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Searching for trade partners: Assessing the feasibility of free trade agreements using principal component analysis
https://doi.org/10.32609/0042-8736-2025-11-60-78
Abstract
The article tackles a problem of rating the Russian Federation’s trading partners based on the advisability of concluding free trade agreements with them. When constructing the rating, the indicators of foreign trade of the Russian Federation and a potential partner are taken into account, which can be divided into three blocks: (1) the economic attractiveness of the partner for the Russian Federation, (2) the potential for reducing trade barriers, and (3) the risks of opening the domestic market. For each block, using the principal component method and the best proximity point, integral indicators are constructed that characterize each of the three aspects of advisability. The indicators for individual blocks are combined into a common indicator of the advisability of concluding a free trade agreement, based on which a rating of partners is compiled. The methodology for assessing the advisability was developed considering Russia’s tasks in increasing non-resource non-energy exports and priority goods for export, Russia’s need for imports, as well as possible threats to the competitiveness of national industries posed by the liberalization of trade in goods “sensitive” to imports. Priorities for exports and the need for imports are determined in accordance with national priority projects, orders of the Government of Russia and decisions of the Supreme Eurasian Economic Council. As a result, rankings of 39 potential partners are presented. The first place in the final rating by a significant margin is occupied by Mongolia, with which a free trade agreement has already been signed but has not yet been ratified by members of the Eurasian Economic Union. Among the leaders of the rating were Kenya, Turkey, India and Tanzania.
About the Authors
T. G. Zueva
Russian Foreign Trade Academy of the Ministry of Economic Development of the Russian Federation
Russian Federation
Russian Federation
Tatiana G. Zueva
Moscow
O. V. Savelyev
HSE University
Russian Federation
Russian Federation
Oleg V. Savelyev
Moscow
K. K. Furmanov
Central Economics and Mathematics Institute of the Russian Academy of Sciences
Russian Federation
Russian Federation
Kirill К. Furmanov
Moscow
References
1. Aivazian S. A. (2003). Towards a methodology of measuring of the population’s life quality synthesized categories. Economics and Mathematical Methods, Vol. 39, No. 2, pp. 33—53. (In Russian).
2. Aivazian S. A. (2012). Quality of life and living standards analysis: An econometric approach. Moscow: Nauka. (In Russian).
3. Aivazian S. A., Stepanov V. S., Kozlova M. I. (2006). Measuring the synthetic categories of quality of life in a region and identification of main trends to improve the social and economic policy (Samara Region and its constituent territories). Applied Econometrics, No. 2, pp. 18—84. (In Russian).
4. Arkhipova M. Y., Sirotin V. P., Sukhareva N. A. (2018). Development of a composite indicator for measuring the value and dynamics of digital inequality in Russia. Voprosy Statistiki, Vol. 25, No. 4, pp. 75—87. (In Russian).
5. Barabashev A. G., Zarochintcev S. V., Makarov I. A. (2022). How to find the “black swans” of high-technology development: An indicative approach. Public Administration. E-journal (Russia), No. 95, pp. 192—208. https://doi.org/10.24412/2070-13812022-95-192-208
6. Borzykh D. A., Furmanov K. K., Chernysheva I. K. (2016). On the method of constructing dynamically comparable composite indices. Vestnik NSUEM, No. 4, pp. 67—83. (In Russian).
7. Volkova M. I. (2010). Comparison of objectivistic and subjectivist approaches to measurement of synthetic latent categories of quality of life of the population: Results of the empirical analysis of Russian data. Applied Econometrics, No. 3, pp. 62—90. (In Russian).
8. Zuev V. N., Ostrovskaya E. Y., Skryabina V. Y. (2023). Trade damper effect of regional trade agreements. Voprosy Ekonomiki, No. 2, pp. 83—99. (In Russian). https://doi.org/10.32609/0042-8736-2023-2-83-99
9. Isakin M. A., Teplykh G. V. (2011). Research of higher engineering education quality on the base of students interviewing data by nonlinear principal components analysis (NLPCA). Applied Econometrics, No. 1, pp. 70—96. (In Russian).
10. Isachenko T. M., Medvedkova I. A. (2024). Reorientation of trade between the European Union and the Russian Federation under sanctions. St Petersburg University Journal of Economic Studies, Vol. 40, No. 2, pp. 248—272. (In Russian). https://doi.org/10.21638/spbu05.2024.206
11. Isachenko T. M., Trudaeva T. A., Zueva T. G., (2024). Russian possible effects of concluding of a free trade agreement between the EAEU and Indonesia. Russian Foreign Economic Journal, No. 9, pp. 7—29. (In Russian). https://doi.org/10.24412/2072-80422024-9-7-29
12. Knobel A., Chokaev B. (2014). Possible economic effects of CU—EU trade agreement. Voprosy Ekonomiki, No. 2, pp. 68—87. (In Russian). https://doi.org/10.32609/0042-8736-2014-2-68-87
13. Makarov I. A. (2024). Composite indices for governing digitalization: Methods for construction. Public Administration Issues, No. 3, pp. 81—109. (In Russian). https://doi.org/10.17323/1999-5431-2024-0-381-109
14. Furmanov K. K., Turovets Y. V. (2024). Assessing the impact of external shocks on the development of the manufacturing industry. Problemy Prognozirovaniya, No. 5, pp. 128—140. (In Russian). https://doi.org/10.47711/0868-6351-206-128-140.
15. Balassa B. (1965). Trade liberalization and “revealed” comparative advantage. The Manchester School, Vol. 33, No. 2, pp. 92—123. https://doi.org/10.1111/j.1467-9957.1965.tb00050.x
16. Balassa B. (1989). “Revealed” comparative advantage revisited. In: B. Balassa (ed.). Comparative advantage, trade policy and economic development. New York and London: Harvester Wheatsheaf, pp. 63—79.
17. Bandura R. (2008). A survey of composite indices measuring country performance: 2008 Update. UNDP/ODS Working Paper. New York: Office of Development Studies, United Nations Development Programme.
18. Block S., Emerson J. W., Esty D. C., de Sherbinin A., Wendling Z. A., et al. (2024). 2024 Environmental Performance Index. New Haven, CT: Yale Center for Environmental Law & Policy.
19. Cheong D. (2010). Methods for ex ante economic evaluation of free trade agreements. ADB Working Paper Series on Regional Economic Integration, No. 52.
20. Coulibaly S. (2009). Evaluating the trade effect of developing regional trade agreements: А semi-parametric approach. Journal of Economic Integration, Vol. 24, No. 4, pp. 709—743. https://doi.org/10.11130/jei.2009.24.4.709
21. Dadush U., Prost E. D. (2023). Preferential trade agreements, geopolitics, and the fragmentation of world trade. World Trade Review, Vol. 22, No. 2, pp. 278—294. https://doi.org/10.1017/S1474745623000022
22. Dreher A. (2006). Does globalization affect growth? Evidence from a new Index of Globalization. Applied Economics, Vol. 38, No. 10, pp. 1091—1110. https://doi.org/10.1080/00036840500392078
23. Gonciarz T., Verbeet T. (2025). Significance of most-favoured-nation terms in global trade: A comprehensive analysis. WTO Staff Working Paper, No. ERSD-2025-02.
24. Gygl S., Haelg F., Potrafke N., Sturm J.-E. (2019): The KOF Globalisation Index — revisited. Review of International Organizations, Vol. 14, No. 3, pp. 543—574 https://doi.org/10.1007/s11558-019-09344-2
25. Jha R., Bhanu Murthy K. V. (2006). Environmental sustainability: A consumption approach. New York: Routledge. https://doi.org/10.4324/9780203014394
26. Khachaturian T., Riker D. (2016). The impact of U.S. trade agreements on growth in output and labor productivity of FTA partner countries. U.S. International Trade Commission Working Paper Series, No. 2016-10-A.
27. Krugman P. R. (1987). Is free trade passe? Journal of Economic Perspectives, Vol. 1, No. 2, pp. 131—144. https://doi.org/10.1257/jep.1.2.131
28. Krugman P. R., Obstfeld M., Melitz M. (2012). International economics: Theory and policy. Global Edition. Harlow, etc: Pearson.
29. Mazziotta M., Pareto A. (2013). Methods for constructing composite indices: One for all or all for one? Rivista Italiana di Economia, Demografia e Statistica, Vol. 67, No. 2, pp. 67—80.
30. Mikic M., Gilbert J. (2007). Trade statistics in policymaking. A handbook of commonly used trade indices and indicators. Bangkok: UN Economic and Social Commission for Asia and the Pacific.
31. Plummer M. G., Cheong D., Hamanaka S. (2010). Methodology for impact assessment of free trade agreements. Mandaluyong City: Asian Development Bank.
32. Susanto D., Rosson C. P., Adcock F. J. (2007). Trade creation and trade diversion in the North American Free Trade Agreement: The case of the agricultural sector. Journal of Agricultural and Applied Economics, Vol. 39, No. 1, pp. 121—134. https://doi.org/10.1017/S1074070800022793
33. UNDP (2024). Human development report 2023/2024. Breaking the gridlock: Reimagining cooperation in a polarized world. New York: United Nations Development Programme.
34. U.S. International Trade Commission (2016). Economic impact of trade agreements implemented under trade authorities procedures, 2016 Report.
35. Washington, DC. Viner J. (1950). The customs union issue. New York: Carnegie Endowment for International Peace.
36. World Economic Forum (2024). Travel & tourism development index 2024. Insight Report. Geneva.
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For citations:
Zueva T.G., Savelyev O.V., Furmanov K.K. Searching for trade partners: Assessing the feasibility of free trade agreements using principal component analysis. Voprosy Ekonomiki. 2025;(11):60-78. (In Russ.) https://doi.org/10.32609/0042-8736-2025-11-60-78
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