lagging regions. the results of econometric analysis as well as cluster analysis of regions based on general and integral dynamic indicators are discussed. conclusions. the methodological approach proposed by the authors has been tested by using the data on russian regions. the analysis has revealed the most typical problems faced by russian regions. these problems should be taken into account in strategic decisionand policy-making. keywords region, infrastructure, infrastructure development, static and dynamic indicators, economy, quality of life, public-private partnership acknowledgements this research was supported by the institute of economics of the ural branch of the russian academy of sciences. влияние инфраструктуры на социально-экономическое развитие регионов россии: методология и анализ е.д. игнатьева1 , о.с. мариев1, 2, а.е. серкова1 1 институт экономики уральского отделения российской академии наук, екатеринбург, россия; e-mail: elen_i99@mail.ru 2 уральский федеральный университет, екатеринбург, россия аннотация актуальность. развитие региональной инфраструктуры напрямую влияет на экономический рост, социальное развитие и качество жизни. для выявления ключевых направлений развития инфраструктуры в российских регионах необходимо разработать методологию, анализирующую влияние инфраструктуры на социально-экономическое развитие регионов. цель исследования. цель данного исследования – усовершенствовать методологию оценки роли инфраструктуры в социально-экономическом развитии регионов россии. данные и методы. анализ основан на системе общих и интегральных, статических и динамических показателей, используемых для оценки текущего состояния и динамики инфраструктуры в регионах. анализ учитывает структурные и функциональные особенности инфраструктуры. предлагаемая методология включает в себя методы получения сравнительных оценок развития региональной инфраструктуры, которые можно применять для составления региональных рейтингов. в исследовании также используются эконометрические методы и кластерный анализ с помощью метода k-средних. результаты. сравнительный анализ развития инфраструктуры российских регионов позволил нам оценить ключевые слова регион, инфраструктура, развитие инфраструктуры, статические и динамические показатели, экономика, качество жизни, государственно-частное партнерство for citation ignatieva, e.d., mariev, o.s., & serkova, a.ye. (2020) impact of infrastructure on socio-economic development of russian regions: methodology and analysis. r-economy, 6(2), 65–73. doi: 10.15826/recon.2020.6.2.006 благодарности работа выполнена при поддержке института экономики уральского отделения российской академии наук. http://doi.org/10.15826/recon.2020.6.2.006 http://doi.org/10.15826/recon.2020.6.2.006 66 https://journals.urfu.ru/index.php/r-economy r-economy, 2020, 6(2), 65–73 doi: 10.15826/recon.2020.6.2.006 online issn 2412-0731 introduction comprehensive modernization of productive forces at the regional and macro-regional levels is impossible without infrastructure development. in order to monitor infrastructure development in russian regions and adjust it to the needs of economic growth and to improve the quality of life in these regions, it is necessary to design the appropriate methodology. the purpose of this article is to describe and substantiate the methodological approach to assessing the impact of regional infrastructure development on the socio-economic situation in the country. we are also going to describe the corresponding methodological principles and tools. infrastructure influences all socio-economic processes in regions, creates conditions for the deve lopment of the real sector, helps improve the quality of life and provides opportunities for people’s individual growth. our study focuses on the infrastructure in russian regions and their socio-economic systems. a comprehensive approach should be applied to address the problems of infrastructure development in russian regions, because the development of some types of infrastructure is associated with the development of other types of infrastructure. the high level of infrastructure development ensures the comparative advantages of regions in their interactions with each other and on a global scale. literature review there are various approaches to analyzing and evaluating the impact of certain types of infrastructure on socio-economic development. efimova (2009) identifies four main approaches to assessing the role of transport in regional development: by focusing on the availability of the market of resources and sales; by analyzing transport costs; by analyzing investment activity in the region; and by looking at the role of infrastructure factors in production and location decisions (the fourth approach also implies the use of entrepreneur surveys). kazakova & pospelova (2017) compared the transport infrastructure in russia with that of other countries and found its qualitative characteristics to be among the most significant limitations of economic growth. wang et al. (2020) investigated the impact of transport infrastructure (railway and road) on the economic growth in the countries of the belt and road initiative in 2007–2016. maliy & gusev (2010) assess the impact of energy enterprises on regional development by focusing on the case of saratov region in russia. a number of studies consider the impact of social infrastructure on the reproduction of human capital and the implementation of social projects (tikhonovich, 2012; roskruge, 2011; wai et al., 2013). tiwari (2008) discusses the impact of economic infrastructure on agricultural development, and owualah (1987) on the development of small businesses. chen & fang (2018) exami ned the relationships between economic growth, industrial electricity consumption and human capital by using a panel of 210 chinese prefecture cities in 2003–2012. some studies apply instrumental methods and modeling: for example, shvetsov et al. (2018) analyze the impact of infrastructure on regio nal socio-economic development (the case of the nenets autonomous okrug) with the help of an autoregressive model with equations reflecting the dependence of endogenous indicators (grp, r&d costs, per capita income and volume of polluting emissions) on exogenous variables – factors of infrastructure. cantos et al. (2005) use the production function to study the dependence of regional output on capital investment in transport infrastructure in spanish regions. kiselev & tkachev (2015) propose an economic and mathematical model for assessing the impact of social infrastructure on regional development. malafeev & baskakova (2017) investigate the significance of infrastructure capital for the gross output of the material production sector by applying econometric analysis of panel data using cobb-douglas production function. инфраструктурный потенциал этих регионов, различия в развитии инфраструктуры и сравнить инфраструктурные характеристики регионов. проинтерпретированы результаты эконометрического анализа, а также кластерного анализа регионов на основе общих и интегральных динамических показателей. выводы. предложенный авторами методологический подход апробирован с использованием данных по регионам россии. анализ выявил наиболее типичные проблемы, с которыми сталкиваются российские регионы. эти проблемы должны учитываться при принятии стратегических решений и разработке государственной политики. для цитирования ignatieva, e.d., mariev, o.s., & serkova, a.ye. (2020) impact of infrastructure on socio-economic development of russian regions: methodology and analysis. r-economy, 6(2), 65–73. doi: 10.15826/recon.2020.6.2.006 http://doi.org/10.15826/recon.2020.6.2.006 r-economy, 2020, 6(2), 65–73 doi: 10.15826/recon.2020.6.2.006 67 https://journals.urfu.ru/index.php/r-economy online issn 2412-0731 types of infrastructure and their functions our study aims to provide a comprehensive assessment of the impact that various types of infrastructure have on the socio-economic deve lopment of russian regions. such assessment can then be used for devising infrastructure deve lopment policies. the methodology of this study relies on the structural and functional aspects of infrastructure. infrastructure has a fairly complex structure, including various industries, structures, facilities, and institutions. infrastructure performs various economic, financial, demographic, social, environmental, and other functions. infrastructure is a major factor that determines the economic and social prosperity of a region. for a more in-depth understanding of the impact of infrastructure, we should consider how specific types and element of infrastructure affect regional development (ignatyeva et al., 2018). there are three main types of regional infrastructure depending on its functions: productive-economic, financial and social. productive-economic infrastructure, whose main function is to provide conditions for social production, includes transport, communications, electricity, and construction. transport infrastructure is an enabler for economic activity, an essential part of economic relations at the regional, interregional and global levels. according to pchelintsev (2004), transport and communications contribute to the intensification and improvement of the quality of economic relations and ensure the mobility of production factors and the availability of production results. as the world practice shows, the presence of new infrastructural networks, including motor transport, is the most important competitive advantage of regions, a factor that is crucial for regions’ general development and specialization, formation of local-scale territorial and industrial complexes and effective inter-regional interaction (melnikovet et al., 2019). transport accounts for 8% of the industry structure of grp. according to the data of the federal state statistic service (rosstat), fixed assets of transport at the end of 2018 accounted for 22.4% of the total volume of fixed assets of russia; transport accounted for 18.7% of total investment. the main documents regulating the key strategic areas of transport development in russia are the ‘transport strategy of the russian fede ration for the period until 2030’, federal program ‘development of the transport system of russia (2010–2021)’, ‘development strategy of the russian railways until 2030’, program ‘russian automobile roads in the long term (2010–2020)’, and so on. regional transport infrastructure, ensuring the territorial integrity of the region, is an impor tant element of the system of national economy and economic security (lyutov, 2017). transport is one of the largest basic sectors of the economy and an important component of infrastructure, which provides conditions for economic growth and contributes to national and regional prosperity. a region with developed transport infrastructure is in a relatively better position than its less successful counterparts. moreover, developed transport infrastructure also facilitates the region’s achievement of its strategic and tactical goals and allows it to optimize the use of all types of resources (kudryavtsev & tarasenko, 2014). the fuel and energy infrastructure performs such functions as providing people and enterprises with electricity and fuel and ensuring the energy-related and economic security of the country and regions. it also serves as a source of revenue for state and regional budgets. moreover, its positive impact on regional growth is achieved due to the spatial effects that go beyond the boundaries of individual regions (maliy & gusev, 2010). the construction infrastructure participates in the creation of fixed assets and their expanded reproduction, implementation of housing construction programs, creating conditions for the development of the production and non-production sphere of the region. the financial infrastructure, in its turn, ensures the consolidation of financial resources, their rational allocation and use, creating a favo rable investment climate in the region. the main function of the social infrastructure is to satisfy people’s needs and create conditions for expanded reproduction of labor and creative potential of the region’s population. this function largely depends on the quality of life in the region as well as the development of the real sector, since social infrastructure is ‘the main factor in the formation of human capital that creates labor products’ (tikhonovich, 2012). the social infrastructure of a region includes health care, education and culture, public catering and consumer services, housing and communal services, and so on. for optimal decisionand policy-making in a region, it is necessary to assess the actual state of http://doi.org/10.15826/recon.2020.6.2.006 68 https://journals.urfu.ru/index.php/r-economy r-economy, 2020, 6(2), 65–73 doi: 10.15826/recon.2020.6.2.006 online issn 2412-0731 its infrastructure against other regions (kudryavtsev & tarasenko, 2014), which requires a set of appropriate indicators. depending on the goal, objectives, and time interval of the study, partial, general and integral, static and dynamic indicators are calculated. there are particular indicators reflecting the availability of individual elements of infrastructure in a region, while there are also consolidated indicators that characterize specific types of infrastructure and integrated indicators that reflect the state of infrastructure as a whole. thus, in accordance with the types of infrastructure, it is possible to identify general indicators characte rizing economic, financial, social and other types of infrastructure in a region. general indicators are based on particular indicators that characte rize the availability of elements of specific types of infrastructure in the region. static indicators are used to assess the state of infrastructure in the current period, while dynamic indicators reflect its changes in time. both static and dynamic indicators can be partial, general or integral. methodology and data to calculate indicators and assess their impact on economic growth and the quality of life in a region, we have formulated the following methodological principles: – substantiation of hypotheses about the nature and aspects of the infrastructure’s impact on regional development, regarding specific types of infrastructure and in general; – selection of baseline indicators, their normalization and grouping by infrastructure type, formation of a data base; – calculation of static and dynamic indicators characterizing regional infrastructure; – comparative analysis and rating of regions regarding their infrastructure in general and its specific types; – econometric analysis of the impact of infrastructure-related factors on economic growth and quality of life in a region; – cluster analysis of the regions based on the calculated indicators; – identification of the most typical problems of infrastructure development and the corresponding priority areas of strategic development. in our study, the choice of initial (particular) indicators was determined, as already noted above, by the principles of complexity, consistency, representativeness, reliability and comparability. the indicators also corresponded to specific types of infrastructure. aggregated, static indicators are formed by using normalized particular indicators that characterize elements of a specific type of infrastructure. normalization of individual indicators is done by using the following formula: − = − min max min ,ij irij i i n n n n n where rijn is the normalized estimation of the i-th indicator for the j-th region; nij is the value of the i-th particular indicator for the j-th region; min max,i in n are the lowest and highest values of the i-th indicator for all regions; i, j are the sequential numbers of the indicator and the region, respectively. aggregate static indicators are calculated as arithmetic means of normalized indicators, while aggregate dynamic indicators are calculated as geometric means of indexes of private indicators (iij) for each type of infrastructure. similarly, integral static indicators are calculated as arithmetic means and integral dynamic indicators are calculated as geometric means of aggregate indicators for all types of infrastructure. the k-means method was used to classify russian regions depending on the values of aggregate and integral indicators of specific types of infrastructure. cluster analysis is necessary to identify problems of infrastructure development that are characteristic of certain groups of regions, assess the development of different types of infrastructure in each region, and assess whether the existing infrastructure meets the needs of the real sector and the population. the use of this method makes it possible to identify the weaknesses and comparative advantages of regions in socio-economic development regarding their infrastructure, which is necessary for strategic decision-making. the methodological recommendations were tested by the authors in relation to russian regions. to calculate the indicators, a data base was created drawing from the official rosstat data. the initial data for the econometric analysis is presented as a panel for russian regions for 1999– 2015. to calculate static and dynamic indicators, we used the data from official statistics for 5 years (2012–2016). http://doi.org/10.15826/recon.2020.6.2.006 r-economy, 2020, 6(2), 65–73 doi: 10.15826/recon.2020.6.2.006 69 https://journals.urfu.ru/index.php/r-economy online issn 2412-0731 results the results of the regression analysis (igna tyeva et al., 2018) have shown that the most significant factors that positively affect grp per capita are fixed capital investment and the share of university graduates in the total population. this conclusion confirms the importance of investment and education as factors of regional socio-economic development. the road density index had a very significant impact on grp per capita, in contrast to the railway density index. this can be explained by the following features of rail transport – less flexible schedule of cargo delivery compared to road transport, possible distance of the tracks from the points of cargo delivery, longer transportation times, and “bottlenecks”. intervals of values of static indicators of infrastructure development for 2012–2016 are shown in table 1. our calculations of statistic indicators have shown that moscow is the leader in terms of infrastructure development among russian regions. in all aggregate indicators, as well as in the integral indicator and the volume of grp per capita, it surpasses other russian regions. moscow is also the absolute leader in terms of railways and roads with solid cover, which provided a relatively high level of this region in the aggregate indicator of productive-economic infrastructure. relatively high levels in the indicators characterizing productive-economic, economic and financial infrastructure and in the integral indicator are typical of the khanty-mansiysk, yamalo-nenets and nenets autonomous okrugs, kamchatka and other regions rich in natural and mineral resources. the group of high achieving regions also includes sverdlovsk region, st. petersburg, moscow region, leningrad region, the republic of tatarstan, kaliningrad region and some others. the medium level in aggregate indicators of infrastructure development is characteristic of belgorod, lipetsk, vologda, murmansk, perm and novgorod regions. the lowest levels in all the indicators are found in altai, adygea, kalmykia, astrakhan region, dagestan, ingushetia, the kabardino-balkar, karachay-cherkess and chechen republic. the relatively low level of infrastructure development in these regions impedes the development of the real economy and improvement of the quality of life. these regions are also characterized by the lowest levels of grp per capita. we used the indicators of productive-economic, financial and social infrastructure for cluster analysis and grouping of russian regions. in this article, we discuss primarily the results of cluster analysis based on dynamic indicators (for more on typological groupings of russian regions based on static indicators, see ignatieva et al, 2019) as a result of cluster analysis, 6 typological groups (clusters) of russian regions were identified. table 2 illustrates the comparative characteristics of these groups based on the aggregate dynamic indicators for three types of infrastructure – industrial, financial and social. the table also shows integrated static indicators to show the dynamics of infrastructure development in regions. the figure shows significant discrepancies in regional infrastructure development in russia. the first group constitutes the largest share (45%), the fourth group accounts for 24%, and the fifth, for 15%. the shares of the second, third and sixth groups were 7%, 2% and 7%, respectively. let’s look at some characteristics of each cluster. group 1 45% group 2 7% group 3 2% group 4 24% group 5 15% group 6 7% figure 1. distribution of russian regions based on dynamic indicators of infrastructure development table 1 intervals of values of static indicators of infrastructure development in russian regions № value of indicators type of infrastructure integrated indicator grp per capita, rubproduction-economic social financial 1 maximum value 0,027 0,128 0,003 0,088 106 756,6 2 minimal value 0,664 0,610 0,686 0,595 5 821 559,8 source: the authors’ calculations are based on statistical data (rosstat). http://doi.org/10.15826/recon.2020.6.2.006 70 https://journals.urfu.ru/index.php/r-economy r-economy, 2020, 6(2), 65–73 doi: 10.15826/recon.2020.6.2.006 online issn 2412-0731 as the table illustrates, the highest values in dynamic indicators are found in the third group of regions (especially in financial indicators), although their infrastructure development is at the medium level (bashkortostan) or somewhat lower (mari el). the negative dynamics of infrastructural development (or the lowest figures in dynamic indicators) is typical of the sixth group, which includes both regions with a high level of infrastructure development (tatarstan, perm krai) and regions with a relatively low level of infrastructure development (karachay-cherkess republic, astrakhan region). the relatively stable dynamics of infrastructure development was observed in groups 1, 2, 4, and 5, but each of these groups had its own characteristics. the financial infrastructure in the regions of the second and fifth groups developed relatively dynamically at relatively low starting levels. the stable dynamics of productive-economic and financial infrastructure development is characteristic of the regions of the first group, which is also the largest, including regions whose current level of development for these types of infrastructure is quite high (moscow, saint petersburg, khanty-mansi autonomous okrug). such regions as moscow, tatarstan, and the yamalo-nenets autonomous okrug with high levels of static indicators have demonstrated low levels in the dynamic indicators of social infrastructure development. in a number of regions, the opposite picture was observed – social infratable 2 comparative characteristics of groups (clusters) of russian regions based on aggregate dynamic indicators values general dynamic indicators by type of infrastructure integral static indicatorproductive-economic social financial group 1 (37): belgorod region, vladimir region, voronezh region, ivanovo region, kaluga region, kostroma region, kursk region, moscow region, orel region, smolensk region, tver region, yaroslavl region, moscow, nenets autonomous okrug, murmansk region, novgorod region, saint petersburg, stavropol territory, republic of mordovia, chuvash republic, kurgan oblast, khanty-mansi autonomous okrug – yugra, yamalo-nenets autonomous okrug, tyumen region, chelyabinsk region, republic of altai, republic of buryatia, republic of tuva, republic of khakassia, altai krai, zabaykalsky krai, krasnoyarsk krai, novosibirsk region, tomsk region, republic of sakha (yakutia), kamchatka territory, sakhalin region. maximum 1,464 1,417 0,979 0,595 minimum 0,826 1,122 0,701 0,157 mean 1,034 1,251 0,877 0,256 group 2 (6): krasnodar territory, volgograd region, rostov region, udmurt republic, kirov region, ulyanovsk region maximum 1,479 2,799 1,081 0,350 minimum 1,278 2,040 0,934 0,195 mean 1,375 2,246 1,004 0,253 group 3 (2): republic of bashkortostan, republic of mari el maximum 2,326 4,652 1,132 0,233 minimum 2,071 4,101 1,106 0,182 mean 2,199 4,377 1,119 0,207 group 4 (20): ryazan region, tula region, republic of karelia, komi republic, arkhangelsk region , vologda region, kaliningrad region, leningrad region, pskov region, republic of adygea, republic of kalmykia, republic of ingushetia, republic of north ossetia, kabardino-balkar republic, sverdlovsk region, kemerovo region, omsk region, primorye krai, jewish autonomous okrug, chukotka autonomous okrug maximum 1,142 1,143 1,163 0,357 minimum 0,782 0,913 0,816 0,088 mean 0,976 1,062 0,944 0,217 group 5 (12): bryansk region, lipetsk region, tambov region, republic of dagestan, chechen republic, orenburg region, penza region, saratov region, irkutsk region, khabarovsk krai, amur region, magadan region. maximum 1,189 1,832 1,083 0,367 minimum 0,954 1,436 0,864 0,148 mean 1,024 1,588 0,946 0,231 group 6 (6): astrakhan region, karachay-cherkess republic, republic of tatarstan, perm region, nizhny novgorod region, samara region. maximum 1,041 0,854 0,784 0,284 minimum 0,495 0,403 0,663 0,111 mean 0,694 0,630 0,733 0,217 source: the authors’ calculations are based on statistical data (rosstat). http://doi.org/10.15826/recon.2020.6.2.006 r-economy, 2020, 6(2), 65–73 doi: 10.15826/recon.2020.6.2.006 71 https://journals.urfu.ru/index.php/r-economy online issn 2412-0731 structure developed more dynamically in regions with low initial levels of development (chechnya, north ossetia, mari el, and tambov region). the only exceptions were the chukotka autonomous okrug and leningrad region, characterized by relatively high dynamic estimates with high initial levels of infrastructure development. thus, the calculation of static and dynamic indicators allowed us to compare the levels and dynamics of various types of infrastructure, which is necessary to identify the threats to economic security associated with negative trends in infrastructure development and determining the prospects for infrastructure development in russian regions. according to rosstat, depreciation of fixed assets in transport at the end of 2018 amounted to 39.7% and in construction, 48.9%. to modernize and update fixed assets and introduce new technologies, it is necessary to attract investment, which includes investment from institutional investors (banks, pension funds, insurance companies) through public-private partnership (ppp) mechanisms. this opens new opportunities for investors, developers and consumers as ppp mechanisms allow to combine the potential of the state and business. currently, the most promising ppp projects in the transport sector are implemented in moscow and st. petersburg, since these regions have most advantages in terms of road density, financial infrastructure development, and the level of income (ofin, 2016). to expand the scope and improve the efficiency of ppp mechanisms in russian regions, it may be useful to study the foreign experience of using such financing schemes in infrastructure development. for example, in australia, 10–15% of total investment in infrastructure by the mid-2000s was carried out at the expense of public-private partnerships (gilmour et al., 2010). the bulk of this investment was primarily intended for the creation of economic infrastructure, although in some cases social infrastructure was also created. there is a foreign practice of attracting investment to create and develop infrastructure facilities by issuing infrastructure bonds. in the united states, pension funds are invested in infrastructure bonds to finance infrastructure projects, with preference given to municipal loans. the main issuers of infrastructure bonds in india are banks, and in chile – concessionaires, and concession projects using infrastructure bonds enjoy the highest credit ratings (ivanov, 2011). in russia, infrastructure bonds worth about 50 billion rubles were issued by jsc ‘western high-speed diameter’, jsc ‘main road’, and llc ‘north-western concession company’. the potential amount of funds of the russian pension system invested in infrastructure development may be from $ 3.5 to $7.0 billion in the short term, with the possibility of an almost two-fold increase in the medium term. the participation of the state as an issuer of infrastructure bonds guarantees a reduction in risk and an increase in the investment attractiveness of regional and municipal infrastructure projects (stuart, 2017). as we have noted above, the development of some types of infrastructure leads to the development of other types of infrastructure, i.e. balanced development of infrastructure is an important condition for its effective functioning. one of the key factors of infrastructure development in regions is the efficient performance of the financial infrastructure, since an important area for implementing investment projects in the field of productive economic and social infrastructure is to attract funds from institutional investors (banks, pension funds, insurance companies) to finance the creation of new and improve the already existing facilities. conclusions problems of infrastructure development in russian regions should be solved comprehensively as the development of infrastructure affects all social and economic processes and is necessary to create conditions for the development of the real sector, rational use of material and labor resour ces. infrastructure is also essential to provide opportunities for personal growth, improvement of the demographic situation and the quality of life. the methodological principles described in this article can be used to assess the impact of infrastructure on grp per capita as a general indicator of socio-economic development, assess the comparative advantages of regions related to the state of their infrastructure, and identify strong and weak aspects in infrastructure development. the methodological principles and tools have been tested by using the data for russian regions, which shows the practical significance of this approach. as a result, we identified the most typical problems faced by russian regions. these problems should be taken into account in strategic decisionand policy-making. as our regression and correlation analysis has shown, http://doi.org/10.15826/recon.2020.6.2.006 72 https://journals.urfu.ru/index.php/r-economy r-economy, 2020, 6(2), 65–73 doi: 10.15826/recon.2020.6.2.006 online issn 2412-0731 references cantos, p., gumbau-albert, m., & maudos, j. 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(2016) features of the implementation of public-private partnership projects in the transport infrastructure. news of st. petersburg state university, 6(102), 19–23. one of the major challenges in this respect is to ensure a more balanced development of the country in terms of infrastructure. investment is crucial for the implementation of infrastructure projects, equipment modernization, and digitalization of infrastructure sectors. this will create incentives for the development of the real sector, social sphere and, in the long run, will improve the quality of life in the regions. as russian and international experience has shown, special attention should be paid to the enhancement of the efficiency of investment projects through the active use of ppp mechanisms. further research prospects, in our opinion, consist in a more detailed analysis based on the proposed static and dynamic indicators of infrastructure development and its impact on socio-economic development, with the identification of leaders and laggards, monitoring infrastructure development in regions where large infrastructure projects are being implemented, including using ppp mechanisms. http://doi.org/10.15826/recon.2020.6.2.006 https://mpra.ub.uni-muenchen.de/15261/1/mpra_paper_15261.pdf http://doi.org/10.1108/ 13664381011087506 http://fundamental-research.ru/ru/article/view?id=38906 https://fundamental-research.ru/ru/article/view?id=34241 http://doi.org/10.17059/2017-3-11 r-economy, 2020, 6(2), 65–73 doi: 10.15826/recon.2020.6.2.006 73 https://journals.urfu.ru/index.php/r-economy online issn 2412-0731 owualah, s. 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(2017, august 24). the illusion of infrastructure bonds. why did the focus fail? forbes website. retrieved from https://www.forbes.ru/finansy-i-investicii/349401-illyuziya-infrastrukturnyh-obligaciy-pochemu-fokus-ne-udalsya tikhonovich, e.a. (2012) the influence of social infrastructure on the reproduction of human capital. bulletin of volgograd state university. series 3. economics. ecology, 1(20), 22–28. tiwari, a.k. (2008) economic infrastructure and agricultural development in himachal pradesh: a district level analysis. social change, 38, 245–262. wai, s.h., yusof, a. md, ismail, s., & ng, c.a. (2013) exploring success factors of social infrastructure projects in malaysia. international journal of engineering business management, 5 doi: 10.5772/55659. wang, c., lim, m. k., zhang, x., zhao, l., & lee, p.t.w. (2020). railway and road infrastructure in the belt and road initiative countries: estimating the impact of transport infrastructure on economic growth. transportation research part a: policy and practice, 134, 288–307. information about the authors elena d. ignatieva – cand.sc. (economics), senior researcher, institute of economics of the ural branch of the russian academy of sciences (29, moskovskaya str., yekaterinburg, 620014, russia); e-mail: elen_i99@mail.ru oleg s. mariev – cand.sc. (economics), associate professor, head of the department of econometrics and statistics, ural federal university (19, mira str., yekaterinburg, 620002, russia); senior researcher, institute of economics of the ural branch of the russian academy of sciences (29, moskovskaya str., yekaterinburg, 620014, russia); e-mail: olegmariev@mail.ru alla ye. serkova – leading economist, institute of economics of the ural branch of the russian academy of sciences (29, moskovskaya str., yekaterinburg, 620014, russia); e-mail: muccio@bk.ru article info: received february 9, 2020; accepted may 10, 2020 информация об авторах игнатьева елена дмитриевна – кандидат экономических наук, старший научный сотрудник института экономики уральского отделения российской академии наук (620014, г. екатеринбург, ул. московская, 29); e-mail: elen_i99@mail.ru мариев олег святославович – кандидат экономических, доцент, заведующий кафедрой эконометрики и статистики уральского федерального университета (620002, россия, г. екатеринбург, ул. мира, 19); старший научный сотрудник института экомоники уральского отделения российской академии наук (620014, г. екатеринбург, ул. московская, 29); e-mail: olegmariev@mail.ru серкова алла евгеньевна – ведущий экономист института экономики уральского отделения российской академии наук (620014, г. екатеринбург, ул. московская, 29); e-mail: muccio@bk.ru информация о статье: дата поступления 9 февраля 2020 г.; дата принятия к печати 10 мая 2020 г. http://doi.org/10.15826/recon.2020.6.2.006 https://www.forbes.ru/finansy-i-investicii/349401-illyuziya-infrastrukturnyh-obligaciy-pochemu-fokus https://www.forbes.ru/finansy-i-investicii/349401-illyuziya-infrastrukturnyh-obligaciy-pochemu-fokus http://doi.org/10.5772/55659 mailto:muccio@bk.ru mailto:muccio@bk.ru 198 www.r-economy.ru r-economy, 2019, 5(4), 198–207 doi: 10.15826/recon.2019.5.4.020 online issn 2412-0731 original paper © d. a. safitri, l. a. bespalova, f. wijayanti, 2019 doi 10.15826/recon.2019.5.4.020 changes in land use in eastern surabaya, indonesia, and their impact on coastal society and aquaculture d. a. safitri1, 2 , l. a. bespalova1, f. wijayanti3, 4 1 southern federal university, rostov-on-don, russia; e-mail: dikadede@gmail.com 2 universitas 17 agustus 1945 (untag) surabaya, surabaya, indonesia 3 ural federal university, ekaterinburg, russia; e-mail: febry.ie008@gmail.com 4 universitas negeri malang, malang, indonesia abstract indonesia is an archipelago country which has a large number of coastal areas, including surabaya city. this part of the country, in particular its eastern areas, was affected by changes in land use – more land is now occupied by farms and residential areas. another important type of land use in surabaya is the ponds used for fish farming. this research aims to prove that the change of land use in surabaya affects the socio-economy of the coastal area. this research uses the quantitative approach and descriptive statistic method. it shows that the increase in the number of ponds in surabaya has not affected the growth in the number of fishermen while the amount and the value of fish production increased significantly due to marine fishing. since most of the ponds in surabaya are managed traditionally, they are unable to ensure a high output.therefore, the majority of the community of parmubayain the east coast of surabaya would like to change the function of ponds but are impeded to dos o by the legal regulations due to the special status of this area. consequently, the optimal use of ponds in surabaya would be to train fishermen, fish farmers, and representatives of other related professions. keywords land use, ponds, fish farming, fishermen, economic value of fish production for citation safitri d. a., bespalova l. a., wijayanti f. (2019) changes in land use in eastern surabaya, indonesia, and their impact on coastal society and aquaculture. r-economy, 5(4), 198–207. doi: 10.15826/recon.2019.5.4.020 влияние распределения земельных участков на прибрежное общество и аквакультуру в восточной сурабаи д. а.сафитри1, 2 , л. а. беспалова1, в. фебри3, 4 1 южный федеральный университет, ростoв-на-донy, россия 2 университет 17 августа 1945 (унитаг), сурабая, индонезия 3 уральский федеральный университет, екатеринбург, россия 4 университет негери маланг, маланг, индонезия аннотация индонезия – страна-архипелаг с обширной акваторией, поэтому, большинство районов здесь – прибрежные, одним из них является прибрежная зона города сурабая. структура землепользования изменяется здесь наиболее значительно в восточной части. на это изменение указывает увеличение площади земель, занятых фермерскими хозяйствами и селитебными зонами. изменения заключаются в увеличении количества рыболовных прудов в сурабае, которые становятся вторым по величине площади территории видом землепользования в сурабае, после селитебного. распределение земель должно трансформировать структуру рабочих мест и рыбохозяйственное производство. данное исследование направлено на доказательство того, что изменение землепользования в сурабае влияет на социально-экономическую обстановку в прибрежной зоне. данное исследование проведено с использованием количественного подхода и описательного статистического метода. согласно результатам исследования в сурабае землепользование, связанное с рыбоводными прудами, не повлияло на рост численности рыбаков, тем не менее, количество и стоимость рыбной продукции значительно увеличиваются. кроме того, обработка данных показала, что вылов рыбы сурабаи в основном приходится на море, а не на пруды, это обстоятельство обусловлено традиционным использованием прудов, и вылов рыбы из большинства прудов в сурабаи незначителен. поэтому большая часть общины пармубая рассчитывает изменить вид землепользования на территориях, используемых для прудов, но это не соответствует правительственным постановлениям относительно заповедной зоны. следовательно, оптимально использование прудов в сурабае в целях обучения рыболовному мастерству, разведению рыбы, ведения деятельности по разведению пресноводных рыб и многих других. ключевые слова землепользование, пруды, рыбохозяйственное производство, рыбаки, экономическая ценность рыбопродукции для цитирования safitri d. a., bespalova l. a., wijayanti f. (2019) changes in land use in eastern surabaya, indonesia, and their impact on coastal society and aquaculture. r-economy, 5(4), 198–207. doi: 10.15826/recon.2019.5.4.020 http://doi.org/10.15826/recon.2019.5.4.020 http://doi.org/10.15826/recon.2019.5.4.020 mailto:dikadede@gmail.com mailto:febry.ie008@gmail.com r-economy, 2019, 5(4), 198–207 doi: 10.15826/recon.2019.5.4.020 199 www.r-economy.ru online issn 2412-0731 introduction a quarter of the world’s fish production is controlled by the association of southeast asian nations (asean) countries. according to the asean1, 4 out of 10 asean countries are among the ten largest global fish producers. these four countries are indonesia, thailand, viet nam, and the philippines. based on the total output, indonesia ranks second largest fish producer in the world after china2. in other words, indonesia is leading the way in fish production in asean with total aquaculture of 23,200,000 metric tons in 2016. indonesia is an archipelago with an area of 5.8 million km2, which consists of vast territorial waters and territorial waters of 3.1 million km2, the exclusive economic zone (eez) of 2.7 million km2, a coastline of 80,791 km [1]. of the 67,439 villages in indonesia, approximately 9,261 villages can be described as coastal villages [2]. taking into account all of the above it is not surprising that in 2016, indonesia reached the level of total fishery production of 23.2 million metric tons. while the output of capture fisheries reaches more than 6.5 million metric tons or 28.3% of the total fishery output, from the economic perspective, the amount of land owned by a producer is an important production factor [3]. it will affect production, particularly in the agricultural sector [4]. unsurprisingly, indonesia’s vast water area is an essential factor in fisheries production [5]. however, as the data in table 1 illustrates, in 2016, 1 fisheries, where to invest? retrieved from http://investasean.asean.org/index.php/page/view/fisheries 2 globefish highlights a quarterly update on world seafood markets. retrieved from http://www.fao.org/3/ca4185en/ ca4185en.pdf indonesia experienced a slight decline in fisheries production in comparison with 2015, which made indonesia try to optimize its fishery resources. a way to increase fishery output is to change the land use in surabaya. surabaya is the capital of the province of east java. although surabaya is a coastal city, its capture fisheries income is not substantial. these conditions encourage surabaya to increase its aquaculture. a method to increase the output of fishery production is changing the land use to ponds. according to landsat’s remote sensing data, changes in land use in surabaya have happened mainly in east surabaya, particularly in the coastal areas. according to the spatial plan for 2002–2029 (rencana tata ruang wilayah or rtrw) – the planning program for long-term development of surabaya, most of the area in east surabaya is used for housing, education, trade, and services, protected against nature and industry. open space in the region of east surabaya is occupied by ponds and mangrove forests. furthermore, jihan [6] studied land use in east surabaya and identified such types as housing (residential area), ponds, shrubs, educational facilities, government services, trade areas, health facilities and so on. in the district of sukolilo, there are some changes in land use, as the land that used to be occupied by fishponds is now turning into residential area. an opposite process is happening in east surabaya, where the land is reclaimed to create ponds [6]. sobirin researched land cover change in surabaya for the years of 1994, 2000, and 2011 (using the method of remote sensing) [7]. the results of the analysis included several classifications of land cover water bodies (rivers, reservoirs, etc.), table 1 capture fisheries production (metric tons) in asean, 2014–2016 no country total fisheries production (metric tons) capture fisheries production (metric tons) 2014 2015 2016 2014 2015 2016 1 indonesia 20,900,000 22,400,000 23,200,000 6,530,407 6,739,658 6,584,419 2 vietnam 6,048,983 6,207,514 6,420,471 2,694,641 2,757,314 2,785,940 3 philippines 4,587,385 4,503,067 4,228,906 2,249,780 2,154,908 2,027,992 4 myanmar 2,934,806 2,970,100 3,090,034 1,970,550 1,970,470 2,072,390 5 thailand 2,567,898 2,429,956 2,493,154 1,670,035 1,501,318 1,530,583 6 malaysia 1,989,740 2,003,019 1,992,258 1,468,726 1,496,054 1,584,371 7 cambodia 745,310 751,193 802,450 625,255 608,193 629,950 8 lao pdr 168,597 158,600 180,750 60,237 62,635 70,915 9 singapore 6,695,323 8,161,294 7,346,361 1,433 1,265 1,234 10 brunei darus-salam 3,897,07 4,353,14 14,239,63 3,186 3,370 13,292 source: world bank data. retrieved from https://databank.worldbank.org/reports.aspx?source=2&series=er.fsh.capt. mt&country=# http://doi.org/10.15826/recon.2019.5.4.020 http://investasean.asean.org/index.php/page/view/fisheries http://investasean.asean.org/index.php/page/view/fisheries http://www.fao.org/3/ca4185en/ca4185en.pdf http://www.fao.org/3/ca4185en/ca4185en.pdf https://databank.worldbank.org/reports.aspx?source=2&series=er.fsh.capt.mt&country=# https://databank.worldbank.org/reports.aspx?source=2&series=er.fsh.capt.mt&country=# 200 www.r-economy.ru r-economy, 2019, 5(4), 198–207 doi: 10.15826/recon.2019.5.4.020 online issn 2412-0731 inland water (ponds), dry land agriculture, wetland farming, settlements, industry, etc. ashazy studied the vegetation cover in east surabaya in a buildable area, graveyard, yard, fields, ponds, and others [8]. in east surabaya, most of the land is covered by rice fields and ponds. in the years of 2002 and 2006, the land cover changed [9]. the results showed that there are eight categories of land cover, including ponds, roads, rivers, industry and warehousing, buildings, vegetation, mangrove forest, and abandoned fields [9]. according to experts, the prevailing type of land use is ponds [6; 7; 9]. remote sensing data show that the land use in east surabaya corresponds to the spatial plan (rtrw). the ponds were located in the districts of mulyorejo, sukolilo, rungkut, and gunung anyar. it happens because the fourth region has a considerable fishery potential and also because it located in a protected area, which means that it is better protected from land conversion. for this reason, surabaya government the project of establishing fishing villages: (1) tambak wedi(swedi) fishing village in tambak wedi kelurahan kenjeran district; (2) cumpat fishing village in the kedung cowek kelurahan bulak district; and (3) kejawan fishing village in sukolilo kelurahan bulak district.apart from fishing, the local communities engage in other fishing related activities such as management and transportation of production, sale and processing of fish. these activities are indicated by the increasing income of fishers each year. the official statistical data (badan pusat statistik -bps) in 2007 demonstrated that the income of fishers in surabaya is rp 4,481,003 every month, and in 2017 reached rp 10,800,000. fisheries production in surabaya divided into marine fisheries and inland fisheries production. ponds in surabaya, give the number of the output of fishery but not much. based on the data from the official statistical information, in 2005, the total of marine fishery production was 9,227.00 tons, and the output of inland fisheries (ponds) was 8,825 tons. in 2016, marine fishery production was 10,578.30 tons, and the production of inland fisheries (ponds) was 6,915.03 tons. in 2017, the marine fish production was 8,416.60 tons, and the production of inland fisheries (ponds) was 6.798 tons. these data show that the production of inland fisheries of the ponds was decreasing each year. pond areas do not contribute significantly to the total output of inland fisheries. therefore, this study aims to find out the effect of land allocation (ponds) on the socio-economic situation in local fishing communities of east surabaya. literature review definition of the term ‘land use’ di gregorio and jansen define land cover as the observed biophysical cover on the earth’s surface. it includes all types of vegetation and human structures that cover the land surface [10]. jansen (2006) states that “the term land use has different meanings across disciplines” and that those different perspectives may all be valid. it also terms of socio and economic purpose [11]. batista and silva proposed a new way of land use mapping [12]. additional information regarding the human activities on land or the presence of specific elements in the landscape has to be taken into account [12]. numerous factors determine land use. first of all, biophysical factors enhance or constrain land uses (climate, topography, soil, water). other factors include cultural context, local traditions, institutional, and political aspects [11]. finally, the demographic and economic dynamics may drive demand for particular services and commodities, which in turn influence changes in land-use [12]. land use in surabaya the jica study team (2009) prepared a report on land use in surabaya: 5.11 km2 (1.6%) are used for agriculture; 9.63 km2, agriculture (non-irrigation); 37.16 km2 (11.4%), for ponds; 127.17 km2 (39.0%), residential area; 14.92 km2 (4.6%), commercial area; 27.89 km2 (8.5%), industrial production; 18.78 km2 (5.8%), forests, mangrove forests and swamps; 23.23 km2 (7.1%), public facilities; 27.81 km2 (8.5%), green space and recreation; 7.33 km2 (2.2%), water; 27.23 km2 (8.3%), vacant land; 0.02 km2 (0.0%), other purposes [13]. the study explained that residential purpose is the number one land use in surabaya, followed by the allocation of pond land. the research conducted by viv djanat prasita showed that in some locations, land-use changes have occurred [14]. research in 1996–2015 with remote sensing data shows that there has been a change in land use, namely conservation land (e.g., mangrove forests) were turned into pond land and vice versa, principally in the east surabaya area. this condition agrees with the bps data: the area of ponds in 1996 was 673 hectares, and in 2015 http://doi.org/10.15826/recon.2019.5.4.020 r-economy, 2019, 5(4), 198–207 doi: 10.15826/recon.2019.5.4.020 201 www.r-economy.ru online issn 2412-0731 it was 3,139.66 hectares, which means that it increased by 2,466.66 hectares [15]. according to rosytha, in surabaya the problems of land use reside primarily in the conversion of mangrove lands into settlements and aquaculture zones [16]. the mangrove area, which starts to be used as a pond area, is larger than the coastal and river areas. the transfer of land functions that occur in mangrove areas into pond areas is an activity that can improve the community’s economy. the land conversion, however, does not take into account the sustainability of the ecological functions of the coast and small islands. this conservation can result in changes in mangrove function. ponds that are increasingly large compared to mangrove areas on the coast or rivers can increase abrasion, which may occur during high tides. additionally, land conversion to ponds will open up areas and can increase habitat fragmentation between coastal, mangrove, and river areas. land clearing and fragmentation of mangrove land into fragments or patches of ponds can also affect the fauna of the mangrove [16]. based on several studies that we have described above, it can be concluded that the land in surabaya ismostly occupied by settlements and ponds. most new ponds in surabaya are created in east surabaya, in gunung anyar district, rungkut district, and sukolilo district. we conducted a field check in gunung anyar sub-district dominated by ponds and mangroves. the ponds in the area are mostly traditionally managed ponds. moreover, some ponds are not developed due to the bad quality of roads, which impedes access to them. moreover, some of ponds do not produce large quantities of fish, and the ponds are intentionally left blank (not given fish seeds too) and the rest are non-production ponds (dry ponds – see figure 1). research methodology this quantitative approach in this study is used to determine the impact of the land-use change in surabaya on socio-economy: the life of fishermen’s community (social aspect) and fisheries production (economic aspect) [17; 18]. this research focuses on the case of surabaya, indonesia. surabaya is one of the coastal cities in indonesia, it has 12 coastal districts and 24 coastal villages. the development of land use has an impact on shoreline changes, which, in its turn, has a socio-economic impact on coastal communities. the area of surabaya in 1996 was 326.40 km2, and in 2017 it increased to 350.54 km2 by about 24.14 km2. as the figure below illustrates, there has been a change in the total area in surabaya. based on the remote sensing data, there was an increase in the area in east surabaya, as more lands were added such as ponds and residential districts. new ponds appeared in east surabaya in districts kalisari and keputih (see figure 2). according to the bps data, pond area for 1996 is 673 hectares while for 2017 of 2,470.88 hectares. this area increased by 1797.88 hectares. furthermore, there has been a steady growth in population in surabaya. in 1996, there were 2,344,520 people living in surabaya, and in 2017 this figure was 3,074,883, that is, there was a 23.75% increase in the population. meanwhile, in coastal areas, there were 993,840 people in 2015 (497,336 men and 496,504 women), the population increased by 536,971 or 7.53 percent in 2017. figure 2 was created with the help of arcgis software and illustrates the changes in the coastal area of surabaya. figure 1. condition of pond land in east surabaya, one of the pond was in dry condition (the right picture) source: authors’ collection http://doi.org/10.15826/recon.2019.5.4.020 202 www.r-economy.ru r-economy, 2019, 5(4), 198–207 doi: 10.15826/recon.2019.5.4.020 online issn 2412-0731 the research uses primary and secondary data. the primary data were obtained through observation in coastal areas with photo documentation (for validating the changes of the area), while the secondary data were obtained from research literature and local government agencies. results and discussion problems and condition of capture fisheries in surabaya the development of capture fisheries in indonesia so far has not been successful. as table 1 shows, there was a decline from 2015 to 2016. this decline was due to several problems faced by indonesian fishermen. these problems are as follows [19]: (1) the weak management system of capture fisheries business and weak mastery of appropriate technologies resulting in a low level of production; (2) competition in inter-regional water land use as a result of the increasing number of inhabitants in coastal areas; (3) ongoing overfishing in some areas; (4) the increase and scarcity of fuel, which increasingly burdens fishers to go to sea; (5) high rates of illegal fishing,resulting in state losses, and an increasingly rapid decline in fisheries and marine resources; (6) damage to aquatic ecosystems as a result of overexploitation and natural disasters; (7) overlapping authority in granting permits and regulations that do not provide a conducive climate for fisheries investment; (8) inadequate technologies of handling and processing fish production, resulting in a low quality, added value, and competitiveness of fishery products; (9) unsafe methods of product handling and processing; (10) limited fisheries infrastructure,insufficient capital, inadequate coordination and institutions [19]. meanwhile, capture fisheries activities in surabaya have been going on for a long time. the problem that has to be dealt with at the current stage is fishers who live near the coast of the surabaya, are fishing in the waters of surabaya with a simple fishing gear. their catches are generally figure 2. map for changing of land use in surabaya source: authors’ file with arcgis program http://doi.org/10.15826/recon.2019.5.4.020 r-economy, 2019, 5(4), 198–207 doi: 10.15826/recon.2019.5.4.020 203 www.r-economy.ru online issn 2412-0731 sold in the local market and some are directly distributed to hotels through mediators (tengkulak). surabaya fishermen have been fishing around the madura strait for many years. fish are caught in surabaya as well as in other areas such as probolinggo, brondong, and lamongan [20]. pond conditions in surabaya ponds in surabaya are still managed traditionally. consequently, the arrangement of ponds and the pond infrastructure are always irregular. traditional management has several impacts, one of which is that the pond quality is not optimal (unproductive). moreover, fisheries are in need of modern equipment, for example, water pumps. some cases of providing pond water pumps have several impacts in several areas, and this is related to the existence of groundwater drilling and polluting the environment around the pond. during the dry season, most fisheries ponds in surabaya change their function to become salt ponds. some fishermen think that instead of their ponds being unproductive, their fishing grounds should be transformed into salt ponds. nevertheless, the productive value of salt is not very good, so the amount of fishery production has decreased. switching the function of ponds is a way for fishers to survive. moreover, by creating large fisheries output, ponds in surabaya are also used for recreational fishing. the data from the fisheries and maritime affairs of east java province show that there are several types of fish products such as live fish, fresh fish and processed fish. there are two types of fish products in surabaya, they are fresh (raw) and processed fish. the total production of fresh product types is 3,700,974 tons; processed fish, 140,037 tons; so the total production of fisheries in surabaya is 3,841,011 tons. the sale value of fisheries production in surabaya is rp 175,634,207,369. [21] analysis of the amount and value of fisheries production in surabaya according to the official data, there are two main sources of fisheries production, namely marine fisheries and freshwater fisheries (such as reservoirs, rivers, ponds). for more than 20 years (1996–2017), fish production in surabaya has experienced its ups and downs. the total fish production in 1996 was 13,442 tons while in 2013, it was 23,274.17 tons. after 2013, fishery production declined. compared with the production data in 1996 and 2017, the number of production increased. our calculations of fish productions in surabaya use the official data (see table 2) [15; 22], the linear equation value of y = 104.23x – 192,152 and the regression value of r² = 0.0545 (see figure 3). the decline in the amount of fishery production in surabaya is one of the reasons for the donations from neighboring cities. furthermore, other problems are caused by fishermen’s lack of capital to go to sea to cover the costs of fuel or charter boats. moreover, fishermen need extra training and financial support from the government (e.g. loans). table 2 sea and freshwater fish production in surabaya for 1996–2017 year sea and freshwater fish production (tons) 1996 13,422 2005 18,483 2006 18,441 2007 16,791.88 2008 17,455.4 2009 18,326.7 2010 19,049 2011 16,231.95 2012 16,029.25 2013 23,274.17 2014 15,285.34 2015 14,954.15 2016 18,692.73 2017 16,576.83 source: badan pusat statistik provinsi jawa timur. retrieved from https://jatim.bps.go.id/publication/downl o a d . h t m l ? n r b v f e v e = o t k 5 o w i 3 mj d k m z e 2 y z aw n m v l m m z k n 2 u 3 & x z m n = a h r 0 c h m 6 ly 9 q y x rp b s 5 i chmuz28uawqvchvibgljyxrpb24vmjaxoc8woc8xni85otk5yjcyn2qzmtzjmda2zwuyzmq3ztcvchjvdmluc2ktamf3ys10aw11ci1kywxhbs1hbmdrys0ymde4lmh0bww%3d&twoadfnoarfeauf=mjaymc0wms0wmyaxmjoyodoyoa%3d%3d 25,000 20,000 15,000 10,000 5,000 0 1995 2000 2005 2010 2015 2020 sea and freshwater fish production (ton) linear (sea and freshwater fish production (ton)) y = 104.23x – 192,152 r2 = 0.0545 figure 3. chart of total production of fisheries catch in surabaya http://doi.org/10.15826/recon.2019.5.4.020 https://jatim.bps.go.id/publication/download.html?nrbvfeve=otk5owi3mjdkmze2yzawnmvlmmzkn2u3&xzmn=ahr https://jatim.bps.go.id/publication/download.html?nrbvfeve=otk5owi3mjdkmze2yzawnmvlmmzkn2u3&xzmn=ahr https://jatim.bps.go.id/publication/download.html?nrbvfeve=otk5owi3mjdkmze2yzawnmvlmmzkn2u3&xzmn=ahr https://jatim.bps.go.id/publication/download.html?nrbvfeve=otk5owi3mjdkmze2yzawnmvlmmzkn2u3&xzmn=ahr https://jatim.bps.go.id/publication/download.html?nrbvfeve=otk5owi3mjdkmze2yzawnmvlmmzkn2u3&xzmn=ahr https://jatim.bps.go.id/publication/download.html?nrbvfeve=otk5owi3mjdkmze2yzawnmvlmmzkn2u3&xzmn=ahr https://jatim.bps.go.id/publication/download.html?nrbvfeve=otk5owi3mjdkmze2yzawnmvlmmzkn2u3&xzmn=ahr https://jatim.bps.go.id/publication/download.html?nrbvfeve=otk5owi3mjdkmze2yzawnmvlmmzkn2u3&xzmn=ahr 204 www.r-economy.ru r-economy, 2019, 5(4), 198–207 doi: 10.15826/recon.2019.5.4.020 online issn 2412-0731 the amount of marine fisheries production in 2012 was 7039.16 tons, and in 2017 it increased by 8416.6 tons (see table 3) [22]. over the past five years, the production increased by 1377.44 tons. the value of linear equation for marine fisheries production is y = 496.79x – 992,944 and the regression value is r2 = 0.4073 (see figure  4). the production of marine fisheries in surabaya has not increased too much because the boats used by surabaya fishermen mostly use sailboats and outboard motorboats (usually the type of a small boat is 5gt in size). the catchment area of surabaya fishermen’s sea fisheries is in the madura strait, tanjung perak, and sidoarjo areas. table 3 sea fish production for 2012–2017 year sea fish production (tons) 2012 7,039.16 2013 6,927.63 2014 7,291.45 2015 6,840.06 2016 10,578.3 2017 8,416.6 source: badan pusat statistik kota surabaya. retrieved from https://surabayakota.bps.go.id/publication/download. html?nrbvfeve=mzvkztc2zje5mzm4ztnly2q0ndviodm4&xzmn=ahr0chm6ly9zdxjhymf5ywtvdgeuynbzlmdvlmlkl3b1ymxpy2f0aw9ulziwmtg vmdg vmjevmzvkztc2zje5mzm4ztnly2q0ndviodm4l2tvdgetc3vyywjhewetzgfsyw0tyw5na2etmjaxoc5odg1s&twoadfnoarfeauf=mjaymc0wms0wmyaxmjozmdowmq%3d%3d 12,000 10,000 8,000 6,000 4,000 2,000 0 2010 2012 2014 2016 2018 year to ta l o f p ro du ct io n sea fish production (ton) linear (sea fish production (ton)) y = 496.79x – 992,944 r2 = 0.4073 figure 4. chart of production of the catch of marine fisheries in surabaya land in east surabaya is increasingly used for residential purposes and ponds. in 1996, ponds in surabaya were 673 hectares, and in 2017 it increased sharply by 2,470.88 hectares, which means an increase of 1,797.88 hectares [15; 22]. according to the surabaya city environment department’s report of 2016, the group of fish farmers in surabaya included 15 groups with a total of 781 members. the most numerous group of fish farmers is the roh kelem farmer group, with 132 members [23]. the number of freshwater fishery catches production in surabaya has decreased over the last five years by 837.86 tons (see table 4). according to bps data in 2012, it was 8,998.09 tons, and in 2017 it was 8,160.23 tons [22]. this freshwater fishery catches come not only from ponds, but also from other reservoirs such as rivers and keramba – traditional cages used for fish farming in indonesia [24]. the value of linear equation for fresh water fish production is y = –131x + 272,192 and the regression value is r2 = 0.4073 (see figure 5). table 4 production of fresh water fish (other reservoirs such as rivers and keramba) (ton) year production of fresh water fish (tons) 2012 8,998.09 2013 8,371.39 2014 7,924.94 2015 8,114.09 2016 8,176.43 2017 8,160.23 source: badan pusat statistik kota surabaya. retrived from https://surabayakota.bps.go.id/publication/download. html?nrbvfeve=mzvkztc2zje5mzm4ztnly2q0ndviodm4&xzmn=ahr0chm6ly9zdxjhymf5ywtvdgeuynbzlmdvlmlkl3b1ymxpy2f0aw9ulziwmtg vmdg vmjevmzvkztc2zje5mzm4ztnly2q0ndviodm4l2tvdgetc3vyywjhewetzgfsyw0tyw5na2etmjaxoc5odg1s&twoadfnoarfeauf=mjaymc0wms0wmyaxmjozmdowmq%3d%3d production of fresh water fish (ton) linear (production of fresh water fish (ton)) 2010 2012 2014 2016 2018 year 9,200 9,000 8,800 8,600 8,400 8,200 8,000 7,800 to ta l o f p ro du ct io n y = –131x + 272,192 r2 = 0.4278 figure 5. chart of production catch of freshwater fisheries in surabaya http://doi.org/10.15826/recon.2019.5.4.020 https://surabayakota.bps.go.id/publication/download.html?nrbvfeve=mzvkztc2zje5mzm4ztnly2q0ndviodm4&xzmn=ahr0chm6ly9zdxjhymf5ywtvdgeuynbzlmdvlmlkl3b1ymxpy2f0aw9ulziwmtgvmdgvmjevmzvkztc2zje5mzm4ztnly2q0ndviodm4l2tvdgetc3vyywjhewetzgfsyw0tyw5na2etmjaxoc5odg1s&twoadfnoarfeauf=mjaymc0wms0wmyaxmjozmdowmq%3d%253 https://surabayakota.bps.go.id/publication/download.html?nrbvfeve=mzvkztc2zje5mzm4ztnly2q0ndviodm4&xzmn=ahr0chm6ly9zdxjhymf5ywtvdgeuynbzlmdvlmlkl3b1ymxpy2f0aw9ulziwmtgvmdgvmjevmzvkztc2zje5mzm4ztnly2q0ndviodm4l2tvdgetc3vyywjhewetzgfsyw0tyw5na2etmjaxoc5odg1s&twoadfnoarfeauf=mjaymc0wms0wmyaxmjozmdowmq%3d%253 https://surabayakota.bps.go.id/publication/download.html?nrbvfeve=mzvkztc2zje5mzm4ztnly2q0ndviodm4&xzmn=ahr0chm6ly9zdxjhymf5ywtvdgeuynbzlmdvlmlkl3b1ymxpy2f0aw9ulziwmtgvmdgvmjevmzvkztc2zje5mzm4ztnly2q0ndviodm4l2tvdgetc3vyywjhewetzgfsyw0tyw5na2etmjaxoc5odg1s&twoadfnoarfeauf=mjaymc0wms0wmyaxmjozmdowmq%3d%253 https://surabayakota.bps.go.id/publication/download.html?nrbvfeve=mzvkztc2zje5mzm4ztnly2q0ndviodm4&xzmn=ahr0chm6ly9zdxjhymf5ywtvdgeuynbzlmdvlmlkl3b1ymxpy2f0aw9ulziwmtgvmdgvmjevmzvkztc2zje5mzm4ztnly2q0ndviodm4l2tvdgetc3vyywjhewetzgfsyw0tyw5na2etmjaxoc5odg1s&twoadfnoarfeauf=mjaymc0wms0wmyaxmjozmdowmq%3d%253 https://surabayakota.bps.go.id/publication/download.html?nrbvfeve=mzvkztc2zje5mzm4ztnly2q0ndviodm4&xzmn=ahr0chm6ly9zdxjhymf5ywtvdgeuynbzlmdvlmlkl3b1ymxpy2f0aw9ulziwmtgvmdgvmjevmzvkztc2zje5mzm4ztnly2q0ndviodm4l2tvdgetc3vyywjhewetzgfsyw0tyw5na2etmjaxoc5odg1s&twoadfnoarfeauf=mjaymc0wms0wmyaxmjozmdowmq%3d%253 https://surabayakota.bps.go.id/publication/download.html?nrbvfeve=mzvkztc2zje5mzm4ztnly2q0ndviodm4&xzmn=ahr0chm6ly9zdxjhymf5ywtvdgeuynbzlmdvlmlkl3b1ymxpy2f0aw9ulziwmtgvmdgvmjevmzvkztc2zje5mzm4ztnly2q0ndviodm4l2tvdgetc3vyywjhewetzgfsyw0tyw5na2etmjaxoc5odg1s&twoadfnoarfeauf=mjaymc0wms0wmyaxmjozmdowmq%3d%253 https://surabayakota.bps.go.id/publication/download.html?nrbvfeve=mzvkztc2zje5mzm4ztnly2q0ndviodm4&xzmn=ahr0chm6ly9zdxjhymf5ywtvdgeuynbzlmdvlmlkl3b1ymxpy2f0aw9ulziwmtgvmdgvmjevmzvkztc2zje5mzm4ztnly2q0ndviodm4l2tvdgetc3vyywjhewetzgfsyw0tyw5na2etmjaxoc5odg1s&twoadfnoarfeauf=mjaymc0wms0wmyaxmjozmdowmq%3d%253 https://surabayakota.bps.go.id/publication/download.html?nrbvfeve=mzvkztc2zje5mzm4ztnly2q0ndviodm4&x https://surabayakota.bps.go.id/publication/download.html?nrbvfeve=mzvkztc2zje5mzm4ztnly2q0ndviodm4&x https://surabayakota.bps.go.id/publication/download.html?nrbvfeve=mzvkztc2zje5mzm4ztnly2q0ndviodm4&x https://surabayakota.bps.go.id/publication/download.html?nrbvfeve=mzvkztc2zje5mzm4ztnly2q0ndviodm4&x https://surabayakota.bps.go.id/publication/download.html?nrbvfeve=mzvkztc2zje5mzm4ztnly2q0ndviodm4&x https://surabayakota.bps.go.id/publication/download.html?nrbvfeve=mzvkztc2zje5mzm4ztnly2q0ndviodm4&x https://surabayakota.bps.go.id/publication/download.html?nrbvfeve=mzvkztc2zje5mzm4ztnly2q0ndviodm4&x r-economy, 2019, 5(4), 198–207 doi: 10.15826/recon.2019.5.4.020 205 www.r-economy.ru online issn 2412-0731 the number of freshwater fishery catches production in surabaya has decreased over the past ten years (2005–2017), by 2,026.32 tons (see table  5). according to the bps data in 2005, it was 8825 tons, while in 2017 it was 6,798.68 tons. the value of linear equation for marine fisheries production is y = –190.54x + 390,906 and the regression value is r2 = 0.7166 (see figure 6). one of the issues was that ponds in surabaya are still managed in traditional and not always optimal ways. in the dry season, most fisheries ponds in surabaya change their function to become salt ponds. table 5 fish production from pond (ton) year fish production from pond (ton) 2005 8,825 2006 8,573 2007 7,886.15 2008 8,198.9 2009 8,608.7 2010 9,043.3 2011 7,923.84 2012 7,593.18 2013 6,906.1 2014 6,542.09 2015 6,785.15 2016 6,915.03 2017 6,798.68 source: badan pusat statistik kota surabaya. retrived from https://surabayakota.bps.go.id/publication/ download.html?nrbvfeve=mzvkztc2zje5mzm4ztnly2q0ndviodm4&xzmn=ahr0chm6ly9zdxjhymf5ywtvdgeuynbzlmdvlmlkl3b1ymxpy2f0aw9ulziwmtgvmdgvmjevmzvkztc2zje5mzm4ztnly2q0ndviodm 4 l 2 t vd g etc 3 vy y w j he w et z g f s y w 0 t y w 5 na 2 et m jaxoc5odg1s&twoadfnoarfeauf=mjaymc0wms0wmyaxmjozmdowmq%3d%3d 2000 2005 2010 2015 2020 year 10,000 8,000 6,000 4,000 2,000 0 to ta l o f p ro du ct io n fish production from pond (ton) linear (fish production from pond (ton)) y = –190.54x + 390,906 r2 = 0.7166 figure 6. chart of production catch of freshwater fisheries in surabaya permadi researched the potential of ponds in surabaya, there are several reasons why freshwater catchment production has decreased [25]: 1) the ability of farmers to buy seeds that will be cultivated in ponds; 2) uncertain weather conditions; 3) traditional cultivation methods; 4) decreased water quality due to the proximity to factories or housing. conclusion changes in land use to ponds in surabaya have an impact on coastal communities. there are two types of ponds in surabaya, namely fish ponds and salt ponds. with two kinds of fishery catch production in surabaya, namely the marine catch fisheries and freshwater catch fisheries (ponds, reservoirs, rivers). fishery catch production in surabaya increases every year. unsurprisingly, from 1996 to 2017, a growth in the amount of fisheries production and the production value was tenfold, although the number of fishers reduced by 1,806 people. the amount of output in 1996–2017 increased by 3,134.83 tons, and the production value increased by rp 242,971,338,000. one issue is that fish production from ponds decreased over ten years (2005–2017) by 2026.3 tons. remote sensing data show that more and more land is now occupied by ponds in east surabaya, but this trend is not conducive to the development of fish farming in the area. the majority of fish production in surabaya comes from sea fishing while freshwater production is decreasing due to unproductive fish ponds. therefore, some people who are members of parmubaya region on the east coast of surabaya complain about wanting to change their ponds to other types of land use. however, this plan is hindered by the rules of the area, which has the status of a protected or conservation area. further field studies are needed to investigate and monitor the use of land in coastal areas of surabaya. further research might also include interviews with coastal citizens to find out more about the conditions of social economy. it is also necessary to investigate the question of whether the coastal communities in surabaya consist of indigenous inhabitants or migrants. the synergy between government, society, and community in east surabaya is necessary. for example, to provide fishers with income, it is first necessary to train them. the training should include how to catch fish, the system of irrigahttp://doi.org/10.15826/recon.2019.5.4.020 https://surabayakota.bps.go.id/publication/download.html?nrbvfeve=mzvkztc2zje5mzm4ztnly2q0ndviodm4&x https://surabayakota.bps.go.id/publication/download.html?nrbvfeve=mzvkztc2zje5mzm4ztnly2q0ndviodm4&x https://surabayakota.bps.go.id/publication/download.html?nrbvfeve=mzvkztc2zje5mzm4ztnly2q0ndviodm4&x https://surabayakota.bps.go.id/publication/download.html?nrbvfeve=mzvkztc2zje5mzm4ztnly2q0ndviodm4&x https://surabayakota.bps.go.id/publication/download.html?nrbvfeve=mzvkztc2zje5mzm4ztnly2q0ndviodm4&x https://surabayakota.bps.go.id/publication/download.html?nrbvfeve=mzvkztc2zje5mzm4ztnly2q0ndviodm4&x https://surabayakota.bps.go.id/publication/download.html?nrbvfeve=mzvkztc2zje5mzm4ztnly2q0ndviodm4&x https://surabayakota.bps.go.id/publication/download.html?nrbvfeve=mzvkztc2zje5mzm4ztnly2q0ndviodm4&x 206 www.r-economy.ru r-economy, 2019, 5(4), 198–207 doi: 10.15826/recon.2019.5.4.020 online issn 2412-0731 tion, how to sell, process and cook fish. many people in parmubaya did not want to manage their ponds because their ponds are unproductive, the government gave two solutions, first solution is managing the ponds as conservation area which will accompanied by the government. second solution is land acquisition by the government3. 3 protes tekait lahan ke dprd surabaya, petani tambak pamurbaya diberi dua pilihan. retrieved from https://jatim. tribunnews.com/2018/04/09/protes-tekait-lahan-ke-dprdsurabaya-petani-tambak-pamurbaya-diberi-dua-pilihan references 1. djunarsjah, e. (2004). law of the sea. bandung: itb. (in bahasa) 2. kusnadi (2003). the root of the poverty for fishermen. yogyakarta: lkis. (in bahasa) 3. nicholson, w., & snyder, c. (2008). microeconomic theory basic principles and extensions. 10th ed. ohio: thomson south-western. 4. berczi, a. (1981). information as a factor of production. business economics, 16(1), 14–20. 5. boto, i., phillips, s., & d’andrea, m. (2013). fish-farming: the new driver of the blue economy. brussel: technical centre for agricultural and rural cooperation (cta). 6. jihan, j. c. (2014). analysis of zone change land use in east surabaya based on gis. thesis. the department of geomatics engineering faculty of civil engineering and planning. sepuluh nopember institute of technology surabaya indonesia. (in bahasa) 7. sobirin. (2015). urban heat island in surabaya. geoedukasi, 4(2). (in bahasa) 8. ashazy, a. a. 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(in bahasa) information about the authors dika ayu safitri – phd student in department of oceanography, southern federal university (105/42 bolshaya sadovaya str., rostov-on-don, 344006, russia); lecturer in department of civil engineering, universitas 17 agustus 1945 (untag) (jl. semolowaru no.45, menur pumpungan, kec. sukolilo, kota sby, jawa timur 60118, indonesia); e-mail: dikadede@gmail.com liudmila а. bespalova – professor, department of oceanography, southern federal university (105/42 bolshaya sadovaya str., rostov-on-don, 344006, russia); e-mail : bespalowaliudmila@ yandex.ru febry wijayanti – phd student in economics department, ural federal university (19, mira st., ekaterinburg, 620002, russia); lecturer, economic development department, universitas negeri malang (5, semarang st. malang, 65145, indonesia),  e-mail: febry.ie008@gmail.com article info: received august 13, 2019; accepted december 9, 2019 информация об авторах сафитри дика аю – аспирант департамента океанографии, южный федеральный университет (344006, россия, ростов-на-дону, ул. большая садовая, 105/42), университет 17 августа 1945 (унитаг) (60118, индонезия, сурабая, семоловару, 45); e-mail: dikadede@ gmail.com беспалова людмила александровна – профессор департамента океанографии (344006, россия, ростов-на-дону, ул. большая садовая, 105/42); e-mail: bespalowaliudmila@yandex.ru виджаянти фебри – аспирант института экономики и управления, уральский федеральный университет (620002, россия, екатеринбург, мира, 19); лектор департамента экономического развития, университет негери маланг (65145, индонезия, маланг, семаранг, 5); e-mail: febry.ie008@gmail.com информация о статье: дата поступления 13 августа 2019 г.; дата принятия к печати 9 декабря 2019 г. this work is licensed under a creative commons attribution 4.0 international license эта работа лицензируется в соответствии с creative commons attribution 4.0 international license http://doi.org/10.15826/recon.2019.5.4.020 mailto:dikadede@gmail.com mailto:bespalowaliudmila@yandex.ru mailto:bespalowaliudmila@yandex.ru mailto:febry.ie008@gmail.com mailto:dikadede@gmail.com mailto:dikadede@gmail.com mailto:bespalowaliudmila@yandex.ru mailto:febry.ie008@gmail.com 176 www.r-economy.ru r-economy, 2019, 5(4), 176–188 doi: 10.15826/recon.2019.5.4.018 online issn 2412-0731 original paper © d. yu. fraymovich, m. a. gundorova, z. v. mischenko, s. i. totmyanina, a. zh. panzabekova, 2019 doi 10.15826/recon.2019.5.4.018 estimation of modernization potential of russian federal districts d. yu. fraymovich1 , m. a. gundorova 1, z. v. mischenko 1, s. i. totmyanina1, a. zh. panzabekova2 1 vladimir state university n.a. alexander and nikolay stoletovs, vladimir, russia; e-mail: fdu78@rambler.ru 2 institute of economics of the committee of science of the ministry of education and science of the republic of kazakhstan, almaty, kazakhstan abstract the article discusses the resource potential of russian federal districts involved in processes of modernization. the theoretical framework draws from russian and international studies of economic potential, stability and efficiency in regional development and regional imbalances. methodologically, the research relies on a series of relative indicators of innovation, which can be used to measure federal districts’ modernization potential by applying methods of mathematical statistics. the proposed set of criteria allows us to take into consideration both the current situation and the dynamics of innovation development in russian regions. the selected indicators characterize the returns from innovation investment in socio-economic systems, the degree of regional differentiation within districts and trends of regional development regarding the efficiency of innovation processes. the proposed approach can be used to measure the efficiency of human capital use. to test the above-described methodology, we decided to focus on the central federal district, which has a significant resource potential necessary to meet the demands of intensive modernization. statistical comparison of the actual and limit values has revealed significant underused resources in this district. these resources can be accessed by stimulating the lagging regions. the described methods and results of this study can be used by research organizations, higher education institutions, regional authorities and policy-makers in the process of preparation, adjustment and monitoring of strategic programs of socio-economic development. keywords federal district, resource potential, modernization potential, innovation for citation fraymovich d. yu., gundorova m. a., mischenko z. v., totmyanina s. i., panzabekova a. (2019) estimation of modernization potential of russian federal districts. r-economy, 5(4), 176–188. doi: 10.15826/recon.2019.5.4.018 оценка модернизационно-ресурсного потенциала федеральных округов россии д. ю. фраймович1 , м. а. гундорова1, з. в. мищенко1, с. и. тотьмянина1, а. ж. панзабекова 2 1 владимирский государственный университет имени а. г. и н. г. столетовых, г. владимир, россия; e-mail: fdu78@rambler.ru 2 институт экономики комитета науки министерства образования и науки республики казахстан, г. алматы, казахстан аннотация в статье рассматривается ресурсный потенциал федеральных округов россии, вовлеченных в процессы модернизации. теоретическая основа статьи построена на российских и международных исследованиях экономического потенциала, региональных дисбалансов, стабильности и эффективности регионального. методологически исследование опирается на ряд относительных показателей инноваций, которые можно использовать для измерения модернизационного потенциала федеральных округов путем применения методов математической статистики. предложенный набор критериев позволяет учитывать как текущую ситуацию, так и динамику инновационного развития в российских регионах. выбранные показатели характеризуют отдачу от инновационных инвестиций в социально-экономические системы, степень региональной дифференциации по районам и тенденции регионального развития в отношении эффективности инновационных процессов. предложенный подход может быть использован для измерения эффективности использования человеческого капитала. чтобы проверить вышеописанную методологию, мы решили сосредоточиться на центральном феключевые слова федеральный округ, ресурсный потенциал, модернизационный потенциал, инновация http://doi.org/10.15826/recon.2019.5.4.018 http://doi.org/10.15826/recon.2019.5.4.018 mailto:fdu78@rambler.ru mailto:fdu78@rambler.ru r-economy, 2019, 5(4), 176–188 doi: 10.15826/recon.2019.5.4.018 177 www.r-economy.ru online issn 2412-0731 деральном округе, который обладает значительным ресурсным потенциалом, необходимым для удовлетворения потребностей интенсивной модернизации. статистическое сравнение фактических и предельных значений выявило значительные недоиспользованные ресурсы в этом районе. к этим ресурсам можно получить доступ, стимулируя отстающие области. описанные методы и результаты данного исследования могут быть использованы исследовательскими организациями, высшими учебными заведениями, региональными органами власти и политиками в процессе подготовки, корректировки и мониторинга стратегических программ социально-экономического развития. для цитирования fraymovich d. yu., gundorova m. a., mischenko z. v., totmyanina s. i., panzabekova a. (2019) estimation of modernization potential of russian federal districts. r-economy, 5(4), 176–188. doi: 10.15826/ recon.2019.5.4.018 introduction processes of resource formation and use in russian federal districts are the main focus of a number of state programs aimed at stimulating modernization in federal districts and adapted for specific socio-economic, geographical, infrastructural, scientific and technological conditions in these districts. the programs are targeted at maximizing the economic potential of territories, which makes it pertinent to devise and improve methods of estimating this potential. straightforward estimation is impossible in this case and it is necessary to minimize the statistical parameters characterizing only certain parts of general development trends. it is also important to take into account the long time lag to ensure that the results of monitoring could present an objective picture of regional innovation trends. furthermore, it is crucial to analyze the information about the existing regional imbalances, their causes and measures taken to deal with them. it should be noted that analysis results can be reliable only if the research uses official statistical data, coherent and consistent methodology and quantified measures. theoretical framework the development of conceptual approaches to fostering regional innovation, according to e. b. lenchuk, at its initial stage, requires creation of a full ‘inventory valuation’ of the region’s economic and industrial potential [1, p. 16]. it should be noted that most research papers discussing the methods of evaluating regional innovation capacity identify a specific range of resources which are considered to be strategically important (principal component) [2–4]. for instance, the study of the innovative potential of twelve northern russian regions is based on 21 indicators available in official statistics [2]. after processing primary indicators by method of principal components, the researchers identified five basic factors whose characteristic values were greater than unity and covered most of the total variance (about 90%) in the monitoring period between 2012 and 2014. then, using the hierarchical cluster analysis, the authors identified the groups of regions with different levels of innovation potential and drew these groups’ profiles. the majority of such studies rely on quantitative (precise) calculation methods and representative sets of factors divided into separate blocks and reflecting the degree of resource development. however, this methodology is applied to analyze short intervals, which somewhat limits the judgement about the dynamic component of resource development in particular regions. nevertheless, this approach is quite relevant and can be useful as a part of expanded methodology for diagnostics of innovation potential in russian region. another modern approach of assessing the efficiency of research and development (r&d) activity in regions was proposed by a team of scholars from the financial university (moscow) [3] – the dea-modeling method (data envelopment analysis), based on building an efficient frontier in the space of ‘input’ and ‘output’ variables. the first group of input (i.e. resource-related) components includes the following: the number of r&d organizations; share of innovation-active organizations; number of staff involved in research work; expenses for technological innovations; expenses for research and development. the second group of output (resulting) characteristics includes the following: the number of submitted patent applications and granted patents; scope of shipped innovation products; number of publications in journals indexed in the international abstract research database; developed and used advanced production technologies; share of graduate students and doctoral candidates with defended papers. regions’ performance is determined by degree of their proximity to the specific frontier, adopted as a benchmark (reference point) and built via repeated solution of the linear programming problem. the indisputable methodological advantage of this approach is its focus on using http://doi.org/10.15826/recon.2019.5.4.018 178 www.r-economy.ru r-economy, 2019, 5(4), 176–188 doi: 10.15826/recon.2019.5.4.018 online issn 2412-0731 advanced methods of data analysis (dea-modeling and r-project system) as well as further ranking of regions by various individual indicators by taking into account their entropy defined through shannon’s equation. there is, however, one aspect of this methodology that requires extra clarification – the practical side of the correlation between the results of research and development (r&d) activity and the region’s potential (resources). the researchers have proposed the following formula to calculate efficiency эr&d: =   &   &   ,i r dsia j r d r э p where ri r&d is the results of research and development; i = 1 … r; pi r&d, the potential, j = 1 … p. in general, r ≠ p. what raises most questions is the interpretation of the results of division: for instance, the number of publications (result) by the share of innovation-active organizations (resource description) looks quite problematic. moreover, the selection of the optimal scale which the final figure should tend to is quite complicated. yet another problem is that the proposed approach does not indicate the time interval of calculations to rank the regions according to their r&d performance. nevertheless, we must give credit to the authors of the method for their use of modern analytical systems and tools in processing of significant data arrays and for obtaining valuable results suitable for practical implementation in regional development programs. not denying the importance of assessing efficient resource development in regions, it would be reasonable to add that, to ensure the prosperity of the whole state, it is more important to analyze explicit and latent reserves for innovative growth (in terms of federal districts) on the level of federal districts. a key organizational and managerial aspect is to identify the specific characteristics of the innovation policy design and implementation in federal districts by taking into consideration the structure of their innovation potential and role in the national economy [5, p. 60]. therefore, a closer look is needed at the main trends in regional performance, which renders crucial the questions of the patterns of growth, stability, dynamics, and predictability in development of socio-economic systems. the methodological framework for studying these questions is constantly updated [6-9]. for example, american scholars e.  hill, h. viall, and h. volman define stability as the area’s ability to recover successfully from economic shocks, which either push it off the path of growth or at least have such potential [6]. a similar definition is offered by k. foster, who identifies stability as a region’s ability to anticipate, prepare for, respond to, and recover from disorder [7]. according to l. geely and h. harass [8], who analyzed the dynamics of change in well-being of south-east asia population, the rate of long-term economic growth is of fundamental importance for society’s living standards; it is an irreplaceable mechanism for getting people out of poverty. according to researchers from the russian presidential academy of national economy and public administration (moscow), a conceptual framework for the theory of regional stability as a field of russian regional economics should comply with the contemporary western (european) standards. this will allow russian economists to develop guidelines and recommendations for regions to be able to maintain their viability in situations of crisis by mitigating external threats and their impact on socio-economic growth [9, p. 180]. modernization processes and their effectiveness in federal districts is mostly determined by the depth of innovative transformations on the regional level. of course, territorial transformations occur unevenly, which significantly affects the degree of resource development and realization of the overall economic potential on the national level. recently, much scholarly attention has been focused on the issues of regional differentiation [10–14]. p. krugman introduced his core-periphery model in 1991 and thus made a significant contribution to systematization of our knowledge about the conditions and patterns of resource concentration within a limited area (region) [10]. as most current research shows, however, provision of a higher level of living standards is often impeded by the severe economic imbalance within a state or region. therefore, experts studying socio-economic systems find it crucial to define and justify the reasons behind significant interregional imbalances in specific indicators; to identify the optimal variance boundaries (based on the cases of success); and to describe the prospects of leveling these differences through targeted state support. as for significant regional differences, some regions tend to accumulate the advantages at the expense of others, which can exacerbate the crisis http://doi.org/10.15826/recon.2019.5.4.018 r-economy, 2019, 5(4), 176–188 doi: 10.15826/recon.2019.5.4.018 179 www.r-economy.ru online issn 2412-0731 and leads to the disruption in homogeneity of the socio-economic space. unequal regional development means slower economic growth, depletion of human capital, underperformance of regions in terms of technological development, declining public trust in the government, weaker economic and social relations [11, p. 68]. according to v. n. leksin, apart from depopulation in the vast areas of russia, the crisis of the settlement system has led to the degradation and lumpenization of a large part of the country’s labor force, reduction in the country’s economic potential [12, p. 4]. further increase in the interregional differentiation will require the federal centre to take new political decisions to level the differences [13, p. 148]. there is no doubt that such unbalanced economic structure means higher risk and requires revision of the currently implemented public policies of innovation support as well as a significant reduction in the influence of moscow agglomeration to the benefit of other regions. this is due to the fact that concentration of financial and infrastructural resources in one region in potentially adverse market conditions may lead to deterioration of the entire socio-economic system, whose economic processes mostly depend on a particular area. such trend should be addressed through various state programs aimed at redistribution of funds in favor of depressed, struggling areas. the goals of such programs should include the renewal of fixed assets, development of knowledge-intensive enterprises and establishment of modern infrastructure in the production sector, in research and education. r. bakhtizin, however, is quite pessimistic about this trend, pointing out that ‘financial equalization’ through money transfers from the federal budget to heterogeneous regional economies is nothing but a ‘mothballing’ strategy as it does not create sufficient incentives for economic growth. subsidies have no practical effect on investment processes in regions and do not ensure sufficient stimulation for efforts of regional authorities to develop business and attract investors on the basis of public-private partnership. therefore, financial equalization does not necessarily lead to economic leveling [14, p. 88]. in order to get an understanding of how russian federal districts make use of their resource potential to modernize, we need to analyze this situation in different dimensions and identify the prospects of regional development by taking into account the state of the current socio-economic and innovation environment. research methods the lack of complete data on the dynamics and scope of current transformations in russian federal districts leads us to using combinatorial values based on official rosstat data. it should be noted that significant differences between constituent areas in a federal district (according to the key modernization parameters) imply that there are organizational and economic opportunities to reduce the detected differentiation by involving the resources which often remain unused in certain areas [15, p. 43]. our diagnostics of the modernization potential of federal districts was conducted by using special computer software, whose applicability is confirmed by the state registration certificate [16]. for our assessment, we chose a series of seven relative indicators on the basis of the available rosstat data on r&d development of russian regions. these indicators show the degree of development for certain types of resources and final level of use for economic modernization potential in federal districts – from 2000 to 2017. 1. indicator of efficiency for innovative activities iэ of enterprises in a specific federal district in the last analyzed period (2017) is calculated by formula (1): = = ∑ 1 1 , n i э ii v i n c (1) where vi is the scope of innovative products, works, services in the ith region of the federal district; ci, the costs of technological innovations in the ith region of the federal district; and n, the number of regions in this federal district. it should be noted that to calculate the payoff from innovation in the relevant period, we need to use the data on the expenditures in the previous year – given the chain reaction (delay in a certain time lag) of production facilities for funding the technological innovation. performance indicator of a research organization operated in ip district, achieved in the last analyzed period (2017), is calculated by formula (2): = = ∑ 1 1 , n i р ii t i n o (2) where ti is the number of advanced production technologies in the ith region of the federal district; oi, the number of r&d organizations in the http://doi.org/10.15826/recon.2019.5.4.018 180 www.r-economy.ru r-economy, 2019, 5(4), 176–188 doi: 10.15826/recon.2019.5.4.018 online issn 2412-0731 ith region of the federal district; n is the number of regions in this federal district. this criterion indicates the level of activity for scientific organizations in a certain area. 3. variation factor kэ for efficiency of innovation in regions of a certain federal district, in the last analyzed period (2017), looks the following way (3): σ = ,iэ э k i э (3) where σiэ ia the mean root square deviation of performance indicators for innovation in regions of this federal district. this indicator shows the degree of territorial segregation by payoff from innovation and it should be aimed at the minimum possible value. 4. variation factor for operating performance of r&d organizations kр in regions of a certain federal district, for the last analyzed period (2017), is calculated by formula (4): σ = ,ipp p k i (4) where σiр is the mean root square deviation of operating performance indicators for r&d organizations in regions of this federal district; kр provides information on the degree of regional imbalance (by performance of r&d organizations) and it should have a downward trend. 5. for a federal district, the indicator of stable development (by efficient innovative activities) is found on the basis of (5): ≤ α =  > α ,        , 0,    э э s p s p (5) where kэ is the coefficient of time factor t in linear regression equation iэ = sэ · t + bэ; bэ, the permanent offset; p, the significance of influence caused by time factor t on indicator iэ in the regression model defined during variance analysis; , the critical value of significance level p. indicator (sэ) reflects the tendencies and predictability in the performance indicators of innovation, while characterizing the tangent of the formed trend with respect to the time axis. it should be noted that it is also important to test the significance of regression equation (p). the stability factor is accepted if p ≤ 0.05 6. the stability factor for the development of a federal district (by efficient functioning of r&d organizations sр) is found on the basis of (6): ≤ α =  > α , , 0, p p s p s p (6) where sp is the coefficient of time factor t in linear regression equation ip = sp · t + bp; bp, the permanent offset; p, the significance of influence caused by time factor t on indicator ip in the regression model defined during variance analysis; α, the critical value of significance level p. indicator (sp) shows a stable change in the performance indicators of r&d organizations (ip) in the given federal district. in the way similar to previous criterion, it takes a specific value, if p ≤ 0.05. otherwise, the stability factor is assumed to equal zero. 7. efficiency indicator on use of human capital ic in the federal district, for the last analyzed period (2017), is calculated by formula (7): = = ∑ 1 1 , n i c ii v i n p (7) where pi is the labor force in the ith region of this federal district. the proposed indicator (ic) describes the relative scope of innovation product, made by one able-bodied person in the territory of a certain federal district, within a certain time interval. in fact, you can say that it shows the performance of high-tech labor in monetary terms. an opportunity for successful modernization of the federal district’s economy appears, if the indicators are greater than or equal to the limit values, which can be calculated by using the statistical data on economically successful (in terms of innovation) russian regions or international practice. results for further calculations, we are going to use the data on the three most industrially developed federal districts (central federal district, volga federal district, and ural federal district), which together have for a long time accounted for about 65% of the country’s gdp. furthemore, it would be reasonable to compare the obtained indicators with the corresponding values for the whole of russia, which can be taken as normative values. for our calculations we used the official data from the statistical digests “regions of russia. socio-economic indicators” published by rosstat1. a fragment of the calculations of the performance 1 retrieved from: http://www.gks.ru/wps/wcm/connect/ rosstat_main/ rosstat/ru/statistics/publications/catalog/ http://doi.org/10.15826/recon.2019.5.4.018 http://www.gks.ru/wps/wcm/connect/rosstat_main/ rosstat/ru/statistics/publications/catalog/ http://www.gks.ru/wps/wcm/connect/rosstat_main/ rosstat/ru/statistics/publications/catalog/ r-economy, 2019, 5(4), 176–188 doi: 10.15826/recon.2019.5.4.018 181 www.r-economy.ru online issn 2412-0731 indicators for innovation in the regions of the central federal district and for russia in general, based on formula (1), is shown in table 1. as for the question of potential anomalies in the development of the area (in particular of the central federal district), it should be noted that our study focuses exclusively on relative indicators, which ensure objective assessment of the results of innovation processes. if we look at the absolute statistical indicators (amount of innovative production, turnover of small businesses, etc.), we will see that the city of moscow occupies the dominant position, its results exceeding those of other regions ten and hundred times. if we calculate specific values (turnover per capita, per enterprise, etc.), however, they may present us with a radically different picture. as table 1 illustrates, in 2017, the value of indicator iэ in moscow (0.88) exceeds only that of ivanovo region (0.61) and therefore it is by no means extraordinary. therefore, our methodology enables us to make calculations for geographically and economically large regions. table 2 illustrates the calculations of indicators “2” and “4” (by using formulae (2) and (4)), which characterize the performance of r&d organizations iр and variability kp of these indicators in the regions of the volga federal district in 2017. for the graphical analysis of the distribution of the values of iэ and iр and their changes in the reporting periods (2000–2017), we used statistica 10.1 software to build the range chart (see figure 1 and 2). table 2 performance of r&d organizations in the volga federal district, in 2017 region iрi σip kр volga federal district 0.33 0.24 0.73 republic of bashkortostan 0.11 – – mari el republic 0.38 – – republic of mordovia 0.59 – – republic of tatarstan 0.50 – – udmurtia 0.64 – – chuvash republic 0.11 – – perm region 0.51 – – kirov region 0.04 – – nizhny novgorod region 0.33 – – orenburg region 0.03 – – penza region 0.07 – – samara region 0.39 – – saratov region 0.18 – – ulyanovsk region 0.75 – – table 1 indicators of innovation in russian regions for 2001–2017 territory (region) / year 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 rf 2.95 3.02 3.36 3.58 3.74 5.43 4.54 4.71 3.04 3.12 5.26 3.92 3.88 3.22 3.17 3.63 3.24 central federal district 2.11 3.89 2.54 3.59 3.53 4.86 4.60 6.10 3.86 3.00 4.62 3.40 3.82 3.58 3.95 4.08 2.12 belgorod region 23.48 1.47 2.31 2.15 5.52 1.70 18.21 41.27 8.60 7.84 5.03 10.15 13.04 20.86 7.14 23.57 4.97 bryansk region 8.06 22.56 3.65 22.76 18.46 11.49 13.78 12.22 13.81 10.67 6.25 8.16 2.74 4.00 20.42 20.64 4.37 vladimir region 4.53 3.52 3.66 3.78 3.11 10.46 5.27 2.75 2.38 1.55 6.52 7.99 6.45 4.83 4.57 2.13 5.05 voronezh region 2.39 4.39 5.26 7.01 10.88 3.13 7.64 4.56 1.20 2.87 4.89 1.80 2.05 3.27 7.40 2.74 4.20 ivanovo region 14.98 6.26 4.18 1.24 0.68 1.93 18.53 2.52 2.54 0.61 0.99 0.63 0.58 2.10 5.97 0.92 0.61 kaluga region 5.13 8.00 7.18 9.73 3.67 3.94 6.15 3.50 2.37 5.29 2.94 2.30 2.35 0.88 1.10 1.20 1.80 kostroma region 23.59 3.25 15.99 5.97 1.14 1.20 2.31 7.27 4.93 3.83 3.99 7.51 3.14 4.96 4.52 5.36 12.73 kursk region 2.80 1.62 1.19 1.12 2.18 2.12 1.62 2.17 0.63 1.37 9.94 3.39 3.09 1.73 3.32 24.16 13.58 lipetsk region 7.59 0.98 37.04 58.95 9.59 6.70 9.25 9.42 16.98 1.23 1.40 1.28 4.62 6.40 5.67 6.81 3.99 moscow region 10.22 6.29 5.65 4.99 5.24 7.49 11.32 7.59 7.57 7.93 8.64 13.58 4.56 3.30 2.73 2.66 3.03 orel region 15.44 22.71 38.66 5.35 2.92 6.07 1.20 3.82 1.60 7.34 9.17 1.59 2.99 2.03 1.08 2.14 0.93 ryazan region 10.55 5.41 0.78 2.49 1.48 1.70 2.68 3.54 2.44 3.77 2.16 1.58 0.95 1.01 0.77 2.97 3.08 smolensk region 15.01 15.22 6.87 1.68 0.71 2.17 3.67 3.60 4.17 2.10 1.79 1.60 3.64 7.29 3.18 1.52 3.29 tambov region 3.08 4.87 1.71 9.60 5.91 13.42 6.69 4.23 2.71 2.16 4.21 2.98 0.92 3.41 3.06 2.44 1.90 tver region 2.35 2.94 2.45 4.10 4.03 13.40 4.31 16.55 14.89 10.08 11.66 4.85 4.69 0.73 4.15 4.94 0.98 tula region 1.91 0.91 2.46 2.98 2.03 2.33 0.91 2.90 0.67 1.31 7.38 11.40 4.16 4.40 6.31 5.74 4.65 yaroslavl region 1.40 1.44 0.81 4.60 8.66 6.65 2.60 3.91 2.56 3.69 2.22 2.36 1.51 2.04 1.13 4.13 8.08 moscow city 0.33 0.87 0.38 1.93 2.20 3.38 2.38 3.74 1.87 2.48 6.93 2.88 3.88 4.10 4.80 4.79 0.88 http://doi.org/10.15826/recon.2019.5.4.018 182 www.r-economy.ru r-economy, 2019, 5(4), 176–188 doi: 10.15826/recon.2019.5.4.018 online issn 2412-0731 as seen from the first chart (figure 1), the degree of variation in efficiency indicators for innovation development in the regions of the central federal district for the given period (2001–2017) shows a clear downward trend. on the one hand, in the light of the national task of reducing the interregional differentiation, the current situation in this district looks quite optimistic. on the other hand, we still cannot say that the median values of the analyzed indicators are improving and, therefore, there is no evidence of a pronounced positive trend, which would show any return on the government spending on technological innovation. a change in the median of the efficiency indicator (innovation activity in the regions of the central federal district) may be considered insignificant – compared to random fluctuations 70 60 50 40 30 20 10 0 –10 2001 2003 2005 2007 2009 2011 2013 2015 2017 iэ median 25–75% range w/o anomalies anomalies extreme points figure 1. range chart of performance indicator values for innovation in regions of the central federal district, in 2001–2017 note: “median” signifies the value splitting the analyzed sample of 18 regions in two groups (9 regions demonstrate values below the median, and 9 regions, above the median); “25%–75%” is the rectangle corresponding to 25% and 75% quartiles; “range without anomalies” stands for the range of indicator values with no account for anomalies in observations; “anomalies” are the points corresponding to anomalies; “extreme points” are the points corresponding to extreme values in the sample median 25–75% range w/o anomalies anomalies extreme points 2000 2002 2004 2006 2008 2010 2012 2014 2016 ip 2.8 2.6 2.4 2.2 2.0 1.8 1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2 0 –0.2 figure 2. range chart of performance indicators for r&d organizations in regions of the central federal district, 2000–2017 http://doi.org/10.15826/recon.2019.5.4.018 r-economy, 2019, 5(4), 176–188 doi: 10.15826/recon.2019.5.4.018 183 www.r-economy.ru online issn 2412-0731 of iэ values in individual regions. it allows us to conclude that the average efficiency of innovation in the district remains virtually unchanged. however, this indicator shows isolated positive anomalies, which means that there are leading regions and that other regions also have some potential for modernization due to the available reserves for potential growth in returns on the spending on technological innovation. the analysis of performance indicators for r&d organizations in 2000–2017 (see fig. 2) showed a minor change in ip median in the regions of the central federal district compared to random factors. in the given period, the range of values shows substantial heterogeneity (including the interquartile range), which increased considerably since 2012. it may be interpreted as a sign of significant disparities between the regions in terms of their r&d organizations’ performance. to assess the stability of modernization processes by using formulae (5) and (6), we conducted a retrospective analysis of the values of innovation performance and efficiency of r&d organizations (in the given federal districts and russia in general, in 2000–2017). the results of these calculations are shown in table 3. to calculate the stability of innovation efficiency indicators and performance indicators of r&d organizations (based on the data in table 3), we conducted a paired regression analysis and estimated the statistical significance of the obtained factors. figure 3 illustrates the results of the analysis for the central federal district. as follows from the results of the analysis of innovation efficiency indicator iэ in the central federal district (depending on the reporting period), the effect of the time factor, compared to random factors, is insignificant since fisher’s statistical significance level is 86.8%, which substantially exceeds the critical level of 5%. therefore, the stability value of innovation efficiency indicators sэ (for this district, in 2001–2017, for (5) criterion) is taken as equal to zero. table 3 indicators of innovation efficiency iэ and performance indicators of r&d organizations ip in russian federal districts, 2000–2017 year central volga ural russia iэ ip iэ ip iэ ip iэ ip 2000 – 0.16 – 0.26 – 0.36 – 0.17 2001 2.11 0.13 4.92 0.28 2.12 0.42 2.95 0.16 2002 3.89 0.14 1.95 0.24 7.05 0.66 3.02 0.19 2003 2.54 0.24 3.02 0.24 5.05 0.58 3.36 0.22 2004 3.59 0.14 4.28 0.31 4.17 0.31 3.58 0.18 2005 3.53 0.14 6.74 0.27 2.47 0.35 3.74 0.18 2006 4.86 0.18 9.48 0.30 3.66 0.44 5.43 0.20 2007 4.60 0.18 6.79 0.31 2.64 0.38 4.54 0.20 2008 6.10 0.22 6.68 0.33 2.39 0.25 4.71 0.21 2009 3.86 0.20 4.42 0.30 1.08 0.39 3.04 0.22 2010 3.00 0.27 6.72 0.27 1.34 0.48 3.12 0.25 2011 4.62 0.30 9.86 0.29 1.95 0.59 5.26 0.31 2012 3.40 0.29 5.75 0.42 1.43 0.61 3.92 0.37 2013 3.82 0.38 4.62 0.39 1.78 0.76 3.88 0.40 2014 3.58 0.33 4.14 0.46 1.29 0.76 3.22 0.39 2015 3.95 0.34 3.62 0.33 1.76 0.74 3.17 0.33 2016 4.08 0.37 4.73 0.40 3.03 0.98 3.63 0.38 2017 2.12 0.33 5.58 0.34 3.30 0.96 3.24 0.36 2001 2003 2005 2007 2009 2011 2013 2015 2017 6.10 iэ 4.60 3.82 3.40 3.00 2.54 2.11 figure 3. graph of the linear regression dependence between indicator and time, for the central federal district, in 2001–2017 http://doi.org/10.15826/recon.2019.5.4.018 184 www.r-economy.ru r-economy, 2019, 5(4), 176–188 doi: 10.15826/recon.2019.5.4.018 online issn 2412-0731 the graphical analysis of the dependence between the innovation efficiency indicator and time (in russia and the volga federal district) leads us to a similar conclusion. it is nearly impossible to detect any development in the trend or trend slope (set by the regression equation) against the background of random factors, i.e., confidence limits. it follows from the above that the stability value of innovation efficiency in russia and the volga federal district is sэ = 0. in line with the given criteria, the innovation development is quite pronounced (compared to previous cases) in the ural federal district. location of the observed iэ values along the confidence limits, the negative tangent of the trend line with respect to the time axis, relatively high modulus of the correlation factor (r = –0.51), and significance level р = 0.035 lead us, according to condition (5), to estimate the stability value for the ural federal district as sэ = –0.159. the results of our statistical analysis of the stability factors for performance indicators of r&d organizations ip were obtained for all given territories in the way similar to the previous stage of calculations, based on condition (6). for example, the graph of the linear regression dependence between ip indicator and time (for the volga federal district) looks as follows (figure 4). the results of the regression analysis for the stability indicator (performance parameters of research organizations in the volga federal district), depending on reporting period, show that the effect of the time factor, compared to random factors, is significant: fisher’s statistical significance level is p = 0.5%. in this case, the regression equation looks the following way: ip  =  –0.6213  +  0.0086t, where t is the reporting time period. therefore, for the volga federal district, in 2000–2017, the stability indicator is taken as equal to sp = 0.0086 for the central federal district, this indicator is sp = 0.0146; for russia, sp = 0.0147; for the ural federal district, sp = 0.0296. our calculation of the seventh indicator, reflecting the efficient use of human capital in the district for 2017 (formula (7)), allows us to conclude that, in the central federal district, this potential is not rationally used – compared to average russian figures as well as the results of the ural and volga federal districts. the lag from the reference indicator (for the volga federal district) is 40% (figure 5). ic ufd vfd cfd rf territories 0 10 20 30 40 50 60 70 80 90 72.97 78.42 47.36 54.75 figure 5. graphic interpretation of the indicators of efficiency of human capital use in russian federal districts (ic), ths rbs/person ip 2000 2002 2004 2006 2008 2010 2012 2014 2016 0.46 0.42 0.39 0.33 0.30 0.28 0.26 0.24 figure 4. graph of the linear regression dependence between ip indicator and time (for the volga federal district) http://doi.org/10.15826/recon.2019.5.4.018 r-economy, 2019, 5(4), 176–188 doi: 10.15826/recon.2019.5.4.018 185 www.r-economy.ru online issn 2412-0731 table 4 summarizes the results of our calculation of the actual parameters (1)–(7) in the given federal districts and russia in general. table 4 actual values of (1)–(7) indicators for federal districts and russia indicators central fd russia volga fd ural fd iэ 4.340 8.818 6.156 6.520 ip 0.437 0.430 0.331 1.035 kэ 0.860 3.368 0.510 1.645 kр 1.161 1.484 0.732 1.161 sэ 0.000 0.000 0.000 –0.159 sp 0.015 0.015 0.009 0.030 iс 47.362 54.750 78.424 72.975 however, for accurate comparison of territories within the unified assessment system, these values require some standardization, i.e., being brought to a common comparative base. thus, we are going to conduct a two-level analysis according to standard and reference criteria. the indicator values we obtained for russia can be referred to as standard indicators while the best results for the given federal districts, as reference these limits are taken as 1 (100%). if an increase of the factor is caused by the improvement of the situation in the sphere of innovation (indicators “1”–“2”, “5”–“7”), the specific value for the selected federal district (numerator) is correlated with the standard and reference indicators for other districts (country). the inverse relationship between the changes of the factor and the improved situation (indicators “3”–“4”) means that we need to change the procedure and correlate the limit values with the actual ones (for the given district). we tested our methodology for diagnostics of regional modernization potential by using the data on the central federal district (table 5). table 5 results of calculations of standardized indicators “1”–“7” for the central federal district indicator normative indicators (for the central federal district) reference indicators development of the district’s modernization potential in comparison with: normative indicators reference indicators iэ 1 1 (rf) 0.49 0.49 ip 1 1 (ufo) 1.02 0.42 kэ 1 1 (vfd) 3.92 0.59 kр 1 1 (vfd) 1.28 0.63 sэ 1 1 (–) – – sp 1 1 (ufo) 0.99 0.49 iс 1 1 (vfd) 0.87 0.65 since estimation of modernization of potential of a regional economy is conducted by using a set of indicators “1”–“7”, the general result will be presented as a radar chart. figure 6 shows the diagram of the summary data from table 5. 4.0 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0 attitude to normative indicators attitude to reference indicators iэ ipic kэ kpsэ sp figure 6. radar chart for estimating modernization potential of the economy of the central federal districts for indicators (1)–(7) we compared indicators “1”–“7” for the central federal district with the standard and reference values, which led us to the following conclusion. the results of this district are unsatisfactory for the majority of parameters. moreover, this alarming trend can be observed in other, more developed regions of russia as well as for the overall situation in the country (standard values). thus, iэ indicator for the central federal district is twice lower than the standard and reference value for the whole country, while being 30% below that of the volga and ural federal districts. the dynamics of all the given federal districts in terms of innovation efficiency also leaves much to be desired. in this situation, the position of the central federal district can be described as “equal among the worst”: russia in general as well as the central and volga federal districts demonstrate zero stability in the indicators of return on innovation investment (see table 4). within the confidence limit, pronounced stability in the selected indicators with respect to the time axis is characteristic only of the ural federal district. however, the annual decrease in efficiency, which can be seen from the negative tangent of trend (sэ  = –0.159), does not give us grounds for optimism regarding the turnover of innovative products (per one ruble of modernization expenses). http://doi.org/10.15826/recon.2019.5.4.018 186 www.r-economy.ru r-economy, 2019, 5(4), 176–188 doi: 10.15826/recon.2019.5.4.018 online issn 2412-0731 the results of the central federal district, on the contrary, offer some hope, compared to standard values of interregional variability in innovation efficiency (kэ) and effectiveness of r&d organizations (kp). moreover, it should be noted that stability (sp) of (ip) indicators in 2000-2017 is comparable to the limit values for russia. these facts mean that the district has some real potential for adoption of new knowledge (iэ), efficient functioning of r&d organizations (ip), and the full use of human capital (ic). furthermore, variation factor kp for the central federal district is almost 60% above the similar reference value for the volga federal district, thus indicating significant under-used resources in the district, which can be accessed by stimulating lagging regions. thus, it seems appropriate to classify the central federal district as a territory with considerable modernization potential. our analysis on the basis of quantitative approach has enabled us to create an indicator system (for diagnostics of a federal district) and conduct comprehensive monitoring of the district’s capabilities. at that, the system of indicators (1–7) allows us to take into consideration the current situation as well as to estimate the dynamic component. indicators iэ, ip, and iс characterize the return on the unit of resources invested into innovation within a district; kэ and kр, differentiation of regions within a district; sэ and sр, trends of district development in terms of innovation efficiency and performance. based on that, the proposed indicator system and analytical methods can be applied to conduct diagnostics of the modernization potential of a federal district, relying on the minimum possible amount of statistical data. in general, although the central federal district has a developed infrastructure and considerable research and manufacturing capabilities as well as a favourable geographical location, it fails to use its modernization potential efficiently enough. meanwhile, there are actual targets for building this potential – in the form of specific innovation results demonstrated by the district, both in the reporting period and in a long period of time. furthermore, the reference values of indicators ip and sp for the central ural district as well as indicators kэ, kр and, ic for the volga federal district indicate that there are opportunities for better use of territorial economic reserves. conclusions modernization transformations in russian federal districts are stimulated through state strategic programs adapted for specific socio-economic, geographical, infrastructural, scientific and technological conditions of territories. analysis of these conditions cannot consist only of straightforward estimations and rely on a limited number of factors. calculation results need to reflect innovation trends in federal districts by taking into account a long retrospective time lag. it should be noted that for adequate diagnostics of modernization potential of territories, we need to use official statistical data, coherent and consistent methodology and quantified measures. the proposed series of relative indicators of innovation can be used to measure federal districts’ modernization potential by applying methods of mathematical statistics. our approach is based on analysis of national data and official statistics characterizing modernization processes in central, volga and ural federal districts in the 18-year period (from 2000 to 2017). the proposed set of criteria allows us to take into consideration both the current situation and the  dynamics of innovation development. the selected indicators characterize the returns from innovation investment in socio-economic systems, the degree of regional differentiation within the district and trends of regional development regarding the efficiency of innovation processes. the proposed approach can be used to measure the efficiency of human capital use. the methodology was tested on the data on the central federal district, which was found to hold a considerable potential for modernization in socio-economic systems of its regions. statistical comparison of the actual and limit values revealed significant underused resources in this district. these resources can be accessed by stimulating the lagging regions. we found significant variability in innovation efficiency within the central federal district in comparison with reference values for other districts. the district has also demonstrated some comparatively positive dynamics regarding the efficiency of its r&d organizations in 2000–2017, which means that it is possible to improve the district’s overall performance and realize its human potential more fully. the proposed system of indicators and quantitative methods can be applied to conduct diagnostics of federal districts’ modernization potential by using the minimum amount of statistical information and to identify the regions that do not fit into the general development trends. http://doi.org/10.15826/recon.2019.5.4.018 r-economy, 2019, 5(4), 176–188 doi: 10.15826/recon.2019.5.4.018 187 www.r-economy.ru online issn 2412-0731 references 1. lenchuk, e. b. 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(in russ.) information about the authors denis yu. fraymovich – professor of economics, vladimir state university n.a. alexander and nikolay stoletovs (79 gorkogo st., vladimir, 600005, russia); e-mail: fdu78@rambler.ru marina a. gundorova – associate professor of economics, vladimir state university n.a. ale xander and nikolay stoletovs (79 gorkogo st., vladimir, 600005, russia); e-mail: mg82.82@mail.ru http://doi.org/10.15826/recon.2019.5.4.018 https://iurd.berkeley.edu/wp/2007-08.pdf https://www.econstor.eu/bitstream/10419/59420/1/592859940.pdf http://documents.worldbank.org/curated/en/517971468025502862/pdf/399860replacem1601offical0use0only1 http://documents.worldbank.org/curated/en/517971468025502862/pdf/399860replacem1601offical0use0only1 mailto:fdu78@rambler.ru mailto:mg82.82@mail.ru 188 www.r-economy.ru r-economy, 2019, 5(4), 176–188 doi: 10.15826/recon.2019.5.4.018 online issn 2412-0731 zorislav v. mischenko – associate professor of economics, vladimir state university n.a. alexan der and nikolay stoletovs (79 gorkogo st., vladimir, 600005, russia) svetlana i. totmyanina – associate professor of economics, vladimir state university n.a. ale xander and nikolay stoletovs (79 gorkogo st., vladimir, 600005, russia) aksanat zh. panzabekova – phd in economic sciences, associate professor, deputy director for science of the institute of economics of the committee of science of the ministry of education and science of the republic of kazakhstan (29 kurmangazy, almaty, 050000, kazakhstan); e-mail: aksanat@mail.ru article info: received august 20, 2019; accepted october 30, 2019 информация об авторах фраймович денис юрьевич – доктор экономических наук, доцент, профессор кафедры экономики и управления инвестициями и инновациями, владимирский государственный университет имени александра григорьевича и николая григорьевича столетовых (600000, россия, г. владимир, ул. горького, 87); e-mail: fdu78@rambler.ru. гундорова марина александровна – кандидат экономических наук, доцент кафедры экономики и управления инвестициями и инновациями, владимирский государственный университет имени александра григорьевича и николая григорьевича столетовых (600000, россия, г. владимир, ул. горького, 87); e-mail: mg82.82@mail.ru. мищенко зорислав владимирович – кандидат технических наук, доцент, владимирский государственный университет имени александра григорьевича и николая григорьевича столетовых (600000, россия, г. владимир, ул. горького, 87). тотьмянина светлана игоревна – кандидат экономических наук, доцент, владимирский государственный университет имени александра григорьевича и николая григорьевича столетовых (600000, россия, г. владимир, ул. горького, 87). панзабекова аксана жакитжановна – кандидат экономических наук, доцент, заместитель директора по международному сотрудничеству и внедрению, институт экономики комитета науки министерства образования и науки республики казахстан (050000, казахстан, алматы, ул. курмангазы, 29; e-mail: aksanat@mail.ru. информация о статье: дата поступления 20 августа 2019 г.; дата принятия к печати 30 октября 2019 г. this work is licensed under a creative commons attribution 4.0 international license эта работа лицензируется в соответствии с creative commons attribution 4.0 international license http://doi.org/10.15826/recon.2019.5.4.018 mailto:aksanat@mail.ru mailto:mg82.82@mail.ru mailto:aksanat@mail.ru 100 https://journals.urfu.ru/index.php/r-economy r-economy, 2020, 6(2), 100–110 doi: 10.15826/recon.2020.6.2.009 online issn 2412-0731 original paper © chen, q., 2020 doi 10.15826/recon.2020.6.2.009 chinese and russian transport corridors and the belt and road initiative: prospects of sino-russian cooperation q. chen institute of russia, harbin academy of social sciences of heilongjiang province, china; e-mail: 284748191@qq.com abstract relevance. the article discusses mutually beneficial cooperation between russia and china within the framework of the belt and road initiative and the role of russia as a key link between china and the eurasian economic union. the relevance of the study is determined by the need for a comprehensive ana lysis of the current state of transport cooperation between the countries with shared borders (russia and china) and on a more global level. it is especially important to identify the priority areas of intergovernmental cooperation in the transportation sphere. research objective. the study is aimed at evalua ting the prospects of sino-russian transport cooperation in connection with the belt and road initiative. data and methods. for comparative analysis, we use qualitative and quantitative indicators to consider the current state of sino-russian cooperation. our research draws from the official statistical data of russia and china and from the findings of the previous studies. results. the research has shown that there is a steady trend for integration of russian and chinese crossborder infrastructure. in particular, the economic corridor china-mongolia-russia relies on the expansion and modernization of the railway and highway infrastructure. conclusions. the connection of the belt and road initiative with the eurasian economic union will contribute to transport cooperation between china and russia. sino-russian transport cooperation will develop not only on the state level but also on regional and local levels. the belt and road initiative will enable russia and china unite their transport infrastructure into a single network. apart from the transport infrastructure, sino-russian cooperation also encompasses other aspects, such as training of specialists in logistics and transportation technologies. keywords crossborder infrastructure, belt and road initiative, container trains, economic corridor china-mongolia-russia, transport corridor, transport infrastructure, eurasian economic union китайский и российский транспортные коридоры и инициатива «один пояс – один путь»: перспективы китайско-российского сотрудничества ц. чень институт россии академии общественных наук провинции хэйлунцзян, харбин, китай; e-mail: 284748191@qq.com аннотация актуальность. в статье рассматривается взаимовыгодное сотрудничество между россией и китаем в рамках инициативы «один пояс – один путь» и роль россии как ключевого звена между китаем и евразийским экономическим союзом. актуальность исследования определяется необходимостью всестороннего анализа текущего состояния транспортного сотрудничества между странами с общими границами (россия и китай) и прочими задействованными странами. особенно важно определить приоритетные направления межгосударственного сотрудничества в транспортной сфере. цель исследования. цель исследования – оценить перспективы китайско-российского транспортного сотрудничества в связи с инициативой «один пояс – один путь» данные и методы. для сравнительного анализа мы используем качественные и количественные показатели, чтобы рассмотреть текущее состояние китайско-российского сотрудничества. наши исследования основаны на официальных статистических данных россии и китая, а также на результатах предыдущих исследований. результаты. исследование показало, что существует устойчивая тенденция к интеграции российской и китайской трансграничной инфраструктуры. в частности, ключевые слова трансграничная инфраструктура, инициатива «один пояс – один путь», контейнерные поезда, экономический коридор китай-монголия-россия, транспортный коридор, транспортная инфраструктура, евразийский экономический союз for citation chen, q. (2020) chinese and russian transport corridors and the belt and road initiative: prospects of sino-russian cooperation. r-economy, 6(2), 100–110. doi: 10.15826/ recon.2020.6.2.009 http://dx.doi.org/10.15826/recon.2020.6.2.009 http://dx.doi.org/10.15826/recon.2020.6.2.009 r-economy, 2020, 6(2), 100–110 doi: 10.15826/recon.2020.6.2.009 101 https://journals.urfu.ru/index.php/r-economy online issn 2412-0731 экономический коридор китай-монголия-россия опирается на расширение и модернизацию железнодорожной и автодорожной инфраструктуры. выводы. связь инициативы «один пояс – один путь» с евразийским экономическим союзом будет способствовать транспортному сотрудничеству между китаем и россией. российско-китайское транспортное сотрудничество будет развиваться не только на государственном, но и на региональном и местном уровнях. инициатива «один пояс – один путь» позволит россии и китаю объединить свою транспортную инфраструктуру в единую сеть. помимо транспортной инфраструктуры, китайско-российское сотрудничество охватывает и другие аспекты, такие как подготовка специалистов в области логистики и транспортных технологий. для цитирования chen, q. (2020) chinese and russian transport corridors and the belt and road initiative: prospects of sino-russian cooperation. r-economy, 6(2), 100–110. doi: 10.15826/ recon.2020.6.2.009 introduction the belt and road initiative (bri) is a new strategy of china implemented within the country’s more general ‘opening-up’ policy (kong, swallow, & thomson, 2020). the eurasian economic union (eaeu) is an international organization comprising post-soviet countries such as russia, kazakhstan, belarus, armenia and kyrgyzstan. russia is the driving force behind the eaeu, especially the organization’s strategic decision-making. the priority goal of the eaeu is to lift the tariff barriers for the member states and create a single economic space, thus increasing the trade turnover between the members (lukin, 2020). it is planned to connect the space created within the eaeu borders with the space covered by the bri, which is what makes the eaeu so attractive for china. the bri in fact is a mechanism of mutually beneficial international cooperation. in may 2015, china and russia signed the joint declaration on cooperation in coordinating the development of the  eurasian economic union and the silk road economic belt. in may 2018, china and the eaeu signed the agreement on trade and economic cooperation, emphasizing the connection of the bri with the eaeu as one of its priority areas. connection of the bri with the eaeu means that the countries involved in both of these projects will be working together to ensure the economic development, prosperity and stability in eurasia (mekhdiev, et al., 2019). this study is aimed at evaluating the prospects of sino-russian transport cooperation in its connection with the bri. this aim determined more specific objectives of our research. first, we are going to consider the results of sino-russian cooperation in the sphere of transportation. second, we are going to describe priority areas of their cooperation in connection to the plans to integrate the bri with that the eaeu. third, we are going to consider the results and prospects of sino-russian cooperation within the framework of the economic corridor china-mongolia-russia. finally, we are going to draw conclusions about the current state and prospects of sino-russian cooperation in the light of global integration processes. theoretical framework and methodology this study relies on the method of comparative analysis. to analyze the similarities and differences in russian and chinese approaches to transport cooperation, we use quantitative and qualitative indicators. there is vast research literature on this question. li (2019) discusses the creation of a railway transport corridor between north-eastern provinces of china and russia’s far east. sazonov & xiao (2018) point out that the integration of the chinese-russian crossborder freight transportation network is crucial for integration of the asia-pacific region and conclude that development of the transport system will have a multiplier effect for all the stakeholders. problems of transport corridors between russia and china are discussed by nan et al. (2017) and yunhao  (2015), who raise the question of uneven distribution of crossborder corridors for freight traffic. moreover, they consider the problems arising from the fact that russia is lagging behind china in terms of logistics infrastructure. yunhao (2015) discusses the role of the trans-siberian railway in creating the international transport corridor and points out that the main challenge in this process is the state of the infrastructure at the railway border crossings, especially the russian ones connected with the trans-siberian railway. careful planning of the routes could enhance the capacity of the trade corridors. diayu (2017), balakin (2012) and labyuk (2016) consider china’s participation in international arctic projects, including the northern sea route. these authors agree that china seeks to gain a more solid footing in the arctic even though http://dx.doi.org/10.15826/recon.2020.6.2.009 102 https://journals.urfu.ru/index.php/r-economy r-economy, 2020, 6(2), 100–110 doi: 10.15826/recon.2020.6.2.009 online issn 2412-0731 it is not an arctic state. no satisfactory solution, however, has so far been found to the problem of the conflict of interests between china and other countries. mei (2019), for example, contends that china should take a part in the administration of the northern sea route by ensuring environmental protection in the area, which is in the interests of russia and china and is in compliance with the law of the sea convention. xin (2018) focuses on waterborne freight transportation between russia and china and analyzes the real cases of conflicts arising between the two countries, which leads him to suggest that specific rules of freight transportation should be agreed upon. much attention is given to the problems associated with infrastructure construction and economic development of crossborder points in russia and china. shuan et al. (2017) discuss the economic and social aspects and problems of chinese and russian border regions. pin (2015) considers the current state and prospects of development of crossborder points in heilongjiang province and shows that intensification of integration processes will have a positive effect on the development of border regions both in china and in russia. yi (2017) suggested creating a cluster of crossborder points to take a full advantage of the strengths of different points and stimulate economic development in russian and chinese border regions. studies of sino-russian crossborder cooperation describe different alternatives of its further development. although the above-discussed studies provide significant evidence, they mostly highlight separate aspects without giving the full picture of sino-russian cooperation. this study applies a more comprehensive approach by taking into account various factors to evaluate the prospects of sino-russian transport cooperation in connection with the belt and road initiative. results and discussion sino-russian cooperation in the sphere of international transport corridors: current stage in recent years, transport cooperation between russian and china has been actively developing. the bri opens new opportunities for cooperation, especially in the light of the future connection of this initiative with that of the eaeu (wang, lim, zhang, zhao, & lee, 2020).  at this stage, the following tasks related to the construction of china-russia transport corridors need to be addressed: first, construct the transport infrastructure; second, develop the already existing cargo routes and open new ones; and, finally, expansion of the two-way transport corridors, turning them into three-way and multi-way transport corridors. let us consider each of these tasks in more detail. the first task is the construction of the transport infrastructure. china and russia share a long land border. the success of their plans largely depends on whether both countries will be able  to elaborate concerted approaches and effective solutions. by connecting the bri with the eaeu, russia and china will be able to ensure a stable progress in the construction of their crossborder infrastructure. geographically, china-russia transport corridors can be divided into the transport corridors across the amur river and the transport corridors connecting china with russia’s far east.the former include bridges and a cross border cableway. the idea to build a bridge across the amur between  blagoveshchensk and heihe started to be discussed as early as in 1995 but officially its construction was launched only in december 2016. thus, it can be said that the bri was a major driving force behind this project. this is the first cable-stayed bridge built in a cold, high-altitude region of china; it is also the first sino-russian crossborder highway bridge across the amur. russia and china connected their sides of the bridge in may 2019. it was expected that by 2020, the passenger traffic between the two cities would reach 1.4 mln people while the cargo traffic would be up to 3 mln tons1. in 2019, the customs in heihe registered the volume of cargo traffic at the level of 743 thousand tons, which is 28.3% higher than in 20182. the number of people going through the border checkpoints in heihe exceeded 1 million3. after the bridge is fully completed, it will ensure uninterrupted allyear transport connection between blagoveshchensk and heihe. construction of the cableway across the amur between heihe and blagoveshchensk started in july 2019. it was the first crossborder cable1 https://www.sohu.com/a/319391405_120051348 (date of access: 23.05.2020) 2 h t t p s : / / w w w. t h e p a p e r . c n / n e w s d e t a i l _ f o r ward_5577445 (date of access: 23.05.2020) 3 h t t p : / / w w w . h l j . x i n h u a n e t . c o m / k l j/2019-12/21/c_138648134.htm (date of access: 23.05.2020) http://dx.doi.org/10.15826/recon.2020.6.2.009 https://www.sohu.com/a/319391405_120051348 https://www.thepaper.cn/newsdetail_forward_5577445 https://www.thepaper.cn/newsdetail_forward_5577445 http://www.hlj.xinhuanet.com/klj/2019-12/21/c_138648134.htm http://www.hlj.xinhuanet.com/klj/2019-12/21/c_138648134.htm r-economy, 2020, 6(2), 100–110 doi: 10.15826/recon.2020.6.2.009 103 https://journals.urfu.ru/index.php/r-economy online issn 2412-0731 way between russia and china. it is planned that the total length of the cableway will be 972 meters while its estimated capacity will be 6 million people a year. the cableway will be put in commission in the second half of 2022, which will stimulate tourism between the two countries4. a trip from heihe to blagoveshchensk will take no more than 10 minutes. it is predicted that after the cableway is completed, there will be a rise in the number of tourists travelling between the twin cities but also between province heilongjiang and amur region. the operation of the cableway does not depend on climatic or seasonal conditions, which means that it can be effective in attracting larger numbers of tourists throughout the year. it should be noted that currently the connection between blagoveshchensk and heihe is provided in summer by motor ships sailing along the amur river and in winter, by a pontoon bridge for cargo and passenger bus transportation. construction of transport corridors across the amur is a major step in crossborder infrastructure development. the crossborder network between russia and china helps the partner countries create a new international transport corridor 4 https://rg.ru/2019/11/04/rossiiu-i-kitaj-sviazhet-unikalnaia-kanatnaia-doroga.html (date of access: 24.05.2020) and enables the exchange of specialists and goods (ryzhova & ioffe, 2009). in the far east, there are two major projects – international transport corridors ‘primorye-1’ and ‘primorye-2’, which are a part of the bri. they are also crucial for the cooperation between the north-eastern provinces of china and russia’s far east. on 4 july 2017, china and russia signed the memorandum of cooperation for the development of primorye 1 and primorye 2 international transport corridors (fig.  1,  2). corridors ‘primorye-1’ and ‘primorye-2’ go through the centre of the far eastern advanced development zone of russia – the free port of vladivostok, which means that there are 24/7  single window  checkpoints available with the single window system, that is, all do cuments are submitted through a  single  entry point. traders can submit documents for shipping goods from china to russia only once when they cross the chinese border and there is no need to submit a similar set of documents at the russian border as russian customs authorities get access to these documents automatically. it is also planned to introduce an electronic customs declaration system and apply the ‘green corridor’ principle for smoother border processing. figure 1. transport corridor ‘primorye -1’ source: administration of primorye region http://dx.doi.org/10.15826/recon.2020.6.2.009 https://rg.ru/2019/11/04/rossiiu-i-kitaj-sviazhet-unikalnaia-kanatnaia-doroga.html https://rg.ru/2019/11/04/rossiiu-i-kitaj-sviazhet-unikalnaia-kanatnaia-doroga.html 104 https://journals.urfu.ru/index.php/r-economy r-economy, 2020, 6(2), 100–110 doi: 10.15826/recon.2020.6.2.009 online issn 2412-0731 provinces heilongjiang and jilin, which play a key role in sino-russian cooperation, are located more than 1,000 km inland from the sea, which increases the logistics costs. freight routes ‘primorye-1’ and ‘primorye-2’ can connect the two provinces with the sea and thus cut the distance of land transportation by 200-500 km, reducing the costs by 10-40%. in the last two years, the volume of freight traffic along ‘primorye-1’ corridor has grown 1.8 times – from 2,138 to 3.934 in twenty-foot equivalent units (teus) – and along ‘primorye-2’, up to 2,145 teus5. second task: development of the already existing cargo routes and opening of new ones. the bri and eaeu integration sets the bar high for the crossborder logistics network. both china and russia are interested in improving the already existing logistics channels and creating new ones. there are over 40 freight shipping routes between heilongjiang province and russian border regions (bardal, 2014). harbin is the capital of heilongjiang province and is crucial to china’s interactions with russia. there is an international cargo route connecting harbin with europe (tjia, 5 https://www.primorsky.ru/news/164469/ (date of access: 25.05.2020) 2020) launched in june 2015, with trains running once a week. currently container trains arrive from china in małaszewicze (poland), hamburg and duisburg  (germany), zeebrugge (belgium), and minsk (belarus). these are among the main international logistics routes created by heilon gjiang province as a part of the bri. as of august 2019, on harbin-europe route, container trains had made 882 journeys and delivered 51,488 teus worth 2 billion us dollars6. the route was largely intended for exporting volvo automobiles, high-tech products, textiles and goods of prime necessity from china to europe and for importing from europe spare car parts, high-quality goods of prime necessity and timber. since the railway connection between harbin and europe prima rily stimulates the development of automotive industry, these trains are commonly referred to as ‘car trains’. apart from harbin-europe trains, in june 2016, the railway between harbin and russia was put in commission. in 2019, lines from har6 哈俄班列增开新线路（梅尔基-绥芬河-哈尔滨）顺 利开通，生活报，2019-08-13 (the new railway line 'mylki -suifenhe harbin' was opened for container trains running between russia and harbin, life daily, 2019-08-13) figure 2. transport corridor ‘primorye -2’ source: administration of khabarovsk region http://dx.doi.org/10.15826/recon.2020.6.2.009 https://www.primorsky.ru/news/164469/ r-economy, 2020, 6(2), 100–110 doi: 10.15826/recon.2020.6.2.009 105 https://journals.urfu.ru/index.php/r-economy online issn 2412-0731 bin to ekaterinburg and biklyan were opened. in the same year, a new container train line ‘mylki-suifenhe-harbin’ was launched. this line specializes on the import of lumber and woodpulp products to china. for more detailed information on harbin-russia trains, see table 1 below. table 1 harbin-russia container trains dispatch station terminal station date of the first departure goods shipped via first train, in mln us dollars* intermediate stations transported goods harbin ekate rinburg 12 march 2016 10 manzhouli, novosibirsk, perm spare car parts harbin biklyan 11 may 2019 7.5 manzhouli, zabaikalsk, irkutsk machinery and equipment mylki harbin 13 august 2019 0.1 khabarovsk, suifenhe lumber and woodpulp source: compiled by the author based on materials http:// hlj.people.com.cn * http://hlj.people.com.cn/n2/2016/0312/c22002727919303.html (date of access: 25.05.2020); https://www. sohu.com/a/313335250_99960365 (date of access: 25.05.2020); http://hlj.people.com.cn/n2/2019/0818/c220027-33261006. html (date of access: 25.05.2020) harbin is an important hub for import of such products as lumber and woodpulp. from harbin, these products are redistributed to other chinese cities, which makes it particularly important for sino-russian cooperation. after the launch of the railway line between china and russia, container trains made 352 journeys delivering 25,150 teus worth 400 billion us dollars7. the route between harbin and russia is one of the most important railway routes connecting eastern china with europe. railway transport provides a regular, nonstop connection between china, russia and europe: in comparison with sea transport, railway enjoys a number of advantages, for example, it is independent from weather conditions or seasons, it is secure and there is a low risk of cargo damage. rail freight transportation is also less costly than air freight. moreover, the train schedule is also 7 哈俄班列增开新线路（梅尔基-绥芬河-哈尔滨）顺 利开通，生活报，2019-08-13 (the new railway line 'mylki -suifenhe harbin' was opened for container trains running between russia and harbin, life daily, 2019-08-13) much more reliable, minimizing the risk of delays in delivery. normally, the transportation time is measured in hours. in addition, container trains can use a modern information platform to provide full monitoring and management of the shipment data, thus enabling the customers to track cargo delivery. harbin-europe and harbin-russia container trains use the eastern corridors of the railway routes between china and europe, which were launched in the period when sino-russian cooperation started to develop. harbin is located in the centre of the international corridor; it is an international logistics centre, which performs a variety of functions such as transportation, storage, customs processing and distribution. the routes harbin-europe and harbin-russia, together with other routes between europe and china starting in guangzhou, qingdao, nanjing, chongqing, xiamen, and zhengzhou, form logistics corridors, which play an important role in the sino-russian trade and economic cooperation. third task: expansion of the two-way transport corridors, turning them into three-way and multi-way transport corridors. the third task is to involve other countries in sino-russian cooperation. the international transport corridor ‘primorye-1’ is a part of the bri. it is a land-sea transport corridor connecting north-eastern asia and europe. the china-mongolia-russia economic corridor has two railway passages in china: one is the northern passage, going from beijing-hebei through hohhot to mongolia and russia; the other is the eastern passage, going from tianjin through dalian, changchun, harbin, manzhouli to russia (dong et al., 2018). construction of the china-mongolia-russia economic corridor requires the implementation of more than 10 plans for integrating the infrastructure of the three countries for unobstructed transborder passage, which includes modernization of railway corridors (see fig. 3). a significant event for the china-mongolia-russia economic corridor project happened in july 2019, when the first meeting of the joint committee on the intergovernmental agreement on the asian highway network was held and the international highway route going through the three countries was declared officially open. the agreement outlines measures aimed at ensuring smooth development of the corridor, such as construction and modernization of the highway infrastructure in russia and mongolia. http://dx.doi.org/10.15826/recon.2020.6.2.009 http://hlj.people.com.cn http://hlj.people.com.cn http://hlj.people.com.cn/n2/2016/0312/c220027-27919303.html http://hlj.people.com.cn/n2/2016/0312/c220027-27919303.html https://www.sohu.com/a/313335250_99960365 https://www.sohu.com/a/313335250_99960365 http://hlj.people.com.cn/n2/2019/0818/c220027-33261006.html http://hlj.people.com.cn/n2/2019/0818/c220027-33261006.html 106 https://journals.urfu.ru/index.php/r-economy r-economy, 2020, 6(2), 100–110 doi: 10.15826/recon.2020.6.2.009 online issn 2412-0731 priority areas of sino-russian cooperation integration of the eaeu with the bri is linked to russia and china’s efforts to expand their transport cooperation in the three priority areas: 1. development of sino-russian transport cooperation not only on the state level but also on regional and local levels. russian and chinese governments attach great significance to integrating the bri with the northern sea route (nsr) and are going to put their joint effort into using the nsr for building the ‘ice silk road’. in 2013, a state chinese company received permission from the nsr administration for three passages, which effectively means the start of commercial transportation via the nsr (including container transportation). so far, the company has been using two ships in its operations (бардаль, 2014). this fact demonstrates that in partnership with russia, china has real opportunities to become an arctic economic power. as a part of the bri, the first large-scale projet ‘yamal lng’ was launched. this project changed the traditional model of raw material imports to china and created a new model of international cooperation in the energy sphere. on 19 july 2018, two tankers with liquefied natural gas for the first time travelled via the nsr and arrived in china. the voyage took 19 days, which is 16 days less in comparison with the traditional route via the suez canal and the malacca straits (zeng, lu, lin, yuen, & li, 2020). in 2018, the overall cargo volume via the nsr was 18 million tons, which signifies an 80% increase in comparison with 2017 (иньань, 2019). the russian government predicts that the cargo volume via the nsr will rise to 51 million tons in 2021 and to 80 million tons in 2024.(lazarev & fisenko, 2020). thus, the sino-russian project ‘yamal -lng’ laid the foundation for joint construction of the ‘ice silk road’. as a result of ‘yamal-lng’, there was an increase in the imports of natural gas to china (see table 2). as table 2 illustrates, since 2018, the amount and value of natural gas imports to china have been growing steadily. in 2018 china became the largest importer of natural gas in the world. increasing gas consumption changes the whole structure of energy consumption in china, which means that the country is gradually switching to cleaner, low-carbon energy materials. potentially, this could have a serious impact on the global gas figure 3. the china-mongolia-russia economic corridor source: on-line magazine ‘zolotaya orda’ http://zolord.ru http://dx.doi.org/10.15826/recon.2020.6.2.009 http://zolord.ru r-economy, 2020, 6(2), 100–110 doi: 10.15826/recon.2020.6.2.009 107 https://journals.urfu.ru/index.php/r-economy online issn 2412-0731 trade. russia is the main supplier of natural gas, which makes energy cooperation crucial for the relationship between the two countries. table 2 china’s natural gas imports in 2016–2019 year amount of natural gas imports (mln tons) compared with the previous year (%) value of natural gas imports (mln us dollars compared with the previous year (%) 2016 54.03 +22.0 16.489 -10.8 2017 68.57 +26.9 23.275 +41.2 2018 90.39 +31.9 34.480 +65.3 2019 96.56 +6.9 41.720 +8.5 source: https://d.qianzhan.com/xnews/detail/541/200324-0fb684fd.html (date of access: 26.05.2020) apart from the state-level strategic cooperation, both countries are committed to developing their cooperation on the regional level. in this case, the north-eastern part of china plays the key role in sino-russian cooperation: it has a large number of crossborder passage points , it is located in close geographical proximity to russia and has a long history of cooperation with russia’s far east in such spheres as agriculture, construction, and transport. the north-east of china participates in the ‘ice silk route’ project, which includes plans for establishing sea routes to vladivostok, zarubino and other ports. creation of the china-mongolia-russia economic corridor will, in its turn, accelerate the revival of china’s north-eastern provinces and development of russia’s far east. it is expected that the zone of marginal economy and the zone of resource supply will thus be transformed into experimental regions for resource development and creation of economically developed territories. 2. projects of transport cooperation and integration of russian and chinese infrastructure. the transport cooperation projects which have been completed or are being currently implemented include construction of an oil pipeline, eastern gas pipeline, railway bridge across the amur (heihe – blagoveshchensk) and a highway bridge across the amur (tongjiang – nizhneleninskoye). these projects undoubtedly contribute to the development of transport infrastructure in border regions and may serve as a platform for further economic cooperation between the two countries. chinese investors, such as state banks, enterprises and investment funds, show a keen interest in russian projects associated with transport infrastructure. it is forecast that in the nearest future table 3 chinese investment in transport infrastructural projects in russia’s far east investor sector planned and ongoing projects shangdong hi-speed group motorways in september 2018, a concession agreement was signed for the construction and operation of the road ‘khabarovsk bypass 13 km-42 km’, involving shangdong hispeed group as a contractor. the amount of potential investment in russia in 2019-2020: 10-20 bln rbs china railway dongfang group railway transport in april 2018, far east investment and export agency and china railway dongfang group signed an agreement of intent on financing the feasibility study of the construction of a high-speed railroad between suifenhe and vladivostok. the cost of the project was estimated as 12 bln us dollars. in august 2018, the chinese side confirmed the feasibility of the project for the construction of the 180 km-long high-speed railroad between suifenhe and vladivostok. the amount of potential investment in russia in 2019-2020: 3–5 bln rbs china railway construction corporation limited (crcc) railway transport the memorandum of intent for building the bridge across the lena was signed in september 2018 the project is worth 80 bln rbs. the amount of potential investment in russia in 2019-2020: 30–40 bln rbs china communications construction company (cccc) motorways, ports the memorandum of cooperation for the development of ‘primorye 1’ and ‘primorye 2’ was signed in july 2017. the amount of potential investment in russia in 2019-2020: 20–40 bln rbs china investment corporation (cic) railway transport, motorways construction of the railway bridge across the amur on the border with china (400 mln us dollars) the amount of potential investment in russia in 2019–2020: 10–20 bln rbs china development bank (cdb) railway transport, motorways the framework agreement on 8 bln us dollar investment in the far east and siberia was signed in 2015 with vnesheconombank. the amount of potential investment in russia in 2019–2020: 200 bln rbs china railway group (crec) railway transport transport corridors ‘primorye-1’ and ‘primorye-2’ the amount of potential investment in russia in 2019–2020: 40–60 bln rbs source: compiled by the author based on the analytical review of the independent russian investment company infraone. http://dx.doi.org/10.15826/recon.2020.6.2.009 https://d.qianzhan.com/xnews/detail/541/200324-0fb684fd.html https://d.qianzhan.com/xnews/detail/541/200324-0fb684fd.html 108 https://journals.urfu.ru/index.php/r-economy r-economy, 2020, 6(2), 100–110 doi: 10.15826/recon.2020.6.2.009 online issn 2412-0731 chinese investment in such projects will amount to 315–385 billion roubles8. the projects indicated above are by no means the only ones. table 3 shows the data on investors ready to invest in russian infrastructure and the joint projects to be realized in 2019-2020. the table shows only the forecast data as companies do not specify the real amount of investment and the actual time of project completion. table 3 includes the data on transport infrastructural projects involving chinese investors in russia’s far east. it should be noted, however, that these projects are in different phases. for example, the construction of the railway bridge across the amur is nearing completion as the bridge is expected to be put in commission in 2020. china investment corporation (cic) invested 400 billion us dollars in this project. the majority of the above-described projects, however, still remain ink on paper. for instance, china railway construction corporation limited (crcc), which was interested in constructing a bridge across the lena near yakutsk, had to withdraw from the project due to its high costs and insufficient feasibility. the russian side, however, has not given up on this project. the draft documents on the transport and financial models have already been devised; the technical and operational evaluation as well as the project’s organizational and legal framework are being prepared. 3. specialist training and cooperation in the transport sphere. an important aspect of the project to connect the bri and eaeu is specialist training, in which transport universities play a key role. both countries need to modernize their higher education models. universities have all the necessary resources to create international intellectual platforms for r&d and to develop high-quality joint education courses and programs. russian and chinese transport universities are ready to offer their students dual diploma programs of the ‘2+3’ model, which means that students will be studying for two years in their home country and then 2–3 years abroad. for example, emperor alexander i st. petersburg state transport university and beijing transportation university have been partners since 2014 and since 2016, have been offering a dual diploma program since 2016. talented chinese graduates can get jobs at the largest transport enterprises in russia and russian graduates, in china. in 2015, the russian-chinese transport institute was established. 8 far east: infrastructure investment. analytical review. moscow, 2019, pp. 79. regular sino-russian forums, conferences and seminars in the sphere of transport and logistics create opportunities for specialists from both countries to share their experience. the annual forum of rectors of russian and chinese transport universities has been held since 2014. in october 2019, beijing hosted the sixth forum of the association of rectors of transport universities  of russia and china, which involved rectors from over 60 higher education institutions in both countries. this forum can serve as an example of successful cooperation between the two countries on the state level. joint education and traineeship programs can help transport engineers from both countries upgrade their professional qualifications. there is every reason to believe that the hands-on approach to specialist training will enable future transport professionals to connect theoretical knowledge with practical contexts and promote transport cooperation between the two countries in the future. conclusion china’s fast economic growth stimulated the development of transport infrastructure, which is why it now has the most  advanced  railway network in the world. china is the first in the world in terms of metro construction, high-speed railway and bridge building. apart from the use of cutting-edge technologies and the remarkable speed of construction, china is also known for its financial power. china’s economic and technolo gical progress opens vast opportunities for trustbased and mutually beneficial cooperation with russia in the sphere of transportation. this article was aimed at evaluating the prospects of sino-russian cooperation within the bri framework. the main results of sino-russian partnership in the sphere of transportation are the construction of the bridge and cableway across the amur and the international projects ‘primo rye-1’ and ‘primorye-2’. these projects enable both countries to significantly expand the potential of their transport infrastructure. since the connection between the two countries is going to become faster and more comfortable, the cargo traffic and the flow of tourists are expected to grow considerably in the nearest future. as for the priority areas in the transport sphere, especially in the context of the integration of the bri and the eaeu, it should be noted that chinese investors are showing keen interest in russian regions. this can be illustrated by the http://dx.doi.org/10.15826/recon.2020.6.2.009 r-economy, 2020, 6(2), 100–110 doi: 10.15826/recon.2020.6.2.009 109 https://journals.urfu.ru/index.php/r-economy online issn 2412-0731 case of ‘yamal lng’ project, which made china the leading world country in terms of natural gas imports. as of today, the majority of investment projects, however, are still a work in progress and require considerable revision in order to become economically feasible. the china-mongolia-russia economic corridor is of particular interest as this project implies substantial modernization of the existing transport infrastructure of mongolia ad russia and building new international transport corridors. as a result, the speed of freight transportation and passenger traffic flow will grow significantly, which will contribute to the economic deve lopment of the related territories. at the current stage of the project, there has been established a highway connection between mongolia, china and russia. our analysis has shown that sino-russian transport cooperation is now gaining momentum. joint projects provide a solid 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(2020). the competitiveness of arctic shipping over suez canal and china-europe railway. transport policy, 86, 34–43. doi: 10.1016/j.tranpol.2019.11.005 information about the author qiujie chen – researcher, institute of russia, harbin academy of social sciences of heilongjiang province (150018, china, harbin, yui, 501); e-mail: 284748191@qq.com article info: received november 28, 2019; accepted april 15, 2020 информация об авторе чэнь цюцзе – научный сотрудник института россии академии общественных наук провинции хэйлунцзян (150018, кнр, г. харбин, ул. юи, 501); e-mail: 284748191@qq.com информация о статье: дата поступления 28 ноября 2019 г.; дата принятия к печати 15 апреля 2020 г. http://dx.doi.org/10.15826/recon.2020.6.2.009 http://dx.doi.org/10.1016/j.tra.2020.02.009 http://dx.doi.org/10.1016/j.tra.2020.02.009 http://dx.doi.org/10.1016/j.tranpol.2019.11.005 http://dx.doi.org/10.1016/j.tranpol.2019.11.005 mailto:284748191@qq.com r-economy, 2020, 6(4), 251–260 doi: 10.15826/recon.2020.6.4.022 251 https://journals.urfu.ru/index.php/r-economy online issn 2412-0731 original paper © pasynkov, a.f., 2020 doi 10.15826/recon.2020.6.4.022 jel p43, h41, h71, h72 compilation of regional financial balances for the ‘general governance’ sector in the ural federal district a.f. pasynkov institute of economics of the ural branch of the russian academy of sciences, ekaterinburg, russia; monografia@mail.ru abstract relevance. in recent years, the significance of financial flows in the public sector in territorial development in russia has been growing. to be able to analyze all public sector revenues and expenditures at the regional level, it is necessary to develop financial balances that take into account all flows of financial resources. research objective. the purpose of this study is to create financial balances of the ‘general governance’ sector by using the example of six regions in the ural federal district. data and methods. the study is based on the theoretical framework of the system of national accounts. the author proposes a methodological approach to the consolidation of official statistical reports from open sources in accordance with the classification of government revenues and expenditures in national accounting. results. the proposed methodology for calculating the income and expenditures of all budgets in the region, including the volume of direct federal expenditures, is based on comparing the data on the sources of added value formation. a database on income and expenditures of the regions of the ural federal district for the period 2014–2018 was made and a matrix of financial balances of the ‘general governance’ sector by regions for 2017 was built. to this end, the structure and amount of public institutions financing costs were specified and donor and recipient regions of the ural federal district were identified. conclusions. financial resources of the public sector affect the economy of the regions of the ural federal district in several ways. the regions specializing on oil and gas production are net donors to the sector, the rest of the regions cannot provide for themselves and are more dependent on federal funds. the sector ‘general governance’ generates more than 10% of grp of chelyabinsk and sverdlovsk regions and more than 20% of kurgan region. the results can be used for planning and forecasting of socio-economic development of certain areas. keywords gross value added, institutional sectors, system of national accounts, public administration, russian regions, ural federal district acknowledgements the study is supported by the russian foundation for basic research, project 18-010-01001 ‘sector “general government”: the formation of financial balances of regions and municipalities on the basis of the principles of the system of national accounts’. for citation pasynkov, a.f. (2020) compilation of regional financial balances for the ‘general governance’ sector in the ural federal district. r-economy, 6(4), 251–260. doi: 10.15826/recon.2020.6.4.022 формирование финансовых балансов сектора «государственное управление» субъектов рф (на примере регионов уральского федерального округа) а.ф. пасынков институт экономики уральского отделения российской академии наук, екатеринбург, россия; monografia@mail.ru аннотация актуальность. в последние годы в российской федерации все возрастающее значение на развитие территорий оказывают влияние финансовые потоки органов государственного управления. для полного отражения всех доходов и расходов государственного сектора на региональном уровне, необходимо разработка финансовых балансов, которые позволяют учитывать все потоки финансовых ресурсов. цель исследования. целью настоящего исследования выступает формирование финансовых балансов сектора «государственное управление» на примере шести субъектов федерации, входящих в уральский федеральный округ. данные и методы. исследование базируется на теоретических положениях формирования системы национальных счетов и авторском методологическом подходе к консолидации официальной статистической отчетности из открытых источников, которая соответствует принятой в национальном счетоводстве классифиключевые слова валовая добавленная стоимость, институциональные сектора, система национальных счетов, государственное управление, субъект рф, уральский федеральный округ http://doi.org/10.15826/recon.2020.6.4.022 http://doi.org/10.15826/recon.2020.6.4.022 252 https://journals.urfu.ru/index.php/r-economy r-economy, 2020, 6(4), 251–260 doi: 10.15826/recon.2020.6.4.022 online issn 2412-0731 кацией доходов и расходов органов государственного управления. результаты. разработана методика расчета доходов и расходов всех бюджетов на территории региона, в том числе объема прямых федеральных расходов на территориях субъекта федерации, через сопоставление данных по источникам формирования добавленной стоимости. на этой основе была сформирована база данных по доходам и расходам регионов уральского федерального округа за период 20142018 гг. и построена матрица финансовых балансов сектора «государственное управление» по субъектам рф за 2017 г. выделена структура и объем расходов финансирования государственных заведений, определены территории доноры и реципиенты уральского федерального округа. выводы. финансовые ресурсы государственного сектора оказывают влияние на экономику регионов урфо разнонаправлено. нефтегазодобывающие территории являются чистыми донорами сектора, остальные регионы не могут обеспечить себя финансовыми ресурсами, с учетом федеральных расходов. сектор «государственное управление» формирует более 10% регионального продукта челябинской и свердловской областей и более 20% курганской области. полученные результаты могут быть использованы при планировании и прогнозировании социально-экономического развития отдельных территорий. благодарности работа поддержана российским фондом фундаментальных исследований, проект 18-01001001 «сектор “государственное управление»: формирование финансовых балансов регионов и муниципальных образований на основе принципов системы национальных счетов». introduction socio-economic development of territories at various levels depends on many different factors that influence the level and dynamics of reproduction processes. the driving force of any economy is the sector of production of goods and services, which creates the added value of the territory. financial resources generated by the manufacturing sector are a source of income for people and regional governments, forming the tax base of the territories. on the other hand, the expenditures of households and budgets of all levels provide the demand for goods in the production sector, ensuring the circulation of financial flows in regions. recently, a general trend for russia and the world in general has been the increasing importance of financial flows in the public sector for the development of territories. the importance of the general government sector in the circulation of financial flows lies in the redistribution of added value between economic units and territories, which allows to solve certain problems, including the equalization of conditions for socio-economic development. therefore, for various territories, financial flows of the public sector are of different importance, both in the structure of value added and in the ratio of revenues and expenditures of the general government sector. however, studies of the financial balances of territories are limited to the generalization and analysis of the data on collected tax payments and consolidated budgets of the regions. therefore, it is impossible to draw conclusions about the degree of dependence of regional economy on budget flows. at the same time, financial balances of public administration imply accounting for all resource flows, regardless of the level and direction of their movement. it is this approach that is incorporated in the concept of building an international system for assessing economic activity – the system of national accounts. the system of national accounts (sna) is an internationally agreed standard set of guidelines for calculating indicators of economic activity in accordance with clear rules for maintaining accounts at the macro level, based on the principles of economic theory. without going into details, it can be noted that the main resulting account indicator, often used by researchers, economists and government officials, is gross domestic product (gdp). at the same time, the sna consists of a large number of accounts and classifications that make it possible to assess the proportions and patterns of economic development of a particular territory. for the regional and municipal level, the author proposes to develop an analogue of such a system – territorial accounts. in this regard, the formation of financial balances of the ‘general governance’ sector in russian regions makes it possible to assess the movement of funds of budgets of all levels and determine the outflow / inflow of resources in certain territories. therefore, the main purpose of this study is the creation of financial balances of the ‘general governance’ sector by using the example of six regions of the ural federal district. the goals of the study are as follows: to determine the total flow of tax payments by regions to the budgetary system of russia; to allocate regional budgetary expenditures in the sna classification; для цитирования pasynkov, a.f. (2020) compilation of regional financial balances for the ‘general governance’ sector in the ural federal district. r-economy, 6(4), 251–260. doi: 10.15826/recon.2020.6.4.022 http://doi.org/10.15826/recon.2020.6.4.022 r-economy, 2020, 6(4), 251–260 doi: 10.15826/recon.2020.6.4.022 253 https://journals.urfu.ru/index.php/r-economy online issn 2412-0731 to calculate the federal part of expenditures in grp of the regions of the ural federal district; and determine donor and recipient regions in accordance with the ‘general governance’ sector. theoretical framework from the theoretical point of view, the problem of assessing the income and expenditures of territories at the level of both regions and individual municipalities has been considered in russian science for a long time. a significant part of the research is devoted to assessing the balance of budgets, the ratio of territories’ own revenues and transfers, the level of subsidization of territories, etc. in this regard, a lot of works have been devoted to the balances of income and expenditures of regional (municipal) budgets. for example, khapsaeva (2014) examines the theoretical aspects of balancing regional budgets. zhuravleva (2015) focuses on the case of ukraine and defines the role of tax revenues in the regional budget system, highlighting approaches to the formation of a balanced municipal budget (bogolib, 2015). the influence of federal transfers and financial macroeconomic policy on the regional financial system is another widely discussed topic. for example, istomina (2016), outlines the special role of federal authorities in planning the income and expenditures of the regional budget. pinskaya & ziganshina (2015) discuss the need to build a new effective model of inter-budgetary interaction. ilyin & povarova (2017) investigated the effect of the tax administration issues of big business in relation to revenues of regional governments. another part of the research is devoted to the analysis of regional budget revenues or expenditures (zumakulova & tereshev, 2015; povarova, 2016; tokaev & basnukaev, 2016; isaev, 2016; khokhlova & ivanko, 2017; ilyukhin, ponomaryova & ilyukhina, 2017; pechenskaya, 2018) or municipalities (fayberg, 2015; sumskaya, 2019). in our opinion, the approach based only on budget analysis is rather limited since the tax and budgetary system in russia does not reflect the real potential of the regions in generating tax payments and the federal budget expenditures used in the territory. in recent years, the financial system of the territory has been understood more broadly. for example, marshalova (2005) considers the assessment of the financial flows of municipalities as the main level of value added formation. klimanov, eremina & mihaylova (2018) use the features of the distribution of ‘direct’ federal budget expenditures to develop a balance of counter financial flows by region. however, these studies focus more on the theoretical aspect of the problem and do not offer methodological approaches to the assessment of financial balances. theoretically, the problem of financial balances of territories is considered by sidorova & tatarkin (2012). this idea is further transformed into a design matrix of financial flows (tatarkin, sidorova & trynov, 2017). in spite of the high importance of these studies, the use of the matrix of financial flows is quite limited, as they are used only aggregated data from official sources. in the international literature, the assessment of the influence of the public sector at the regio nal level is studied by statistical departments1 by identifying the added value formed at the level of regions and municipalities. the impact of state financial flows on the economic development of territories is considered, to a large extent, from the point of view of the effect of urbanization processes and an increase in the productivity of individual territories (simmie&martin, 2010; wang&turkina, 2020; lobo, bettencourt & strumsky, 2013; lobo&smole, 2002; van raan, van der meulen & goedhart, 2016; resende&cravo, 2014). thus, today there is no generally accepted methodological approach to determining financial balances of the ‘general governance’ sector at the territorial level. methodology and data our approach to the development and calculation of financial balances of the ‘general governance’ sector is based on the principles of the international system of national accounts (united nations, 2009). the essence of the proposed approach is the development of a system of accounts and balance ratios for open territorial units, conceptually and methodologically fully compatible with the un sna-2008 standard (for more on the theoretical and methodological aspects of the problem 1 u.s. bureau of economic analysis (2006). gross domestic product by state estimation methodology. retrieved from: https://webcache.googleusercontent.com/search?q=cache:quogphqgmrkj:https://www.bea.gov/sites/default/ files/methodologies/0417_gdp_by_state_methodology.pdf+&cd=1&hl=ru&ct=clnk&gl=ru&client=opera ; eurostat (2008). european regional and urban statistics. reference guide. retrieved from: https://ec.europa.eu/eurostat/ramon/ statmanuals/files/ks-ra-07-005-en.pdf http://doi.org/10.15826/recon.2020.6.4.022 https://webcache.googleusercontent.com/search?q=cache:quogphqgmrkj:https://www.bea.gov/sites/default https://webcache.googleusercontent.com/search?q=cache:quogphqgmrkj:https://www.bea.gov/sites/default https://webcache.googleusercontent.com/search?q=cache:quogphqgmrkj:https://www.bea.gov/sites/default https://webcache.googleusercontent.com/search?q=cache:quogphqgmrkj:https://www.bea.gov/sites/default https://ec.europa.eu/eurostat/ramon/statmanuals/files/ks-ra-07-005-en.pdf https://ec.europa.eu/eurostat/ramon/statmanuals/files/ks-ra-07-005-en.pdf 254 https://journals.urfu.ru/index.php/r-economy r-economy, 2020, 6(4), 251–260 doi: 10.15826/recon.2020.6.4.022 online issn 2412-0731 see the author’s previous articles: zakharchuk & pasynkov, 2017; zakharchuk, pasynkov, & trifo nova, 2020). since this study aims to describe the financial flows of the public sector, first of all, it is necessary to bring the available statistical data into a form comparable to the sna’s methodology. to do this, the author has consolidated the data arrays in accordance with the accepted classification of income and expenditure of government bodies. from the sna’s perspective, the revenues of the ‘general governance’ sector include the following payments to the budget system: – taxes on product and imports: value added tax (on goods sold and imported into the russian federation), excise taxes and tax on the extraction of minerals (rent); – other taxes on production: property tax, transport and land tax of enterprises as well as regular payments for the use of natural resources (except for the mineral extraction tax); – corporate income tax: in fact, according to the sna classification, it is included in current taxes on income. however, to separate tax payments of corporations from households, we need a separate classification. this section includes the corporate income tax calculated in the given region of the russian federation as well as the corporate income tax of consolidated groups of taxpayers; – current taxes on income: households are included as property taxes, transport and land tax for individuals and taxes on total income of small businesses; – personal income tax: it is considered separately as a part of income taxes, due to its analytical value in determining the impact on the overall tax burden of the territory; – other sources of income: government duties and other payments unrelated to tax regulation. at the next stage, it is necessary to determine the expenditures of budgets of all levels in the given territories in order to compile a general balance of the movement of funds in the sector. first of all, it is necessary to distinguish between the concepts of ‘total budget expenditures in the territory’ and ‘added value of the public sector’, since a clear understanding of these terms is necessary for correct calculation of the expenditures of the ‘general governance’ sector. value added of the public sector, according to the sna’s theoretical provisions, consists of salaries of employees (together with social charges) and other taxes on production and gross mixed income of the sector. in the corporate sector, gross mixed income plays a significant role in the formation of added value, since it includes both depreciation charges on fixed assets and the profit received by the sector. in russia, in the corporate sector, mixed incomes make up about a half, in some sectors (e.g. mining), they can be 70–80% of the value added (zakharchuk, 2019). since the ‘general governance’ sector has peculiarities related to the redistributive nature of its flows, the sector does not actually have mixed incomes. this is due to the fact that no profit can be generated in public administration, since only non-profit organizations are included in it and depreciation payments are not refunded. as a result, the added value of the ‘general governance’ sector includes practically only the costs of remuneration of employees with contributions to social funds. consequently, when determining the costs of public administration on wages in the territory, it can rely on the data on the added value of the corresponding sections of the all-russian classifier of economic activities (okved), defining them as ‘wages’. in the categories of okved-1 (valid until 2016), such sections include l, m, and n. according to okved-2, sections o (public administration and military security; compulsory social security), p (education), q (health care and provision of social services), r (activities in the field of culture, sports, leisure and entertainment) belong to the ‘general governance’ sector. another indicator that we need for calculations is the total expenditures of budgets of all levels in the territory, which reflects the costs of the ‘general governance’ sector for all items of expenditure. to draw an analogy with the corporate sector, expenditures can be considered as ‘intermediate consumption’ and included in gross mixed income, for example, investments in fixed assets. therefore, there is a need to develop ways of calculating the costs of the ‘general governance’ sector in the territory where information is provided by various information systems. the basis for calculating expenses is the information on the official website of the treasury of russia on the cash flow of the consolidated budgets of the regions (form 0503323). the data are grouped according to the general government operations classification code (kosgu), ranging from 211 ‘wages’ to 340 ‘increases in inventory value’. in accordance with the requirements of the sna, http://doi.org/10.15826/recon.2020.6.4.022 r-economy, 2020, 6(4), 251–260 doi: 10.15826/recon.2020.6.4.022 255 https://journals.urfu.ru/index.php/r-economy online issn 2412-0731 we reformatted and consolidated data from tables into a form comparable to national accounting. the kosgu codes related to the added value of the ‘general governance’ sector include the following: 1) the added value of the ‘general governance’ sector, which includes direct budget expenditures for payments to employees, other payments, and charges on payments for wages. as a rule, these expenses belong to general administrative expenses for management and are displayed in section o according to okved-2. the second part of the expenses included in this group is ‘subsidies to institutions’ (241,242 kosgu), which are essentially related to transfers. but they are in fact direct financing institutions performing public tasks of regions and municipalities in a given area. of course, in the composition of this subsidy, not all costs are related to wages. we analyzed the ‘report on the implementation of the institution’s plan of its economic activities on subsidies for the fulfillment of the state (municipal) task’ for 2017, which contains all the reported data for the russian federation for this type of activity. according to the report, out of 742.43 billion rubles of funds allocated for the execution of state assignments, almost 507 billion or 68% were spent on paying wages, 206.31 billion rubles (27.7%) were spent on the purchase of goods and services, and the rest of the expenses (4.3%) are insignificant. thus, the overwhelming part of the costs is reflected in the formation of the added value of territories by sections p, q, r in the okved 2 system. 2) transfers to the households sector. social security (262.263 kosgu) includes expenses on social support of the population outside the framework of the federal pension, social, and health insurance systems. the list of such expenses is quite wide, and it concerns both direct cash payments and compensations for various types of benefits (for example, travel expenses). in the sna, such payments are classified as ‘social security’ and correspond to the income sector ‘households’. the value added of the public sector is not included; it is allocated in a separate category. 3) gross savings in the sector. this article includes information on the expenses of 310.330 kosgu ‘capital investments’. these are funds aimed for construction of buildings and structures and for increasing the value of intangible assets. 4) intermediate consumption of the sector ‘general governance’. according to kosgu, it is the most diverse item for spending regional and municipal funds, it includes items from 221 (communication services) to 226 (other works, services) and 340 (an increase in the cost of inventories). 5) other current transfers. the allocation of these payments into a separate class is dictated by the sna concept, since in this case the expenditures of the general government sector do not have a subject link. this applies to both debt service (code 231 of kosgu), which is a transfer to non-financial corporations. the same applies to interbudgetary transfers (code 251 of kosgu), which refer to simple withdrawal of resources from the budget system. as a result, in accordance with the proposed algorithm, we created a database on income and expenditures of the regions of the ural federal district for 2014–2018. the source of the data on revenues was the open data of the federal tax service. the data on expenditures were taken from the official website of the treasury of russia and the value added tables. results at the first stage, income matrices of the ‘general governance’ sector were made for the regions of the ural federal district from 2014 to 2018 (the data for 2017 are shown in table 1). in the whole federal district in this period, the growth of government revenues was 183%, from 3,192.16  billion to 5 833.17 billion rubles. the weakest dynamics was shown by the growth of revenues from personal income tax, which increased on average by 31% over five years. the lowest growth rates of income from personal income tax were in the khanty-mansi autonomous district and kurgan region, and the highest, in tyumen region, about 1.5 times. revenues from other types of taxes grew evenly 1.6-1.7 times. the highest growth in revenues was from taxes on production and imports: the gross collection of payments increased by 92% (from 2,406,383.11 to 4,610,758.87 million rubles). if we consider tax collection in the regions of the ural federal district, from 2014 to 2018, the most significant growth was shown by the yamalo-nenets autonomous district and tyumen region. the main source of tax payments in yamal during this period was the corporate income tax (an increase from 57,939.7 to 133,247.8 million rubles, or 2.3 times), as well as taxes on production and imports (an increase from 569,521,0 to http://doi.org/10.15826/recon.2020.6.4.022 256 https://journals.urfu.ru/index.php/r-economy r-economy, 2020, 6(4), 251–260 doi: 10.15826/recon.2020.6.4.022 online issn 2412-0731 1,200,944.2 million rubles, or 2.1 times). in tyumen region, taxes on production and imports increased even more, 2.6 times, due to an increase in value-added tax collections. moreover, current taxes on household income increased significantly (by 160%), which enabled the government to double tax payments in the region, from 163,870.6 to 324,244.9 million rubles over 5 years. the worst result in the development of its tax base was shown by kurgan region, where the total flow of payments grew by only 27%. the most significant growth was shown by other incomes – 2.2 times – as well as other taxes on production, which increased from 1,793.3 in 2014 to 2,871.6  million rubles in 2018. chelyabinsk and sverdlovsk regions have the largest amounts of collected tax payments. thus, corporate income tax in chelyabinsk region from 2014 to 2018 increased by 246%, while the overall growth in the ural federal district was only 172%. sverdlovsk region in this period demonstrated the most significant increase in receipts from other taxes on production: the whole federal district had a 1.72 times increase and sverdlovsk region, 2 times. the next step in calculating financial balances was the conversion of budgetary expenditures from kosgu to the sna and the distribution of spending by regions (table 1 shows an example of such calculations for 2017). the results of the calculations showed that the expenditures of budgets related to value added vary conside rably. while in the yamalo-nenets autonomous district, the share of these costs is about 63%, in kurgan region it is less than 50%. the average value of costs in value added in the ural federal district is 56.84%, while the costs of tyumen, chelyabinsk and sverdlovsk regions fluctuate with a half percent difference. this may indicate a certain standardized distribution of budgetary funds in the regions, allocated to the costs of paying salaries to public institutions. moreover, the lower is the budgetary provision of the region, the lower is the share of such expenses, and vice versa. table 1 calculation of financial balances of the ‘general governance’ sector by the regions of the ural federal district, 2017, mln rbs kurgan region sverdlovsk region tyumen region chelyabinsk region khmao – yugra yamalo-nenets autonomous district income taxes on production and imports 10,343.3 87,443.3 123,729.7 69,768.6 1,981,107.9 934,620.9 other taxes on production 2,504.1 32,770.5 11,265.4 17,573.4 63,236.5 65,230.8 corporate income tax 4,856.6 82,518.6 54,028.4 52,208.0 81,747.2 87,274.5 current taxes on household income 2,391.1 18,057.9 5,869.3 11,703.9 7,513.4 2,597.3 tax on personal income 9,268.3 89,897.7 31,271.2 58,440.1 79,629.0 50,443.9 other revenues 433.1 1,448.6 586.7 4,261.3 673.3 562.0 total income 29,796.4 312,136.6 226,750.7 213,955.3 2,213,907.2 1,140,729.4 expenditures consolidated regional budget added value of the sector 20,313.1 147,884.9 90,345.6 95,622.4 147,800.3 105,972.2 transfers to the households sector 10,797.5 54,412.5 18,597.5 37,807.9 31,087.1 21,478.8 gross savings 2,812.8 17,603.6 25,145.5 10,042.2 18,040.0 13,630.8 intermediate consumption of the sector 6,752.4 36,305.0 18,318.9 25,616.8 31,301.7 19,562.3 other current transfers 1,289.3 5,420.4 7,616.1 961.7 16,312.3 7,609.0 total 41,965.1 261,626.5 160,023.6 170,051.0 244,541.4 168,253.1 federal budget of the russian federation added value of the sector 19,860.5 92,076.7 32,181.1 66,205.4 27,756.1 14,638.5 gross savings 1,527.7 7,082.8 2,475.5 5,092.7 2,135.1 1,126.0 intermediate consumption of the sector 8,249.8 38,247.2 13,367.5 27,500.7 11,529.5 6,080.6 other current transfers 916.6 4,249.7 1,485.3 3,055.6 1,281.1 675.6 total 30,554.7 141,656.5 49,509.4 101,854.4 42,701.7 22,520.8 total expenditures 72,519.7 403,282.9 209,533.0 271,905.4 287,243.2 190,773.8   net lending borrowing of the sector –42,723.3 –91,146.3 17,217.7 –57,950.1 1,926,664.1 949,955.5 http://doi.org/10.15826/recon.2020.6.4.022 r-economy, 2020, 6(4), 251–260 doi: 10.15826/recon.2020.6.4.022 257 https://journals.urfu.ru/index.php/r-economy online issn 2412-0731 another factor that reduces the share of wages in the budget can be the higher social security costs. thus, kurgan region is the leader in terms of spending on transfers to the “households” sector; more than a quarter of all expenses (25.73%) were spent for these purposes. the lowest costs in this area are observed in tyumen region (only 11.62%); in sverdlovsk and chelyabinsk regions, social assistance costs are approximately equal (20-22%); oil and gas producing regions are the same in relative spending on social protection of the population (12.71-12.77%). in general, in the ural federal district, 174.18 billion rubles were allocated to social protection in 2017 or 16.6% of all expenses across the territory. the study of regional expenditures on capital construction did not reveal any regularities in the structure of financial balances. the smallest share of expenses is in chelyabinsk region (5.91%); in kurgan, sverdlovsk regions, khanty-mansiysk and yamalo-nenets autonomous district, this indicator is around 6.7–8.1%. the leader in terms of capital investments from the budget is tyumen region, which allocated 25.15 billion rubles to investments or 15.71% of total expenses. thus, expenditures on capital construction are determined by the challenges that the regions face and not by financial opportunities. in general, the budgets of the regions and municipalities of the ural federal district spent 1,046.46 billion rubles. despite the significant lack of their own financial resources, the biggest budget in 2017 was in sverdlovsk region. the poorest region in terms of budget expenditures was kurgan region. comparing tax revenues and expenditures of the consolidated budgets of the regions of the ural federal district, we can see that in almost all regions (except for kurgan region) income from the economy exceeds expenditures. however, after calculating the contribution of the federal part to the added value of each region of the ural federal district (table 2), it can be seen that the situation has changed a lot. the most significant federal expenditures were in kurgan region, they amount to 19.86 billion rubles or 9.89% of the region’s gross value added. sverdlovsk, chelyabinsk and tyumen regions depend on federal revenues for 3-5% of their grp, and the khanty-mansi autonomous district and yamalo-nenets autonomous district have minimal significant funding from the federal budget – less than 1%. at the same time, as we have already noted, the financial balance in the ‘general governance’ sector consists of both the value added costs of the sector (mainly salaries) and other expenses. if, according to the consolidated budget of the region, the sums of expenditures on investments, social security, purchase of goods and services were calculated by using the ‘direct’ method, then the federal budget expenditures for these purpo ses can be determined only indirectly. the official website of the federal treasury of the russian federation contains only fragmentary information on the structure of financing of federal budgetary institutions. based on these data, when calculating the total costs of the federal budget in the regions, it was decided, very tentatively, to assume that the proportions of the costs are as follows: 65% – costs of wages and social charges; 27% – purchase of goods, works and services; 5% – investments; and 3% – other expenses. in accordance with this distribution, the financial balances of the ‘general governance’ sector were compiled by region for 2017 (table 1). it can be seen that if we take into account direct fe deral costs in regions of the ural federal district, table 2 calculation of the value added of the federal part of expenditures in grp of the regions of the ural federal district, 2017, mln rbs and % regions of the ural federal district gross regional product added value of the sector ‘general governance’ regional consolidated budget expenditures federal budget expenditures federal expenditures as% of grp kurgan region 200,868.2 40,173.6 20,313.1 19,860.5 9.89 sverdlovsk region 2,142,514.3 239,961.6 147,884.9 92,076.7 4.30 khmao – yugra 3,511,127.5 175,556.4 147,800.3 27,756.1 0.79 yamalo-nenets autonomous okrug 2,461,442.8 120,610.7 105,972.2 14,638.5 0.59 tyumen region 1,013,424.5 87,154.5 54,973.4 32,181.1 3.18 chelyabinsk region 1,348,564.7 161,827.8 95,622.4 66,205.4 4.91 total 10,677,942.0 825,284.6 572,566.3 252,718.3 2.37 the author’s calculations based on the data of rosstat and the ministry of finance http://doi.org/10.15826/recon.2020.6.4.022 258 https://journals.urfu.ru/index.php/r-economy r-economy, 2020, 6(4), 251–260 doi: 10.15826/recon.2020.6.4.022 online issn 2412-0731 then only tyumen region with national districts can claim to be ‘self-sufficient’ enough. kurgan region is the most dependent on external financing through all budgetary channels: in this region, the expenses were more than twice the level of tax payments. sverdlovsk and chelyabinsk regions show a lack of their own tax base, the former amount to a little more than 91 billion rubles, and the latter, almost 58 billion rubles. at the same time, if we compare net lending / borrowing in relation to the sector’s income, it turns out that the indicators are practically equal, about 27–29%. tyumen region, the only one of all the regions of the ural federal district, has an equal amount of income and expenses. finally, the autonomous districts demonstrate an impressive financial redundancy of the budget system; out of 2,213.91 billion rubles of taxes transferred in the khanty-mansiysk district, only 287.24 billion rubles were used at all levels of the budget system in the territory, or only 13%. the situation is similar in the yamalo-nenets autonomous district – 1,140.72 billion rubles were received, 190.77 billion rubles were spent, that is, 83.3% of taxes remained in the federal budget. in general, in the ural federal district, tax and other payments of over 2,702 billion rubles were transferred to the federal budget in 2017. conclusion the study on the development of financial balances of the ural federal district led us to the following basic conclusions: 1. the development of the account ‘general governance’ at the regional level allows us to more accurately determine the directions of transfer and spending of funds on all levels in the territory. this can contribute to the development of a methodology for assessing the ‘interregional’ movement of financial resources. 2. the calculation of the federal part of expenditures in a given region, in the absence of reliable data, can be carried out by deducting the regional budget expenditures from the added value of the region. the problem of including activities in the public sector involving commercial companies can be solved depending on the specifics of the region and additional calculations. the problem of including activities in the public sector with the presence of commercial companies will vary depending on the specifics of the region, but this can be eliminated by additional calculations. 3. financial balances of each region of the ural federal district have their own characteristics. the oil and gas regions – the khanty-mansi and yamalo-nenets autonomous districts – are net donors of the ‘general governance’ sector, while kurgan region, on the contrary, is a reci pient. tyumen region, due to the redirection of a part of the financial resources of the autonomous districts, has practically zero net lending/borrowing. industrialized sverdlovsk and chelyabinsk regions cannot provide themselves with financial resources due to the high federal budget expenditures in the territories. 4. the expenditures of the ‘general 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(2015). consolidated budgets of subjects of russian federation: analysis of acuestss and charges. science almanac, 11-1(13), 230–236. doi: 10.17117/ na.2015.11.01.230 information about the author alexey f. pasynkov – cand.sc. (economics), associate professor, senior researcher, institute of economics of the ural branch of the russian academy of sciences (29, moskovskaya str., ekaterinburg, 620014, russia); e-mail: monografia@mail.ru article info: received september 15, 2020; accepted december 1, 2020 информация об авторе пасынков алексей федорович – кандидат экономических наук, доцент, старший научный сотрудник института экономики уральского отделения российской академии наук (620014, россия, г. екатеринбург, ул. московская, 29); e-mail: monografia@mail.ru информация о статье: дата поступления 15 сентября 2020 г.; дата принятия к печати 1 декабря 2020 г. http://doi.org/10.15826/recon.2020.6.4.022 http://doi.org/10.17059/2017-1-28 http://doi.org/10.17059/2019-2-7 http://doi.org/10.26794/1999-849x2020-13-1-86-98 http://doi.org/10.17117/na.2015.11.01.230 http://doi.org/10.17117/na.2015.11.01.230 mailto:monografia@mail.ru mailto:monografia@mail.ru r-economy, 2020, 6(2), 111–124 doi: 10.15826/recon.2020.6.2.010 111 https://journals.urfu.ru/index.php/r-economy online issn 2412-0731 original paper © solosina, m.i., shchepina, i.n., 2020 doi 10.15826/recon.2020.6.2.010 analytical tools for economic research of small municipalities and gaming techniques for community involvement (the case of voronezh region in russia) m.i. solosina1 , i.n. shchepina1, 2 1 voronezh state university, voronezh, russia; e-mail: maria.solosina@gmail.com 2 cemiras, moscow, russia abstract relevance. the article deals with the issues of strategic territorial development in russian regions and municipalities and the analytical tools for studying them. while there is a diversity of tools for studying large municipalities, the choice of tools for smaller urban and rural settlements is quite limited. this is the research gap this study seeks to address. research objective. this study focuses on the case of municipal districts and settlements in voronezh region. the aim is to show how the proposed methodology can be applied for such cases. data and methods. the study relies on the methods of systemic analysis and synthesis, comparison and generalization, multidimensional statistics as well as on the use of gaming techniques. the data for the analysis were obtained from federal, regional and municipal statistics; municipal information systems of settlements of voronezh region; municipal information system miss ‘volost’; and from the executive authorities of voronezh region. results. the analysis of the set of indicators, including the municipal product to grp, for the period between 2006 and 2015 has shown that the town of liski is one of the leading municipalities in voronezh district (the municipal product of liskinsky accounts for over 5% of the region’s grp). we also applied our gaming technique to establish communication between the authorities and local communities in developing the project for creation of a historical and archeological park in the settlement of kostenki in voronezh region. conclusions. the proposed methodology can be quite productive in building socio-economic profiles of small municipalities, comparing them with others and revealing the interrelations between them. the gaming techniques are effective for enhancing the involvement of local communities in municipal strategic planning. keywords analytical tools, gaming techniques, strategic territorial development, municipality, systemic approach аналитические инструменты экономических исследований малых муниципалитетов и игровые техники для вовлечения общественности (пример воронежской области в россии) м.и. солосина1 , и.н. щепина1, 2 1 воронежский государственный университет, воронеж, россия; e-mail: maria.solosina@gmail.com 2 центральный экономико-математический институт российской академии наук, москва, россия аннотация актуальность. в статье рассматриваются вопросы стратегического территориального развития российских регионов и муниципалитетов и аналитические инструменты для их изучения. хотя существует множество инструментов для изучения крупных муниципалитетов, выбор инструментов для небольших городских и сельских поселений весьма ограничен. это пробел в исследованиях, на устранение которого нацелено это исследование. цель исследования. данное исследование рассматривает муниципальные районы и поселки в воронежской области. цель состоит в том, чтобы на их примерах показать применение предложенной методологии. данные и методы. исследование опирается на методы системного анализа и синтеза, сравнения и обобщения, многомерного статистического анализа, а также на использование игровых технологий. данные для анализа были получены из федеральной, региональной и муниципальной статистики; муниципальные информационные системы населенных пунктов ключевые слова аналитический инструментарий, организационные механизмы, стратегическое территориальное развитие, муниципалитет, системный подход for citation solosina, m.i., shchepina, i.n. (2020) analytical tools for economic research of small municipalities and gaming techniques for community involvement (the case of voronezh region in russia). r-economy, 6(2), 111–124. doi: 10.15826/recon.2020.6.2.010 http://doi.org/10.15826/recon.2020.6.2.010 http://doi.org/10.15826/recon.2020.6.2.010 112 https://journals.urfu.ru/index.php/r-economy r-economy, 2020, 6(2), 111–124 doi: 10.15826/recon.2020.6.2.010 online issn 2412-0731 воронежской области; муниципальная информационная система мисс «волость»; и от органов исполнительной власти воронежской области. результаты. анализ набора показателей, включая муниципальный продукт к врп, за период с 2006 по 2015 г. показал, что город лиски является одним из ведущих муниципальных образований в воронежской области (муниципальный продукт лискинского района составляет более 5% врп региона). мы также применили организационный игровой механизм для установления связи между властями и местными сообществами при разработке проекта создания историко-археологического парка в поселке костенки воронежской области. выводы. предложенная методология может быть весьма продуктивной для построения социально-экономических профилей малых муниципальных образований, сравнения их с другими и выявления взаимосвязей между ними. игровые технологии эффективны для повышения вовлеченности местных сообществ в муниципальное стратегическое планирование. для цитирования solosina, m.i., shchepina, i.n. (2020) analytical tools for economic research of small municipalities and gaming techniques for community involvement (the case of voronezh region in russia). r-economy, 6(2), 111–124. doi: 10.15826/recon.2020.6.2.010 introduction strategic planning has now become essential for settlements, towns, cities and other territorial entities as they get involved into the global competition for development resources (investment, human capital, technologies, etc.). strategic plans and similar documents should incorporate the vision and aspirations of local communities. these documents should also be based on comprehensive analysis of the current situation and development prospects of the territorial unit, including its strengths and weaknesses and development priorities. in russia, the system of strategic territorial planning has been developing intensively over the past 15 years. one of the significant stages was federal law no. 172 ‘on strategic planning in the russian federation’ adopted in 2014. the law requires methodological uniformity of such documents on the regional and municipal levels, as well as their consistency with the state strategy for economic and social development. to devise such strategies, it is necessary to conduct preliminary quantitative analysis of the statistics characterizing the socio-economic situation and development trends of the territory. national, regional and municipal-level documents are usually drawn based on federal and regional statistics, while for smaller municipalities (urban and rural settlements), this can be a problem due to the lack of statistical data. this problem can be addressed through the expansion of the database and development of tools of regional and muni cipal statistics. the lack of data in the official statistics database (russian federal state statistic service – rosstat) causes a shortage of available tools for analyzing the socio-economic situation in small municipalities. for our research, we used alternative resources, such as the municipal information system miss ‘volost’ and the data provided by the executive authorities of voronezh region (department of economic development, department of communications, department for the development of municipalities of voronezh region). as a result, we were able to create our own research database. since there are more than 22,000 municipa lities in russia, and only in 15 of them the population exceeds one million, the available tools for studying urban and rural settlements often prove ineffective in the russian context. for example, more than a half of inhabitants of voronezh region live in the municipalities (446 urban and rural settlements of voronezh region) selected for our empirical analysis. to measure the socio-economic parameters in these municipalities, we need appropriate tools that would also help us make adequate comparisons. an important factor and the main resource for the development of settlements is human capital. the strategic nature of the social system (settlement, city, country) determines its readiness for dynamic changes and development (arshinov, 2007). some territories may turn out to be more attractive to people than others due to the opportunities they offer, which inevitably affects migration trends (tiebout, 1956). the article describes a set of analytical tools that could be used for building socio-economic profile of small municipalities (urban and rural settlements) and gaming techniques for creating projects of strategic territorial development involving local communities. questions of territorial strategic development are discussed by glazyrin (2016), glazychev (2005), zubarevich (2010), makarov (2010), and pilyasov (2016). ayvazyan, afanasyev, kudrov http://doi.org/10.15826/recon.2020.6.2.010 r-economy, 2020, 6(2), 111–124 doi: 10.15826/recon.2020.6.2.010 113 https://journals.urfu.ru/index.php/r-economy online issn 2412-0731 (2016, 2018) give particular attention to these questions on the regional level. most studies, however, focus on territorial strategic development on the national and regional levels, some also consider the level of municipal districts, but little is said about smaller settlements. the 2009 world bank report ‘a new look at economic geography’ (2009) discusses the growth points of a territory in regional and global economies and ways of determining them. socio-economic development of territories was analyzed by lee (2000), florida (2010), shachar (1971), efrat (1994), portnov (2004), malizia (1986), bontje (2004), grimm (1995), shapero (1981). the issues related to territorial development projects involving local communities are investigated by v. e. lepsky (2009), vagin (2016), kutuzov, koveshnikova (2007), myasnikova (2015), and tyurin (2007). the second part of our study discusses the use of gaming techniques for involvement of communities in municipal strategic planning and is thus based on the concept of the game. conceptually, this part relies on the works by huizinga (2014) and shchedrovitsky (1981). a significant contribution to the discussion of the theoretical and practical studies of municipal strategic management in russia is made by such organizations as the institute for urban econo mics foundation, leontief center, center for strategic research, and the network of centers for applied urban studies. it should be noted, however, that most of the above-described economic studies dealing with the methodological problems of studying muni cipalities in russia are of theoretical or descriptive character. there is a perceived need for applied research in this sphere, which is the gap that our paper seeks to address. methodology and data this study focuses on the case of voronezh region, which comprises 446 urban and rural settlements and 32 municipal districts, excluding the city of voronezh. the study relies on the analysis of the legal acts, including those regulating the development of municipalities; federal, regional and municipal statistics; data from municipal information systems of settlements of voronezh region or rias (regional information and analytical system); data from municipal information system miss ‘volost’; data from the executive authorities of voronezh region (department of economic development, department of communications, department for the development of municipalities of voronezh region) (bystryantseva et al., 2016). the first part of the study uses multidimensional statistics and relies on the methods of systemic analysis and synthesis, comparison and generalization. the second part of the article describes a specific case when gaming techniques were applied to stimulate community engagement. the methodological approach includes the following stages. at the first stage, the data are collected from various sources: rosstat, regional and municipal statistics, municipal information systems, reports on the performance of local authorities, passports of municipalities, and so on. at the second stage, we select and cross-validate indicators and identify the typological data blocks. finally, the socio-economic status of municipalities is assessed through the following procedure: 1. evaluation and comparison of the indicators of the gross municipal product (gmp) (petrykina et al., 2016). to assess the gmp, we used the values of the average number of employees and the average monthly wage: g ,ii i r r asgrp mp ae ae as = ⋅ ⋅ where gmpi is the gross municipal product estimate for the i-th municipal district; grp, gross regional product; aer, the average number of employees in the region; aei, the average number of employees of the i-th municipal district; asr, the average monthly wage in organizations of the region; asi, the average monthly wage in organizations in the i-th municipal district. g ,jij j i i asgmp mp ae ae as = ⋅ ⋅ where gmpj is the gross municipal product estimate for the j-th settlement; gmpi is the assessment of the gmp of the i-th district; aei, the average number of employees of the i-th municipal district; aej, the average number of employees of the j-th settlement; asi, the the average monthly wage in organizations of the i-th municipal district; asj, the average monthly wage in organizations of the j-th settlement. to compare the gmp at the level of urban settlements, we introduced an adjusted coefficient for calculating the gmp of urban settlements http://doi.org/10.15826/recon.2020.6.2.010 114 https://journals.urfu.ru/index.php/r-economy r-economy, 2020, 6(2), 111–124 doi: 10.15826/recon.2020.6.2.010 online issn 2412-0731 (petrykina et al., 2017), due to the differences in databases: the gmp of settlements was calculated according to the data of the settlement passports while the gmp of municipal districts was calculated according to the rosstat data. 2. allocation of clusters of municipalities by using the methods of multivariate statistical analysis according to the following criteria: by economic specialization (in accordance with okved (all-russian classifier of economic activities), by the level of socio-economic development, and by the number of workers employed in various types of economic activity (petrykina et al., 2017). a comparative analysis of the results obtained through cluster analysis (solosina, 2019). 3. construction and comparison of economic profiles of settlements (solosina, 2019). the methodology for constructing an economic profile proposed in this study includes several stages. first, a database is formed and indicators are selected for urban settlements of voronezh region. second, the maximum, minimum and average value for each indicator are calculated: max , 1 ;,maxj ij i x x j n= = min , 1 ;,minj ij i x x j n= = 1 , m ij j i x x m= = ∑ where j is the number of the indicator, i is the number of the city settlement, xij is the value of the indicator. third, the average value is taken as the comparison base, equal to 100% or 1, in relation to which the levels for each indicator are calculated for each urban settlement. , 1, , 1, ; ijij j x z i m j n x = = = , ; 1, max jmax j j x z j n x = = , ; 1, min jmin j j x z j n x = = 1, .1, jz j n= = the minimum and maximum values are calculated for the levels relative to the average for each indicator. finally, for each urban settlement, a diagram of the scatter of values for each indicator is built. at the same time, two graphs are plotted on the chart: average values and indicator values for the given settlement. the resulting diagram represents the economic profile of the given settlement (fig. 1). another key aspect of our research methodology is the focus on the organizational mechanism – system-social design methodology (ssd) (solosina, 2019), which has been proven effective for engaging members of local communities in strategic territorial development. this is a communicational method aimed at involving people in the process of strategic planning and implementation of strategic documents. 1 2 x1 n j value of zi1–zin for i-th municipality zij max min zj = 1 z1 figure 1. economic profile of a settlement http://doi.org/10.15826/recon.2020.6.2.010 r-economy, 2020, 6(2), 111–124 doi: 10.15826/recon.2020.6.2.010 115 https://journals.urfu.ru/index.php/r-economy online issn 2412-0731 there are two approaches to the process of strategic development at the municipal level: ‘administrative-expert’ and ‘partner’ (solosina & schepina, 2016). a distinctive feature of the latter approach is the involvement of residents in the process of strategic decision-making and development of appropriate tools for doing so. members of local communities are involved into the strategic planning process with the help of gaming techniques. the basis of the ssd methodology is the ‘game square’ method proposed by m.a. kutuzova, which includes a series of game seminars (problem seminar / project seminar / strategic game / operational game) and developed on the basis of military operational-tactical games and organizational-activity games (the format was initially developed by g.p. shchedrovitsky (1981)). the main stages of the game and its preparation within the ssd framework are shown in figure 2 below. first, the technical task for the game is agreed upon with the customer. the customer may be, for example, the municipal administration, a regional executive authority, a self-governing territorial body, an action group, or a business. after agreeing on the technical specifications, the game master and the game support team develop the scenario by conducting preliminary research and analysis. second, the list of participants is drawn: it is necessary to involve all the participants interested in solving the problem posed by the customer. to participate in the game, one must know the rules of the game and the terminology, which is why the preparatory materials should be sent to participants in advance. when the game starts, the first stage is to discuss and revise the rules and terminology, which is necessary to stimulate creative thinking of the participants. then, in accordance with the methodology, game participants go through all ssd stages such as research, situation analysis, forecasting, development of scenarios, creation of a project line, and start-up projects. following that, the participants are transferred from the game into the real project space. at this stage, the participants discuss the future prospects of the project developed during the game. based on the results of the game, the game report is prepared, which contains all the material that was collected and analyzed. there are three types of game project outcomes: the game product; development of the participants’ soft skills; and the network. the game product is a system-social model of the project which includes: concepts, values, project characteristics, activities, system of management and leadership, roadmap, and potential risks. soft skills are the skills and competencies of the participants that are developed through their experience of team work. a network is here understood as an action group that creates and signs the project declaration, thereby indicating their interest in further participation. the uniqueness of ssd lies in the gaming component, since it is the game tools that help create a common strategy for a system-social project, motivate people to join such projects and become part of project teams. the ssd methodology is focused on the creation of a system-social project and the formation of the institutional environment for creating other projects within the framework of the ssd project. expert support at all stages allows project participants to maintain the strategic focus of the project. results we applied the above-described methodological approach to assess the socio-economic status of municipalities in russia by focusing on the case of the town of liski in voronezh region. technical task for the game list of participants distribution of materials to prepare for the game game game report research, problematization, analysis, forecast, scenario creation game scenario 1 2 3 4 5 figure 2. stages of the game and its preparation http://doi.org/10.15826/recon.2020.6.2.010 116 https://journals.urfu.ru/index.php/r-economy r-economy, 2020, 6(2), 111–124 doi: 10.15826/recon.2020.6.2.010 online issn 2412-0731 in accordance with the regional plan for the development of voronezh region, liski is the administrative center of liskinsky district, which in total includes 23 urban and rural settlements. since 2013, liskinsky district has been one of the leading municipal districts in voronezh region, according to the results of the comprehensive assessment of the regin’s socio-economic development. we used the rosstat data and settlement passports to obtain gmp estimates for liskinsky municipal district for 2006, 2010 and 2015, and then for the town of liski itself. let us compare the gmp values of liskinsky municipal district for 2006, 2010 and 2015 (see table 1), given that the average monthly wage in voronezh region in 2015 amounted to 27,772.7 rubles, grp was 823,133.6 million rubles, the average number of employees was 500,356. the gmp was just over 5% of the region’s grp. since 2006, liskinsky municipal district, along with rossoshansky municipal district and borisoglebsky city district, has been among the three leading municipalities in terms of gmp (table 1). table 1 the gmp of liskinsky municipal district in 2006, 2010 and 2015 year average number of employees, people average monthly wage, rub gmp, mln rub gmp in % to grp 2006 29,870 7,773.7 8,908.05 5.36 2010 27,651 15,181.3 17,933.96 5.17 2015 26,247 26,571.0 41,310.52 5.02 source: compiled by the authors. after evaluating the general indicator of socio-economic development – the gmp at the district and settlement levels, we identifed the typological group of this municipality. to do this, we used cluster analysis (tables 2, 3). in 2015, according to the results of clustering in terms of socio-economic development, liskinsky municipal district belonged to cluster a together with rossoshansky, pavlovsky, novousmansky municipal areas and borisoglebsky municipal districts. in terms of economic specialization, the areas like pavlovsky, novousmansky, bobrovsky, kalacheevsky, ostrogozhsky, and talovsky municipal districts belong to cluster 2 (table 2) – the leading cluster in terms of crop and livestock production. at the same time, the town of liski ranks second in terms of the volume of production (works and services) in such types of economic activities as “production and distribution of electricity, gas and water” and “manufacturing”. thus, the municipalities in this cluster can be characterized as “agricultural leaders”, although they also have a fairly well developed sphere of industrial production (table 3). in each column of table 2, the leading municipalities are highlighted in orange. those municipalities that rank second after the leaders are highlighted in yellow. these two groups include municipalities with the following characteristics: – clustering: a combination of clusters a – 1 and a – 2 (for both groups); – gross municipal product (gmp): more than 2% of grp (orange group) and 1–2% of grp (yellow group); – population: over 70,000 (orange group) and 40,000–70,000 (yellow group); – wages: more than 25,000 rubles (for both groups). other colors highlight the groups of municipalities that have the same types in two clusters. next, we turn to the adjusted estimate of the gmp obtained for some urban settlements of voronezh region in 2015, including liski (table 3). liski is the leader in terms of the gmp (22,241.72 million rubles), followed by rossosh (18,425.98 million rubles). as for the number of employees and type of activity (table 3), liski, along with rossosh, belongs to cluster 1 with a high number of employees in “manufacturing industries” and with fairly high rates of employees in “agriculture, hunting and forestry”, “production and distribution of electricity, gas and water.” thus, according to the selected indicators of economic specialization, the employment structure of liski does not fully correspond to the specialization of liskinsky municipal district. it is more industrial than in the district as a whole. the city has large enterprises manufacturing metal structures and building materials and processing agricultural products. at the following stage, we are going to turn to the economic profile of the town of liski and consider the town’s progress during the given period (figures 2–4). in 2006–2015, liski maintained the leading position in the following indicators: total number of employees; the number of employees in ‘manufacturing’; ‘transport and communications’ (the town has a large railway junction and a river port); ‘agriculture, hunting and forestry’; ‘wholesale and retail trade, repair of motor vehicles, motorcycles, http://doi.org/10.15826/recon.2020.6.2.010 r-economy, 2020, 6(2), 111–124 doi: 10.15826/recon.2020.6.2.010 117 https://journals.urfu.ru/index.php/r-economy online issn 2412-0731 table 2 municipal districts in voronezh region in 2015 municipal districts clusters by the level of socio-eco-nomic development (a-f) clusters by economic specialization (1–4) gmp in % grp population, people wages, rub. rossoshansky a 1 3.74 93,368 25,571.3 borisoglebsky a 1 2.01 63,678 21,046.8 liskinsky a 2 5.02 101,764 26,571.0 pavlovsky a 2 1.70 55,990 21,476.4 novoysmansky a 2 1.52 79,183 25,594.6 semiluksky a 3 1.27 67,558 22,340.7 anninsky b 2 1.05 41,195 19,513.8 ramonsky b 3 1.72 32,440 25,361.3 bobrovsky c 2 1.23 49,148 21,004.6 kalacheevsky c 2 1.08 53,670 19,732.4 buturlinovsky c 3 0.88 47,918 18,846.2 ertilsky c 3 0.51 23,839 18,430.2 novohopersky c 4 0.71 38,787 20,119.0 bogucharsky c 4 0.62 35,732 19,069.6 khokholsky c 4 0.61 29,702 22,213.6 verhnemamonsky c 4 0.38 19,890 19,526.9 petropavlovsky c 4 0.23 18,103 20,542.5 repyevsky c 4 0.23 15,742 21,055.7 talovsky d 2 0.86 39,785 20,320.7 verkhnekhavsky d 3 0.65 24,665 23,856.3 kashirsky d 3 0.49 24,343 23,979.1 ternovsky d 3 0.36 19,824 18,791.5 vorobyevsky d 3 0.33 17,071 19,239.2 podgorensky d 4 0.54 25,338 20,726.4 nizhnedevitsky e 4 0.40 18,989 24,963.0 ostrogozhsky f 2 1.51 58,950 23,236.9 gribanovsky f 2 0.74 31,100 21,096.1 kantemirovsky f 3 0.85 34,923 21,898.2 paninsky f 3 0.54 26,531 19,435.3 povorinsky f 4 0.60 32,755 21,014.2 olkhovatsky f 4 0.54 23,356 20,585.7 kamensky f 4 0.48 18,921 22,470.7 source: compiled by the authors. table 3 urban settlements in voronezh region in 2015 clusters in terms of socio-economics development economy: cluster specialization (1–4) clusters of municipalities gmp adjusted for settlements’ gmp, million rub. population wage, rub rossosh a 1 industrial 1 industrial 18,425.98 62,688 22,776 liski a 2 agricultural leaders + electroenergy 1 industrial 22,241.72 54,788 26,572 pavlovsk a 2 agricultural leaders + electroenergy 4 with low rates 6,426.22 25,081 22,063 davydovskoe a 2 agricultural leaders + electroenergy 4 with low rates 1,343.52 5,258 16,725 latnensky a 3 agricultural 4 with low rates 1,050.44 7,359 20,626 anninsky b 2 agricultural leaders + electroenergy 4 with low rates 3,441.91 16,729 19,221.8 ramon b 3 agricultural 4 with low rates 2,856.75 8,381 19,800 kalach c 2 agricultural leaders + electroenergy 2 agricultural 1,956.36 19,248 12,065 http://doi.org/10.15826/recon.2020.6.2.010 118 https://journals.urfu.ru/index.php/r-economy r-economy, 2020, 6(2), 111–124 doi: 10.15826/recon.2020.6.2.010 online issn 2412-0731 clusters in terms of socio-economics development economy: cluster specialization (1–4) clusters of municipalities gmp adjusted for settlements’ gmp, million rub. population wage, rub bobrov c 2 agricultural leaders + electroenergy 4 with low rates 3,290.01 19,956 16,780 buturlinovka c 3 agricultural 2 agricultural 3,772.99 25,230 18,600 ertil c 3 agricultural 2 agricultural 1,904.31 10,740 18,530 kantemirovskoe c 3 agricultural 4 with low rates 1,888.86 11,113 22,600 novokhopersk c 4 with low rates 2 agricultural 2,022.34 13,845 19,500 boguchar c 4 with low rates 4 with low rates 1,446.83 11,162 17,322 khokholskoe c 4 with low rates 4 with low rates 855.34 7,549 14,916 yelan-kolenovskoe c 4 with low rates 4 with low rates 560.92 3,635 20,600 nizhnekislyayskoye c 4 with low rates 4 with low rates 465.77 3,576 16,200 talovskoe d 2 agricultural leaders + electroenergy 4 with low rates 1,643.26 11,736 15,937 podgorensky d 4 with low rates 4 with low rates 1,026.02 5,750 21,004 gribanovskoe f 2 agricultural leaders + electroenergy 2 agricultural 3,193.01 15,255 22,400 ostrogozhsk f 2 agricultural leaders + electroenergy 3 electrical energy 5,027.35 32,944 16,772 pereleshinskoe f 3 agricultural 4 with low rates 437.31 2,797 18,100 source: the authors’ calculations based on the original dataset 0 2 4 6 8 10 12 po pu la tio n de ns ity pe rc en ta ge o f a gr ic ul tu ra l l an d pe rc en ta ge in du st ri al la nd t ot al e m pl oy ed in th e ec on om y t ot al n um be r of e m pl oy ee s n um be r of e m pl oy ee s ‘a gr ic ul tu re , hu nt in g an d fo re st ry ’, pe op le n um be r of e m pl oy ee s ‘m in er al e xt ra ct io n’ , p eo pl e n um be r of e m pl oy ee s ‘m an uf ac tu ri ng ’, pe op le n um be r of e m pl oy ee s ‘p ro du ct io n an d di st ri bu tio n of e le ct ri ci ty , g as … n um be r of e m pl oy ee s ‘c on st ru ct io n’ , p eo pl e n um be r of e m pl oy ee s ‘w ho le sa le a nd re ta il tr ad e, r ep ai r, e tc .’, p er s. n um be r of e m pl oy ee s ‘t ra ns po rt an d co m m un ic at io ns ’, pe op le n um be r of e m pl oy ee s ‘f in an ci al a ct iv iti es ’, pe op le n um be r of e m pl oy ee s ‘e du ca tio n’ n um be r of e m pl oy ee s ‘h ea lth an d so ci al s er vi ce s’ , p eo pl e n um be r of e m pl oy ee s ‘� e pr ov is io n of o th er u til ity , s oc ia l a nd … n um be r of e m pl oy ee s in b ud ge t or ga ni za tio ns � na nc ed fr om th e… a ve ra ge m on th ly s al ar y a ve ra ge h ou si ng h ou si ng e qu ip m en t w at er s up pl y h ou si ng e qu ip m en t w ith g as su pp ly pr op or tio n of p er so ns o ld er th an w or ki ng a ge c oe � ci en t o f n at ur es . p op ul at io n gr ow th m ig ra tio n gr ow th r at e average liski figure 3. economic profile of liski for 2006 source: the authors’ calculations based on the original dataset end table 3 http://doi.org/10.15826/recon.2020.6.2.010 r-economy, 2020, 6(2), 111–124 doi: 10.15826/recon.2020.6.2.010 119 https://journals.urfu.ru/index.php/r-economy online issn 2412-0731 household products and personal items’; ‘education’ (the town has several professional colleges and branches of universities); ‘healthcare and social services’. it should be noted that we don’t have the data for 2006 on such indicators as the share of industrial land and the share of agricultural land. moreover, in 2010 and 2015, the share of industrial land reached its maximum, and the share of agricultural land, its minimum, which characterizes the city as an industrial center. in comparison with other settlements, liski was losing its position in terms of the number of employees in ‘construction’ (even though the town is producing building materials) and ‘financial activity’. the indicators of natural and migration growth showed negative dynamics since 2010, the population of the city decreased by 2%. in the other indicators, the city retained its position (fig. 3–5). we believe that the proposed methodological approach and its visualization can help be used for managerial decision-making and strategic planning of municipalities. engaging and involving local communities in municipal strategic planning: gaming techniques involving people into the process of strategic planning is a key to successful implementation of municipal strategies. the proposed ssd methodology was tested in the settlement of kostenki in 2017. kostenki is a comparatively small settlement, located 47 km from the city of voronezh. the population is 1485 people, according to the settlement’s passport, aged 0-6 (45 people); 7–17 (96 people); 18–45 (560 people); 46–59 (295 people); and 60 or older (479 people). on the territory of the settlement, there are two agricultural 0 1 2 3 4 5 6 7 8 9 10 po pu la tio n de ns ity pe rc en ta ge o f a gr ic ul tu ra l l an d pe rc en ta ge in du st ri al la nd t ot al e m pl oy ed in th e ec on om y t ot al n um be r of e m pl oy ee s n um be r of e m pl oy ee s ‘a gr ic ul tu re , hu nt in g an d fo re st ry ’, pe op le n um be r of e m pl oy ee s ‘m in er al e xt ra ct io n’ , p eo pl e n um be r of e m pl oy ee s ‘m an uf ac tu ri ng ’, pe op le n um be r of e m pl oy ee s ‘p ro du ct io n an d di st ri bu tio n of e le ct ri ci ty , g as a nd … n um be r of e m pl oy ee s ‘c on st ru ct io n’ , p eo pl e n um be r of e m pl oy ee s ‘w ho le sa le a nd re ta il tr ad e, r ep ai r, e tc .’, p er s. n um be r of e m pl oy ee s ‘t ra ns po rt an d co m m un ic at io ns ’, pe op le n um be r of e m pl oy ee s "f in an ci al a ct iv iti es ’, pe op le n um be r of e m pl oy ee s ‘e du ca tio n’ n um be r of e m pl oy ee s ‘h ea lth a nd s oc ia l s er vi ce s’ , p eo pl e n um be r of e m pl oy ee s ‘� e pr ov is io n of o th er ut ili ty , s oc ia l a nd p er so na l… n um be r of e m pl oy ee s in b ud ge t o rg an iz at io ns �n an ce d fr om th e m un ic ip al … a ve ra ge m on th ly s al ar y a ve ra ge h ou si ng h ou si ng e qu ip m en t w at er s up pl y h ou si ng e qu ip m en t w ith g as su pp ly pr op or tio n of p er so ns o ld er th an w or ki ng a ge c oe � ci en t o f n at ur es . p op ul at io n gr ow th m ig ra tio n gr ow th r at e average liski figure 4. economic profile of liski for 2010 source: the authors’ calculations based on the original dataset http://doi.org/10.15826/recon.2020.6.2.010 120 https://journals.urfu.ru/index.php/r-economy r-economy, 2020, 6(2), 111–124 doi: 10.15826/recon.2020.6.2.010 online issn 2412-0731 enterprises and 639 private farms. according to the statistics, the average monthly wage in the district in 2015 was 22,213.6 rubles, and the average wage of workers in peasant farms, 10,644 rubles. the average number of workers in peasant farms was 8 people. in total, the average number of workers (external part-timers excluded) in the district in 2015 was 3809. kostenski rural settlement (kostenki) is located in khokholsky district, which has the mp of 5011.91 million rubles or 0.61% of grp (tables 2 and 3). the settlement of kostenki has a unique tourist potential. kostenki is world-famous for its rich historical and cultural heritage and natural beauty. the first people settled in these places 50,000 years ago, the first dwellings date back 25,000 years, there 0 2 4 6 8 10 12 14 po pu la tio n de ns ity pe rc en ta ge o f a gr ic ul tu ra l l an d pe rc en ta ge in du st ri al la nd t ot al e m pl oy ed in th e ec on om y t ot al n um be r of e m pl oy ee s n um be r of e m pl oy ee s ‘a gr ic ul tu re , hu nt in g an d fo re st ry ’, pe op le n um be r of e m pl oy ee s "m in er al e xt ra ct io n’ , p eo pl e n um be r of e m pl oy ee s ‘m an uf ac tu ri ng ", pe op le n um be r of e m pl oy ee s ‘p ro du ct io n an d di st ri bu tio n of e le ct ri ci ty , g as a nd w at er ’,… n um be r of e m pl oy ee s ‘c on st r u ct io n’ , p eo pl e n um be r of e m pl oy ee s ‘w ho le sa le an d re ta il tr ad e, r ep ai r, e tc .’, p er s. n um be r of e m pl oy ee s ‘t ra ns po rt an d co m m un ic at io ns ’, pe op le n um be r of e m pl oy ee s ‘f in an ci al a ct iv iti es ’, pe op le n um be r of e m pl oy ee s ‘e du ca tio n’ n um be r of e m pl oy ee s ‘h ea lth an d so ci al s er vi ce s’ , p eo pl e n um be r of e m pl oy ee s ‘� e pr ov is io n of o th er ut ili ty , s oc ia l a nd p er so na l s er vi ce s’ ,… n um be r of e m pl oy ee s ‘h ot el s an d re st au ra nt s’ n um be r of e m pl oy ee s ‘o pe ra tio ns w ith r ea l e st at e ... ’ a ve ra ge m on th ly s al ar y a ve ra ge h ou si ng h ou si ng e qu ip m en t w at er s up pl y h ou si ng e qu ip m en t w ith g as s up pl y pr op or tio n of p er so ns o ld er th an w or ki ng a ge c oe � ci en t o f n at ur es . p op ul at io n gr ow th m ig ra tio n gr ow th r at e liski average figure 5. economic profile of liski for 2015 source: the authors’ calculations based on the original dataset are the cultural layers in the area that store samples of primitive art (paleolithic venus). the modern village of kostenki is the heir to the city of kostyensk, an outpost of the 17th century on the southern outskirts of russia. kostyensk constituted a part of the belgorod system of defensive fortifications protecting the local communities from tatar raids from the south. then, with the decline of its functionality as a fortress, the city lost its status and became a rural settlement. the customer of the game was the entrepreneur who planned to create an archeological park on the territory of kostenki. the game was aimed at developing a ssd model for creation of such a park, devising possible scenarios for this project and a roadmap for its implementation. there were http://doi.org/10.15826/recon.2020.6.2.010 r-economy, 2020, 6(2), 111–124 doi: 10.15826/recon.2020.6.2.010 121 https://journals.urfu.ru/index.php/r-economy online issn 2412-0731 20 participants in the game: students, entrepreneurs, historians, journalists and economists. the key participants were the director of the kostenki open-air museum and the customer (initiator of the project). the participants of the game belonged to various age and professional groups. residents of the settlement participated in a number of regional programs: for example, in 2016 the municipality received 96,000 rubles for the improvement of a children’s playground and in 2017, the residents of the settlement decided to participate in the budgeting program and submitted their road repair project for the 2018 competition. below are the outcomes of the game, which fall within three categories: the game product, the participants’ soft skills, and the network. 1. game product participants of the game pointed out that there recently russian people has started to take more interest in the history of their country, region, community and family, which means that the project of kostenki may benefit from this trend. the result of the game was the participants’ common vision of the future development of archeological park ‘kostenki’ and the surrounding area. 1.1. system-social model of the project. the historical and archaeological park is the result of a joint effort of the community, entrepreneurs and local authorities. participants of the game pointed out that free time is now becoming a key development resource for people and that archaeological park in kostenki could follow the concept of life history, which corresponds to this trend. the creation of an archaeological park includes the study of the types of activities that could be offered to its visitors such as educational online and off-line events involving representatives of the academia and members of local communities; amateur archeology course; expositions with augmented reality experiences; experience-based programs for tourists (e.g. experience life in the paleolithic age) and volunteering programs. all types of project activities fall within the concept of leisure as time for personal development and education. 1.2. the main characteristics of the project include the following. 1.2.1. collective decision-making mechanism and creation of an appropriate management structure. the proposed range of activities, on the one hand, makes the system more stable, on the other hand, it requires appropriate management at all stages of the project development; 1.2.2. networking. the project, among other things, stimulates participants to build relations within the project team and interact with external stakeholders; 1.2.3. brand development. the archeological park as a heritage project capitalizes on the site’s unique location and history; 1.2.4. rules of cooperation. the game relies on a system of rules devised by the participants themselves; participants should meet a set of requirements such as willingness to invest resour ces; motivation; sharing the project’s values; 1.2.5. megaproject. in order to manage several projects at once, efficient leadership and an organizational structure are necessary. the management should include an expert council responsible for the development and implementation of the project strategy, the search for strategic partners, analysis of the project’s trajectory and so on. there should also be mana gers responsible for specific areas and issues. in order to create such a management structure, it is necessary to distinguish between operational and strategic aspects of the project. for example, to realize a subproject aimed at organizing a series of lectures on kostenki, it is necessary to devise a strategy, select topics, prepare materials, choose the time and place, coordinate the work of organizers, and so on. all this requires the organizational structure to be horizontal and flexible, able to quickly adapt to the changing situation. 1.3. project risks. certain risks, primarily of organizational nature, should be considered: for example, the loss of strategy or uniqueness of the project or disagreements between the parties involved in project realization. 2. development of participants’ soft skills and the network for the project team, it is essential that all its participants should enhance their teamwork and other basic skills. at the first stage of the project, a project declaration is devised and signed. the declaration is necessary to indicate the participants’ commitment to the values and goals of the project. one of the significant outcomes of the game is to create an action group that would be responsible for implementation of the project in real life. according to the ssd methodology, the participants of the game go through the following http://doi.org/10.15826/recon.2020.6.2.010 122 https://journals.urfu.ru/index.php/r-economy r-economy, 2020, 6(2), 111–124 doi: 10.15826/recon.2020.6.2.010 online issn 2412-0731 stages: research – analysis – forecasting – devising development scenarios – developing subprojects – start-up stage. in the game, these stages take less time than in real life, so the game prepares participants for future realization of the project and helps them develop the necessary skills. the ssd methodology is aimed at developing a strategic territorial development project and can be used at the stages of strategy development and implementation. conclusions the article proposes methodological tools for investigating socio-economic development of small municipalities and gaming techniques for involving local communities in municipal strategic planning. the methodological approach is based on the integrated use of our original databases (bystryantseva et al., 2016) and enables us to conduct analysis of individual municipal districts and compare them with other municipalities. we tested these tools by using the data on voronezh region and showed the role specific municipalities (for example, the town of liski) play in the region’s socio-economic system (solosina, shchepina, 2016). to make the proposed approach more effective, it could be combined with other analytical tools, for example, swot analysis. we could also build socio-economic profiles of municipalities to reveal their strengths and weaknesses and development trends and describe their relationships with other municipalities. as for the ssd methodology, in general, it is aimed at developing large-scale strategic projects and at developing participants’ management competencies. it is applicable both in business and in territorial development; it can also be used for educational purposes. as our experiment in the settlement of kostenki has shown, the development and implementation of projects using ssd techniques can stimulate cooperation between businesses, authorities and local communities. the results of this study can serve as a methodological and instrumental foundation for comprehensive regional diagnostics and improvement of the system of strategic planning and management at the municipal level. references arshinov, v.i. 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(1956). a pure theory of local expenditures, journal of political economy, 64(5), 416–424. tyurin, g.v. (2007). the experience of the revival of russian villages. moscow: generation, 240. (in russ.) vagin, v.v. (2016). proactive budgeting: a development strategy. the second all-russian conference on proactive budgeting. financial magazine. scientific and practical publication, 6, 129. (in russ.) world development report 2009: reshaping economic geography. retrieved from https://openknowledge.worldbank.org/handle/10986/5991 zubarevich, n.v. (2010). regions of russia: inequality, crisis, modernization. moscow: independent institute for social policy, 160. (in russ.) http://doi.org/10.15826/recon.2020.6.2.010 http://www.inesnet.ru/article/regionalnye-strategii-razvitiya-mezhdu-strategicheskim-proryvom-i-strategicheskim-tupikom/ http://www.inesnet.ru/article/regionalnye-strategii-razvitiya-mezhdu-strategicheskim-proryvom-i-strategicheskim-tupikom/ http://www.inesnet.ru/article/regionalnye-strategii-razvitiya-mezhdu-strategicheskim-proryvom-i-strategicheskim-tupikom/ https://openknowledge.worldbank.org/handle/10986/5991 https://openknowledge.worldbank.org/handle/10986/5991 124 https://journals.urfu.ru/index.php/r-economy r-economy, 2020, 6(2), 111–124 doi: 10.15826/recon.2020.6.2.010 online issn 2412-0731 information about the authors maria i. solosina – phd. in economics, leading engineer of interfaculty research laboratory of economics and management (khusulnova st. 40, 394068, voronezh, russia); e-mail: maria.solosina@gmail.com irina n. shchepina – doctor of economic sciences, professor of informational technology and mathematical methods in economy department (khusulnova st. 40, 394068, voronezh, russia); chief researcher, central economics and mathematics institute russian academy of sciences (117418, moscow, nakhimovsky pr. 47); e-mail: shchepina@mail.ru article info: received january 24, 2020; accepted may 6, 2020 информация об авторах солосина мария игоревна – кандидат экономических наук, ведущий инженер межфакультетской научно-исследовательской лаборатории экономики и управления воронежского государственного университета (394068, россия, воронеж, ул. хользунова, 40); e-mail: maria.solosina@gmail.com щепина ирина наумовна – доктор экономических наук, профессор кафедры информационных технологий и математических методов в экономике воронежского государственного университета (394068, россия, воронеж, воронежская обл., ул. хользунова, 40); главный научный сотрудник цэми ран (117418, россия, москва, нахимовский пр., 47); e-mail: shchepina@mail.ru информация о статье: дата поступления 24 января 2020 г.; дата принятия к печати 6 мая 2020 г. http://doi.org/10.15826/recon.2020.6.2.010 mailto:shchepina@mail.ru mailto:shchepina@mail.ru r-economy, 2022, 8(1), 5–20 doi: 10.15826/recon.2022.8.1.001 5 r-economy.com online issn 2412-0731 original paper © naumov, i.v., krasnykh, s.s., otmakhova, yu.s., 2022 doi 10.15826/recon.2022.8.1.001 udc 330.43 jel c33, c53, r11 scenario forecasting of the socio-economic consequences of the covid-19 pandemic in russian regions i.v. naumov1, 2 , s.s. krasnykh1, yu.s. otmakhova3 1 institute of economics of the ural branch of russian academy of sciences, ekaterinburg, russia; naumov.iv@uiec.ru 2 ural federal university named after the first president of russia b. n. yeltsin, ekaterinburg, russia 3 central economic and mathematical institute of the russian academy of sciences, moscow, russia abstract relevance. there is a perceived lack of methods that can accurately, reliably and comprehensively reflect the epidemiological situation in regions and its impact on their socio-economic development. the approaches that are currently described in research literature do not take into account the multivariance of scenarios of the covid-19 pandemic, both in time and space. research objective. the article aims to present a methodological framework that could be used to predict the socio-economic consequences of the covid-19 pandemic in regions and to detect the most vulnerable regions. data and methods. the study relies on a set of methods, including the methods of regression modeling, arima forecasting and spatial correlation analysis. results. the panel regression analysis has confirmed the negative impact of the pandemic on socio-economic development, in particular, the growth of overdue wage arrears, unemployment, arrears, the number of liquidated organizations, and the industrial production index. we have also identified the most vulnerable regions that need to be prioritized for government support. conclusions. the resulting models and scenarios can be used by policy-makers to set the priorities of state policy for the economic support of the regions and stabilization of the epidemiological situation in the country. keywords scenario forecasting, covid-19, regression analysis, arima forecasting, spatial correlation analysis acknowledgments the research was supported by the russian foundation for basic research (grant no. 20-04-60188 “methods for forecasting and scenario modeling of socio-economic consequences of viral epidemics, taking into account spatial and communicative interactions”). for citation naumov, i.v., krasnykh, s.s., & otmakhova, yu.s. (2022). scenario forecasting of the socio-economic consequences of the covid-19 pandemic in russian regions. r-economy, 8(1), 5–20. doi: 10.15826/recon.2022.8.1.001 сценарное прогнозирование социально-экономических последствий пандемии covid-19 в регионах россии и.в. наумов1, 2 , с.с. красных1, ю.с. отмахова3 1 институт экономики уральского отделения российской академии наук, екатеринбург, россия; naumov.iv@uiec.ru 2 уральский федеральный университет, екатеринбург, россия 3 центральный экономико-математический институт российской академии наук, москва, россия аннотация актуальность. ощущается недостаток методов, способных точно, достоверно и всесторонне отражать эпидемиологическую ситуацию в  регионах и ее влияние на их социально-экономическое развитие. подходы, описанные в настоящее время в научной литературе, не учитывают многовариантность сценариев пандемии covid-19 как во времени, так и в пространстве. цель исследования. в статье ставится задача представить методологическую базу, которая может быть использована для прогнозирования социально-экономических последствий пандемии covid-19 в регионах и выявления наиболее уязвимых регионов. данные и методы. исследование опирается на методы регрессионного моделирования, arima-прогнозирования и пространственного корреляционного анализа. ключевые слова сценарное прогнозирование, covid-19, регрессионный анализ, arima-прогнозирование, пространственный корреляционный анализ благодарности исследование выполнено при финансовой поддержке рффи в рамках научного проекта № 20-04-60188 «методы прогнозирования и сценарного моделирования социальноэкономических последствий https://doi.org/10.15826/recon.2022.8.1.001 http://r-economy.com https://doi.org/10.15826/recon.2022.8.1.001 6 r-economy.com r-economy, 2022, 8(1), 5–20 doi: 10.15826/recon.2022.8.1.001 online issn 2412-0731 introduction the deterioration of the epidemiological situation in russia caused by the spread of the novel coronavirus infection (naumov et al., 2021) has spatial heterogeneity. there are poles of growth in the incidence of the covid-19 (regions with a high concentration of cases), spatial clusters (regions with similar characteristics), and zones of their influence (directions in which the infection is spreading). in other words, the pandemic has affected the socio-economic development of russian regions differently. in the light of the above, the research and forecasting of the pandemic’s spatial patterns, modeling their impact on socio-economic development have now become urgent tasks. such research could provide evidence for policy-makers in setting spatial priorities for the stabilization of the epidemiological situation and in identifying the most vulnerable regions in need of state support. the purpose of this work is to model and predict the socio-economic consequences of the covid-19 pandemic in the regions of russia and to search for spatial priorities of their state support. to achieve them, we set the following tasks: first, to analyze the main methodological approaches to scenario forecasting of the socio-economic consequences of the pandemic; second, to create an approach for scenario forecasting of the pandemic in russian regions; third, to model результаты. панельный регрессионный анализ подтвердил негативное влияние пандемии на социально-экономическое развитие, в частности, на динамику индекса промышленного производства, уровня безработицы, просроченной задолженности по выплате заработной платы и числа ликвидированных организаций в регионах россии. мы также определили наиболее уязвимые регионы, которые нуждаются в приоритетной государственной поддержке. выводы. полученные модели и сценарии могут быть использованы политиками для определения приоритетов государственной политики по экономической поддержке регионов и стабилизации эпидемиологической ситуации в стране. от вирусных эпидемий с учетом пространственных и коммуникативных взаимодействий» для цитирования naumov, i.v., krasnykh, s.s., & otmakhova, yu.s. (2022). scenario forecasting of the socio-economic consequences of the covid-19 pandemic in russian regions. r-economy, 8(1), 5–20. doi: 10.15826/recon.2022.8.1.001 动态预测新冠疫情（covid-19）对俄罗斯地区社会经济的冲击 诺莫夫1, 2 ，克拉斯尼赫1，奥特玛哈娃3 1 俄罗斯科学院乌拉尔分院经济研究所；naumov.iv@uiec.ru 2 俄罗斯乌拉尔联邦大学 3 俄罗斯科学院中央经济数学研究所 摘要 现实性：现在缺乏能够准确、可靠、全面地反映地区疫情状况及其 对社会经济发展影响的研究方法。 目前在科学文献中没有考虑到新 冠疫情在时间和空间上的多变量动态情景。 研究目标：本文旨在提出一个研究框架，可用于预测新冠疫情对地 区社会经济的冲击。并从而确定受影响最大的地区。 数据和方法：该研究基于回归建模、arima预测和空间相关分析的 方法。 研究结果：面板数据回归分析证实了新冠疫情对社会经济发展的负 面影响。特别是对俄罗斯地区工业生产指数、失业率、拖欠工资和 清算组织数量的动态影响。 该研究还确定了需要国家优先支持的最 脆弱地区。 结论：政治活动家可以使用该模型来确定国内的一些地区。这些地 区可优先获得国家财政支持，从而稳定流行病期间的社会状况。 关键词 动态预测，covid-19，回归分 析，arima预测，空间相关分析 致謝 該研究得到了俄羅斯基礎研究基金 會的支持（第 20-04-60188 號贈 款“考慮到空間和交流互動的病毒 流行的社會經濟後果的預測和情景 建模方法”）。 供引用 naumov, i.v., krasnykh, s.s., & otmakhova, yu.s. (2022). scenario forecasting of the socio-economic consequences of the covid-19 pandemic in russian regions. r-economy, 8(1), 5–20. doi: 10.15826/recon.2022.8.1.001 http://r-economy.com https://doi.org/10.15826/recon.2022.8.1.001 r-economy, 2022, 8(1), 5–20 doi: 10.15826/recon.2022.8.1.001 7 r-economy.com online issn 2412-0731 the impact of the pandemic on the indicators of socio-economic development in russian regions; fourth, to design the most probable basic scenarios of the pandemic in russian regions and the corresponding forecast scenarios for changing the socio-economic indicators of their development; and, finally, to conduct a spatial analysis of the impact of the pandemic on the socio-economic development of regions and identify the most vulnerable territories. thus, our findings could help substantiate the spatial priorities of the state policy to stabilize the epidemiological situation in russia until 2022. literature review in the research literature, there are several methodological approaches to predicting the socio-economic consequences of the covid-19 pandemic in territorial systems of various levels, ranging from municipal to macroeconomic. the most widely used methods include multiple regression on panel data, box-jenkins autoregressive moving average models (arima), agentbased modeling, artificial neural networks, seir, sird and so on. the seir and sird methods as well as their modified versions were mainly used by russian researchers to study the localization of the covid-19 pandemic in russia (osipov et al., 2021); to model the impact of the pandemic on household finances (lebedev & lebedev, 2021); and to model the spread of the covid-19 in the republic of khakassia (kozlitin & shiganov, 2021). we found that these methods are well suited for predicting the dynamics of the pandemic, but at the same time, they are not sufficient to conduct a full assessment of its impact on the socio-economic development of various territorial systems. similarly, these methods are not enough to realize the full potential of the scenario approach to forecasting, which implies creating a system of various scenarios to take into account multiple factors. agent-based modeling can be used to design various predictive scenarios of the pandemic in different territorial systems and to estimate its socio-economic consequences. this method is sui table for developing a model of a real epidemiolo gical situation in a certain area, taking into account many factors. for example, a team from the central economic mathematical institute of the russian academy of sciences designed such a model for the municipality of moscow (makarov et al., 2020). in this model, human agents pass through various stages of the disease from infection to recovery or death, and these transitions are modeled not on the group level but on the individual level. this way it is possible to take into account the heterogeneity of the population in terms of the vulnerability to catching coronavirus and the part each individual takes in spreading the disease (makarov et al., 2020). this model is suitable for creating various predictive scenarios concerning the number of cases and deaths, the date when the peak of the wave is reached, the number of hospital beds needed, including intensive care units in moscow, taking into account various quarantine measures. however, the model cannot be used to assess the socio-economic consequences of the pandemic in this municipality. another study that used agent-based mo delling was conducted by kerr et al. (2021). their open-source model included the demographic information about age and population size, realistic modes of transmission among the populations including households, schools, workplaces, age-specific incidence rates, dynamics of the spread of the virus, etc. agent-based modeling is a powerful tool for multivariate scenario modeling and forecasting of the socio-economic consequences of the deteriorating epidemiological situation in territorial systems. however, its main limitation is the need to create a large number of agents that reflect actual socio-economic processes, to construct a complex system of equations describing the influence of various factors on the pandemic in various groups of agents, and its impact on the indicators of the socio-economic development of the given territory. moreover, such models are not very good at capturing the spatial aspects of the pandemic. the most popular method of scenario-based forecasting of the impact of the pandemic on the socio-economic development of territories is currently the method of regression analysis. this method was used to form a predictive model for assessing the impact of the covid-19 pandemic on the economies of some countries in eastern europe (vasileva et al., 2021). the study investigated the impact of the pandemic on the labor productivity index, the growth rate of production and services, the world oil price index, the trade cost index, the growth rate of exports and imports, and other indicators of economic development. as a result, it was predicted that the pandemic would lead to a 6.1% decline in gdp in eastern europe by the end of 2020 (vasileva et al., 2021). https://doi.org/10.15826/recon.2022.8.1.001 http://r-economy.com 8 r-economy.com r-economy, 2022, 8(1), 5–20 doi: 10.15826/recon.2022.8.1.001 online issn 2412-0731 yiting et al., (2021), using a multiple stepwise linear regression, investigated the impact of the deteriorating epidemiological situation on the indicators of socio-economic development of 39 large cities in china (population size, population density, regional gross domestic product, gdp per capita, number of migrants from rural areas, share of migrants from rural areas, level of urbanization, disposable incomes of the population, number of hospitals and doctors). the authors found that the level of urbanization, socio-economic development, infrastructure, including the urban density, directly affects the number of cases of the coronavirus infection. multiple regression analysis was used by uttrani et al., (2021) to model the impact of the pande mic on global population mobility and mental health. the authors found a significant negative correlation between the reported cases of domestic violence and mobility in the workplace. this indicates an increased level of stress and anxiety in people due to forced isolation during the pandemic. regression analysis has also been used to study the impact of the covid-19 on financial markets in developing countries. the authors confirmed the negative impact of the covid-19 on the daily market profitability of various sectors of economy, the resilience of the healthcare and banking sector (rao et al., 2021). shimizutani & yamada (2021), using regression analysis, assessed the impact of the pandemic on food security, financing of basic needs, health care costs, employment, economic and financial well-being of households in tajikistan. this tool was also used to assess the impact of the covid-19 on gdp of developed countries. yan (2021) studied the impact of the coronavirus on the us economy based on a simple linear regression model. shanshan et al. (2022) used binary logistic regression to investigate the impact of the covid-19 on the purchasing power and behavior of consumers and food security in china. this method was also used in (chan et al., 2021; ogundokun et al., 2021; raji, lakshmi, 2020; khan et al., 2021). the main advantage of regression analysis is the ability to establish cause-and-effect relationships between the processes of the pandemic in territorial systems and indicators of their socio-economic development, and to study the factors that are detrimental to the epidemiological situation. geographically weighted regression modeling can also be applied to take into account spatial effects when generating data for forecast scenarios. regression analysis fully realizes the possibi lities of the scenario approach. moreover, by using regressing analysis, we can give due regard to the so-called “controlled variables” in designing predictive scenarios. however, the models built with the help of regression analysis do not always adequately describe the relationship between the processes in question. the relationships between the variables may turn out to be false or change over time, and this requires constant updating and in some cases rebuilding of the regression models. to assess the impact of the pandemic on the socio-economic development of territories, we also used integrated autoregressive modeling with a moving average according to the box-jenkins methodology (arma, arima). this method was applied by davidescu et al. (2021), to predict the unemployment rate, taking into account the dynamics of the incidence of covid-19. as a result, the authors showed an increase in unemployment in 2020 and predicted its slight decrease until the end of 2023. altig et al. (2020) built a regression model to show the uncertainty of the socio-economic development of territories during the pandemic. this method was used to predict the spread of the coronavirus infection in (ahmar & del val, 2020; benvenuto et al., 2020; bertschinger, 2020; ding et al., 2020; kumar et al., 2020; singh et al., 2020). the main advantage of this forecasting method is that it is easy to use and the resulting data are easy to interpret. the forecasts are sufficiently accurate for the short term if the trends are stable. this method, however, cannot be used to design a system of various scenarios, it is suitable only for building the most probable scenarios (inertial, that is, scenarios assuming that the current trends will continue in the future, extremely pessimistic and optimistic scenarios). the box-jenkins models, in contrast to multiple regression, are not suitable for establishing causal relationships between the spread of the infection and indicators of socio-economic development or for studying the spatial characteristics of the epidemiological situation. the method for predicting the socio-economic consequences of the pandemic that has recently gained popularity is neural network modeling based on a multilayer artificial neural network (mlann). this method was used by jena et al. (2021) to study the impact of the covid-19 on http://r-economy.com https://doi.org/10.15826/recon.2022.8.1.001 r-economy, 2022, 8(1), 5–20 doi: 10.15826/recon.2022.8.1.001 9 r-economy.com online issn 2412-0731 gdp in developed countries. the authors predicted a decrease in the economic growth rates of eight countries from april to june 2020. thus, the neural network has proven effective for capturing nonlinearities present in quarterly time series data and for making accurate predictions. the machine learning methods were used in other studies (gambhir et al., 2020; majumder et al., 2021; zoabi et al., 2021; gavrilov et al., 2021; kushwaha et al., 2020; mahdavi et al., 2021). the methods such as arima modeling, however, are capable of predicting with high accuracy the socio-economic consequences of pandemic only in a particular region. these methods cannot identify the spatial patterns of the pandemic but, unlike arima modelling, they can help detect causeand-effect relationships. to develop mechanisms for stabilizing the socio-economic situation in regions, a more comprehensive approach is needed that integrates various methods of modeling and forecasting. such an approach is more suitable for considering the spatial characteristics of the pandemic and for identifying the most vulnerable territories. thus, not only the most probable basic scenarios can be designed, but a whole system of these scenarios. methodology as was shown in the previous section, regression analysis is an effective method for predicting the socio-economic consequences of the pandemic. using the established functional dependencies, this method can be applied to design a system of predictive scenarios, which is why we have chosen it to build the methodolo gical framework of our study. at the initial stage, we used panel data to assess and build models of the impact of the pandemic on the following socio-economic indicators: the industrial production index, the volume of shipped products, the unemployment rate, overdue wage arrears, the number of liquidated organizations, and the volume of exports of products (see figure 1 below). the choice of indicators was limited due to the lack of monthly data required for panel regression analysis for 2020 and 2021 in the statistical database of the federal state statistics service. the regression models using panel data will be used to test the hypothesis about the negative impact of the pandemic on the socio-economic development of the regions. in the process of modeling, we are going to build regressions with fixed and random effects, assess their adequacy using the hausman test, schwarz, akaike and hennan-quinn information tests, analyze the statistical significance of the regression parameters, check the autocorrelation between model errors using the darbin-watson test, the normality of  the distribution of residuals using the jarque-bera test, etc. the panel data regression models were built with the following variables: the number of cases of coronavirus infection, the industrial production index, the unemployment rate, the volume of overdue wage arrears, the number of liquidated organizations in the regions, and the volume of products shipped. the data were obtained by using the yandex datalens service1 and official statistics from rosstat2 for 85 regions of the russian federation between march 2020 and august 2021 (1530 observations). panel models were built using the gretl software. the use of panel data in modeling is necessary to take into account space and time as the two key criteria in scenario forecasting to form a signi ficant sample of observations. the models built this way, however, can be used to assess the impact of the pandemic on the economic development of regions in general but they do not reflect the strength of the pandemic’s impact on certain regions. therefore, in order to assess the spatial characteristics of the impact of the pandemic and identify the most vulnerable regions, at the next stage, it is planned to conduct a correlation ana lysis. the value of the correlation coefficient exceeding 0.7 will indicate a strong negative impact of the pandemic on the socio-economic deve lopment of the regions. in addition, it is planned to identify the regions with less significant consequences of the pandemic (with the correlation coefficient ranging from 0.3 to 0.7) and regions that were slightly affected by the pandemic (with the correlation coefficient of less than 0.3). thus, we will be able to assess and predict the spatial characteristics of the impact of the pandemic and make recommendations concerning the spatial priorities of the state policy. at the third stage of the study, we will construct regression models of the pandemic’s impact on the index of industrial production, the volume of shipped products, the unemployment rate, the 1 coronavirus. dashboard and data / yandexcloud. retrieved from: https://cloud.yandex.ru/marketplace/products/ yandex/coronavirus-dashboard-and-data 2 operational statistics / rosstat. retrieved from: http:// bi.gks.ru/biportal/contourbi.jsp?solution=dashboard&allsol=1 https://doi.org/10.15826/recon.2022.8.1.001 http://r-economy.com https://cloud.yandex.ru/marketplace/products/yandex/coronavirus-dashboard-and-data https://cloud.yandex.ru/marketplace/products/yandex/coronavirus-dashboard-and-data http://bi.gks.ru/biportal/contourbi.jsp?solution=dashboard&allsol=1 http://bi.gks.ru/biportal/contourbi.jsp?solution=dashboard&allsol=1 10 r-economy.com r-economy, 2022, 8(1), 5–20 doi: 10.15826/recon.2022.8.1.001 online issn 2412-0731 amount of arrears on wages, the number of liquidated organizations and the volume of exports in regions with a high correlation. this will help us clarify the models obtained at the first stage and improve their accuracy. this stage is necessary for the construction of scenario and multivariate forecasts of the socio-economic consequences of the pandemic, because panel regression models complicate this process and lead to errors and inaccuracies. the regression models formed at this stage will allow us in the future to design “active” forecast scenarios of changes in the indicators of the socio-economic development of regions, depending on the changes in the dynamics of the covid-19 morbidity. to form the basic predictive scenarios of the pandemic in russia regions, we are going to use integrated autoregressive moving average modeling (arima). this toolkit is suitable for building an accurate inertial forecast, assuming that the trends observed for march 2020-october 2021 will remain stable. we are also going to build two extreme scenarios (optimistic and pessimistic). the assessment of the adequacy of the arima models will be made according to the statistical significance of their parameters, the size of the determination coefficient and information criteria of akaike, schwartz, hennan-quinn. the forecasts of the pandemic will be used in the future to design the corresponding forecast scenarios for changes in the socio-econo mic consequences in the regions according to the models developed at the third stage. for each indicator, we intend to create the most probable inertial scenario, which assumes that the rates of the pandemic will remain stable in the future. we also going to build extreme scenarios (optimistic and pessimistic). the methods of regression analysis and autoregressive modeling by time series (arima) will be applied to design not only basic, but the whole system of different predictive scenarios. at the final stage, the models will be used to determine the target values of the incidence of coronavirus infection in the regions. after these values are reached, it will be possible to reduce the negative socio-economic consequences. the proposed approach, in contrast to those currently used, can be applied to systematically assess and predict the socio-economic consequen ces of pandemic, taking into account the most probable scenarios. the novelty of this approach 1. regression modeling using panel data a study of the in�uence of the pandemic on: • industrial production index; • volume of products shipped, • unemployment rate; • amount of overdue wage arrears; • number of liquidated organizations; • exports • • • 6. development of state policy measures for stabilization of the epidemiological situation in russian regions and their economic support 5. designing the basic, most likely predictive scenarios of the pandemic and its in�uence on regional socio-economic development 5. construction of the most probable forecasts of changes in the dynamics of the pandemic in the regions according to arima models 4. arima modeling the dynamics of covid-19 cases in regions heavily a�ected by the pandemic 3. construction of regression models of the in�uence of pandemic on the socio-economic development of vulnerable regions search for regions experiencing a strong negative impact of the pandemic (r > 0.7); search for regions experiencing the average negative impact of the pandemic (0.3 < r < 0.7); search for regions experiencing a weak negative impact of the pandemic (r < 0.3) 2. correlation analysis of the in�uence of the pandemic on the socio-economic development of russian regions: figure 1. research methodology source: developed by the authors http://r-economy.com https://doi.org/10.15826/recon.2022.8.1.001 r-economy, 2022, 8(1), 5–20 doi: 10.15826/recon.2022.8.1.001 11 r-economy.com online issn 2412-0731 lies in the possibility to assess the spatial characteristics of the influence of the pandemic on the socio-economic development of regions by using correlation analysis. by applying this approach, the most vulnerable regions can be identified. results in accordance with the procedure described above, we built panel regression models of the impact of the number of covid-19 cases on such indicators as the industrial production index, unemployment rate, overdue wage arrears, the number of liquidated organizations in the regions and the volume of shipped products. we used panel data for 85 russian regions from march 2020 to august 2021 (1,530 observations). for each indicator, we built three types of models by applying the combined least squares method, with random and fixed effects and assessed their reliability by using the hausman test and information criteria. as a result, we found the negative impact of the pandemic on the amount of overdue wage arrears (table 1). as the regression model shows, an increase in the number of cases in russian regions leads to an increase in arrears in wage payments. the regression parameters confirming this relationship are statistically significant (regression coefficients have low p-values, less than 5%). the model's reliability is also confirmed by the low values of the information criteria. there is no autocorrelation of residuals and a normal distribution of errors in the model. the model only shows the negative impact of the pandemics on the dynamics of this indicator. for a more detailed study of the spatial characteristics of this impact, we conducted a correlation analysis (see fig.2). we found a close correlation exceeding 0.7 that confirms the strong influence of the pandemic on the growth of overdue wage arrears in kursk, tambov, novgorod, tyumen, moscow, rostov, lipetsk, kaliningrad, krasnodar, khabarovsk and stavropol regions, and the udmurt republic. the dynamics of overdue debt in these regions may be due to other factors, however. the pandemic had a less significant impact on the growth of arrears in the republic of mordovia (r = 0.68), crimea (0.61), nenets autonomous district (0.54), in smolensk region (0.35), and in the republic of altai (0.32). the dynamics of the incidence of covid-19 had a weak effect on the indicator under consideration in oryol (0.27), amur (0.26), irkutsk (0.22), sakhalin (0.1), and sverdlovsk (0.1) regions. in these regions, other factors contributed to the growth of overdue wage arrears. to form predictive scenarios concerning the dynamics of overdue wage arrears in regions heavily influenced by covid-19, we built regression mo-dels (see table 2 below). while according to the results of panel regression analysis, the increase in the incidence of covid-19 in the regions on average contributed to an increase in overdue debt by 59 rubles, the temporary models built separately for each region showed a more significant increase in this indicator. for example, in kursk region, an increase in the incidence of coronavirus infection contributed to the growth of the prophesied wage arrears by 1600 rubles; in khabarovsk region, 1080  rubles; in tambov table 1 regression model of the dependence of the volume of overdue wages on the number of cases of covid-19 with fixed effects coefficient standard error t-statistic p-value const 20596.7 1209.7 17.03 1.05e-194*** x1 0.059 0.012 4.87 7.10e-06*** lsdv r-squared 0.749 within r-squared 0.015 lsdv f (85, 1359) 47.8 p-value (f) 0.000 schwarz criterion 33620.3 akaike criterion 33166.6 rho parameter 0.86 hennan-quinn criterion 33335.9 breusch-pagan test statistic: lm = 5147,5 0.000 hausman test statistic: h = 9,56 0.0019 wald test for heteroscedasticity (null hypothesis – observations have total error variance): chi-square (85) = 6,5e+013 0.000 source: the authors’ calculations based on statistical data (rosstat), indices: overdue wages, 2021. url: https://rosstat.gov. ru/compendium/document/13267; yandex cloud, coronavirus. dashboard and data, 2021. url: https://cloud.yandex.ru/marketplace/products/yandex/coronavirus-dashboard-and-data/ (accessed: 13.01.2022) https://doi.org/10.15826/recon.2022.8.1.001 http://r-economy.com https://rosstat.gov.ru/compendium/document/13267 https://rosstat.gov.ru/compendium/document/13267 https://cloud.yandex.ru/marketplace/products/yandex/coronavirus-dashboard-and-data/ https://cloud.yandex.ru/marketplace/products/yandex/coronavirus-dashboard-and-data/ 12 r-economy.com r-economy, 2022, 8(1), 5–20 doi: 10.15826/recon.2022.8.1.001 online issn 2412-0731 strong negative impact of covid-19 on the industrial production index (r2 > 0.7) average negative impact of covid-19 on the industrial production index (0.3 < r2 < 0.7) weak negative impact of covid-19 on the industrial production index (r2 < 0.3) figure 2. diagram of the correlation dependence of overdue wage arrears on the number of covid-19 cases source: developed by the authors based on the model table 2 models of the dependence of the volume of overdue wage arrears on the number of covid-19 cases and forecast scenarios for this indicator by may 2022, thousand rubles correlation model current value forecast scenarios inertial pessimistic optimistic kursk region 0.94 y = –17113 + 1.6x 85569 109099 135989 82208 tambov region 0.93 y = 39291 + 0.97x 85087 102198 113957 90441 novgorod region 0.89 y = 820 + 0.31x 15968 19396 24976 13816 tyumen region 0.87 y = –2139 + 0.31x 19182 26123 31813 20433 moscow region 0.86 y = 7456 + 0.24x 128004 144392 161427 127356 krasnodar region 0.85 y = –6250 + 0.67x 47286 65197 79616 50779 kaliningrad region 0.85 y = 8326 + 0.14x 17045 18480 21573 15388 stavropol region 0.85 y = 5740 + 0.4x 43818 85643 116253 55034 khabarovsk region 0.74 y = 3938 + 1.08x 103030 141826 175554 108098 rostov region 0.73 y = 5888 + 0.45x 74460 98276 119390 77163 udmurtia 0.70 y = –243.5 + 0.2x 10800 18492 23239 13860 lipetsk region 0.70 y = –933.6 + 0.2x 12941 16549 21276 11822 source: developed and predicted by the authors based on calculations region, 970 rubles; in krasnodar region, 670 rubles. the forecast scenarios built on the basis of the regression models and the results of arima modeling indicate a further deterioration in the socio-economic situation of the regions. the level of overdue debt, according to optimistic forecasts, will be lower than the current value for october 2021, only in a few regions: kursk, novgorod, moscow, kaliningrad and lipetsk. in the rest of the regions, by may 2022, we forecast a significant increase in overdue wage arrears, which will exacerbate the already high level of social tension in the regions. as a result, we found the negative impact of the pandemic on the unemployment rate in the regions (table 3). http://r-economy.com https://doi.org/10.15826/recon.2022.8.1.001 r-economy, 2022, 8(1), 5–20 doi: 10.15826/recon.2022.8.1.001 13 r-economy.com online issn 2412-0731 thus, according to the panel regression model with fixed effects, an increase in morbidity per 100 people leads to an increase in the number of unemployed people by an average of 6 people. the correlation analysis showed that the pandemic had the strongest impact on the unemployment rate in lipetsk region, the republic of ingushetia and dagestan, and the altai republic (figure 3). the pandemic had a less significant impact on the unemployment rate in magadan (r = 0.68), astrakhan (0.65), smolensk (0.64), novosibirsk (0.57), moscow (0.48), nizhny novgorod (0.43), tyumen (0.41), novgorod (0.32), saratov (0.31) regions, the altai republic (0.66), north ossetia (0.57), tyva (0.47), moscow (0.63), the yamalo-nenets autonomous district (0.58), khantable 3 regression model of the dependence of the unemployment rate on the number of covid-19 cases with fixed effects coefficient standard error t-statistic p-value const 49196.1 295.7 166.3 0,000*** x1 0.06 0.005 11.5 2.3e-029*** lsdv r-squared 0.95 within r-squared 0.101 lsdv f (865, 1189) 300.5 p-value (f) 0.000 schwarz criterion 27456.1 akaike criterion 27013.1 rho parameter 0.84 hennan-quinn criterion 27179.5 breusch-pagan test statistic: lm = 7020.2 0.000 hausman test statistic: h = 20.3 6.49e-6 wald test на гетероскедастичность (null hypothesis – observations have total error variance): chi-square (85) = 1.13e+9 0.000 source: the authors’ calculations based on statistical data (rosstat), indices: total number of unemployed, 2021. url: https:// fedstat.ru/indicator/33414с; yandex cloud, coronavirus. dashboard and data, 2021. url: https://cloud.yandex.ru/marketplace/ products/yandex/coronavirus-dashboard-and-data/ (accessed: 13.01.2022) strong negative impact of covid-19 on the industrial production index (r2 > 0.7) average negative impact of covid-19 on the industrial production index (0.3 < r2 < 0.7) weak negative impact of covid-19 on the industrial production index (r2 < 0.3) figure 3. diagram of the correlation dependence of the unemployment rate on the number of covid-19 cases in russian regions source: developed by the authors based on the model https://doi.org/10.15826/recon.2022.8.1.001 http://r-economy.com https://fedstat.ru/indicator/33414с https://fedstat.ru/indicator/33414с https://cloud.yandex.ru/marketplace/products/yandex/coronavirus-dashboard-and-data/ https://cloud.yandex.ru/marketplace/products/yandex/coronavirus-dashboard-and-data/ 14 r-economy.com r-economy, 2022, 8(1), 5–20 doi: 10.15826/recon.2022.8.1.001 online issn 2412-0731 ty-mansi autonomous district (0.52) and in stavropol region (0.38). in other regions, the increase in the unemployment rate is largely caused by other factors that are unrelated to the deterioration of the epidemiological situation. the regression models of the dependence of the indicators on the time series confirmed the significant influence of the pandemic on unemployment in regions with high correlation values (table 4). an increase in the number of covid-19 cases in dagestan per 100 people provides an increase in the number of unemployed people by 85  people; in ingushetia, by 79 people; the altai republic and lipetsk region, 15 people. if the growth in morbidity continues by may 2022, the number of unemployed people in dagestan may increase by 6.6%. in the pessimistic scenario, the number of unemployed people may increase by 9.8%. according to the optimistic scenario, the unemployment rate is expected to exceed the current value in almost all the regions, which signifies serious socio-economic consequences of the pandemic. we used a regression model with random effects to show the relationship (1) between the industrial production index and the number of cases of covid-19: ipp = 102,347 + 0.000015 · c# (1) where ipp is the industrial production index, %; c is the number of cases of covid-19 in russian regions although we found a direct relationship between these indicators, the correlation analysis and subsequent regression modeling showed the negative impact of the pandemic in some regions (figure 4). according to the correlation diagram, the pandemic has a strong impact on the decline in the industrial production index in tambov, sakhalin, tyumen, tula, irkutsk, voronezh, sverdlovsk, volgograd and amur regions, in the kabardino-balkarian republic, the republic of dagestan, ingushetia, karelia, jewish autonomous region, and chukotka autonomous district. the correlation coefficient in all of the above regions significantly exceeds the value of 0.7, indicating a close relationship of the indicators (table 5). these regions faced serious socio-economic consequences of pandemic. for example, an increase in the number of covid-19 cases per 1,000 people leads to a decrease in the industrial production index by 9.4% in the chukotka autonomous district; by 3% in the jewish autonomous region; by 2.1% in the republic of ingushetia; and by 1.8 % in the kabardino-balkarian republic. in more resource-rich regions, such as sverdlovsk and tyumen regions, the level of decline in the industrial production index is lower. however, there is still evidence of the strong impact of the pandemic on these regions. the regions shown in table 5 thus should be prioritized for state economic support. the projected forecast scenarios showed that even a significant reduction in the number of covid-19 cases will not help these regions recover their current level of the industrial production index (as of october 2021) by may 2022. according to the results of the correlation analysis shown in figure 4, the pandemic also had a negative impact on industrial production in arkhangelsk (r = –0.62), vladimir (–0.46), magadan (–0.43), belgorod (–0.36), penza (–0.35), astrakhan and lipetsk (–0.3) regions, khabarovsk (–0.61), transbaikal (–0.39) territories, the republic of adygea (–0.58), mordovia (–0.56), chechnya (–0.49), komi (–0.4), altai (–0.31), and the khanty-mansi autonomous district (–0.38). however, this influence is less significant in comparison with the above considered territories. as a result, we showed the negative impact of the pandemic on the number of liquidated organizations (table 6). table 4 models of the dependence of the number of unemployed on the number of covid-19 cases and forecast scenarios for this indicator by may 2022, thousand people correlation model current value forecast scenarios inertial pessimistic optimistic republic of ingushetia 0.90 y = 73750.8 + 0.789x 89.1 94.5 98.6 90.3 lipetsk region 0.87 y = 24965.6 + 0.146x 33.8 36.1 39.1 33.1 republic of dagestan 0.84 y = 192682 + 0.853x 236.0 251.6 259.3 243.9 altai region 0.77 y = 63123.5 + 0.154x 76.9 80.7 84.4 77.0 source: developed and predicted by the authors based on calculations http://r-economy.com https://doi.org/10.15826/recon.2022.8.1.001 r-economy, 2022, 8(1), 5–20 doi: 10.15826/recon.2022.8.1.001 15 r-economy.com online issn 2412-0731 strong negative impact of covid-19 on the industrial production index (r2 > 0.7) average negative impact of covid-19 on the industrial production index (0.3 < r2 < 0.7) weak negative impact of covid-19 on the industrial production index (r2 < 0.3) figure 4. diagram of the correlation dependence of the industrial production index on the dynamics of covid-19 cases in russian regions source: developed by the authors based on the model table 5 models of the dependence of the industrial production index on the number of covid-19 cases and scenarios for this indicator by may 2022, % correlation model current value forecast scenarios inertial pessimistic optimistic tambov region –0.92 y = 111.8 – 0.0003x 98.2 93.0 89.5 96.6 sakhalin region –0.96 y = 100.8 – 0.0005x 83.9 78.4 74.2 82.6 kabardino-balkar republic –0.96 y = 133.8 – 0.0018x 71.9 48.8 37.1 60.5 republic of dagestan –0.93 y = 123.1 – 0.00056x 92.3 81.4 76.0 86.8 tyumen region –0.91 y = 136.9 – 0.00069x 89.5 74.1 61.4 86.7 jewish autonomous region –0.90 y = 136.9 – 0.003x 81.0 73.6 54.2 93.1 republic of ingushetia –0.89 y = 121.41 – 0.0021x 72.7 59.3 46.9 71.7 tula region –0.87 y = 124.7 – 0.0005x 94.8 87.0 78.1 95.9 chukotka autonomous district –0.84 y = 103.3 – 0.0094x 82.0 85.4 82.5 88.3 irkutsk region –0.83 y = 105.1 – 0.00009x 94.4 91.5 88.8 94.2 republic of karelia –0.80 y = 105.8 – 0.00014x 95.6 93.2 88.3 98.0 voronezh region –0.79 y = 113.2 – 0.00013x 93.8 82.8 76.5 89.1 sverdlovsk region –0.75 y = 104.1 – 0.00007x 93.3 91.1 89.5 92.7 volgograd region –0.68 y = 101.2 – 0.00001x 91.0 86.4 83.4 89.4 amur region –0.66 y = 102.3 – 0.00024x 93.0 89.6 85.5 93.8 source: developed and predicted by the authors based on their calculations https://doi.org/10.15826/recon.2022.8.1.001 http://r-economy.com 16 r-economy.com r-economy, 2022, 8(1), 5–20 doi: 10.15826/recon.2022.8.1.001 online issn 2412-0731 table 6 regression model of the dependence of the number of liquidated organizations on the number of covid-19 cases and predictive scenarios for this indicator by may 2022, units coefficient standard error z-score p-value const 300.86 40.37 7.45 <0.0001 x1 0.006 0.0004 15.97 <0.0001 schwarz criterion 24654.9 akaike criterion 24644.3 rho parameter 0.05 hennan-quinn criterion 24648.3 breusch-pagan test statistic: lm = 669.45 1,3e-147 hausman test statistic: h = 1895.98 0.000 wooldridge test for assessing autocorrelation: statistic: f (1, 84) = 6.57 0.012 null hypothesis – normal distribution: chi-square (2) = 43509.4 0.000 source: the authors’ calculations based on statistical data (rosstat), indices: number of registered and liquidated organizations, 2021. url: http://bi.gks.ru/biportal/contourbi.jsp?solution=dashboard&allsol=1&project=%2fdashboard%2fcompany_statistics/; yandex cloud, coronavirus. dashboard and data, 2021. url: https://cloud.yandex.ru/marketplace/products/yandex/coronavirus-dashboard-and-data/ (accessed: 13.01.2022) table 7 scenarios of changes in the incidence of covid-19 in regions with serious economic consequences of the pandemic by may 2022, cases regions current value inertial scenario pessimistic scenario optimistic scenario moscow region 502,283 570,563 641,542 499,583 sverdlovsk region 153,237 185,394 207,974 162,813 rostov region 152,382 205,307 252,226 158,389 voronezh region 149,620 234,070 282,385 185,756 irkutsk region 119,001 151,229 181,089 121,369 volgograd region 101,459 147,260 177,127 117,393 stavropol region 110,850 199,758 276,282 123,234 khabarovsk region 91,752 127,674 158,904 96,444 altai region 85,889 110,134 133,229 87,040 krasnodar region 79,905 106,638 128,158 85,117 republic of karelia 72,745 90,390 125,076 55,703 tyumen region 68,778 91,168 109,522 72,814 kursk region 64,176 78,883 95,689 62,076 kaliningrad region 62,275 72,532 94,622 50,442 udmurtia 61,354 104,085 130,461 78,355 lipetsk region 60,324 76,011 96,562 55,459 tula region 58,695 74,061 91,478 56,645 republic of dagestan 55,059 74,453 84,083 64,823 novgorod region 48,863 59,922 77,921 41,923 tambov region 47,212 64,853 76,975 52,732 amur region 38,800 52,979 70,240 35,717 sakhalin region 34,415 45,715 54,247 37,184 kabardino-balkar republic 34,360 47,190 53,686 40,694 republic of ingushetia 23,193 29,577 35,484 23,668 jewish autonomous region 8,983 11,442 17,929 4,955 chukotka autonomous district 1,847 1,903 2,207 1,598 source: developed and predicted by the authors based on calculations according to the regression model with random effects, an increase in the number of cases per 1,000 people on average leads to the liquidation of 6 enterprises. unfortunately, the correlation analysis has failed to identify the regions where the business bankruptcy rate was seriously affected by the pandemic. as a result, we identified he territories that are experiencing a medium influence of the pandemic (stavropol and kaluga regions and the nenets autonomous district) and a weak influence of the pandemic (other regions). thus, we can conclude that socio-economic factors have a greater impact on the number of liquidated organizations in the regions. the impact of http://r-economy.com https://doi.org/10.15826/recon.2022.8.1.001 http://bi.gks.ru/biportal/contourbi.jsp?solution=dashboard&allsol=1&project=%2fdashboard%2fcompany_s http://bi.gks.ru/biportal/contourbi.jsp?solution=dashboard&allsol=1&project=%2fdashboard%2fcompany_s https://cloud.yandex.ru/marketplace/products/yandex/coronavirus-dashboard-and-data/ https://cloud.yandex.ru/marketplace/products/yandex/coronavirus-dashboard-and-data/ r-economy, 2022, 8(1), 5–20 doi: 10.15826/recon.2022.8.1.001 17 r-economy.com online issn 2412-0731 the epidemiological situation in the regions is less significant. scenario modeling and forecasting of the socio-economic consequences of the pandemic showed that the most vulnerable regions are moscow, sverdlovsk, rostov, voronezh, irkutsk, volgograd, khabarovsk, stavropol, altai, and krasnodar (see table 7). despite the lower number of covid-19 cases compared to moscow, sverdlovsk and other regions, certain regions are strongly affected by the pandemic. these regions include the republic of ingushetia, dagestan, kabardino-balkaria, sakhalin, amur, novgorod and tambov regions, the jewish autonomous region, and the chukotka autonomous district. correlation analysis confirmed a close relationship between the increase in the incidence of covid-19 in the regions presented in table 7 and the decrease in the industrial production index, increase in the number of unemployed people, the volume of overdue wage arrears, and the number of liquidated enterprises. other regions not presented in table 7 are less affected by the pandemic. the decline in the indicators of socio-economic development of these regions depends to a greater extent on other factors. the above findings can be used by policy-makers in developing measures for stabilizing the epidemiological situation and providing support for the most vulnerable regions. conclusion the proposed methodological approach involves studying the influence of the pandemic on specific indicators of socio-economic development of regions by using panel regression analysis and correlation analysis. the latter is used to assess the tightness of the relationship between these indicators for each region. we have also built regression models to create active predictive scenarios of the pandemic and applied arima forecasting methods to design the most probable (inertial) and extreme scenarios (pessimistic and optimistic). the panel regression analysis has confirmed the negative impact of the pandemic on socio-economic development, in particular, the growth of overdue wage arrears, unemployment, arrears, the number of liquidated organizations, and the industrial production index. we have also identified the most vulnerable regions with the help of correlation analysis. scenario modeling and forecasting of the socio-economic consequences of the pandemic showed that the regions that were hit the hardest were moscow, sverdlovsk, rostov, voronezh, irkutsk, volgograd, khabarovsk, stavropol, altai, and krasnodar. these regions should, in our opinion, be targeted by the state policy for containing the coronavirus pandemic and providing economic support. our findings can thus be used to develop regulatory tools to minimize the adverse effects of the pandemic on regional development. references ahmar, a.s., & del val, e.b. 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(2021). machine learning-based prediction of covid-19 diagnosis based on symptoms. digital medicine, 4(3), 1–5. doi: 10.1038/s41746-02000372-6 information about the authors ilya v. naumov – phd in economics, head of the laboratory for modeling the spatial development of territories, institute of economics of the ural branch of russian academy of sciences (620014, russia, ekaterinburg, moskovskaya st. 29), ural federal university named after the first president of russia b. n. yeltsin (620002, rf, ekaterinburg, st. mira, 19); e-mail: naumov.iv@uiec.ru sergey s. krasnykh – junior researcher, laboratory for modeling the spatial development of territories, institute of economics of the ural branch of russian academy of sciences (620014, russia, ekaterinburg, moskovskaya st. 29); e-mail: krasnykh.ss@uiec.ru yulia s. otmakhova – phd in economics, leading researcher of the laboratory of computer modeling of socio-economic processes, central economic and mathematical institute of the russian academy of sciences (117418, russia, moscow, nakhimovsky prospect, 47); e-mail: otmakhovajs@yandex.ru article info: received december 16, 2021; accepted march 01, 2022 информация об авторах наумов илья викторович – кандидат экономических наук, руководитель лаборатории моделирования пространственного развития территорий, институт экономики уральского отделения российской академии наук (620014, россия, г. екатеринбург, ул.  московская,  29), уральский федеральный университет имени первого президента россии б.н. ельцина» (620002, россия, г. екатеринбург, ул. мира, 19); e-mail: naumov.iv@uiec.ru красных сергей сергеевич – младший научный сотрудник лаборатории моделирования пространственного развития территорий, институт экономики уральского отделения российской академии наук (620014, россия, г. екатеринбург, ул. московская, 29); e-mail: krasnykh.ss@uiec.ru https://doi.org/10.15826/recon.2022.8.1.001 http://r-economy.com https://doi.org/10.1016/j.foodcont.2021.108352 https://doi.org/10.1371/journal.pone.0257469 https://doi.org/10.1371/journal.pone.0257469 https://doi.org/10.1016/j.chaos.2020.109866 https://doi.org/10.3390/joitmc6030092 https://doi.org/10.1145/3465631.3465778 https://doi.org/10.3389/fpubh.2020.546637 https://doi.org/10.1038/s41746-020-00372-6 https://doi.org/10.1038/s41746-020-00372-6 20 r-economy.com r-economy, 2022, 8(1), 5–20 doi: 10.15826/recon.2022.8.1.001 online issn 2412-0731 отмахова юлия сергеевна – кандидат экономических наук, ведущий научный сотрудник лаборатории компьютерного моделирования социально-экономических процессов, центральный экономико-математический институт российской академии наук (117418, россия, г. москва, нахимовский пр., д. 47); e-mail: otmakhovajs@yandex.ru информация о статье: дата поступления 16 декабря 2021 г.; дата принятия к печати 1 марта 2022 г. 作者信息 诺莫夫·伊利亚·维克托罗维奇 – 经济学博士，地区空间发展建模实验室主任，俄罗斯 科学院乌拉尔分院经济研究所（邮编：620014，俄罗斯叶卡捷琳堡市，莫斯科路29号） ，乌拉尔联邦大学（邮编：620002，俄罗斯叶卡捷琳堡市，米拉路19号），邮箱：naumov.iv@uiec.ru 克拉斯尼赫·谢尔盖·谢尔盖耶维奇 – 地区空间发展建模实验室初级研究员，俄罗斯科 学院乌拉尔分院经济研究所（邮编：620014，俄罗斯叶卡捷琳堡市，莫斯科路29号）， 邮箱：krasnykh.ss@uiec.ru 奥特玛哈娃·尤利娅·谢尔盖耶娃 – 经济学博士，社会经济计算机建模实验室高级研究 员，俄罗斯科学院中央经济数学研究所（邮编：117418，俄罗斯莫斯科市，纳希莫夫街 47号），邮箱：otmakhovajs@yandex.ru http://r-economy.com https://doi.org/10.15826/recon.2022.8.1.001 74 https://journals.urfu.ru/index.php/r-economy r-economy, 2020, 6(2), 74–88 doi: 10.15826/recon.2020.6.2.007 online issn 2412-0731 original paper © celetti, d., 2020 doi 10.15826/recon.2020.6.2.007 small businesses in the global market: evidence from the fashion system of vicenza province (italy) d. celetti university of padua, padua, italy; e-mail: david.celetti@unipd.it abstract relevance. the paper seeks to explore how small and medium handicrafts can successfully compete in the globalized market. it questions, in particular, the relevance of the territory, of industrial districts and of the use of information technology to create innovative approaches to production and marketing, and consolidate the territory’s competitive position in global value chains. it highlights actual viable strategies for small and medium businesses operating in particularly complex sectors like those that are part of the “fashion system”. thus, the article deals with an important part of the national industry in the moment of world-wide crisis. research objective. the article discusses successful strategies of small firms in clothing and fashion industry. its purpose is to verify if and how handicrafts operating in the sectors particularly exposed to international competition succeed in competing effectively in international markets. the study tests the thesis that local dimension does not necessarily represent a disadvantage in the age of globalization and that even handicrafts can play at the international level. the study also verifies the role of territory in granting unique competitive advantage in the global market. data and methods. the methodological approach combines ana lysis of statistical data with four case studies. the work combines analytical and empirical approaches to highlight how a single business can reach levels of excellence in troubled markets. results. the study demonstrates that handicrafts can find spaces for growth in such declining sectors as cloth production in developed countries, provided that they succeed in focusing on niche markets through process, product, and marketing innovations; in using up-to-date technology; and in exploiting territorially embedded values. in this context technology emerges as a strategic tool as it lowers transaction costs and entrance barriers, offers innovative opportunities for re-organizing production processes, and enlarges potential markets. industrial districts, then, continue to represent a viable strategic advantage in terms of flexibility, know-how, and cooperation. finally, the brand “made in italy” confirms its status as an internationally recognized synonym of quality and fashionable design, opening companies the way to high level, luxury niches. keywords textiles, fashion, clothing, industrial districts, handicraft, made in italy, economic history acknowledgements the research was supported by the project “the economy of excellence. italian handicraft in the international networks: traditional knowledge, technological innovation and communication strategies (19th – 20th centuries)”, university of padua (it), department of historical, geographical sciences and of the antiquity. for citation celetti, d. (2020) small businesses in the global market: evidence from the fashion system of vicenza province (italy). r-economy, 6(2), 74–88. doi: 10.15826/recon.2020.6.2.007 малые предприятия в глобальном рынке: пример сектора моды провинции виченца (италия) д. челетти падуанский университет, падуя, италия; e-mail: david.celetti@unipd.it аннотация актуальность. статья посвящена изучению того, как малые и средние ремесленные изделия могут успешно конкурировать на глобализированном рынке. в ней рассмотрены, в частности, роль территории, промышленных районов и использования информационных технологий для создания инновационных подходов к производству и сбыту, а также для укрепления конкурентоспособности территории в глобальных цепочках создания стоимости. освещены актуальные жизнеспособные стратегии для малого и  среднего бизнеса, работающего в особенно сложных секторах, таких как те, которые являются частью «системы моды». таким образом, статья посвящена важной части итальянской промышленности в момент мирового кризиса. цель исследования. в статье рассматриваются стратегии малых фирм в индустрии одежды и моды. цель исследования состоит в том, чтобы проверить, успешно ли эти фирмы конкурируют на международных рынках. в исследовании проверяется тезис о том, что размер фирмы не обязательно является ключевые слова текстиль, мода, одежда, кластеры, ремесленная продукция, макроэкономика, экономическая история http://doi.org/10.15826/recon.2020.6.2.007 http://doi.org/10.15826/recon.2020.6.2.007 mailto:david.celetti@unipd.it mailto:david.celetti@unipd.it r-economy, 2020, 6(2), 74–88 doi: 10.15826/recon.2020.6.2.007 75 https://journals.urfu.ru/index.php/r-economy online issn 2412-0731 благодарности исследование было поддержано проектом «экономика совершенства. итальянское ремесло в международных сетях: традиционные знания, технологические инновации и коммуникационные стратегии (xix – xx века)», университет падуи (ит), факультет исторических, географических наук и античности. для цитирования celetti, d. (2020) small businesses in the global market: evidence from the fashion system of vicenza province (italy). r-economy, 6(2), 74–88. doi: 10.15826/recon.2020.6.2.007 недостатком в эпоху глобализации и что даже ремесленные фирмы могут эффективно играть на международном уровне. статья также подтверждает роль территории в предоставлении уникального конкурентного преимущества на мировом рынке. данные и методы. методологический подход объединяет теоретическое обсуждение выбранной научной литературы и статистических данных с углублённым анализом четырёх фирм. работа сочетает в себе аналитические и эмпирические подходы, чтобы подчеркнуть, успешные стратегии отдельных фирм. результаты. исследование показывает, что ремесленные фирмы могут найти пространство для роста в таких сокращающихся секторах, как производство одежды в развитых странах, при условии, что им удастся сосредоточиться на нишевых рынках с помощью инноваций в процессах, продуктах и маркетинге; в использовании современных технологий; и в использовании территориально заложенных ценностей. в  этом контексте технология становится стратегическим инструментом, поскольку она снижает операционные издержки и входные барьеры, предлагает инновационные возможности для реорганизации производственных процессов и расширяет потенциальные рынки. таким образом, промышленные районы продолжают представлять собой жизненно важное стратегическое преимущество с точки зрения гибкости, ноу-хау и сотрудничества. наконец, бренд «сделано в италии» подтверждает свой статус признанного во всем мире синонима качества и модного дизайна, открывая компаниям путь к нишам класса люкс высокого уровня. introduction the italian fashion system, even its most dynamic clusters, suffered from the prolonged decline of the early 2000s. though traditionally strong and playing for decades a leading role in domestic economy, it started losing firms, employees, and turn-over. the negative trend affected both small and big companies in all the country’s regions, including north-eastern ones, where textile manufactures have been strongly present since venetian time (fontana, 2004), and lived world-known success stories, such as the rossi, marzotto, stefanel, or benetton (belussi, 1992; rovizzi, 1992; tait, 1998; fontana, 2005; favero, 2012). within this broadly adverse trend, there is, however, evidence of single firms having managed to re-organize their own business and develop innovative strategies within rentable niches (bettiol, 2015). the paper aims at enhancing our understanding of the possibilities of reaction of small and medium enterprises (smes) operating in highly competitive markets combining analysis of empirical data and case study methods. our main goal is to verify if and through which approaches small businesses can withstand unfavorable economic trends and compete successfully in global markets. the paper investigates, in particular, how handicrafts succeed in changing the ‘traditional rules of the game’ in their favour through marketing, product, and process reorganization. the research has focused on the fashion and clothing sector in vicenza province because of its relevance in regional and national economy; its historical importance; its recent critical trends in terms of turnover, number of firms, and employees. the case studies of individual firms, on the other hand, have been selected because they represent clear examples of small family-run artisanal businesses successfully operating in complex environments. the reference period of the paper is 2000–2018, which overlaps with the economic stagnation following the european monetary union, the 2008 financial crisis, and the following restructuring of the world economy. the study is divided into three parts. first of all, it provides a critical review of selected literature on the formation of the clothing and fashion industry in vicenza province, of its development, of its strengths and weaknesses. then we reconstruct, through statistical and empirical analysis, the sector’s most recent trends, focusing on firms’ strategies to counteract negative economic conditions. it concludes by explaining how smes can, within certain conditions, find successful strategies in the time of enduring crisis, when the markets are shrinking. literature review the so-called ‘fashion system’ includes businesses producing clothing and accessories. it traditionally represents a core sector of the national economy in italy (paris, 2006; merlo, 2011). even nowadays, though significantly reduced in scope in comparison with the 1990s, it still holds a relevant position in italian industrial production and international trade (paris, 2006; merlo, 2015). http://doi.org/10.15826/recon.2020.6.2.007 76 https://journals.urfu.ru/index.php/r-economy r-economy, 2020, 6(2), 74–88 doi: 10.15826/recon.2020.6.2.007 online issn 2412-0731 researchers explain such results by stressing historical and culturally embedded entrepreneurial skills and by pointing out the ability of italian firms to interpret and mould consumers’ preferences (scarpellini, 2019; belfanti, 2015; merlo, 2012). scholars also highlight italian firms’ capa city to play successfully within global value chains, upgrade their position effectively, use the possibilities offered by collaboration with internatio nal brands and buyers, and promote collaboration at the district level (dunford, 2006; merlo, 2018; bettiol, 2017). the latter aspect emerges especially strong among little enterprises operating within close territorial boundaries, such as the textile districts located in veneto (bettinelli, 2016). studies on veneto’s and vicenza’s ‘fashion system’ focused first of all on its century-long history; on the role of industrial districts and clusters; and on its resilience to market transformation and crisis. the sector experienced a remarkable deve lopment from the late middle ages, when home spinning and weaving where inserted in highly competitive, proto-industrial networks (riello, 2013; caracausi, 2017. from the early 19th century it was deeply industrialized, and major factories, often integrated into company towns in the pre-alpine area, transformed economy, landscape and social life (fontana, 2004; roverato, 2004, leoni, 2017). the process, however, didn’t substitute home-based production. industrial plants and independent spinners and weavers established complementary relations (fontana, 2009; celetti, 2015). similarly, industrial and agricultural work coexisted at family level within pluri-activity frameworks, adding resilience to local societies and competitiveness to major companies (fontana, 2005; celetti, 2015). in that pe riod there emerged features that still characterize the regional economy and landscape, such as the so-called ‘diffused industrialization’, shops and cultivated fields, rural and industrial areas following each other without solution of continuity (ferrario, 2013; belfanti, 2013; celetti, 2019). from the 1960s, the ‘subcontracting revolution’ increased dramatically the number of little factories, large firms externalizing labor intensive production phases to focus on conception, design, marketing, and commercialization (belussi, 1992; ketelhöhn, 1993; favero, 2012). downscaling and reorganization processes induced, as we stressed, the emergence of numerous small subcontractors, which, by the 1980s, contributed to the formation of internationally competitive clusters, where shops specialized in different parts of the production chain, built synergies with those working in related sectors (e.g. machine building) and with larger companies controlling the strategic parts of the value chain and promoting international brands (coro’, 1999; mistri, 2009). there is vast research literature on cluster and industrial districts1 (cainelli, 2008; bettiol, 2019). of particular interest for our research are the studies on the role of the territory as a complex asset for competitiveness (lacquement, 2016) as well as on the latest transformation of indust rial districts in the fast changing and globalizing economy (brioschi, 2002; mariotti, 2020). studies highlight the financial and managerial limits of the ‘small-scale’ factories (whitford, 2001); their resilience to crisis (coro’, 2010; busato, 2011); and the effects of delocalization and offshoring practices on districts and clusters (tattara, 2010; coro’, 2013). for our research particularly interesting are the studies on the reaction capacities of clusters, and, generally speaking, of smes operating in linked sectors. these studies stress the role of territory in enhancing resilience, on the one hand, and in building viable positions within global commodity chains, on the other (coro’, 2007; volpe, 2012; camagni, 2013; buciuni, 2018; barzotto, 2018). in that context, territory assumes a central role as a source of material and immaterial assets, including the exploitation of the brand “made in italy” as a world-wide recognized insurance of upper class design, aesthetic and quality (lees-maffei, 2004; gilmore, 2007; fontana, 2010; balland, 2015; celetti, 2019b). this study draws in particular from these studies and highlights how small handicrafts operating in the sector that is particularly exposed to global competition can reach excellence, namely by creating unique quality and using territorially-based competitive advantages. methodology methodologically, the work unites quantitative analysis of statistical data with qualitative, empirical observations gained from interviews and from field research of production proces ses. the combination of these approaches gives us insights into the strategies that small handicrafts follow for building their success stories in declining and turbulent markets. 1 on differences between the two concepts cfr. porter, 2009; ortega-colomer, 2016. http://doi.org/10.15826/recon.2020.6.2.007 r-economy, 2020, 6(2), 74–88 doi: 10.15826/recon.2020.6.2.007 77 https://journals.urfu.ru/index.php/r-economy online issn 2412-0731 we used statistical data to reconstruct the sector’s trends of textile, clothing, and leather production at the provincial level2. the data have been obtained from istat3, ice4, and unioncamere-infocamere5 official publications. the four case studies we discuss further have been selected by the joint team of padua university and confartigianato vicenza6 among the 529 clothing and fashion firms that are members 2 these activities are classified within istat – ateco (economic activity) classification numbers 13, 14, and 15 (2007), excluding 15.11 (leather and fur preparation). 3 italian statistical institute (www.istat.it). 4 italian institute for foreign trade (www.ice.it). 5 information and statistical service of italian chamber of trade (www.unioncamere.gov.it › infocamere). 6 “confartigianato vicenza” is an association of small and medium handicraft firms operating in vicenza (https://www. confartigianatovicenza.it). of the above-mentioned association on the basis of four parameters: dimension; production’s specialization; location; and competitive success in the global market (tables 1 and 2). the field research has been realized by working with the interviewees and entailed visits to the shops; reconstruction of the business process; acquisition of the ‘grey material’, such as brochures, photographs, newspaper articles; and formal, recorded interviews with companies’ founders, owners, directors, and selected personnel. the interviews were based on questionnaires divided into five parts (the firm’s history and recent development; business models; strengths; critical issues; and prospects) with a focus on the relevance of the firms’ dimension, the value of the ‘made in italy’ brand, and the role of the territory’ in the time of globalization. table 1 case studies main characteristics arca di noe’ (a) vicenza mode (v) la pony confezioni (p) four horses (f) denomination, address, web-site l’arca di noe’ srl – unipersonale via rambolina 31/ b – 36061 bassano del grappa (vicenza -italy) – no web site vicenza mode srl – via delle industrie, 78, 36050 cartigliano (vicenza itally) – https:// www.vicenzamode.com la pony confezioni snc – via della cooperazione, 19 36025 noventa vicentina (vicenza – italy) https://www.lapony.it/ for horses srl – via j.f. kennedy 59 – san vito di leg. (vi – italy) https://forhorses.it/ branch outwear, in particular using technical fabrics and heating tape technologies for brands working in high quality, ready to wear segments (designer/ diffusion) knitwear manufacturing for brands working in high quality, ready to wear segments (designer/ diffusion) production of men’s and women’s trousers production of equestrian outwear and accessories years of activity 34 30 (following the transformation of the preceding family business in the same sector created in 1970) 39 (founded in 1980) 18 (founded in 2002) employees 26 part-time employees (20 hours a week) 60 full-time employees 30 full-time employees 15 production process cutting, tailoring, washing, ironing, testing, and shipping choice of yarn, weaving, cutting, tailoring, washing, ironing, testing, and shipping cutting, tailoring, washing, ironing, testing, and shipping. the firm also offers projecting and testing services cutting, tailoring, washing, ironing, testing, and shipping markets and clients final product for major brands of the international fashion system working in high quality, ready to wear segments (designer/diffusion) final product for major brands of the international fashion system working in high quality, ready to wear segments (designer/diffusion) final product for major brands of the international fashion system working in high quality, ready to wear segments (designer/diffusion) final product sold worldwide under its own brand to buyers, distributors, shops, and private clients (riders), also on-line source: interviews to roberto sartori (arca di noe’ srl), interviewed by david celetti, september 20th, 2018 at the firm’s offices, via rambolina 31/b, bassano del grappa (vicenza, it): riccardo garbosso (vicenza mode srl), interviewed by david celetti, september 20th, 2018 at the firm’s offices, via delle industrie 78, cartigliano (vicenza, it); riccardo barbato (la poni confezioni snc), interviewed by david celetti, september 20th, 2018 at the firm’s offices, via della cooperazione, 19, noventa vicentina (vicenza, it); andrea piovan (for horses srl), interviewed by david celetti, march 14th, 2019 at the firm’s offices, via kennedy 59, san vito di leguzzano (vicenza, it). http://doi.org/10.15826/recon.2020.6.2.007 http://www.istat.it http://www.ice.it https://www.confartigianatovicenza.it https://www.confartigianatovicenza.it 78 https://journals.urfu.ru/index.php/r-economy r-economy, 2020, 6(2), 74–88 doi: 10.15826/recon.2020.6.2.007 online issn 2412-0731 table 2 case studies results (a: arca di noe’ – v: vicenza mode – p: la pony confezioni – f: for horses). origins and development business model strengths critical issues prospects family business directly managed by the owner (a, p, v, f) subcontractor furnishes the final product and operates in all the phases of the production chain (v) or from cutting downwards (a, p). the business process includes projecting and prototyping (a, p, v, f) the firm operates with its own brand, selling directly to distributors or final clients (f) extremely high quality, versatility and flexibility (a, p, v) technical competences for professional riding necessities with attention to style and fashion (f) difficulty in finding highly qualified personnel at all levels (a, p, v, f) building continuously in knowledge, skills, and know-how as instruments for enhancing quality and service (a, p, v, f) the owner is: a. former manager of a big textile company (a) b. son of the founder with technical experience in the sector (p, v). c. a former technician in a chemical company and a former designer of classical dance outwear offer includes counseling services to current or potential clients (a, p, v, f) original production process management – innovative organization model based on remote team work with the clients (v, p) – innovative organization model using part-time to enhance flexibility (a) – coexistence of high technology, technical innovation and handicraft approaches (f) keeping the perceived value of the ‘made in italy’ brand with enhanced protection of the brand (a,p,v, f) process and product innovation, uniting tradition and technology (a,p,v, f) the firms have been constantly moved towards the upper market’s segments and are now positioned in the luxury fashion segment (a, p, v) product specialization on knitwear manufacturing (v), trousers (p), technical outwear (a), equestrian outwear (f) highly qualified personnel in measur to work manually and exploit at the same time the highest technology (a, p, v, f) keeping enough firms working in the territory and building up more effective policies for maintaining ‘the vitality’ of the clothing and fashion industrial district (a, p, v, f) focusing on luxury brands for limiting price competition (a, p, v) enhancing its visibility at world level in the niche market also exploiting it (f) the firms have been operating in the niche segment since the very beginning (f) focus on the highest market levels. clients are international renowned luxury fashion brands (a, p, v) clients are professional and high-level amateur riders served directly or through distributors worldwide, the domestic market remaining marginal (f) upper-class services, including innovation, and problem-solving, which helps to build long-term relations with clients (a,p,v, f) keeping very close long -term relations with fashion luxury brands, which are linked not only to the firm’s performance, but also to the values ‘embedded’ in the territory (a, p, v) communicate effectively the tangible and intangible (cultural) values of the “made in italy” brand and of the regional textile districts (a, p, v, f) strong links with french luxury brands: showroom in paris, and valuable products’ archive (v) strong links to the american market: office in miami (f) the production is totally under the ‘made in veneto’ brand, exploiting the territory as a competitive advantage (a, p, v, f) source: interview with roberto sartori (arca di noe’ srl) conducted by david celetti, september 20th, 2018 at the firm’s office, via rambolina 31/b, bassano del grappa (vicenza, it): interview with riccardo garbosso (vicenza mode srl) conducted by david celetti, september 20th, 2018 at the firm’s office, via delle industrie 78, cartigliano (vicenza, it); interview with riccardo barbato (la poni confezioni snc) conducted by david celetti, september 20th, 2018 at the firm’s office, via della cooperazione, 19, noventa vicentina (vicenza, it); interview with andrea piovan (for horses srl) conducted by david celetti, march 14th, 2019 at the firm’s office, via kennedy 59, san vito di leguzzano (vicenza, it). http://doi.org/10.15826/recon.2020.6.2.007 r-economy, 2020, 6(2), 74–88 doi: 10.15826/recon.2020.6.2.007 79 https://journals.urfu.ru/index.php/r-economy online issn 2412-0731 results vicenza’s ‘fashion system’ (textile, clothing, leather) manifests evident degrees of territorial specialization within one of the most industrialized italian provinces (table 3). this aspect is clearly highlighted both by istat analysis of the sector’s districts7 and by that of bancaintesa (bancaintesa 2018, 126, 205). firms of the fashion sector are mainly concentrated in the south-eastern part of the territory (municipalities of barbarano and noventa) and in the ‘traditional textile centers’ of the medium and northern communes, such as those of thiene, bassano, and marostica. similar results are obtained applying the ‘economic specialization index’ (palan, 2010) to the handicraft shops operating in single municipalities. in 2017, the index showed concentration rates of 0.141–0.300 (7 municipalities) and 0.301–1.000 (2 municipalities), namely in the south-eastern and central areas of vicenza province (figure 1). however, no municipality has rates higher than 1.000, which theoretically correspond to the presence of an industrial district. this configuration is the consequence of both the 1990s transformation, marked by diffused delocalization, and of the crisis of the two last decades, which, in the way similar to the national trends8 (banca intesa, 2018) heavily influenced the territorial economic structure, reducing the number of active handicrafts and therefore lowering the concentration index itself (figure 1). 7 istat 2001. 8o censimento generale dell’industria e dei servizi. distretti indusrtiali e sistemi locali del lavoro. (53–95) (https://www.istat.it/it/files/2011/01/volume_distretti1.pdf ); istat 2011. 9o censimento dell’industria e dei servizi e censimento delle istituzioni non profit. i distretti industriali. (42–50) 8 istat 2011. 9o censimento dell’industria e dei servizi e censimento delle istituzioni non profit. i distretti industriali. (25); istat 2018. rapporto annuale 2018. la situazione del paese (57–72) figure 1. concentration index of textile and clothing handicraft in vicenza (2017 – dark blue 0.301-1; blue 0.141-0.3: light blue less than 0.140; white 0) source: confartigianato vicenza – elaborazione flash 04/03/2020 however, in contiguous territories we still notice the presence of numerous firms operating in different parts of the production chain. proximity represents an important competitive advantage at provincial level. it enhances the sector’s capacity to respond positively to the demand of flexibility, quality, and ‘customization’ of the final buyers, optimizing production processes through inter-company cooperation. it fosters innovation, mutual learning, and knowledge spillover. it increases resilience to any sudden variations of demand. areas with higher concentration indexes, therefore, better react to crisis and faster develop new business approaches (balland, 2015). this aspect appears all the more as a strategic asset if we take into account that the main business model table 3 gross domestic product (mln euro) of vicenza province, veneto region and italy gdp/year 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 vicenza 21 971 23 590 24 018 24 219 25 470 25 113 24 464 25 125 26 157 25 883 26 302 26 603 27 125 veneto 124 288 130 716 133 488 140 576 147 009 145 923 142 364 145 053 149 642 147 215 147 317 149 888 151 791 perc. vicenza gdp vs veneto’s gdp 17,68 18,05 17,99 17,23 17,33 17,21 17,18 17,32 17,48 17,58 17,85 17,75 17,87 italia 1 335 354 1 390 539 1 436 379 1 493 031 1 554 199 1 575 144 1 573 655 1 604 515 1 637 463 1 613 265 1 604 599 1 621 827 1 645 439 perc. veneto gdp vs italy’s gdp 9,31 9,40 9,29 9,42 9,46 9,26 9,05 9,04 9,14 9,13 9,18 9,24 9,22 sources: author’s own calculations by using the data from vicenza chamber of trade (https://www.vi.camcom.it/it/servizi/ statistica-e-studi/tabelle-statistiche-dati-settoriali.html) http://doi.org/10.15826/recon.2020.6.2.007 https://www.istat.it/it/files/2011/01/volume_distretti1.pdf https://www.vi.camcom.it/it/servizi/statistica-e-studi/tabelle-statistiche-dati-settoriali.html https://www.vi.camcom.it/it/servizi/statistica-e-studi/tabelle-statistiche-dati-settoriali.html 80 https://journals.urfu.ru/index.php/r-economy r-economy, 2020, 6(2), 74–88 doi: 10.15826/recon.2020.6.2.007 online issn 2412-0731 of vicenza’s fashion system is ‘contract manufacturer’. the option is one of the consequences of the outsourcing processes of major companies in the 1960s and 1970s. traditionally, artisans produce parts of the final product according to the quality standards set by the client. their focus is therefore on the production process, which only rarely includes projecting and development (design, prototype, collection, etc.). however, in the recent years, the latter is becoming a part of the “upgrading” strategies of successful handicrafts. in any case, proximity and cooperation are essential strategic tools for subcontracting firms (bettiol, 2017; magnani, 2019). as we have seen, the relatively low concentration index also mirrors the sector’s crisis and transformations that diminished the number of active firms. since the late 1980s, when it reached its heights, clothing industry has endured significant changes under the pressure of fierce international competition on the part of developing countries (figure 2). at provincial level, active handicraft firms went from 1,315 in 2009 to 1,113 in 2018, showing a reduction of more than 15 %, which reflects regional (–16,12) and national (–15.42) trends (figures 3 and 4). although it is difficult to make comparisons throughout the whole period due to the modification in the classification of sectors in 2008, figures show that the reduction in the number of firms has been an ongoing tendency since the beginning of the 21st century, suggesting structural rather than conjuncture trends (table 4, figures 5, 6 and 7). similarly, the evolution of handicrafts’ labor levels underwent a negative evolution (figure 8) whereas the number of workers per production unit remained stable (7,29 in 2012 and 7,25 in 2028). this might suggest the limits of increasing productivity through the process of reorganization and/or technologic innovation in the sector where labor remains a central asset. at national level, for example, only 11.9 per cent of fashion firms operating in industrial districts show excellent use of it, whereas the average industry level reaches 16.6 (banca intesa, 2018, 134). 160 140 120 100 80 60 40 20 0 19 90 19 91 19 92 19 93 19 94 19 95 19 96 19 97 19 98 19 99 20 00 20 01 20 02 20 03 20 04 20 05 20 06 20 07 20 08 20 09 20 10 20 11 20 12 20 13 20 14 20 15 figure 2. total production index of italy’s clothing and fashion industry (2004 = 100). source: http://seriestoriche.istat.it/ 900 800 700 600 500 400 300 200 100 0 2000 2001 2002 2003 2004 2005 2006 2007 2008 figure 3. number of active artisan companies in the clothing (red) and textile (blue) sectors sources: the author’s own calculations based on infocamere data (economic sectors db17: textile industries; db18 clothing production including furs – https://www.infocamere.it/statistiche/-/most_viewed_assets/zaats5lj6qvi/ content/cerca-tabelle-movimprese?inheritredirect=false) 800 700 600 500 400 300 200 100 0 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 figure 4. number of active artisan companies in the clothing (red), leather and textile (blue) sectors source: the author’s own calculations based on infocamere data (economic sectors b13: textile industries; b14 clothing production; b 15: leather goods production – https:// www.infocamere.it/statistiche/-/most_viewed_assets/zaats5lj6qvi/content/cerca-tabelle-movimprese?inheritredirect=false) table 4 clothing and fashion firms. vicenza province and italy year 2012 2013 2014 2 015 2016 2017 2018 handicrafts firms (vicenza province) 905 870 839 834 831 814 786 total firms (vicenza province) 1 709 1663 1 634 1 645 1 717 1 617 1 587 handicrafts firms (italy) 48 431 47272 46 290 45 617 44 782 44 004 43 092 total firms (italy) 93 973 91 682 89 926 89 030 87 721 86 403 85 177 source: istat (http://www.coeweb.istat.it/ april 19th 2020), and the author’s calculations http://doi.org/10.15826/recon.2020.6.2.007 http://seriestoriche.istat.it/ https://www.infocamere.it/statistiche/-/most_viewed_assets/zaats5lj6qvi/content/cerca-tabelle-movimp https://www.infocamere.it/statistiche/-/most_viewed_assets/zaats5lj6qvi/content/cerca-tabelle-movimp https://www.infocamere.it/statistiche/-/most_viewed_assets/zaats5lj6qvi/content/cerca-tabelle-movimp https://www.infocamere.it/statistiche/-/most_viewed_assets/zaats5lj6qvi/content/cerca-tabelle-movimprese?inheritredirect=false https://www.infocamere.it/statistiche/-/most_viewed_assets/zaats5lj6qvi/content/cerca-tabelle-movimprese?inheritredirect=false https://www.infocamere.it/statistiche/-/most_viewed_assets/zaats5lj6qvi/content/cerca-tabelle-movimprese?inheritredirect=false https://www.infocamere.it/statistiche/-/most_viewed_assets/zaats5lj6qvi/content/cerca-tabelle-movimprese?inheritredirect=false http://www.coeweb.istat.it/ r-economy, 2020, 6(2), 74–88 doi: 10.15826/recon.2020.6.2.007 81 https://journals.urfu.ru/index.php/r-economy online issn 2412-0731 9 8 7 6 5 4 3 2 1 0 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 figure 7. indexes of natality (green) and mortality (red). province of vicenza. all industrial sectors source: the author’s own calculations based on infocamere data – https://www.infocamere.it/statistiche/-/most_ viewed_assets/zaats5lj6qvi/content/cerca-tabelle-movimprese?inheritredirect=false) 200 0 –200 –400 –600 –800 –1000 –1200 1 2 3 4 5 6 7 8 9 10 figure 8. employees (blue) and variation (red). province of vicenza. fashion system artisanal firms sources: the author’s own calculations based on ufficio studi confartigianato data (elaborazione flash 04.03.2020) 14 12 10 8 6 4 2 0 te xt ile c lo th in g te xt ile c lo th in g te xt ile c lo th in g te xt ile c lo th in g te xt ile c lo th in g te xt ile c lo th in g te xt ile c lo th in g te xt ile c lo th in g 2001 2002 2003 2004 2005 2006 2007 2008 figure 5. indexes of natality (blue) and mortality (red) textile and clothing artisanal firms source: the author’s own calculations on infocamere data (economic sectors db17: textile industries; db18 clothing production including furs – https://www.infocamere.it/statistiche/-/most_viewed_assets/zaats5lj6qvi/content/cerca-tabelle-movimprese?inheritredirect=false) 14 12 10 8 6 4 2 0 te xt ile c lo th in g le at he r te xt ile c lo th in g le at he r te xt ile c lo th in g le at he r te xt ile c lo th in g le at he r te xt ile c lo th in g le at he r te xt ile c lo th in g le at he r te xt ile c lo th in g le at he r te xt ile c lo th in g le at he r te xt ile c lo th in g le at he r te xt ile c lo th in g le at he r 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 figure 6. indexes of natality (blue) and mortality (red). province of vicenza. fashion system artisanal firms source: the author’s own calculations on infocamere data (economic sectors b13: textile industries; b14 clothing production; b 15: leather goods production – https://www.infocamere.it/statistiche/-/most_viewed_assets/zaats5lj6qvi/content/cerca-tabelle-movimprese?inheritredirect=false) vicenza’s ‘fashion system’ shows a strong orientation to the foreign markets, exports having a relevant share of turnover (tables 5, 6 and 7)9. the most important clients are european, in particular germany, france and the uk. asia, however, is growing much faster as a result of rampant chinese and, to a lesser extent, indian demand. 9 rapporto ice 2017/2018. l’italia nell’economia interna zionale. roma: marchesi grafiche editoriali (22-24, 38, 45-54). the last two countries, though still considered ‘emerging’, nevertheless, increasingly generate demand for high quality, luxury fashion products. the importance of western countries, in particular france, is also linked to the focus of italian fashion industry on upper class production largely controlled by french luxury brands. conversely, it highlights the diminishing numbers of firms working in medium and low segments, exposed http://doi.org/10.15826/recon.2020.6.2.007 https://www.infocamere.it/statistiche/-/most_viewed_assets/zaats5lj6qvi/content/cerca-tabelle-movimprese?inheritredirect=false https://www.infocamere.it/statistiche/-/most_viewed_assets/zaats5lj6qvi/content/cerca-tabelle-movimprese?inheritredirect=false https://www.infocamere.it/statistiche/-/most_viewed_assets/zaats5lj6qvi/content/cerca-tabelle-movimprese?inheritredirect=false https://www.infocamere.it/statistiche/-/most_viewed_assets/zaats5lj6qvi/content/cerca-tabelle-movimprese?inheritredirect=false https://www.infocamere.it/statistiche/-/most_viewed_assets/zaats5lj6qvi/content/cerca-tabelle-movimprese?inheritredirect=false https://www.infocamere.it/statistiche/-/most_viewed_assets/zaats5lj6qvi/content/cerca-tabelle-movimprese?inheritredirect=false https://www.infocamere.it/statistiche/-/most_viewed_assets/zaats5lj6qvi/content/cerca-tabelle-movimprese?inheritredirect=false 82 https://journals.urfu.ru/index.php/r-economy r-economy, 2020, 6(2), 74–88 doi: 10.15826/recon.2020.6.2.007 online issn 2412-0731 to price competition of emerging countries. the latter suggests that upgrading towards higher segments represents the best possible option for staying in the market (table 5 and 7). table 5 fashion system (including leather). share in the international trade of the province of vicenza imports imports (% on total imports) 2013 2014 2015 2013 2014 2015 1 886 552 2 030 996 2 143 061 22,3% 22,9% 24,0% exports exports (% on total imports) 2013 2014 2015 2013 2014 2015 3 857 124 4 102 129 4 358 586 24,7% 25,3% 25,5% sources: author’s elaboration on data from vicenza chamber of trade (https://www.vi.camcom.it/it/servizi/statistica-e-studi/tabelle-statistiche-dati-settoriali.html) empirical research on case studies confirms the evidence shown by statistical analysis, adding, however, insights into how handicraft reached top positions through innovative interpretation of their business models10. 10 empirical analysis in mainly based on the interview of roberto sartori (arca di noe’ srl) conducted by david celetti, september 20th, 2018 at the firm’s office, via rambolina 31/b, bassano del grappa (vicenza, it); the interview of riccardo garbosso (vicenza mode srl) conducted by david celetti, september 20th, 2018 at the firm’s office, via delle industrie 78, cartigliano (vicenza, it); the interview of riccardo barbato (la poni confezioni snc) conducted by david celetti, september 20th, 2018 at the firm’s office, via della cooperazione, 19, noventa vicentina (vicenza, it); interview with andrea piovan (for horses srl) conducted by david celetti, march 14th, 2019 at the firm’s office, via kennedy 59, san vito di leguzzano (vicenza, it). the analysis also uses the data from the websites: https://www.vicenzamode.com/; https://www.lapony.it/; https://forhorses.it/. table 6 italian exports year 2019 2020 var. % product tons (1000) euro (1,000,000) tons (1000) euro (1,000,000) difference (%) difference (%) pharmaceutical 2 376 26 2 429 25 2,2 –5,1 automotive 1 400 121 1 463 114 4,5 –6,4 oil products 866 1 944 1 081 2 403 24,9 23,6 components and accessories for autonotive 1 071 156 1 060 143 –1,1 –7,9 shoes 896 17 906 16 1,2 –4,5 cloths and accessories 820 20 853 22 4,0 12,6 clothing accessories 781 5 821 5 5,1 7,2 ship’s and aircraft’s stores and supplies, returned national goods, miscellaneous goods 702 332 711 273 1,3 –17,8 precious metals including semi-finished goods 388 .. 705 .. 81,5 40,1 industrial machines 696 32 695 29 –0,1 –9,2 others 25 742 8 980 25 829 8 694 0,3 -3,2 total 35 738 11 632 36 553 2,3 0,8 export’s composition pharmaceutical 6,6 0,2 6,6 0,2 automotive 3,9 1,0 4,0 1,0 oil products 2,4 16,7 3,0 20,5 components and accessories for automotive 3,0 1,3 2,9 1,2 shoes 2,5 0,1 2,5 0,1 cloths and accessories 2,3 0,2 2,3 0,2 clothing accessories 2,2 .. 2,2 .. ship’s and aircraft’s stores and supplies, returned national goods, miscellaneous goods 2,0 2,9 1,9 2,3 precious metals including semi-finished goods 1,1 .. 1,9 .. industrial machines 1,9 0,3 1,9 0,2 others 72,0 77,2 70,7 74,2 total 100,0 100,0 100,0 100,0 source: istat ( http://www.coeweb.istat.it/ april 19th 2020), and the author’s own calculations http://doi.org/10.15826/recon.2020.6.2.007 https://www.vi.camcom.it/it/servizi/statistica-e-studi/tabelle-statistiche-dati-settoriali.html https://www.vi.camcom.it/it/servizi/statistica-e-studi/tabelle-statistiche-dati-settoriali.html https://www.vicenzamode.com/ https://www.lapony.it/ https://forhorses.it/ http://www.coeweb.istat.it/ r-economy, 2020, 6(2), 74–88 doi: 10.15826/recon.2020.6.2.007 83 https://journals.urfu.ru/index.php/r-economy online issn 2412-0731 the four selected case studies (tables 1 and 2) are family businesses with 15 years of history. two of them (vicenza mode – vand la pony – p) have already successfully experienced generational transition, whereas four horses (f) and arca di noe’ (a) are still managed by founders and do not foresee, at the moment, any transfer of competences and duties to younger entrepreneurs. the origins of the business are strictly linked to technical competences and formal personal experiences in major fashion companies or in related sectors in three cases (a, p, f). only the founder of v had no direct experience in the sector and started his business on the simple assumption that the booming demand of the early 1970s would create opportunities for new entrants. the ‘second generation’, which is currently at the head of v and p, obtained higher education and practical hands-on experience before joining the business. this shows the relevance of personal experience and skills, which might be managerial as in the case of a and p, or linked to specific knowledge of product characteristics, as in the case of f (table 2). we also found that in the time of expansion, the simple feeling of market might play a positive role in entrepreneurial decision-making. moreover, in all the cases, family emerges as a relevant actor, bringing competences and work, but also supporting effective decision-making. this last aspect confirms another central characteristic of vicenza’s – and veneto’s – industrial system, which can still be considered ‘family based’ and ‘family led’. each story highlights typical stages of deve lopment of vicenza’s fashion clusters. v found its origins in the demand boom of the 1970s in veneto’s knitwear production, largely pulled by the success of the brands like benetton, stefanel, and their subcontracting strategies. p was founded as a spill-over of marzotto, when valdagno-based company started outsourcing labor intensive production phases. a was also created through company restructuration. what in fact happened is that in the late 1980s, a manager and a group of workers from a struggling major firm, which had to lay off, personnel decided to start their own business. both of these stories represent, though each in its own way, a successful reaction to market transformations. f tells the story of its own. the business started in the early 2000s, when vicenza’s fashion system already suffered a structural crisis. the firm was established as a result of its founder’s passion for professional riding and his need for technical outwear. from the very beginning, the firm focused on the specific market niche where it managed to combine the technical requirements for professional riders, exclusive textiles, aesthetics, and functionality. the uniqueness of f’s product, and the specificity of the market allowed the firm to create a new brand serving distributors (buyers and retailers) but also delivering directly to professional riders. a, v and p entered the markets as contractors of major brands and still hold this position. v develops the whole production chain from yarn selection to ironing, testing, and shipping; a and p receive the cloths from their clients, whereas f buys it directly. having very specific requirements, f works together with producers of fabric, mainly located in the nearby territory, to conduct research and testing. all firms deliver the final product, ready to be used by the consumer. this last aspect is considered extremely relevant, because it means that these firms avoid ‘hyper-specialization’ (e.g. performing only one task as is the case with benetton’s contracts) and they can acquire competences and know-how, which, in turn, represents the basis for their further progress and consolidation in upper market niches. quality, specialization on specific textiles, work procedures, outwear as well as the capacity to provide table 7 exports (1.000 euro) of clothing and textile handicrafts and clothing and textile industry. province of vicenza (2011–17) sector/year 2011 2012 variation 2011–12 (perc.) 2016 2017 variation 2016–17 (perc.) variation 2011–17 (perc.) clothing (including fur and leather) 1 078,00 1 165,00 9,10 1 239,60 1 227,30 -1,00 13,85 textiles 464,00 435,00 -6,30 528,50 541,90 2,50 16,79 total handicrafts 6 627,00 7 014,00 5,80 7 807,60 8 134,50 4,20 22,75 total manufactures 14 341,00 14 807,00 3,20 16 604,20 17 536,40 5,60 22,28 source: the author’s own calculations by using the data from confartigianato vicenza elaborazione flash 2011–2019 http://doi.org/10.15826/recon.2020.6.2.007 84 https://journals.urfu.ru/index.php/r-economy r-economy, 2020, 6(2), 74–88 doi: 10.15826/recon.2020.6.2.007 online issn 2412-0731 additional services, such as technical counseling, are also a way to attract buyers internationally and to expand potential markets. all firms have built over time their own unique competences, which enable them to enrich the product with particular services. clients value the company’s providing counseling on fibers’ technical and aesthetical characteristics, co-projecting new fabrics, and delivering final products. these activities, on the other hand, are not viewed as a ‘generating income directly’, but as an asset for ensuring customer loyalty; promoting higher results through team work at the early stages of projecting and prototyping; for acquiring new competences; testing new production methods; and for ensuring constant ‘upgrading’ along the value chain (a, v, p). similarly, f co-generates outwear and accessories in cooperation with professional riders, who actively test them and suggest changes, and with cloth produ cers, who do not simply receive specific technical and aesthetic requirements from f, but participate in developing them. all the firms consider collaboration as an essential competitive advantage. territory plays in this sense a relevant role as it enhances collaboration potential through perso nal networks and attracts international buyers. currently all the selected firms are solidly positioned in the highest market segments delivering to world best brands or selling, as f, through its own brand to high class clients. though all firms are extremely open to international markets, they also have some specific orientations. v, for example, is oriented towards french luxury brands. it opened its own showroom in central paris to attract firstclass clients as well as to comply to what is seen as a ‘must’ in the luxury fashion world. the reasons why the firm decided to go for the ‘french option’ are explained by the world fame of parisian brands and by the stability in business relationships, financial reliability, cooperative approaches, and price policy of french multinationals. in this segment, quality matters more than price in building business relations. a and p have no offices abroad, but they are also tightly linked to french high-class luxury brands, an option that is justified by highlighting the same advantages as mentioned by v. f, on the other hand, is more concerned with the american market and has opened an office in miami to serve local riders and distributors. all the firms, generally speaking, try to choose their clients, rather than to be chosen by them and to develop cooperation all along the value chain. the selected firms see the near future as a time of complexity, but also of renewed potentialities. mastering complexity is considered the most serious challenge. complexity is interpreted by interviewees as a trend in contemporary and future markets – products are becoming increasingly personalized and they have a shorter life in the context of stricter quality rules and global competition. managing complexity requires constant mastering of new techniques, technological innovation, acquisition of skills and know-how, effective organization. technology and human capital emerge, therefore, as two pillars for serving successfully the market. it, for instance, is seen as a strategic tool for developing cooperation both with clients and suppliers, shortening distances, limiting transaction costs, ensuring partnerships rather that competition. production technologies help to enhance quality and flexibility (forza, 1997). labor, however, is still viewed as a central competitive factor, and special attention is given to selection, training, and management of the workforce. for example, a introduced for all its employees 20-hour part-time shifts, which brought some positive results. quality and productivity increased and at the same time stress and fatigue diminished. the firm also experienced remarkable gains in flexibility as it can now rapidly reset to regular time in case of higher demand. the workers’ loyalty was improved as it would be difficult for them to find similar conditions in other firms. major costs, determined by the increased number of workers and machines, have been partially absorbed by reduced profits and increased productivity. finally, all companies confirmed the positive role of the territory in their success in the global market. although these firms are not officially based in recognized fashion districts, they are nevertheless located in areas hosting a relevant number of little shops working in the fashion system. interviewees consider that this represents a very important competitive advantage as it adds flexibility, quality, and specialization through inter-firm cooperation; creates social networks allowing circulation of ideas, and therefore innovation; attracts major brands that can find diverse specialization within a limited space in the same production chain. the diminishing number of firms operating in the fashion sector is perceived as a major critical issue since it could jeopardize the ‘territorial competitive advantage’. another relevant challenge for the nearby future is to keep enough firms active on http://doi.org/10.15826/recon.2020.6.2.007 r-economy, 2020, 6(2), 74–88 doi: 10.15826/recon.2020.6.2.007 85 https://journals.urfu.ru/index.php/r-economy online issn 2412-0731 references balland, p.a. 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(2001). the decline of a model? challenge and response in the italian industrial districts. economy and society, 30, 38–65. information about the author david celetti – phd in economic history, research professor, professor of local development, chair of economic history, at the department of historical, geographical sciences and of the antiquity of the university of padua (via 8 febbraio 1848, 2, 35122 padova, italy); e-mail: david.celetti@unipd.it article info: received march 9, 2020; accepted may 5, 2020 информация об авторе челетти давид – phd в экономической истории, профессор-исследователь, профессор департамента исторических, географических наук и древности падуанского университета (35122, ул. 8 февраля 1848, 2, падуя, италия); e-mail: david.celetti@unipd.it информация о статье: дата поступления 9 марта 2020 г.; дата принятия к печати 5 мая 2020 г. http://doi.org/10.15826/recon.2020.6.2.007 http://doi.org/10.4067/s0718-27242016000200014 http://doi.org/10.1111/j.1467-8616.1992.tb00036.x http://doi.org/10.1111/j.1467-8616.1992.tb00036.x http://doi.org/10.1080/00343401003596299