Economic effects of pandemic-related restrictions in Russia and their spatial heterogeneity

Abstract

Relevance. The spatial dimension of economic development is always in the focus of the political and research agenda. Regional disparities, along with different rates of the spread of the coronavirus pandemic and decentralization of restrictive measures, resulted in significant differences in Russian regions’ economic responses to the pandemic. The relevance of this study is determined by the need to investigate the reasons behind these regional discrepancies. Research objective. This study aims to analyze the economic consequences of the pandemic-related restrictions and the degree of the spatial heterogeneity of these effects in Russia. Data and methods. We rely on the Rosstat data to build the indicator of the level of economic activity in Russian regions in April-May 2020. We tested the hypothesis that developed regions, large cities and small businesses will suffer more, and considered the impact of the reduced demand in world markets. The significance of the factors was tested by using regression analysis. Results. The results of our analysis have shown that economic activity in the country decreased by almost 25% due to the lockdown measures, and in some regions, the decline in production output was more than twofold. The urban economy proved to be more resilient to the restrictive measures compared to the average business activity in the country. Due to its diversified structure, the urban system has a wider adaptive capacity and survived the first period of the lockdown with less losses. SMEs, due to their flexibility and entrepreneurial initiative, supported the economies of their regions. Larger and more developed regions, all other things being equal, suffered more from the pandemic. This influence, however, was offset by other factors, and the expected trend towards spatial convergence was not observed. Conclusions. While all the previous crises that Russia experienced in the post-Soviet period were accompanied by decreasing regional discrepancies, during the COVID-19 pandemic, the spatial differences, on the contrary, increased.

How the 2020 pandemic affected tax revenues in Russian regions?

“…The conclusion that advanced regions (with a large GRP per capita) are more susceptible to the pandemic is consistent with (Kolomak, 2020). On the one hand, most of these regions are home to the lucrative extractive industries that have been hit hardest by the pandemic.…”

“…Our finding that tax revenues are positively associated with the share of small businesses contradicts the widespread belief that small businesses are significantly more affected by the pandemic shock (Shafi et al, 2020;Dai et al, 2021), albeit it again coincides with (Kolomak, 2020). This Russian phenomenon can be explained by the fact that Russian SMEs received significant government support during the pandemic (Mau (Ed.…”

“…By incorporating data on credit cards consumer spending into an input-output model, Darougheh (2021) concludes that the biggest recession during the pandemic is in end-user industries, especially in the service sector, while the production of intermediate goods act as an output stabilizer. In the study of Russian regions, Kolomak (2020) proposes the index of regional economic activity. Plotting a regression for this index shows that the 2020 pandemic has dealt the biggest blow to the economies of larger and more advanced regions.…”

Impact of the 2020 Pandemic on Revenue from Various Taxes in the Russian Regions

“…In addition, scientists explore the resilience of various regional economies to economic crises, including pandemics (Brada et al, 2021;Mikheeva, 2021), and the factors affecting resilience (Kolomak, 2020;Pietro et al, 2020). Few studies directly focus on the response of the Russian regional fiscal systems, their revenues and expenditures, and the level of debt to the 2020 pandemic (Klimanov et al, 2021).…”

Econometric Analysis of Poverty Factors of the Working Population

“…В наибольшую группу вошли 53% респондента, которые могут позволить еду и новую одежду, но не могут позволить себе приобрести необходимые товары Keywords: questioning, econometric modeling, Republic of Bashkortostan, logit models, probit models, significance of coefficients, probability, Gretl software package, poverty of the working population, composition of respondents. В настоящее время актуален вопрос, связанный с пандемией коронавируса, влиянием его не только на национальные экономики, но и на всемирную экономику и уровень жизни [15]. Пока рано обследовать полное влияние пандемии на экономику, но возможно рассмотреть некоторые вопросы, связанные с ней.…”