Factors and Indicators of Russian Shadow Economy: An Empirical Analysis of Regional Data
https://doi.org/10.34023/2313-6383-2022-29-5-17-34
Abstract
The purpose of the research is to assess factors influencing the rescaling of the shadow economy in the Russian Federation (on the example of certain regions). The analysis was carried out using mathematical and statistical methods according to regional statistics for 2013–2019. In particular, a model of multiple indicators and factors (MIMIC) was built. It adapted to the panel data structure. Variables characterizing the tax burden, government regulation and the state of the labor market were used as factors. As indicators of the shadow economy – monetary variables and characteristics of the formal economy.
It is shown that in the conditions of economic difficulties there was a «compression» of the scale of the shadow economy in certain regions. According to the authors, a significant role in reducing the shadow component in the regional economy over the period under review was played by the improvement of the tax administration mechanism in the process of forming regional and local budgets (personal income tax, property taxes) as well as coordination of interdepartmental interaction in order to reliably determine the size of the taxable base. The positive role of preferential taxation regimes, which can be established by regional authorities, was proved. A significant impact on the scale of shadow activity of the structure of the regional economy and conditions in the labor market was discovered: a high share of the extractive industry and an increase in wages in the region compared to the average Russian level create incentives for participation in the formal economy and reducing the scale of the shadow economy.
The modeling results confirmed the relevance of shadow economy indicators: the larger size of the regional shadow economy entails less participation in the labor force and an increase in cash turnover.
The conclusions obtained from a new angle focus on the task of improving the investment climate, reducing pressure on entrepreneurship, and supporting small and medium-sized businesses.
About the Authors
S. V. ArzhenovskiyRussian Federation
Sergey V. Arzhenovskiy – Dr. Sci. (Econ.), Professor, Chief Economist; Professor, Department of Statistics, Econometrics and Risk Assessment
22-a, Pr-t Sokolova, Rostov-on-Don, 344006
69, Bol'shaya Sadovaya Ulitsa, Rostov-on-Don, 344002
Yu. A. Orlova
Russian Federation
Yulia A. Orlova – Cand. Sci. (Econ.), Assistant Professor
20, Myasnitskaya Str., Moscow, 101000
E. V. Semerikova
Russian Federation
Elena V. Semerikova – Cand. Sci. (Econ.), Senior Lecturer
20, Myasnitskaya Str., Moscow, 101000
E. E. Sidorova
Russian Federation
Elena E. Sidorova – Cand. Sci. (Econ.), Junior Research Fellow, Institute for Industrial and Market Studies
18, Myasnitskaya Str., Bldg. 1, Moscow, 101000
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Review
For citations:
Arzhenovskiy S.V., Orlova Yu.A., Semerikova E.V., Sidorova E.E. Factors and Indicators of Russian Shadow Economy: An Empirical Analysis of Regional Data. Voprosy statistiki. 2022;29(5):17-34. (In Russ.) https://doi.org/10.34023/2313-6383-2022-29-5-17-34