Human and demographic capital in peripheral and core municipalities and regions and its development (northwest Bohemia) 57Veselý, V. and Kubeš, J. Hungarian Geographical Bulletin 74 (2025) (1) 57–70.DOI: 10.15201/hungeobull.74.1.4 Hungarian Geographical Bulletin 74 2025 (1) 57–70. Introduction The Karlovy Vary Region is located in the very west of Czechia, on the borders with the developed Bavaria and with Saxony in Germany. It has a peripheral location within Bohemia and Czechia and is part of one of the inner peripheries of Central Europe. The region has great internal socio-geographic heterogeneity due to physical-geographical conditions and specific and problematic po- litical, ethnic, economic and social develop- ments (Hampl, M. 2003; Lipovská, Z. et al. 2012). These characteristics of the region are then reflected in its current level of develop- ment and in the demographic and human capital of its municipalities and the region as a whole (also Wielechowski, M. et al. 2021). For these reasons, it is important to recog- nize, understand and positively direct its demographic and human capital. The aim of the paper is to identify and ex- plain differences in human capital (in peo- ple’s abilities, skills and activity) and in de- mographic capital (in demographic stability and development of population structure) in peripheral, semi-peripheral, suburban and central municipalities (meso- and micro- 1 University of West Bohemia, Faculty of Economics, Department of Geography, Univerzitní 2732/8, 301 00 Plzeň, Czechia, E-mail: vesely.vlastimil@email.cz 2 University of South Bohemia in České Budějovice, Department of Geography, Branišovská 1645/31A, 370 05 České Budějovice 2, Czechia, E-mail: kubes@pf.jcu.cz, ORCID: 0000-0001-7929-4539 Human and demographic capital in peripheral and core municipalities and regions and its development (northwest Bohemia) Vlastimil VESELÝ1 and Jan KUBEŠ2 Abstract The paper compares the human and demographic capital of central, suburban, semi-peripheral and periph- eral municipalities of the Karlovy Vary Region and also the regions of Czechia and neighbouring regions in Germany. Peripheral municipalities are considerably distant from meso- and micro-regional towns in terms of time spent on public transport. The demographic capital of municipalities is assessed according to indicators of population development, natural and migration balance, and age structure. In the evaluation of human capital, indicators of education, unemployment, foreclosures, entrepreneurship, and housing construction are used. The assumption of low human capital in peripheral municipalities compared to more geographically exposed municipalities was not confirmed. Suburban municipalities have the highest human and demographic capital. Although the studied region borders the developed regions of Germany, it has the least favourable values of human and demographic capital of all Czech regions and neighbouring German regions. This is a consequence of the complete population exchanges after World War II, the existence of the Iron Curtain on the region’s borders with the West during the socialist (communist) period, the peripheral location of the region within Czechia, the inappropriate development of industry under socialism, and the problems of this sector and weak cross-border cooperation in the post-socialist period. The paper also presents strategies and measures to support human capital in the types of municipalities of the region and throughout the region. Keywords: Human capital, regional development, settlement centres, periphery, semi-periphery, small towns Received December 2024, accepted February 2025. https://www.google.com/maps/place/data=!4m2!3m1!1s0x4773502fb6a8966b:0x8fa803906de72611?sa=X&ved=1t:8290&ictx=111 https://www.google.com/maps/place/data=!4m2!3m1!1s0x4773502fb6a8966b:0x8fa803906de72611?sa=X&ved=1t:8290&ictx=111 mailto:kubes@pf.jcu.czO Veselý, V. and Kubeš, J. Hungarian Geographical Bulletin 74 (2025) (1) 57–70.58 regional towns) of the Karlovy Vary Region, sub-regions of this region, and also between this region and other Czech and neighbour- ing German regions. It also includes the proposal of strategies and measures for the further development of human capital in the region and its municipalities. As for the research questions, the first is auxiliary – it asks about the distribution of higher and lower settlement centres, subur- ban zones, semi-peripheries and peripher- ies of the region, the second is the main one and is aimed at identifying and comparing human and demographic capital of types of municipalities and sub-regions on the terri- tory of the region, and the third is focused on comparing the region with other Czech regions and neighbouring German regions. The introduction of the paper is followed by a theoretical part defining the issue of hu- man and demographic capital and their de- velopment effect and also the issue of periph- erality. The next part of the paper presents the specifics of the Karlovy Vary Region. In the methodological part of the paper, the procedure for defining settlement centres and other types of municipalities is given, and the human and demographic capital in- dicators used are defined here. A compari- son of the human and demographic capital of the monitored types of municipalities, sub- regions and regions is made in the results part of the paper. This is followed by a Discussion with proposals for strategies and measures for the development of human capital in the region and a Conclusion. Theoretical background American economist Gerry Becker defined human capital as the sum of people’s abili- ties and skills and the application of those abilities and skills, and also pointed out the importance of education and health in hu- man capital (Becker, G. 1964). The concept of human capital was then often used by so- ciologists (e.g. Coleman, J.S. 1988) and also human geographers in studies devoted to the new economic geography, regional dispari- ties and regional development (Krugman, P.R. 1991; Elhorst, J.P. 1998, and others). Some developmental elements of social capi- tal were also included in human capital (Sv- endsen, G. and Sørensen, J.F. 2006; Weaver, R.D. and Habibov, N. 2012). In developed countries, developed or stable demographic capital (Sagan, I. and Masik, G. 2014; Wiec- zerzak, J. 2018) can be considered such a natural and migratory balance of the popu- lation that leads to long-term stability in the number of the population and the balance of its structure. The question is whether to consider demographic capital as part of hu- man capital or as a separate issue. Investments and other supports in youth and adult education contribute to economic growth (Mincer, J. 1984; Blundell, R. et al. 1999 and many recent studies). Growth in education benefits the entire country, its re- gions and their communities (Agarwal, S. et al. 2009; Weaver, R.D. and Habibov, N. 2012, and others). Also, in the business and employer sphere, the state and development of working knowledge, abilities and skills is important (Bontis, N. and Serenko, A. 2007; Ployhart, R.E. et al. 2014). In countries, re- gions and municipalities of developed coun- tries with low birth rates, high emigration and a high proportion of elderly people, strategies and measures to gradually im- prove these unfavourable demographic char- acteristics must be sought (Sleebos, J. 2003; Adsera, A. 2004; Lutz, W. 2006). The literature lacks a unified view of “periphery” in the territory. According to some authors, it is the socio-economically un- derdeveloped part of the region (Leimgruber, W. 2004), according to others, it is a part of the area quite distant from the city or town (this paper), or it may be a combination of both views (Agarwal, S. et al. 2009; Bernard, J. and Šimon, M. 2017). In the peripheries, weak human capital is usually assumed (Musil, J. and Müller, J. 2008; Novotná, M. et al. 2013). However, some peripheral mu- nicipalities far from larger towns can benefit from their location near a border crossing, 59Veselý, V. and Kubeš, J. Hungarian Geographical Bulletin 74 (2025) (1) 57–70. near an important road, in an area with sig- nificant tourism or high cultural capital and identity (Kubeš, J. and Podlešáková, N. 2021; PRKK, 2021). In this paper, human capital will be evaluated on the continuum: micro- regional towns – suburban – semi-peripheral – (remote) peripheral municipalities. The Karlovy Vary Region The Karlovy Vary Region is one of the 14 territorial-administrative regions of Czechia. It is located in the westernmost Bohemia, on the border with Bavaria (Upper Franconia and Upper Palatinate regions) and Saxony (Chemnitz region) in Germany. The region has a peripheral location within Bohemia and Czechia and is part of one of the inner peripheries of Central Europe. The border area with Saxony is mountainous with nar- row valleys, in the central part there is an elongated west–east basin with the Ohře river flowing through it, and in the southern and south-eastern parts there are highlands. The region has a population of just under 300,000 (in 1930 it was 500,000). The regional (meso-regional) centre is the city of Karlovy Vary, with only 50,000 inhabitants, larger towns are Sokolov (centre of the brown coal area) and Cheb. There are a total of 134 mu- nicipalities of various population sizes in the region. In this paper, municipalities are di- vided into meso- and micro-regional towns (10), (very) small towns (11), townships (11) and functionally less significant municipali- ties (see the methodological and results part of the paper). In the 19th century, world-famous spa towns developed near mineral springs, es- pecially Karlovy Vary and Mariánské Lázně. During the industrial revolution, brown coal mining and related industries developed in the heart of the region. Based on coal min- ing and related industries, smaller towns and townships were established here, sup- plemented by panel housing estates dur- ing the socialist period. The southern and south-eastern parts of the region had and still have a rural character. The almost complete removal of the German-speaking popula- tion from the region after World War II and the insufficient settlement of the region by Czech people is still evident today. During the socialist period, an impenetrable Iron Curtain existed on the border with Bavaria. Post-socialist public administration repre- sentatives are trying to restore cross-border relations with neighbouring German regions, but so far not very successfully (Teufel, N. et al. 2022). The region’s post-socialist econo- my is suffering from the end of coal mining and the problems of the local textile, glass and porcelain industries. Research methodology When delimiting the peripheries, it is first necessary to define the higher settlement cen- tres. According to Hampl, M. and Marada, M. (2015), the 50,000-person city of Karlovy Vary is a meso-regional city, albeit a very weak one. Micro-regional towns are one hi- erarchical level lower. In their micro-region, they have a relatively closed daily commute to work and services. In the environment of Czechia, a micro-regional town should have a gymnasium or another high school for pu- pils aged 15–18, at least 10 specialist doctors, a food supermarket, 2000 occupied jobs, 1000 commuters for work and study (verified on the territory of the Pilsen Region – Kubeš, J. and Podlešáková, N. 2021) and at least 5,000 inhabitants (Hampl, M. and Marada, M. 2015). The ranking of micro-regional towns (and also lower settlement centres) was created using four indicators – number of inhabitants, number of types of services (the presence of thirty administrative, school, health, purchasing, financial and cultural ser- vices), number of people commuting to work or study, and the number of bus and train connections arriving on a working day. The numerical data are then converted to point values, where the data for the city of Kar- lovy Vary represent 100 points. The last two interrelated indicators have half the weight, Veselý, V. and Kubeš, J. Hungarian Geographical Bulletin 74 (2025) (1) 57–70.60 as they are interconnected. Lower settlement centres are (very) small towns and townships with low point values. In the second step, peripheral municipali- ties need to be defined. In this paper they are delineated in the territory behind the 30-minute isochrone when travelling by bus or train to the time-nearest meso- or micro- regional town in working days. If the journey to the stop and the journey from the stop to work are added to the half hour and the re- turn journey is also included, then this com- mute is at the limit of long-term endurance. If clusters of neighbouring peripheral mu- nicipalities have at least three municipalities and an area of more than 50 km2, they form a peripheral area at the micro-regional level. Two types of these peripheral areas can be distinguished – state-border (outer) and be- tween Czech meso-regions (inner). Suburban municipalities are characterized by a large presence of houses of a suburban character, they are located in the immediate hinterland of larger towns. Semi-peripheral municipali- ties lie between peripheral and suburban municipalities. In addition to the above, the territory of the Karlovy Vary Region was di- vided into 9 sub-regions. In the third step, 6 demographic-capital and 6 human-capital indicators for the level of municipalities are used (Table 1). Municipalities should not have a popula- tion decline, they should have a zero or positive natural and migratory population balance, a sufficient proportion of children and a not too high proportion of elderly people*.3Residents of municipalities should be educated and active in business, should build (finance) new housing and should not be in debt and unemployed. Indicator val- ues in the first quartile of descending values are considered favourable, values in the last quartile as unfavourable. At the level of regions of Czechia, indicator of life expectancy, gross monthly wages and employment in science and research were add- ed to the above indicators (LEM, MSC and SAR * In Czechia, these parameters may not be favour- ably evaluated in municipalities with large socially excluded localities. Table 1. Used indicators of demographic and human capital Code Indicators Indicators of demographic capital LD SD NT MT CH SE LEM Index of long-term population development 2022/19911,2,3 Index of short-term population development 2022/20181,2,3 Average annual natural balance of population per 1000 inhabitants 2017–20211,2,4 Average annual migration balance of population per 1000 inhabitants 2017–20211,2,4 Percentage of children under 14 in 20221,2 Percentage of seniors aged 65+ in 20221,2 Life expectancy at birth in years in 20222,3 Indicators of human capital EE UE NA NE EX UN MSC SAR GDP UEX HTS Percentage of the population over 15 years of age with at most elementary education in 20211,2,5 Percentage of inhabitants older than 15 years with tertiary education in 20211,2 Number of new apartments 2018–2022 per 1000 inhabitants in 20221,2 Number of business entities per 1000 inhabitants aged 15 and over in 20221,2 Percentage of inhabitants in foreclosure in 20221,2 Percentage of unemployed inhabitants older than 15 years in 20221,2 Average gross monthly salary in thousands of CZK in 20222 Number of people working in science and research per 1000 economically active people in 20222 GDP in purchasing power standard (in thousands of EUR) in 20232,3 Percentage of inhabitants aged 25–64 years with tertiary education in 20223 Percentage of employment in high-technology sectors in 20223 1Indicator used for comparison types of municipalities of Karlovy Vary Region. 2Indicator used for comparison of Czech regions. 3Indicator used for comparison of neighbouring German and Czech regions. 4The year 2022 was affected by arrival of Ukrainian refugees. 5It includes primary and lower secondary education. 61Veselý, V. and Kubeš, J. Hungarian Geographical Bulletin 74 (2025) (1) 57–70. in Table 1). The comparison of the Karlovy Vary Region with neighbouring German and Czech regions is limited due to the unavailability and incomparability of some data. It includes these indicators – LD, SD, LEM, GDP (GDP in pur- chasing power standard), UEX (percentage of inhabitants aged 25–64 years with tertiary edu- cation) and HTS (percentage of employment in high-technology sectors) (see Table 1). Data and indicators for assessing the de- mographic and human capital should be contextual (associated with these capitals), complete (covering all components of these capitals), representative (indicators should be constructed to produce values close to re- ality), and correct (also actual) – see Chytil, M. K. (1982). Ensuring “completeness” at the municipal level is difficult due to the unavail- ability of some data at this level. Creating a summary indicator that would include the values of individual indicators is not appro- priate, because both the demographic and hu- man capital of a municipality or region are complex and multidimensional concepts, the individual dimensions of which need to be ex- pressed by separate indicators (Hendrick, R. M. 2004). Therefore, a separate assessment of demographic and human capital and their in- dividual aspects was carried out in the paper. Results The meso-regional city, micro-regional towns, (very) small towns and townships of the Kar- lovy Vary Region are shown in Figure 1 and Table 2. The map also shows suburban, semi- peripheral and peripheral municipalities. Pe- ripheral municipalities create two state-bor- der peripheral areas (“a” and “b”) and two larger peripheral areas between meso-regions (“α” and “β” in Figure 1). The peripheral ar- eas α and β extend beyond the borders of the region into neighbouring Czech regions and, thus, co-create an extensive inner rural periphery in the west of Czechia (Kubeš, J. and Podlešáková, N. 2021). Table 3 shows the situation with demo- graphic and human capital in higher and lower settlement centres, other types of mu- nicipalities and in nine sub-regions of the Karlovy Vary Region. Meso-, micro- and small towns are losing residents mainly due to low birth rates and migration to the sub- urbs of the region and to other regions of Czechia (see LD, SD, NT, MT). Of the sub- regions, those adjacent to advanced Bavaria had a more favourable population develop- ment. They have important border cross- ings and roads that help with commuting to work to Bavaria. The urbanized sub-regions of Sokolov and Kraslice, heavily affected by deindustrialization, had a greater relative de- crease in population than rural peripheries α and β. The balance of migration (MT) over the past few years indicates a strong subur- ban migration and documents the decline of the population in towns. The high migration loss of the Ostrov nad Ohří sub-region can be attributed to the loss of the population of mountain settlements of this sub-region. The city of Karlovy Vary has the oldest pop- ulation (CH, SE), even among all cities in Czechia. So far, the suburban municipalities have a young population, because mainly young families with children moved there from the relevant town and other towns. In the next part of Table 3, the human capi- tal of types of municipalities and sub-regions is compared. The values of the education lev- el indicators (EE, UE) are particularly favour- able for the meso-regional city of Karlovy Vary, where university-educated medical doctors (including spa doctors), various man- agers, teachers and key public administration employees are concentrated. However, the city has the second lowest value of university education among cities in Czechia (after the industrial city of Ústí nad Labem) (see also Minařík, B. and Borůvková, J. 2014). Due to the arrival of young educated suburbanites, some of the suburban municipalities in the vicinity of the city of Karlovy Vary achieve a higher level of education than the city. The construction of apartments (NA) stands out in suburban municipalities (mainly apart- ments in family houses) and in some moun- tain municipalities with the construction https://www.sciencedirect.com/science/article/pii/S0743016719314032?via%3Dihub#bib11 https://www.sciencedirect.com/science/article/pii/S0743016719314032?via%3Dihub#bib11 Veselý, V. and Kubeš, J. Hungarian Geographical Bulletin 74 (2025) (1) 57–70.62 Fig. 1. Settlement centres, peripheral areas and sub-regions of the Karlovy Vary Region, 2022. Source: Authors’ own processing based on the procedure in the research methodology (GIS by Křenek, P.). Table 2. Definition of higher settlement centres of the Karlovy Vary Region, 2022 Settlement centres Population in 2023* persons Number of types of services, 2023 Number of commuters, 2021* Number of bus and train connections, 2023** Weighted average score Strength of higher settlement centre Type: meso-regional city Karlovy Vary 52,081 55 15 055 362 100.00 very strong Type: micro-regional town Cheb Sokolov Ostrov nad Ohří Mariánské Lázně Chodov Aš Františkovy Lázně Nejdek Kraslice 31,954 26,211 15,894 16,591 13,157 12,804 5,707 7,772 6,614 41 37 29 30 15 24 11 15 16 5432 8078 3622 3522 1996 792 1315 1494 694 249 234 177 133 198 55 230 69 68 62.78 58.92 39.91 38.82 28.84 26.15 22.36 18.90 17.83 strong strong medium strong medium strong weak weak very weak very weak very weak Sources: *Databases of the Czech Statistical Office, **IDOS timetables. " ! # ! ! " ! ! # ! " " # % " # ! # ! ! " " # # " ! # ! " # # # β α b b a Germany (Saxony) Germany (Bavaria) Aš Luby Cheb Teplá Loket Toužim Skalná Rotava OstrovNejdek Chodov Hazlov Citice Bochov Žlutice Sokolov Pernink Lomnice Březová Kraslice Jáchymov Habartov Nová Role Hroznětín Nové Sedlo Karlovy Vary Horní Slavkov Lázně Kynžvart Mariánské Lázně Bečov nad Teplou Kynšperk nad OhříFrantiškovy Lázně 0 10 km Hradiště military training area Types of settlement centres % Meso-regional city " Micro-regional towns # ( ery) small townsV ! Townships Types of peripheral areas BoundariesRemoteness types of municipalities Micro-regional towns and meso-regional city Suburban municipalities Semi-peripheral municipalities Peripheral municipalities State Regional Subregional Military training area a, b - state border (outer) α β, - between meso - regions (inner) 63Veselý, V. and Kubeš, J. Hungarian Geographical Bulletin 74 (2025) (1) 57–70. of apartments intended for recreation. The incidence of business entities (SV) is high in Karlovy Vary (economic centre of the region, busi- ness in the care of spa guests), Mariánské Lázně (care for spa guests) and in suburban mu- nicipalities (immigration of entrepreneurs from towns). The assumption of the high- est incidence of foreclosures (EX) in the predominantly working-class settlements of the Sokolov sub-region was not confirmed. The most fore- closures are in the state-border Aš and Kraslice sub-regions. Unemployment (UN) is low and not very different, it is higher only in the deindustri- alized Kraslice sub-region. In the last column of Table 3, an attempt is made to pro- vide an overall assessment of demographic and human capital. The meso-regional city of Karlovy Vary has no good values of demographic capi- tal, but it has predominantly favourable human capital. The collapse of a number of in- dustrial enterprises in micro- regional and small towns has an adverse impact on the hu- man and demographic capital in these towns, also suburban- ization negatively affects the demographic capital of these towns. Suburban municipali- ties enriched by younger, edu- cated and well-earning people have favourable demographic and human capital values. Individual semi-peripheral and peripheral municipalities are different in terms of the values of the monitored indica- tors. If they have quality lead- Ta bl e 3 . H um an a nd d em og ra ph ic ca pi ta l i n ty pe s o f m un ic ip al iti es a nd su b- re gi on s o f t he K ar lo vy V ar y Re gi on , 2 02 2 Ty pe s of m un ic ip al iti es Su b- re gi on s Va lu es o f d em og ra ph ic c ap ita l i nd ic at or s Va lu es o f h um an c ap ita l i nd ic at or s Fo ur th /fi rs t qu ar til es 1 LD SD N T M G C H SE EE 2 U E2 N A N E EX U N Ty pe s of m un ic ip al iti es – a ve ra ge v al ue s M es o- re gi on al c ity (K ar lo vy V ar y) M ic ro -r eg io na l t ow ns Su bu rb an m un ic ip al iti es Se m i-p er ip he ra l m un ic ip al iti es Pe ri ph er al m un ic ip al iti es Sm al l t ow ns To w ns hi ps 0. 88 0. 94 1. 80 1. 13 1. 09 0. 94 1. 04 1. 01 0. 99 1. 06 1. 01 1. 01 0. 98 1. 00 -4 .9 3 -3 .9 0 -1 .7 4 -2 .7 9 -1 .8 6 -2 .9 1 -5 .8 6 0. 50 -2 .0 2 15 .9 7 1. 55 1. 28 -3 .9 6 4. 94 14 .0 14 .8 16 .0 15 .8 16 .5 15 .4 15 .1 24 .2 21 .5 17 .7 19 .0 20 .2 20 .3 20 .9 12 .3 17 .0 15 .0 19 .7 19 .8 19 .9 18 .6 15 .8 8. 8 10 .6 7. 1 6. 4 6. 8 7. 8 11 .6 6. 4 28 .5 12 .7 22 .2 7. 4 13 .1 44 8 29 2 34 2 29 3 33 5 26 4 27 6 9. 1 10 .5 6. 5 10 .3 11 .8 11 .3 9. 7 5. 2 4. 0 2. 5 4. 0 4. 8 4. 8 3. 5 5/ 3 2/ 0 0/ 4 0/ 0 1/ 1 2/ 0 1/ 0 Su b- re gi on s – to ta l v al ue s A š su b- re gi on C he b su b- re gi on M ar iá ns ké L áz ně s ub -r eg io n So ko lo v su b- re gi on K ra sl ic e su b- re gi on N ej de k su b- re gi on K ar lo vy V ar y su b- re gi on To už im -Ž lu tic e su b- re gi on O st ro v na d O hř í s ub -r eg io n 1. 04 1. 04 0. 98 0. 92 0. 91 1. 01 0. 96 0. 95 0. 96 0. 97 1. 00 1. 05 1. 00 0. 98 1. 00 1. 02 0. 98 0. 96 -3 .7 3 -3 .7 8 -4 .2 4 -3 .2 5 -4 .1 6 -4 .1 4 -3 .8 6 -2 .0 3 -3 .4 5 1. 64 1. 43 2. 64 -2 .4 0 -1 .1 4 3. 15 2. 57 -2 .2 8 -5 .1 2 15 .7 15 .0 14 .9 15 .5 15 .5 14 .6 14 .7 15 .5 15 .1 19 .5 19 .8 22 .7 19 .8 22 .3 20 .8 23 .0 21 .1 21 .3 21 .3 16 .8 15 .2 18 .9 18 .7 17 .1 12 .8 19 .8 17 .8 5. 9 9. 3 11 .0 7. 7 5. 9 7. 2 14 .9 6. 5 9. 00 5. 2 15 .3 13 .7 6. 9 6. 3 10 .6 14 .7 5. 7 10 .4 26 8 30 4 39 4 23 4 26 2 26 2 42 8 28 6 30 6 13 .2 10 .5 8. 4 9. 0 14 .0 7. 8 8. 1 10 .3 9. 1 2. 4 3. 2 5. 2 5. 4 6. 5 3. 4 4. 7 5. 2 4. 1 2/ 0 0/ 0 2/ 3 4/ 0 4/ 0 0/ 0 1/ 3 2/ 0 2/ 0 N ot es : D es cr ip tio n of in di ca to r co de s ar e in T ab le 1. U nd er lin ed v al ue : t he v al ue li es in th e fo ur th q ua rt ile in te rm s of v al ue s so rt ed in d es ce nd in g or de r; Va lu e in it al ic s: th e va lu e lie s in th e fir st q ua rt ile . 1 N um be r of v al ue s in th e fo ur th /fi rs t q ua rt ile . 2 D at a fr om th e 20 21 C en su s. S ou rc es : D at ab as es o f t he C ze ch St at is tic al O ffi ce , b ut E X: d at a ar e fr om th e Ex ec ut or ’s C ha m be r of th e C ze ch R ep ub lic . A ut ho rs ’ o w n ca lc ul at io ns . Veselý, V. and Kubeš, J. Hungarian Geographical Bulletin 74 (2025) (1) 57–70.64 ership and no environmental burden, they can have favourable values. The sub-regions of Karlovy Vary and Mariánské Lázně have the most favourable values for sub-regions, also thanks to their spa character. The Karlovy Vary Region did not fare well in the comparison of human and de- mographic capital of 14 (territorial-admin- istrative) regions of Czechia, despite the fact that it borders developed Bavaria. According to the average ranking of the values of 7 de- mographic indicators, the region ranked last with an average of 12.5 (Figure 2). The region was placed in the top ten regions of Czechia only in the case of the representation of sen- ior citizens (SE). The Karlovy Vary Region also finished last in the evaluation of human capital using 8 indicators (average ranking 12.9) (Figure 3). The region has particularly unfavourable values in the indicators of the level of education (EE, UE), gross monthly salary (MSC) and employment in science and research (SAR). Close behind the monitored Karlovy Vary Region is the Ústí Region (av- erage rank in human capital 12.6), which is also struggling with the post-socialist trans- formation of its brown-coal industry. Žítek, V. and Klímová, V. (2016), Wielechowski, M. et al. (2021) or Hamplová, E. et al. (2021) con- firm the poor position of the Karlovy Vary Region among Czech regions. A somewhat simplified comparison of the demographic and human capital of the Karlovy Vary Region and neighbouring re- gions in Bavaria, Saxony, and Bohemia is offered in Table 4. The Karlovy Vary Region is losing population slightly, but the popu- lation development in the eastern German region of Chemnitz is significantly worse due to the departure of young people to the western parts of Germany. The relatively advanced Czech healthcare system contrib- utes to the small differences in life expec- tancy between Czech and German regions. However, there are fundamental differences in the wealth (GDP) of the Bavarian regions on the one hand and the Saxon and mainly Czech regions on the other, especially in the case of the Karlovy Vary Region. The need to retain university graduates, create a uni- versity, and develop science, research, and high-tech industries in the studied region is documented by the unfavourable values of the UEX and HTS indicators for the region. Fig. 2. Average order of indicator values of demographic capital in the regions of Czechia, 2022. The list of indicators is in Table 1. Region codes: PR = Prague; CB = Central Bohemia Region; SB = South Bohemia Region; PI = Pilsen Region; KV = Karlovy Vary Region; US = Ústí Region; LI = Liberec Region; HK = Hradec Králové Region; PA = Pardubice Region; VY = Vysočina Region; SM = South Moravian Region; OL = Olomouc Region; ZL = Zlín Region; MS = Moravian-Silesian Region. Sources: Databases of the Czech Statistical Office, and authors’ own calculations. 65Veselý, V. and Kubeš, J. Hungarian Geographical Bulletin 74 (2025) (1) 57–70. Discussion and strategies and measures for the development of human capital The above-mentioned unfavourable demo- graphic-capital and human-capital values of the Karlovy Vary Region are the result of a number of factors operating both in the past and in the present. Immediately after World War II, there was a population exchange – the displacement of the vast majority of German- speaking residents and the arrival of mostly poor Czech and Slovak new settlers without ties to the local settlements and landscape. This non-rootedness and residential instabil- ity of the region’s inhabitants is now no long- er as strong, but it still exists. The region’s human capital was subsequently adversely affected by the political, social and economic measures of the socialist (communist) gov- ernments between 1948–1989. The Iron Cur- tain of barbed wire with high electric voltage built near the border with Bavaria prevented Table 4. Human and demographic capital in the Karlovy Vary Region and neighbouring Bavarian, Saxon and Czech regions according selected indicators, 2022 Region, country NUTS EU region Values of demographic capital indicators Values of human capital indicators LD SD LEM GDP UEX HTS Chemnitz (Saxony, Germany) Upper Franconia (Bavaria, Germany) Upper Palatinate (Bavaria, Germany) Germany Karlovy Vary Region (Bohemia, Czechia) Ústí Region (Bohemia, Czechia) Pilsen Region (Bohemia, Czechia) Czechia NUTS2 NUTS2 NUTS2 NUTS0 NUTS3 NUTS3 NUTS3 NUTS0 0.76 1.07 1.12 1.04 0.97 0.99 1.08 1.05 0.98 1.00 1.00 1.01 1.00 0.99 1.04 1.02 80.3 80.0 80.5 81.5 78.1 77.5 79.6 79.7 29.6 38.8 43.7 48.6 19.3 23.5 26.2 27.6 25.1 27.5 30.6 32.0 14.0 16.2 23.6 26.7 3.4 3.8 5.0 5.3 1.5 2.9 4.7 5.1 Note: Description of indicator codes are in Table 1. Sources: Databases of the Czech Statistical Office and Eurostat. Authors’ own calculations. Fig. 3. Average order of indicator values of human capital in the regions of Czechia, 2022. For explanations and sources see Figure 2. Veselý, V. and Kubeš, J. Hungarian Geographical Bulletin 74 (2025) (1) 57–70.66 cross-border relations. The problematic post- socialist development and subsequent not very successful post-socialist transformation of the brown-coal, textile, glass and porcelain industries in the region led to low wages, job losses and the departure of many young and educated residents from the region. Economic transformation and further economic development in the post-socialist countries of Central Europe led to an intensi- fication of economic, social and demographic contrasts between the cores and the periph- eries within regions and on the east-west gradient within these countries, with more positive developments in the cores (includ- ing their suburban zones) and in the western regions of the countries (while eliminating the influence of the capital cities) (Downes, R. 1996; Blažek, J. and Csank, P. 2005; Matlovič, R. et al. 2018). However, this may not be the case for those regions that entered the post-socialist transformation with the sig- nificant weight of coal mining and process- ing, textile and metallurgical industries, as these sectors have been going through crises here since the 1990s. In Czechia, this applies to the Ústí and Karlovy Vary regions located in the west of the country. The Karlovy Vary Region and the neigh- bouring regions in Bavaria and Saxony (Upper Franconia, Upper Palatinate and Chemnitz) have a peripheral location within Central Europe, as they are far from large settlement agglomerations and economic cores and axes of Czechia and Germany (it is a “macro-regional” periphery). This pe- ripherality leads to the migration of young and educated people to the aforementioned major agglomerations, cores and axes, where they find interesting and well-paid work (Brixy, U. et al. 2022), diverse services and culture. If the municipalities of these regions are also characterized by meso-regional and micro-regional peripherality (they are locat- ed far from the meso-regional city and micro- regional towns), then this migration is even stronger. However, we cannot forget the not yet very strong migration counter-current – counter-urbanization, which in recent years has been bringing some people from towns and agglomerations to rural and ecologically valuable areas (Šimon, M. and Bernard, J. 2016 in Czechia, Steinführer A. et al. 2024 in Germany). The key strategy for developing human capital in the Karlovy Vary Region is to develop the education of the population, including university education. There is no public university here, but its establishment is being prepared. The organizational form of the planned school is now being decided – whether it will be a full-fledged university or polytechnic college, or just a separate fac- ulty of a university located outside the re- gion, in Pilsen or Prague. The school’s focus should respect the specifics of the region and the needs of employers in the region. So far, economic, ICT, public administration, balne- ology and rehabilitation fields are planned. It would be good to add bachelor’s degree technical fields that would support the main- tenance and development of mechanical en- gineering in the region (Gál, Z. and Páger, B. 2017). This is what representatives of these companies in the region want (PRKK, 2021). A problem can be the region’s small popula- tion base (300,000 inhabitants), which affects the number of potential students and the va- riety of potential fields of study. The region has a sufficient network of schools providing diverse upper secondary education (for students aged 15–18) in micro- regional towns, the exception is the periph- eral Toužim-Žlutice sub-region in the south- east of the region. Manufactory factories pro- ducing unique, world-renowned products in the region for more than 100 years – musical instruments, unique and serial porcelain and glass products – should retain the relevant craft disciplines and lecturers. A greater expansion of dual education can be recom- mended – education in schools and at the same time directly in industrial companies, as proposed by local industrialists (Vaishar, A. et al. 2012). Primary and lower secondary education (“ele- mentary education” in Czechia) in the region should be of high quality and accessible even 67Veselý, V. and Kubeš, J. Hungarian Geographical Bulletin 74 (2025) (1) 57–70. in rural peripheries and in socially excluded localities. In the rural periphery of the cen- tral, southern and south-eastern parts of the Karlovy Vary Region, where there are mainly small rural settlements without schools, com- muting pupils to distant schools is difficult, time-consuming and dangerous. This may be the reason for the departure of young families with children from rural peripher- ies (Kubeš, J. and Podlešáková, N. 2021). Insufficient qualifications and insufficient language skills of representatives and employees of public administration in the region is one of the reasons for the still weak cross-bor- der cooperation with neighbouring Bavaria and Saxony and within the cross-border Euregio Egrensis. According to Welter, F. et al. (2007), and Stoffelen, A. et al. (2017) the development of cooperation is hindered by the lack of initiative and impulsiveness of the Czech partners, insufficient language skills of partners on both sides of the border, reminiscences of residents on both sides of the problematic stages of the development of Czech-German relations in the 20th century, and persistent socioeconomic differences. Lipovská, Z. et al. (2012) recommend expand- ing and intensifying cooperation between schools (including regional universities) on both sides of the border in education and getting to know each other. Daily or weekly commuting of Czech workers to neighbour- ing German regions for work is not the form of interstate cooperation. The Karlovy Vary Region is struggling with a shortage of medical doctors in its hospitals and polyclinics, and in the peripheral coun- tryside. Many doctors have aged or left for better-paid work in Germany (Mareckova, M. 2004), and young doctors do not want to go to this peripheral region. State, regional and municipal financial and other incentives for doctors and medical students are already being implemented. World-famous spas are concentrated in the region – in Karlovy Vary, Mariánské Lázně, Františkovy Lázně, Jáchymov. Around 650,000 guests use them annually, of which 70 percent are foreign (Vystoupil, J. et al. 2017). Balneology, accommodation, catering and other services come together in this spa industry (Speier, A.R. 2011). These spas have many employees, but they often lack the nec- essary education (including language skills) (Boleloucka, E. and Wright, A. 2020). It is therefore necessary to establish a spa tertiary education system in the region and strength- en the relevant secondary education system as well as a balneological research institute. After 1989, especially near the highway near Cheb, Sokolov and Karlovy Vary, large halls of logistics and assembly plants, mostly owned by foreigners, were created. They mainly employ cheap and poorly qualified Czech workers here. Now the leadership of the region and the state should rather support the development of modern and high-tech in- dustry associated with a qualified workforce (Žítek, V. 2010). It is also important to pre- serve the production of original, internation- ally recognized glass and porcelain products, musical instruments and some food products requiring special craftsmanship. If a region- al innovation centre were to be established in the region, it could support these higher production activities more, support start-ups, overall technical development and, thus, im- prove the human capital of the workforce. In the Sokolov sub-region, surface mining of brown coal took place and to a lesser ex- tent is still taking place, which is provided by workers living mainly in local towns and townships. The management of the Sokolovská uhelná company (regional brown- coal company), representatives of the towns and the Karlovy Vary Region, and local la- bour authorities come up with a series of measures related to the gradual reduction of brown coal mining and related energy and with a plan to end mining by 2035 (see Lipovská, Z. et al. 2012). The Sokolovská uhelná company wants to focus on new carbon-free energy, other new technologies and on the reclamation and revitalization of the landscape destroyed by surface mining (Frantál, B. et al. 2024). This will require a skilled, partly new workforce. Laid-off work- ers from brown-coal mining and processing Veselý, V. and Kubeš, J. Hungarian Geographical Bulletin 74 (2025) (1) 57–70.68 should undergo retraining, which will also contribute to the growth of human capital in the region. Similar problems are faced by the Most brown-coal area (Ústí region, Czechia) and brown-coal areas in Hungary (Salgótarján – Horváth, G. and Csüllög, G. 2012) and in eastern Germany (Lusatia – Matern, A. et al. 2023). Conclusions Favourable demographic capital and the growth of human capital are key factors for the further development of the Karlovy Vary Region as a whole, sub-regions of the region and individual municipalities located both in the peripheral, semi-peripheral and core areas of the region. The paper uses a settlement-geo- graphical approach – first, the higher and low- er settlement centres of the region are defined, and based on the time distance from micro- regional towns, the semi-peripheries and re- mote peripheries of the region are delimitated. Using the indicators, the paper then evaluates and compares the demographic and human capital of the types of municipalities and sub- regions of the Karlovy Vary Region, as well as this region and other regions of Czechia and neighbouring regions in Germany. The meso-regional city of Karlovy Vary has a weaker demographic capital influenced by the aging of the local population and the de- parture of suburbanites to suburbs. Its human capital is favourable. Meso- and micro-region- al towns are losing residents primarily as a re- sult of suburbanization, which enriches their nearby suburban hinterland in terms of popu- lation and human capital. The municipalities in the semi-peripheral and peripheral rural areas of the region are diverse as a whole. If they have quality management and a good lo- cation, their capital values can be favourable. In the case of the Karlovy Vary Region, lo- cated in the west of Czechia, on the border with developed Germany, the east-west gra- dient of human capital development within Czechia has not been confirmed. The Karlovy Vary Region is not doing well in comparison with other regions. It is in last place among Czech regions and lags even further behind neighbouring regions in Bavaria. The reason is primarily the specific development of the region after World War II, its peripheral po- sition within Czechia, and the problematic post-socialist transformation of its economy until recently based mainly on brown coal. The paper also includes strategies and meas- ures to increase human capital in the Karlovy Vary Region and its municipalities. The key is the retention of university graduates and the establishment of a university or polytechnic college in the region. The development of up- per secondary education, including dual train- ing in companies, is also important. Another significant benefit to the human capital of the region should be high-quality and affordable retraining of laid-off work- ers from the ceasing brown coal mining and from other declining industries, and the sup- port of industrial enterprises with higher added value and high-tech production. The qualification development of workers in the region’s world-famous spas is also impor- tant. Intensifying real (not paper) Czech- German cross-border cooperation would bring development incentives, improved language skills, and mutually beneficial economic and cultural cooperation to the re- gion, its public administration, associations, schools, and businesses. REFERENCES Adsera, A. 2004. Changing fertility rates in developed countries. 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