Статья

The effectiveness of Russian government policy to support smes in the COVID-19 pandemic

E. Razumovskaia, L. Yuzvovich, E. Kniazeva, M. Klimenko, V. Shelyakin,
2021

This study was aimed at developing a cognitive—econometric model for assessing the effectiveness of the current governmental policies to support enterprises in Russia in the context of pandemic propagation. Using the Granger test and correlation analysis, we formed a system of key indicators that characterizes the economic development of SMEs (small and medium-sized enterprises) in Russia. Based on the revealed causal relationships and correlation coefficients, a model describing the impact of public policy support instruments on SME economic development was built using cognitive modeling. By means of the additive convolution method, the correlation coefficient between the Russia Small Business Index (RSBI) and the COVID-19 prevalence rate was used to predict the 2020 year-end RSBI value. Regarding the RSBI index forecast, the effectiveness of instruments of the state support for SMEs was evaluated. It was determined how much these indicators of the anti-crisis package of measures should change to increase SMEs’ business activities. The developed cognitive model can be utilized by private and governmental institutions to continuously monitor the effectiveness of public policies that support SMEs. It can also be used as a preventive indicator to evaluate the impact of the anti-crisis measures during pandemics and in the case of other exogenous risks threatening SMEs. The originality of the research results was determined by the econometric methods applied to empirically assess the effectiveness and degree of impact of governmental measures on the operation of SMEs under conditions of uncertainty. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.

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Версии

  • 1. Version of Record от 2021-04-27

Метаданные

Об авторах
  • E. Razumovskaia
    Department of Finance, Money Circulation, and Credit, Ural Federal University Named after the First President of Russia B.N., Yeltsin, 19 Mira St., Yekaterinburg, 620002, Russian Federation
  • L. Yuzvovich
    Department of Finance, Money Circulation, and Credit, Ural State University of Economics, 8 Marta St., Yekaterinburg, 620144, Russian Federation
  • E. Kniazeva
    The Sverdlovsk Region Legislative Assembly, 10 Borisa Yeltsina St., Yekaterinburg, 620031, Russian Federation
  • M. Klimenko
    Territorial Fund of Compulsory Medical Insurance of Sverdlovsk Region, 54 Moskovskaya St., Yekaterinburg, 620102, Russian Federation
  • V. Shelyakin
Название журнала
  • Journal of Open Innovation: Technology, Market, and Complexity
Том
  • 6
Выпуск
  • 4
Страницы
  • 1-20
Издатель
  • MDPI AG
Тип документа
  • journal article
Тип лицензии Creative Commons
  • CC
Правовой статус документа
  • Свободная лицензия
Источник
  • scopus