25 Research on World Agricultural Economy | Volume 03 | Issue 02 | June 2022 Research on World Agricultural Economy https://ojs.nassg.org/index.php/rwae Copyright © 2022 by the author(s). Published by NanYang Academy of Sciences Pte. Ltd. This is an open access article under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License. (https://creativecommons.org/licenses/by-nc/4.0/). *Corresponding Author: K. Nirmal Ravi Kumar, Department of Agricultural Economics, Agricultural College, Bapatla, Acharya NG Ranga Agricultural University (ANGRAU), Andhra Pradesh, India; Email: kn.ravikumar@angrau.ac.in DOI: http://dx.doi.org/10.36956/rwae.v3i2.514 Received: 7 April 2022; Received in revised form: 10 May 2022; Accepted: 18 May 2022; Published: 26 May 2022 Citation: Kumar, K.N.R., 2022. Competitiveness of Indian Agricultural Exports: A Constant Market Share Analysis. Research on World Agricultural Economy. 3(2), 514. http://dx.doi.org/10.36956/rwae.v3i2.514 RESEARCH ARTICLE Competitiveness of Indian Agricultural Exports: A Constant Market Share Analysis K. Nirmal Ravi Kumar* Department of Agricultural Economics, Agricultural College, Bapatla, Acharya NG Ranga Agricultural University (ANGRAU), Andhra Pradesh, India Abstract: The 1991 Indian reforms aimed at economic liberalization, as a part of its economic structural adjustment, and transformed the nation’s economy into a more global market-based and service-oriented system, which revolution- ized its agricultural trade facet. The new regime paved the way for the self-reliant Indian agriculture to expand its roots into the spheres of global competitiveness and export orientation. India enjoys competitive advantage in the interna- tional market and considering the growth in India’s exports of major agricultural commodities. This study employed Constant Market Share model to analyze the export performance of its various facets such as diversification, instability, elasticity, competitiveness, etc. The findings revealed that India’s growth performance of major agricultural commodi- ties’ exports both in terms of quantity and value was found satisfactory (except wheat and cashew nuts, shelled (quantity)) during 1991-2020. During the recent past decade, i.e., 2011-2020, World Demand Effect (WDE) is the main sources of India’s agricultural export performance (due to general rise/fall in world demand given a constant market share of the India, unlike Market Distribution Effect (MDE), Commodity Composition Effect (CCE) and the Residual Competitive- ness Effect (RCE) due to high inconsistency arising out of changes in external environment). Both MDE and RCE with respect to commodity-wise exports and CCE and RCE with respect to country-wise exports are found negative for ma- jority of commodities and countries (markets) respectively. Consistently negative CCE for exports of agricultural prod- ucts, total and across major export destinations were found more disheartening and this should deserve special attention. So, it is imperative to boost the export competitiveness of agricultural commodities from India and the future prospects of exports depend on how much the latest surge in COVID-19 infections in India affects its agricultural production and global demand conditions. Keywords: Indian exports; World exports; Export performance; Export competitiveness; World demand 1. Introduction Economic reforms and trade liberalization policies have been widely adopted by developing countries to im- prove their position in world trade. Since 1991, India en- tered the Liberalization-Privatization-Globalization (LPG) phase to overcome its debt crisis, food shortage and at the http://dx.doi.org/10.36956/rwae.v3i2.514 https://orcid.org/0000-0002-0041-572X 26 Research on World Agricultural Economy | Volume 03 | Issue 02 | June 2022 same time to gain from net agricultural exports, as it en- joys comparative advantage for majority of the agricultur- al commodities. With the advent of this LPG phase, more focus is now given towards export promotion through enhancing both domestic and export competitiveness of agricultural commodities. Emphasis on cost-effective and quality production of agriculture gained more significance. With the emergence of World Trade Organization (WTO) in 1995, it was expected that India would be benefited through multilateral trade, as it enjoys comparative advan- tage with reference to majority of the agricultural com- modities and also fulfill the import requirements like puls- es, edible oils, technology etc. In this context, a number of studies investigated the effects of trade liberalization on export performance of agricultural commodities in In- dia. Many studies have identified positive effects of trade liberalization on export performance of majority of the agricultural commodities. In the post-WTO regime, Indian agricultural commodities exports performance has under- gone paradigm shift through the tremendous structural and qualitative changes [1]. India is the second most populous country with the fifth largest economy occupying only 13th position in world trade and earning US$ 623 billion of merchandise trade and US$ 294 billion of services trade. In India, agriculture exports have significantly increased by multiple folds from US$ 3.35 billion to US$ 41.56 bil- lion and registered impressive growth rates during 1990- 1991 to 2020-2021. India imports an immense catalogue of 6000 agri-products from 140 nations, bested only by its exports comprising about 7500 types of products to 190 countries globally. As of 2020-2021, India’s agri-exports amount to US$ 41.56 billion, which constitutes 14.20 per cent of its total exports. On the contrary, the nation’s agri-imports were valued at US$ 21.47 billion, the 5.42 per cent piece of the total national import pie (Table 1). This shows that India’s agricultural economy enjoys a whopping US$ 20.09 billion global trade surplus. Yet, on more narrow spectra, the nation enjoys trade surplus with Bangladesh, Belgium, Germany, Hongkong, Italy, Ma- laysia, Nepal, Netherlands, Singapore, Sri Lanka, UAE, UK, USA, Vietnam, etc., but looks to a trade deficit with nations such as Australia, China, Nigeria, South Korea, Switzerland, Saudi Arabia, Iran, Iraq, Qatar, etc., which could be cited as some of the nations serving as epicenters of shifts in the global economic power. The nation record- ed an increase in its share of global exports from 0.53 per cent in 1994 before the commencement of WTO to 1.71 per cent in 2019. In the same time-frame, India’s share in global imports hiked from 0.7 per cent to 2.5 per cent [2]. India has consistently maintained a trade surplus in ag- ricultural commodities over the years. The agricultural ex- ports from India registered an increase of nearly 50 times in the span of 30 years per cent till 2020-2021. However, in 2019-2020, there was a slight drop in agri-exports by around 8 per cent. In the next year during 2020-2021, India’s agri-exports reached the highest. So, with the in- creased international trade opportunities, the agricultural exports from India gained the rapid surge. However, be- sides absolute growth in agri-exports, the competitiveness of the agricultural commodities is an important dimension. The tendency of a nation to produce and distribute prod- ucts that can withstand the competitiveness of global mar- kets and sustain its producers by ensuring a continuous improvement in their real incomes and living standards is a measure of the nation’s export competitiveness. It gained more prominence in modern times, owing to the increas- ing foreign exchange to the exporting country. A nation, on realization of export competitiveness, embodies several advantages such as strengthening of ports’ export infra- structure, quality enhancement of commodities, capture of monopoly gains in the international market, earning sig- nificant amounts of foreign exchange, ease in regulation of procedural formalities at ports, increase in the pace of making exports, planning towards need-based exports on client specifications, quality enhancement of commodities, strengthening of international trade relationships, analysis of the tariff levels of market players and fixation of export prices in accordance, etc. These advantages may move the Government of a nation with a liberalized economy to formulate appropriate trade policies aimed towards its significant exports. Keeping in view of the importance of export competitiveness and increase in exports value of agricultural commodities from India, it demands analysis of its various facets such as diversification, instability, elasticity, competitiveness, etc. So, this article investigates the major sources of India’s exports performance during the recent past decade of post-WTO regime period (2011- 2020) by using Constant Market Share Analysis (CMSA). The article is organized into five sections. Beginning with an introduction in the first section, brief review of liter- ature is presented in the section, followed by the meth- odology, data used in the analysis and brief description about CMSA model in the third section, the fourth section presents the results and discussions. Summary and conclu- sions are presented in the last section. 27 Research on World Agricultural Economy | Volume 03 | Issue 02 | June 2022 Table 1. India’s Imports and Exports of Principal Agricultural Commodities (US$ Billion) Year Agricultural Imports Total National Imports % of Agricultural Imports to Total National Imports Agricultural Exports Total National Exports % of Agricultural Exports to Total National Exports Net agricultural export 1990-1991 0.67 24.08 2.79 3.35 18.14 18.47 2.68 1991-1992 0.60 19.55 3.09 3.20 18.00 17.80 2.60 1992-1993 0.94 20.68 4.54 2.95 17.52 16.84 2.01 1993-1994 0.74 23.31 3.18 4.01 22.24 18.05 3.27 1994-1995 1.89 28.65 6.60 4.21 26.33 15.99 2.32 1995-1996 1.76 36.68 4.80 6.10 31.79 19.18 4.34 1996-1997 1.86 39.13 4.76 6.81 33.47 20.33 4.94 1997-1998 2.36 41.48 5.70 6.68 35.01 19.09 4.32 1998-1999 3.46 42.39 8.17 6.06 33.22 18.25 2.60 1999-2000 3.71 49.74 7.45 5.84 36.71 15.91 2.13 2000-2001 2.65 50.54 5.24 6.27 44.56 14.08 3.63 2001-2002 3.41 51.41 6.63 6.23 43.83 14.22 2.82 2002-2003 3.64 61.41 5.92 7.16 52.72 13.58 3.52 2003-2004 4.78 78.15 6.12 7.92 63.84 12.41 3.14 2004-2005 5.08 107.13 4.74 9.26 83.54 11.08 4.18 2005-2006 3.61 129.69 2.78 10.32 103.09 10.02 6.72 2006-2007 5.08 185.60 2.74 12.76 126.26 10.10 7.68 2007-2008 5.60 251.56 2.23 18.56 162.98 11.39 12.95 2008-2009 6.25 299.33 2.09 17.65 183.10 9.64 11.40 2009-2010 11.47 287.61 3.99 17.81 178.32 9.99 6.34 2010-2011 11.21 369.37 3.03 24.80 249.46 9.94 13.60 2011-2012 14.64 489.42 2.99 38.14 305.90 12.47 23.50 2012-2013 17.99 501.62 3.59 42.70 307.14 13.90 24.71 2013-2014 14.17 448.82 3.16 43.43 314.87 13.79 29.26 2014-2015 19.84 447.58 4.43 39.20 310.15 12.64 19.36 2015-2016 21.43 380.38 5.63 32.90 262.17 12.55 11.47 2016-2017 24.56 384.31 6.39 33.79 275.74 12.26 9.23 2017-2018 23.60 465.60 5.07 39.03 303.55 12.86 15.43 2018-2019 19.60 514.09 3.81 39.27 330.04 11.90 19.67 2019-2020 20.94 477.41 4.39 35.93 315.32 11.40 14.99 2020-2021 21.47 395.90 5.42 41.56 292.76 14.20 20.09 Source: DGCI & S, 2020-2021 28 Research on World Agricultural Economy | Volume 03 | Issue 02 | June 2022 2. Review of Literature Though there are several definitions for export compet- itiveness, no definition or measurement was found univer- sally accepted. According to Cook and Bredahl [3], compet- itiveness can be seen from the perspective of geographical market or product. However, they opined that this defini- tion is even not clear regarding at what level ie., either at national level or industry level or firm level, the competi- tiveness should be measured. Pursell and Gupta [4] opined that market distortion by price policy for agricultural com- modities is one of the major causes for regional dispersion of competitiveness of Indian wheat. Singh [5] employed CMSA model to analyze the India’s exports performance of major commodity groups during the post-liberaliza- tion period (1991-2011). The findings revealed that the increased world demand is the major contributing factor for export growth from India. However, the exports from India are highly prone to changing external environment and trading policies of importing countries. Alberto’s [6] study revealed that Spain has experienced stiff competi- tion from China and other emerging economies and this led to decline in export share of commodities. However, the former enjoyed more export competitiveness com- pared to other European advanced economies. Mamta [7] employed CMSA model to analyze and compare export competitiveness of cotton between India and China. It is found interesting that both the countries improved their export competitiveness post Multi Fiber Agreement (MFA) and the comparative picture revealed that China outpaced India. Though India is the second largest producer of cot- ton in the world, it could not keep a cotton buffer, unlike China. So, maintenance of buffer stocks is essential to regulate cotton prices and for streamlining cotton supply to the domestic industry at competitive rates. Varalakshmi and Suresh [8] employed CMSA model and found that bo- vine meat exports were more competitive in new markets compared to traditional export destinations. So, the policy should focus on penetrating into new markets at the same to promote competitiveness in the traditional markets to enhance bovine meat trade. Sonu and Rajni [9] employed CMSA model and found that export growth of wheat in India is attributed only to World Demand Effect (WDE) and Market Distribution Effect (MDE) and concluded that there is competitive disadvantage in the wheat exports as compared to rest of world. Though CMSA model is popular and has wider adopt- ability in quantifying the export performance and in determining the factors underlying the export potential of commodities etc., there are certain limitations and as- sociated criticisms with respect to its potential. The results of CMSA are sensitive to the extent of market consolida- tion [10,11]. For example, market consolidation as in Euro- pean Union has varied results over the individual compo- nent markets with respect to analysis using CMSA model. Moreover, the selection of destination markets also can have impact on the results. The selected regions should ideally have true competitors only for obtaining optimum results using CMSA model and however, this situation of availability of true competitors is not realistic [10,12]. However, considering its broad consistent framework, this model still serves as a popular tool to explore the export potential of commodities over a period of time for a given country. 3. Materials and Methods The India’s export performance with reference to ma- jor agricultural commodities viz., apples; cashew nuts, shelled; chillies and peppers, dry; cotton lint; maize; mangoes, mangosteens, guavas; rice; sorghum; wheat and agricultural products, total has been examined by using the CMSA model [5,13]. The period from 1991 to 2020 was considered for the study in view of data availability for all the selected commodities and their major importers in the world. The relevant data on India’s exports both commodity-wise and country-wise, imports of selected commodities across major importing countries and world agricultural products exports are collected from www.fao. org. 3.1 CMSA Model Introduced by Tysznskin [14] and Richardson [10] and lat- er, Ahmadi-Esfahani [15] adapted Jepma’s [16] version to an- alyze the competitiveness of agricultural commodities in the international market. This model is often employed to analyze the structural changes in international trade both in terms of exports and imports [17] and thus, ascertain the export performance of a country across major geograph- ical destinations in the world [18]. This model helps to de- compose the world exports into four categories or effects viz., WDE, the Commodity Composition Effect (CCE), the MDE and the Residual Competitiveness Effect (RCE). It is interesting that this model explains the divergence be- tween actual export growth and export growth computed on the assumption the focus country’s export share of each commodity in each market remains constant. Following is the main equation of the CMSA model in terms of actual export change: ∆X = r + - r + – + ∆X- (1) where, ∆X = actual change in India’s agricultural exports http://www.fao.org http://www.fao.org 29 Research on World Agricultural Economy | Volume 03 | Issue 02 | June 2022 (difference between 2020 and 2011); r = percentage increase in total world (excluding India) exports from period 2011 to period 2020; = percentage increase in world (excluding India) ex- ports of commodity “i” from period 2011 to period 2020; = percentage increase in world (excluding India) ex- ports of commodity “i” to country “j” from period 2011 to period 2020; = India’s exports of commodity “i” to the rest of the world in period 2011, and India’s exports of commodity “i” to country “j” in period 2011. In the above Equation (1), r represent MDE; - r represent CCE; - represent to MDE and ∆X- represent RCE. The analysis is done in MS Excel. WDE: This effect analyzes the increase/decrease in focus (India) country’s exports due to general increase/ decrease in world exports. So, a positive/negative value of WDE indicates an increase/decrease in focus country’s exports due to general rise/fall in world demand given a constant market share of the focus (India) country. CCE: This effect measures the magnitude of concen- trations of country’s export composition in products/com- modities, where import demands are high. It is the weight- ed sum of export values of selected commodities. The weights are calculated by subtracting the individual com- modity’s growth rate from the world’s total export growth rate in aggregate (represented by “r” in previous formula). A positive CCE indicates that the focus country’s exports are concentrated for those commodities whose demand is increasing at a higher rate than aggregate growth rate (r) of the total world exports. A negative CCE value indicates the inverse situation. MDE: This is a measure of the magnitude of country’s export concentrations to those markets (importing coun- tries), where the demand is growing relatively higher or slower rate as compared to total growth of world exports of particular commodity in those markets (presented by ri in previous formula). It is the weighted sum of export val- ues for individual commodities directed to a particular im- porting country. A positive value of MDE indicates that a focus country’s exports are directed to relatively growing markets. A negative value indicates that the exports of the focus country are concentrated in markets where demand is growing slowly than the rest of the world. RCE: This will assess the difference between actual change in focus country’s exports and changes that would have taken place if the constant market share has been sustained in those markets by the focus country. This is a residual term, as from the actual change in the exports of the focused country, the earlier three effects i.e., WTE, CCE and MDE have been deducted. If this residual term is positive, it means there is improvement in the focus country’s competitiveness and vice versa. 3.2 Actual Increase in Exports This is the difference between agricultural exports of focus country (India) between 2020 and 2011. This is given by: = X1-X0 (2) where, = Actual increase in exports of the focus coun- try (India); X1 = Actual value of exports of focus country in the peri- od 2020; X0 = Actual value of exports of focus country in the peri- od 2011. 3.3 Potential Increase in Exports This is derived from the following formulae: ( )/100 (3) where, = Potential value of focus country’s exports in period 2020; = Value of world exports in period 2020; = Share of focus country in world exports in period 2011. So, = X0, = Potential increase in focus country’s exports Practical utility: This analysis shed light on the on the export performance of major agricultural commodities from India through splitting it across various effects viz., WDE, CCE, MDE and RDE. This helps the policy makers to reveal the underlying reasons for export performance of selected agricultural commodities and overall exports. It also enables the researchers to compare the export per- formance from India with other competing countries and thereby, help to figure out the competitiveness of focus country in global trade. Accordingly, relevant policy sug- gestions can be figured out to enhance the export competi- tiveness of India. 4. Results and Discussion 4.1 Growth in Exports of Selected Commodities from India Table 2 shows the growth in exports (both in terms of quantity and value) of selected commodities and agri- cultural products, total from India during 1991 to 2020. The findings revealed that India registered noticeably positive and significant export growth rates both in terms of quantity and value for all the selected commodities, ex- 30 Research on World Agricultural Economy | Volume 03 | Issue 02 | June 2022 cept wheat and cashew nuts, shelled (quantity) during the overall reference period, 1991-2020. Across the selected commodities, chillies and peppers, dry showed promising performance during all the selected sub-periods, except in terms of value during 1991-2000. Sub-period, 2001-2010 was found favourable to register positive and significant export growth rates of apples, cotton lint, maize, mangoes, mangosteens, guavas and sorghum. Though total market size in importing countries is dwarfed by increased pro- duction volumes, the above commodities are well-suited to value-added processing. On the contrary, majority of the commodities viz., apples, cashew nuts, shelled, cotton lint, maize and mangoes, mangosteens, guavas registered declining growth performance during sub-period 3, i.e., 2011-2020. Though these commodities enjoyed increased exports in the past decade, their exports in the recent de- cade found more challenging in the context of increasing demand for Sanitary and Phyto-Sanitary (SPS) require- ments, increased competition from foreign producers (ca- shew), high rates of import duties, declining incentives (for cotton), higher transaction costs (mangoes, mangosteens, guavas) etc. It is important to note that though Pakistan and Bangladesh enjoyed duty free or concessional duty access in India, in turn, they imposed higher higher rates of duty on Indian yarn. Further, countries like Bangladesh and Vietnam enjoy duty-free access in world’s largest cot- ton yarn markets such as China, unlike India. The positive and significant growth rates both in terms of quantity and value for apples and sorghum during sub-period 2, i.e., 2001 to 2010 has compensated their respective poor per- formances during other two sub-periods viz., 1991-2000 and 2011-2020 and thus, these commodities registered impressive (significant) growth rates during overall refer- ence period, 1991-2020. It is quite disheartening to note that wheat, one of the major cereal crops cultivated in the country had shown dismal (negative) performance both in terms of quantity and value during all the selected sub-pe- riods and hence, the export performance is not significant during the overall reference period. This is because, ex- port ban significantly influenced export volume of wheat. The ratio of domestic market price and international price has a strong adverse significant impact on wheat exports [19]. Table 2. Export growth (%) of selected commodities from India during 1991 to 2020 Commodity 1991-2000 2001-2010 2011-2020 1991-2020 Quantity Value Quantity Value Quantity Value Quantity Value Apples –6.927 –7.188 13.381** 17.317** –3.878 –3.950 4.060** 5.695** Cashew nuts, shelled 4.670** 5.193* 0.696 5.987** –9.010** –6.305* 1.055 3.372** Chillies and pep- pers, dry 11.336* 7.281 16.023** 26.100** 6.220** 8.586** 12.004** 15.289** Cotton lint –20.410 –18.478 82.631** 95.665** –11.085** –12.339** 16.060** 18.240** Maize 64.522 50.833 47.547** 9.247** –20.587* –20.195* 33.167** 34.457** Mangoes, mango- steens, guavas 7.915** 2.397 21.888** 32.057** –6.501** –3.262* 9.130** 12.370** Rice 98.802* 104.933** –3.806 15.192 13.134 10.195 40.601** 45.398** Sorghum –3.225 –3.152 64.096** 75.969** –9.349 –7.263 34.575** 37.640** Wheat –42.029 –36.082 –75.734** –71.540** –23.874 –24.618 12.178 15.165 Agricultural prod- ucts, total 3.029* 12.037** 1.103 6.254** Note: ** & * - Significant at 1 and 5 percent levels respectively Raw Data Source: www.fao.org 31 Research on World Agricultural Economy | Volume 03 | Issue 02 | June 2022 4.2 Percent Share of India’s Exports in the World Table 3 highlights the share of India’s exports in terms of selected commodities and agricultural exports, total in world agricultural exports and their respective growth (both actual and potential) in value terms (US$ millions) between 2011 and 2020. The findings revealed that In- dia’s exports of agricultural products, total rose from US$ 30291.63 million to US$ 32083.77 million, i.e., by US$ 1792.14 million (5.92%) and accordingly, the actual increase in exports is higher than the potential (of US$ 1412.08 million) offered by the growth of world trade. However, the share of India’s agricultural products, total in world’s agricultural exports declined from 2.29 per cent to 2.15 per cent during 2011 to 2020. Regarding commod- ity-wise exports, India’s share in world trade during 2020 compared to 2011 showed impressive performance with reference to chillies and peppers, dry; rice and wheat, un- like other commodities during the above reference period. Only chillies and peppers, dry registered rapid (actual) increase in exports (US$ 603.53 million) over and above the potential increase (US$ 245.26 million) during the selected period. However, for other commodities, their respective actual increase in exports is far lower than their potential exports. It is interesting that the actual increase in exports is positive for chillies and peppers, dry (US$ 603.53 million) followed by rice (US$ 112.47 million), wheat (US$ 97.62 million) and sorghum (US$ 0.48 mil- lion). Regarding country-wise performance (Table 4), In- dia’s share in world’s total imports showed increasing trend for Bangladesh (from 8.28% to 10.12%), Iran (from 0.13% to 0.60%) and Thailand (from 0.92% to 1.03%). Accordingly, the actual increase in exports is higher than potential increase in these three countries. However, for other selected countries, it is disappointing that the share of India’s exports showed a declining trend during the ref- erence period and further, their actual increase in exports is considerably less than respective potential increase in exports. It is interesting that the actual increase in exports is highest for Bangladesh (US$ 546.17 million) followed by Thailand (US$ 43.90 million), Iran (US$ 36.88 mil- lion) and Saudi Arabia (US$ 4.23 million). On the whole, though India’s exports of agricultural products, total showed considerable increase in absolute (value) terms, its share in world agricultural exports showed a declining trend during 2011 to 2020. The impressive total export performance in terms of absolute value over and above the potential increase can be attributed to lower trade barriers in developed countries followed more recently by devel- oping countries and India’s structural reforms (especially external sector reforms) at domestic level. Further, re- duction in tariffs/non-tariffs barriers across the importing countries, depreciation of Indian rupee (historical low of 76.91 on 1.1.2020) and development of Export Promotion Zones (EPZs) has laid favourable environment for boost- ing overall agricultural exports from the country. Further, buoyed by rising global food prices since June 2020 with countries coming out of lockdowns and lifting the curbs imposed on trade, Indian agricultural exports have bene- fitted from favourable prices and according there is actual increase in exports during the reference period. However, the worry-some aspect is regarding the declining trend in share of India’s exports (agricultural products, total and for majority of selected agricultural commodities) in world agricultural exports in the liberalized regime. On the supply side, the main focus of the Government’s policies is to ensure the nation’s self sufficiency of staple commodities, distributing the production among the ur- ban and rural poor on subsidy and maintaining sufficient stocks by procurement largely from rural areas. The rising food prices resulting from the widening demand-supply gap consequent to the population increase have resulted in a major political issue forcing the Government to has- ten many unsuccessful measures to counter price hikes of essentials such as pulses, rice, sugar and wheat. The Government utilized input subsidies and MSPs as key domestic policy tools to promote agricultural interests by encouraging domestic production for food self-sufficien- cy. This hiked the farm subsidy and domestic support bill at about $51.2 billion during 2016-2017, which included certain farm input subsidies, price supports, storage and public food distribution. Further, in this direction, India directed its focus towards export control and highly re- stricted the import regime. India’s trading potential is also hurdled by trade barriers, market-distorting policies and Government’s excessive involvement in the marketing and procurement aspects of agricultural goods. India’s capacity to export has been hampered by some factors on the importers’ side such as high agricultural tariffs, SPS and non-tariff barriers like quality standards, import bans, labeling and packaging rules. As the recent COVID-19 outbreak shocked the world’s economies since 2020, there are apprehensions that agricultural businesses may suffer decline. However, notwithstanding the COVID-19 pan- demic, India’s agricultural exports have shown remarkable growth aided by favourable domestic weather conditions and export curbs implemented by many countries. Howev- er, future prospects of these exports depend on how much the latest surge in COVID-19 infections in India affects its agricultural production and global demand conditions. During 2021, the pandemic induced curbs and lockdowns 32 Research on World Agricultural Economy | Volume 03 | Issue 02 | June 2022 have not adversely impacted the production and export of agricultural products. There is spectacular growth of a few products that have led the overall growth in exports. The five products in this regard are wheat, vegetable oils, other cereals, molasses and non-basmati rice [20]. The ex- ceptionally robust growth in exports of these products has led to their total share increasing by 140 per cent in agri- cultural exports during 2021. The bumper harvest of these commodities is the key factor behind higher agricultural exports from India. The increasing agricultural exports from India during the past one decade and the satisfactory performance even during the COVID-19 pandemic has prompted the researchers to analyze the India’s export performance across selected commodities and countries and decompose the same into WDE, CCE, MDE and RCE through fitting CMSA model. 4.3 Decomposition of India’s Exports across Selected Commodities It is interesting to note from the Table 5 and Figure 1 that between 2011 to 2020, India’s agricultural products, total exports in absolute terms increased by US$ 1792.15 million. This was largely attributed to the highly posi- tive MDE (US$ 1761.51 million) followed by the WDE (US$ 821.28 million). However, both CCE (US$-216.41 million) and RCE (US$-574.22 million) are found to be negative. The higher value of actual increase in India’s exports compared to its potential increase implies higher competitiveness of Indian agricultural products during the reference period. So, it can be inferred that WDE and MDE are the main sources of India’s agricultural export performance, unlike CCE and RCE due to changes in external environment (trading policies of importing coun- tries and COVID-19 pandemic). Regarding decomposition of export performance of selected commodities, the CCE is equal to zero as per- centage increase in total world exports (r) and percentage increase in total world exports of commodity i (ri) would be equal, that is, (r = ri). The findings revealed that chillies and peppers, dry realized highest actual increase of US$ 603.53 million in its value, followed by rice (US$ 112.47 million), wheat (US$ 97.62 million) and sorghum (US$ 0.482 million). On the other hand, the export values for cotton lint (US$ –1947.17 million), maize (US$ –696.90 million), cashew nuts, shelled (US$ –490.92 million) and mangoes, mangosteens, guavas (US$ –63.90 million) showed declining trend. In case of all nine commodi- ties analyzed, the WDE was found to be positive for six commodities viz., apples; cashew nuts, shelled; chillies and peppers, dry; maize; mangoes, mangosteens, guavas and rice ranging from US$ 0.86 million (apples) to US$ 779.13 million (cashewnuts, shelled), unlike for remaining three commodities viz., cotton lint; sorghum and wheat. On the contrary, the MDE was negative in case of five commodities namely, cashewnuts, shelled (US$ –680.64 million); chillies and peppers, dry (US$ –440.97 million); cotton lint (US$ –131.65 million); rice (US$ –115.46 million) and sorghum (US$ –2.76 million) and positive in case of the remaining four commodities. Similarly, the RCE was also found to be negative in case of five com- modities and was found to be the lowest in case of maize (US$ –5373.83 million) and highest in case of chillies and peppers, dry (US$ 721.80 million). On the whole, the commodity-wise analysis asserts that positive net export performance of chillies and peppers, dry and rice could be attributed to higher WDE and RCE. In case of sorghum, positive value of RCE and in case of wheat, positive val- ues of both MDE and RCE contributed for their positive net export performance during the reference period. 4.4 Decomposition of India’s Exports across Selected Countries (Markets) It is interesting from Table 6 and Figure 2 that in case of country-wise analysis, the MDE is equal to 0 as ri = rij. During this period, actual increase in India’s exports was the highest in case of Iran (US$ 1035.83 million), fol- lowed by Saudi Arabia (US$ 702.43 million), Bangladesh (US$ 585.11 million) and Thailand (US$ 29.07 million). The WDE is found to be highest with China mainland (US$ 1568.95 million), followed by Vietnam (US$ 1240.37 million) and Bangladesh (US$ 1076.66 million). On the other hand, it is lowest with UAE (US$ –384.02 million) followed by USA (US$ –34.62 million) and Iran (US$ –10.95 million). Positive CCE was recorded in case of China, mainland, Iran, UAE and USA. It was highest with UAE (US$ 1157.14 million), followed by USA (US$ 187.50 million), China, mainland (US$ 102.90 million) and Iran (US$ 7.27 million) and lowest with Vietnam (US$ –1035.08 million), followed by Bangladesh (US$ –726.11 million) and Thailand (US$ –45.94 million). As India could not diversify their exports across above three export destinations, the CCE recorded negative values Again, the RCE was recorded to be negative in five markets. Highest negative value was recorded in case of China, mainland (US$ –2904.50 million) and the lowest in case of Thai- land (US$ –1.61 million). It is interesting that the negative values of RCE contributed to decline in India’s exports across the selected markets, except Thailand. Positive val- ues of WDE contributed to actual increase in India’s ex- ports for Bangladesh (also RCE), Saudi Arabia (also RCE) and Thailand. Highly negative CCE was compensated by positive WDE in case of Bangladesh and Thailand. How- 33 R es ea rc h on W or ld A gr ic ul tu ra l E co no m y | V ol um e 03 | Is su e 02 | Ju ne 2 02 2 Ta bl e 3. P er ce nt ag e Sh ar e of In di a in th e w or ld e xp or ts o f s el ec te d co m m od iti es (V al ue in U S$ M ill io n) d ur in g 20 11 a nd 2 02 0 C om m od it ie s 20 11 20 20 A ct ua l ∆ in I nd ia ’s ex po rt s P ot en ti al ∆ in I nd ia ’s ex po rt s (A ∆ /P ∆ )* 10 0 W or ld e xp or ts (R s) In di a’ s ex po rt s (R s) W or ld e xp or ts ex cl I nd ia (R s) Sh ar e of I nd ia ’s ex po rt s in W or ld ex po rt s (% ) W or ld ex po rt s (R s) In di a’ s ex po rt s (R s) W or ld e xp or ts ex cl I nd ia (R s) Sh ar e of I nd ia ’s ex po rt s in W or ld ex po rt s (% ) A pp le s 71 49 .6 0 14 .8 0 71 34 .8 0 0. 21 75 65 .6 8 14 .0 7 75 51 .6 2 0. 19 -0 .7 3 14 .7 1 67 9. 45 C as he w n ut s, sh el le d 30 37 .1 7 89 5. 14 21 42 .0 3 29 .4 7 44 10 .6 7 40 4. 23 40 06 .4 4 9. 16 -4 90 .9 1 12 8. 64 77 .7 4 C hi lli es a nd pe pp er s, d ry 13 17 .2 2 49 7. 05 82 0. 17 37 .7 3 24 53 .2 4 11 00 .5 8 13 52 .6 6 44 .8 6 60 3. 53 24 5. 26 10 8. 33 C ot to n lin t 20 84 1. 55 33 95 .6 9 17 44 5. 86 16 .2 9 14 03 2. 70 14 48 .5 2 12 58 4. 18 10 .3 2 -1 94 7. 17 31 6. 51 3. 15 M ai ze 33 78 6. 74 10 86 .1 8 32 70 0. 57 3. 21 36 75 0. 36 38 9. 28 36 36 1. 08 1. 06 -6 96 .9 0 17 0. 08 58 .8 0 M an go es , m an - go st ee ns , g ua va s 13 71 .5 2 20 1. 36 11 70 .1 7 14 .6 8 31 95 .8 4 13 7. 46 30 58 .3 8 4. 30 -6 3. 90 18 7. 61 53 .3 0 R ic e 79 5. 51 23 .8 5 77 1. 67 3. 00 11 87 .8 2 13 6. 32 10 51 .5 0 11 .4 8 11 2. 47 14 2. 32 72 3. 12 So rg hu m 17 17 .3 2 15 .9 9 17 01 .3 4 0. 93 17 09 .4 2 16 .4 7 16 92 .9 6 0. 96 0. 48 18 .0 5 55 4. 17 W he at 46 86 3. 89 14 5. 45 46 71 8. 45 0. 31 44 83 4. 11 24 3. 07 44 59 1. 04 0. 54 97 .6 2 99 .0 2 30 9. 98 O th er p ro du ct s 12 04 56 4. 65 24 01 6. 14 11 80 54 8. 51 1. 99 13 76 07 1. 26 28 19 3. 79 13 47 87 7. 47 2. 05 41 77 .6 5 89 .8 8 4. 74 A gr ic ul tu ra l pr od uc ts , t ot al 13 21 44 5. 18 30 29 1. 63 12 91 15 3. 56 2. 29 14 92 21 1. 09 32 08 3. 77 14 60 12 7. 32 2. 15 17 92 .1 4 14 12 .0 8 7. 08 R aw D at a So ur ce : w w w .fa o. or g Ta bl e 4. P er ce nt ag e sh ar e of In di a in th e ov er al l i m po rt s of s el ec te d co un tr ie s (V al ue in U S$ M ill io n) d ur in g 20 11 a nd 2 02 0 C ou nt ri es 20 11 20 20 A ct ua l ∆ in I nd ia ’s ex po rt s P ot en ti al ∆ in I nd ia ’s ex po rt s (A ∆ /P ∆ )* 10 0 O ve ra ll im po rt s In di a’ s ex po rt s W or ld im po rt s ex cl I nd ia Sh ar e of I nd ia ’s ex po rt s in W or ld im po rt s ex cl I nd ia (% ) O ve ra ll im po rt s In di a’ s ex po rt s W or ld im po rt s ex cl I nd ia Sh ar e of I nd ia ’s ex po rt s in W or ld im po rt s ex cl I nd ia (% ) B an gl ad es h 73 80 .2 1 61 0. 74 67 69 .4 7 8. 28 11 42 6. 66 11 56 .9 1 10 26 9. 75 10 .1 2 54 6. 17 37 2. 32 30 .9 4 C hi na m ai nl an d 95 51 7. 54 24 26 .6 6 93 09 0. 89 2. 54 15 76 93 .9 0 85 2. 71 15 68 41 .1 6 0. 54 -1 57 3. 95 17 1. 79 65 .6 1 Ir an 10 17 1. 70 13 .0 7 10 15 8. 64 0. 13 83 31 .3 8 49 .9 5 82 81 .4 3 0. 60 36 .8 8 17 .0 5 58 6. 66 M al ay si a 18 67 4. 35 41 1. 05 18 26 3. 30 2. 20 17 61 0. 11 73 .3 0 17 53 6. 81 0. 42 -3 37 .7 5 12 .5 80 0. 00 Sa ud i A ra bi a 19 55 3. 53 88 .9 5 19 46 4. 58 0. 45 20 47 2. 96 93 .1 8 20 37 9. 79 0. 46 4. 23 17 .7 7 56 2. 65 T ha ila nd 97 94 .8 0 89 .9 1 97 04 .8 9 0. 92 13 03 5. 97 13 3. 81 12 90 2. 15 1. 03 43 .9 0 34 .7 1 28 8. 18 U A E 14 02 1. 19 23 9. 70 13 78 1. 49 1. 71 16 36 6. 14 19 6. 23 16 16 9. 91 1. 20 -4 3. 47 47 .6 8 20 9. 73 U SA 10 71 41 .1 0 40 2. 08 10 67 39 .0 0 0. 38 14 64 94 .7 0 11 5. 68 14 63 79 .0 3 0. 08 -2 86 .4 0 41 .0 5 24 3. 60 V ie tn am 12 44 4. 25 23 7. 97 12 20 6. 28 1. 91 21 76 5. 68 17 9. 49 21 58 6. 20 0. 82 -5 8. 48 22 .2 3 -4 49 .8 5 O th er s 10 26 74 7. 00 25 77 1. 53 10 00 97 5. 01 2. 51 10 79 01 4. 00 29 23 2. 52 10 49 78 1. 10 2. 71 34 60 .9 9 30 3. 26 32 .9 7 To ta l a gr ic ul tu r- al im po rt s 13 21 44 5. 00 30 29 1. 63 12 91 15 3. 56 2. 29 14 92 21 1. 00 32 08 3. 77 14 60 12 7. 32 2. 15 17 92 .1 4 10 46 .3 6 9. 56 R aw D at a So ur ce : w w w .fa o. or g 34 R es ea rc h on W or ld A gr ic ul tu ra l E co no m y | V ol um e 03 | Is su e 02 | Ju ne 2 02 2 35 Research on World Agricultural Economy | Volume 03 | Issue 02 | June 2022 Table 5. Decomposition of India’s total agricultural products exports across selected commodities during 2011-2020 (Value in US$ Million) Commodities Actual ∆ in India’s exports WDE CCE MDE RCE Apples –0.73 (100.00) 0.86 (–118.57) 0.00 16.62 (–2279.68) –18.21 (2498.25) Cashew nuts, shelled –490.92 (100.00) 779.13 (–158.71) 0.00 –680.64 (138.65) –589.41 (120.06) Chillies and peppers, dry 603.53 (100.00) 322.70 (53.47) 0.00 –440.97 (–73.07) 721.80 (119.60) Cotton lint –1947.17 (100.00) –946.29 (48.60) 0.00 –131.65 (6.76) –869.24 (44.64) Maize –696.90 (100.00) 121.59 (–17.45) 0.00 4555.35 (–653.66) –5373.83 (771.11) Mangoes, mangosteens, guavas –63.90 (100.00) 324.91 (–508.50) 0.00 –9.80 (15.34) –379.01 (593.16) Rice 112.47 (100.00) 8.65 (7.69) 0.00 –115.46 (–102.65) 219.28 (194.97) Sorghum 0.48 (100.00) –0.08 (–16.34) 0.00 –2.76 (–572.17) 3.32 (688.50) Wheat 97.62 (100.00) –6.62 (–6.78) 0.00 34.92 (35.77) 69.32 (71.01) Agricultural products, total 1792.15 (100.00) 821.28 (45.83) –216.41 (–12.08) 1761.51 (98.29) –574.22 (–32.04) Note: Figures in parentheses indicate percent to respective total Raw Data Source: www.fao.org Figure 1. Decomposition of India’s total agricultural products exports (US$ Million) across selected commodities (2011-2020) ever, negative CCE in case of majority of the selected markets indicates India’s specialization in exporting the commodities having slow growing world demand during the study period. It is important that since December, 2019, the export curbs imposed by the majority countries in view of COVID-19 pandemic have affected the CCE and RCE of majority of the selected commodities. That is, though domestic food security was not threatened during COVID-19 pandemic, the export curbs across the major importing countries led to lower actual increase in exports 36 Research on World Agricultural Economy | Volume 03 | Issue 02 | June 2022 of selected commodities compared to their respective potential exports. However, in countries like Bangladesh, Iran and Thailand, the actual increase in exports is great- er than their respective potential exports in view of their importing policies and Government contracts to import and stock under present circumstances of COVID-19. So, this pandemic also helped India to augment exports to these countries. While unrelated to COVID-19, the ongoing political disturbances in Myanmar have di- verted grain demand of Southeast Asia towards India and their exports increased to Vietnam, Thailand and Malaysia [21]. Table 6. Decomposition of India’s total agricultural products exports across selected countries during 2011-2020 (Value in US$ Million) Commodities Actual ∆ in India’s exports WDE CCE MDE RCE Bangladesh 585.11 (100.00) 1076.66 (184.01) –726.11 (–124.10) 0.00 234.55 (40.09) China mainland –1232.66 (100.00) 1568.95 (–127.28) 102.90 (–8.35) 0.00 –2904.50 (235.63) Iran 1035.83 (100.00) –10.95 (–1.06) 7.27 (0.70) 0.00 1039.52 (100.36) Malaysia –102.44 (100.00) 7.57 (–7.39) –29.88 (29.17) 0.00 –80.12 (78.22) Saudi Arabia 702.43 (100.00) 11.47 (1669.74) –10.41 (–990.54) 0.00 701.37 (–579.20) Thailand 29.07 (100.00) 76.62 (160.79) –45.94 (297.47) 0.00 –1.61 (–358.26) UAE –828.91 (100.00) –384.02 (–162.40) 1157.14 (–81.09) 0.00 –1602.02 (343.49) USA –204.81 (100.00) –34.62 (–24.65) 187.50 (–54.55) 0.00 –357.68 (179.20) Vietnam –477.09 (100.00) 1240.37 (–120.72) –1035.08 (–681.82) 0.00 –682.38 (902.53) Note: Figures in parentheses indicate percent to respective total Raw Data Source: www.fao.org Figure 2. Decomposition of India’s total agricultural products exports (US$ Million) across selected countries (2011-2020) 37 Research on World Agricultural Economy | Volume 03 | Issue 02 | June 2022 5. Conclusions Findings of the CMSA revealed that though Indian exports of agricultural products, total showed increasing trend (absolute terms), the shares of selected commodi- ties’ exports and agricultural products, total in total world agricultural exports showed declining trends during the past decade, 2011 to 2020. All the selected commodities except wheat registered significant and positive growth rates in terms of value of exports during 1991-2020. It is heartening that even with the advent of COVID-19 pan- demic and the imposition of export curbs by the importing countries, the India’s export performance in Bangladesh, Iran and Thailand markets showed impressive perfor- mance. This was mainly attributed to WDE compared to CCE, MDE and RCE. That is, the competiveness of India’s exports remained prone to high inconsistency arising out of changing external environment and import restrictions in view of COVID-19 pandemic. Both MDE and RCE with respect to commodity-wise exports and CCE and RCE with respect to country-wise exports are found negative for majority of commodities and countries (markets) respectively. These findings are in tune with the Indonesian cinnamon exports, as the MDE was found negative implying the difficulty of its exports to the US market [22]. However, the findings are contrast to China’s performance of high technology, medium technology and low technology exports, as it is mainly attributed to its competitive strength in the global market, though decreas- ing trend has been observed in the competitiveness of all three categories [23]. In view of these findings, sustaining India’s agricultural export performance deserves special attention through boosting CCE, MDE and RCE. This will certainly depend on India’s internal situation and glob- al demand conditions. Further, it would also depend on whether importing countries continue to maintain export restrictions and trade curbs. Since, India’s overall agricul- tural export performance seem satisfactory during the past decade, it is essential to promote export competitiveness through withstanding export curbs imposed by the import- ing nations in the context of pandemic, foreign exchange rate fluctuations (not only absolute but relative also) and able to respond quickly to changes in external trade en- vironment should deserve special attention. Accordingly, boosting the export competitiveness in traditional markets and exploring new markets to increase the export share is of immediate concern to make India as major player in the world trade. So, in the future, India should focus on countries where it enjoys competitive advantage to increase foreign exchange in the years to come. So, India should harness its agricultural export potential, through suitable policy instruments, to make India global power in agriculture and raise farmers income. Public and private stakeholders across the value chain of each agricultural commodity should be updated with innovative solutions to address the challenges of upgrading the products, tech- nologies, business models, policy environments etc., to realize competitive trade in the global market [24]. One of the important limitations of CMSA is that it considers demand as an exogenous component and further the exporters help generate demand by activating inno- vation and product differentiation processes [25]. So, price competitiveness alone cannot explain about the market penetration, as the demand evolution is influenced by a number of policies being implemented by the exporter countries. Conflict of Interest There is no conflict of interest. References [1] Singh, K., Sain, I., 2003. Prospects of Agricultural exports of India: A Composite Index Approach. In- dian Journal of Agricultural Economics. 58(4), 781- 799. [2] Directorate General of Commercial Intelligence and Statistics (DGCI&S), Kolkata, under the Ministry of Commerce, Government of India. [3] Cook, M.L., Breadhl, M.E., 1991. Agribusiness Competitiveness in the 1990s: Discussion. Ameri- can Journal of Agricultural Economics. 73(5), 1472- 1473. [4] Pursell, G., Gupta, A., 1997. Trade Policies and Incentives in Indian Agriculture: Methodology, Background Statistics and Protection and Incentive Indicators, 1965-1995. New Delhi: Policy Research Working Paper Series 1953, The World Bank (Back- ground Paper No.1). [5] Singh, K., 2014. A Constant Market Share Analysis of India’s Export Performance. Foreign Trade Re- view. 49(2), 141-161. DOI: https://doi.org/10.1177/0015732514525190 [6] González Pandiella, A., 2015. A Constant Market Share Analysis of Spanish Goods Exports, OECD Economics Department Working Papers, No. 1186, OECD Publishing, Paris. DOI: https://doi.org/10.1787/5js69lb4b5mt-en [7] Pankaj Jain, M., 2017. Constant Market Share Anal- ysis of Export Competitiveness of Cotton: A Com- parative Study of India and China. Pacific Business Review International. 10(1), 77-84. 38 Research on World Agricultural Economy | Volume 03 | Issue 02 | June 2022 [8] Varalakshmi, K., Devatkal, S., 2017. Competitive- ness of Indian bovine meat exports-constant market share analysis. Indian Journal of Animal Sciences. 87(8), 1026-1033. [9] Madan, S., Sharma, R., 2018. Trade Competitiveness of Indian Wheat during Post-Reform Period, Asian Review of Social Sciences. 7(1), 25-32. [10] Richardson, J.D., 1971. Some Sensitivity Tests for a Constant Market Share Analysis of Export Growth. The Review of Economics and Statistics. 53, 300- 304. [11] Bowen, H.P., Pelzman, J., 1980. A Constant Market Share Analysis of U.S. Export Growth. Economic Discussion Paper No. 10. U.S.: Department of La- bour. [12] Margarida, P.F., Rayment, P., 1984. Export of Man- ufactures from South European Countries: Deman and Competitiveness Factors. Journal of World Trade Law. 8, 235-251. [13] Veeramani, C., 2007. Sources of India’s export growth in pre and post-reform periods. Economic and Political Weekly. XLII(25), 2419-2427. [14] Tyszynskin, H., 1951. World trade in manufactured commodities, 1899-1950. The Manchester School of Economics and Socials Studies. 19(3), 272-304. DOI: https://doi.org/10.1111/j.1467-9957.1951.tb00012.x [15] Ahmadi-Esfahani, F.Z., 1995. Wheat market shares in the presence of Japanese import quotas. Journal of Policy Modeling. 17(3), 315-323. DOI: https://doi.org/10.1016/0161-8938(94)00036-F [16] Jepma, C.J., 1989. Extensions of the constant-mar- ket-shares analysis with an application to long-term export data of developing countries. The balance between industry and agriculture in economic devel- opment. International Economic Association Series, Palgrave Macmillan UK. pp. 129-143. [17] Richardson, J.D., 1971. Constant market shares anal- ysis of export growth. Journal of International Eco- nomics. 1(2), 227-239. DOI: https://doi.org/10.1016/0022-1996(71)90058-4 [18] Capobianco-Uriarte, M., Aparicio, J., De Pablo-Va- lenciano, J., 2017. Analysis of Spain´s competitive- ness in the European tomato market: An application of the Constant Market Share method. Spanish Jour- nal of Agricultural Research. 15(3), e0113. DOI: https://doi.org/10.5424/sjar/2017153-10629 [19] Kozicka, M., Kalkuhl, M., Saini, S., et al., 2015. Modelling Indian Wheat and Rice Sector Policies. In- dian Council for Research on International Economic Relations. [20] Love, J., 1984. External Market Conditions, Compet- itiveness, Diversification and LDC’s Export. Journal of Development Economics. 16, 279-291. [21] Murali, D., Palit, A., 2021. India Records High Agricultural Export Growth amidst COVID-19 Pandemic, ISAS Briefs, Quick analytical responses to occurrences in South Asia. [22] Sari, E.T., Divinagracia, M.R.G., 2021. Revealed comparative advantage and constant market share analysis of Indonesian cinnamon in the world market. International Journal of Economic Policy in Emerg- ing Economies. 14(2),187-198. [23] Bagaria, N., Ismail, S., 2019. Export Performance of China: A Constant Market Share Analysis. Frontiers of Economics in China. 14(1), 110-130. DOI: https://doi.org/10.3868/s060-008-019-0007-9 [24] Neven, D., 2014. Developing sustainable food value chains - Guiding principles. Food and Agriculture Organization of the United Nations, Rome. [25] Fagerberg J., Sollie G., 1985. The Method of Con- stant-Market-Shares Analysis Revisited. Central Bu- reau of Statistics of Oslo, WP N. 9. https://doi.org/10.1111/j.1467-9957.1951.tb00012.x https://doi.org/10.1016/0161-8938(94)00036-F https://doi.org/10.1016/0022-1996(71)90058-4