Koshkin A.V., Shcheglov M.Y., Bit-Zaya G.A., Kalinichenko A.S., Mikhaleva D.M. —
Anti-Crisis Industrial Policy of the Constituent Entities of the Russian Federation during the COVID-19 Pandemic
// Finance and Management. – 2024. – ¹ 1.
– P. 12 - 38.
DOI: 10.25136/2409-7802.2024.1.69641
URL: https://en.e-notabene.ru/flc/article_69641.html
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Abstract: The COVID-19 pandemic was one of the first “black swan” for the global economy. Regional authorities in Russia were faced to support their regional economies but they were faced with uncharacteristic independence. The issue of assessing the effectiveness of regional anti-crisis industrial policy measures in Russia during the COVID-19 crisis is becoming urgent. The purpose of this study is to search for the most successful measures of regional support in Russia during the designated period. The study is based on the conceptual framework of the St. Petersburg School of Industrial Policy. Descriptive statistics, cluster analysis, and correlation analysis are used as statistical methods of analysis. 1196 anti-crisis industrial policy measures were classified in all 85 regions of the Russian Federation. A scatter diagram of regions was constructed with indicators of the scale for assessing the intensity of the anti-crisis industrial policy and the scale of the impact of the crisis on socio-economic indicators. Four clusters were identified: (1) regions that practically did not implement an anti-crisis industrial policy and suffered during the crisis; (2) regions that have significant economic stability and are less likely to resort to active anti-crisis policies; (3) regions, the values of indicators of the dynamics of socio-economic indicators of which are at an average and below level, but are pursuing, on average, a more intensive anti-crisis policy; (4) regions that pursued an active anti-crisis industrial policy and achieved good socio-economic indicators. Correlation analysis did not reveal a stable connection between the intensity of the anti-crisis policy and the crisis dynamics of socio-economic indicators. The study also presents leading regions and outsider regions in terms of anti-crisis industrial policy measures for each of the 4 clusters.