2072-64142411-140610.17059/ekon.reg.2024-1-2Stress in the Real Economy of Russian Regions under the Pandemic and SanctionsСтресс реального сектора российских регионов в условиях пандемии и санкцийhttps://orcid.org/0000-0002-3152-3934MalkinaMarina Yu. МалкинаМарина Юрьевна mmuri@yandex.ruLobachevsky State University of Nizhny NovgorodНижегородский государственный университет им. Н.И. Лобачевского2011632Copyright © 2024 Marina Yu. MalkinaCopyright © 2024 Марина Юрьевна Малкина2024Marina Yu. MalkinaМарина Юрьевна МалкинаCC BY 4.0https://www.economyofregions.org/ojs/index.php/er/article/view/468https://www.economyofregions.org/ojs/index.php/er/article/download/468/271

Recently, the Russian economy has been affected by sanctions and pandemic shocks. Russian regions reacted differently depending on their spatial location and sectoral structure of economies. Using monthly data for 2016-2023, the article assesses the dynamics of stress of regions’ industrial production volume, retail turnover and volume of paid services to the population. A stress index is calculated as a moving difference between the standard deviation and the average growth rate of the indicator compared to the corresponding period of the previous year. An integrated stress index is a simple sum of individual stress indices normalised using the Z-score method within the panel data framework. As a result, time series of individual and integrated stress indices at the national, federal district and regional levels were obtained. The average stress levels of different Russian regions were compared for the entire period and three sub-periods: pre-pandemic, pandemic (from March, 2020 to February, 2022) and post-pandemic/new sanctions. The data revealed a greater and relatively uniform sensitivity of the service sector of Russian regions to the pandemic; various reactions of regional industries to sanctions, causing the diversification effect across the country; greater trade response to pandemic shocks and industry response to new sanctions. On average, the constituent entities of the North Caucasus Federal District turned out to be the most vulnerable to shocks, while the regions of the Siberian Federal District showed the greatest stability. The study demonstrated that sectoral structure and regional income level are significant factors determining the resilience of the regional real economy to pandemic shocks, while spatial location is also important in response to sanctions.

В последние годы российская экономика пережила серию санкционных и пандемических шоков, однако реакция российских регионов на них оказалась весьма различной, что объясняется разным пространственным положением и отраслевой структурой их экономик. В настоящей статье на основе помесячных данных за 2016–2023 гг. оценивается в динамике уровень стресса региональных физических объемов промышленного производства, оборота розничной торговли и объема платных услуг населению. Индекс стресса рассчитывался как скользящая разница между стандартным отклонением и средним темпом прироста показателя к сопоставимому периоду прошлого года. Интегральный индекс стресса представлен в виде простой суммы частных индексов стресса, нормированных с помощью метода эквивалентных дисперсий в пределах панельной выборки. В результате получены временные ряды частных и интегрального индексов стресса в масштабах страны, федеральных округов и субъектов РФ, проведены межрегиональные сравнения среднего уровня стресса в рассматриваемом периоде и в трех его подпериодах (допандемическом, пандемическом (03.2020 — 02.2022) и постпандемическом / новом санкционном). Полученные данные свидетельствуют о большей и относительно однотипной чувствительности сферы услуг российских регионов к пандемии, разной реакции промышленности регионов на санкционные шоки, что создавало эффект диверсификации в масштабах страны, большей реакции торговли на пандемический шок и промышленности на новый санкционный шок. В среднем наиболее уязвимыми к шокам оказались субъекты Северо-Кавказского ФО, а наибольшую устойчивость проявили регионы Сибирского ФО. Исследование показало, что важными факторами устойчивости реального сектора региональных экономик к пандемическому шоку являются отраслевая структура и уровень доходов в регионе, а к санкционным шокам— также его пространственное размещение.

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The transmission of financial stress from advanced to emerging economies. Emerging Markets Finance and Trade, 47 (sup2), 40-68. https://doi.org/10.2753/REE1540-496X4703S203Cevik, E. I., Dibooglu, S., & Kutan, A. M. (2013). Measuring financial stress in transition economies. Journal of Financial Stability, 9 (4), 597-611. https://doi.org/10.1016/j.jfs.2012.10.001Du, X., & Wang, Z. (2022). Multinationals, global value chains, and the welfare impacts of economic sanctions. Economics Letters, 220 , 110870. https://doi.org/10.1016/j.econlet.2022.110870Giannakis, E., & Bruggeman, A. (2020). Regional disparities in economic resilience in the European Union across the urban–rural divide. Regional Studies, 54 (9), 1200-1213. https://doi.org/10.1080/00343404.2019.1698720Haddou, S. (2022). International financial stress spillovers to bank lending: Do internal characteristics matter? International Review of Financial Analysis, 83 , 102289. https://doi.org/10.1016/j.irfa.2022.102289Hakkio, C. S., & Keeton, W. R. (2009). Financial stress: What is it, how can it be measured, and why does it matter? Economic Review, 94 (2), 5-50.Kolomak, E. (2020). Economic effects of pandemic-related restrictions in Russia and their spatial heterogeneity. R-Economy, 6 (3), 154-161. https://doi.org/10.15826/recon.2020.6.3.013Lagravinese, R. (2015). Economic crisis and rising gaps North-South: evidence from the Italian regions. Cambridge Journal of Regions, Economy and Society, 8 (2), 331–342. https://doi.org/10.1093/cjres/rsv006Malkina, M. Yu., & Balakin, R. V. (2022). Stress Index of the Tax System of the Russian Federation in Terms of Tax Revenues. Journal of Tax Reform, 8 (3), 251–269. https://doi.org/10.15826/jtr.2022.8.3.120Martin, R. (2012). Regional economic resilience, hysteresis and recessionary shocks. Journal of Economic Geography, 12 (1), 1–32. https://doi.org/10.1093/jeg/lbr019Martin, R., Sunley, P., Gardiner, B., & Tyler, P. (2016). How Regions React to Recessions: Resilience and the Role of Economic Structure. Regional Studies, 50 (4), 561–585. https://doi.org/10.1080/00343404.2015.1136410Martini, B. (2020). Resilience and economic structure. Are they related? Structural Change and Economic Dynamics, 54 , 62-91. https://doi.org/10.1016/j.strueco.2020.03.006Nazlioglu, S., Soytas, U., & Gupta, R. (2015). Oil prices and financial stress: A volatility spillover analysis. Energy Policy, 82 , 278-288. https://doi.org/10.1016/j.enpol.2015.01.003Nguyen, T. T., & Do, M. H. (2021). Impact of economic sanctions and counter-sanctions on the Russian Federation’s trade. Economic Analysis and Policy, 71 , 267-278. https://doi.org/10.1016/j.eap.2021.05.004Polat, O., & Ozkan, I. (2019). Transmission mechanisms of financial stress into economic activity in Turkey. Journal of Policy Modelling, 41 (2), 395-415. https://doi.org/10.1016/j.jpolmod.2019.02.010Semin, A., Vasiljeva, M., Sokolov, A., Kuznetsov, N., Maramygin, M., Volkova, M., Zekiy, A., Elyakova, I., & Nikitina, N. (2020). Improving Early Warning System Indicators for Crisis Manifestations in the Russian Economy. Journal of Open Innovation: Technology, Market, and Complexity, 6 (4), 171. https://doi.org/10.3390/joitmc6040171Sheng, X., Kim, W. J., Gupta, R., & Ji, Q. (2023). The impacts of oil price volatility on financial stress: Is the COVID-19 period different? International Review of Economics & Finance, 85 , 520-532. https://doi.org/10.1016/j.iref.2023.02.006Turgel, I. D., Chernova, O. A., & Usoltceva, A. A. (2022). Resilience, robustness and adaptivity: Large urban Russian Federation regions during the COVID-19 crisis. Area Development and Policy, 7 (2), 222-244. https://doi.org/10.1080/23792949.2021.1973522Tuzova, Y., & Qayum, F. (2016). Global oil glut and sanctions: The impact on Putin’s Russia. Energy Policy, 90 , 140-151. https://doi.org/10.1016/j.enpol.2015.12.008Zhang, D., & Li, B. (2022). What can we learn from financial stress indicator? Finance Research Letters, 50 , 103293. https://doi.org/10.1016/j.frl.2022.103293