Assessing the size of the shadow economy in an industrial region (case study of the Donetsk People’s Republic)

Abstract

Introduction. Combating tax evasion, the shadow economy and unofficial (illegal) employment are important policy goals in every region. Achieving those goals requires various resources; therefore, it is important to determine the size of the shadow economy to use the resources efficiently.

Purpose. The paper aims at developing and testing a methodology for neural simulation estimates to find the size of the shadow economy in an industrial region taken as an example, i.e. the Donetsk People’s Republic.

Materials and Methods. The study refers to the data from the World Bank Group’s Ease of Doing Business Index and data about the size of the shadow economy calculated with L. Medina and F. Schneider’s methodology. The neural network learns from the generated data array of 17,160 values for the economies of the world for 2006–2015 with the Statistica software package. The result was then used to estimate the value of the shadow economy in the industrial region.

Results. The hypothesis that the Ease of Doing Business Index and the size of the shadow economy are correlated has been proposed and tested. The indicators of the Ease of Doing Business Index and the size of the shadow economy by country were sampled. The neural network was taught to assess the size of the shadow economy with the Statistica software package. The values of the Ease of Doing Business Index have been determined for the Donetsk People’s Republic. The taught neural network calculates the size of the shadow economy in the Donetsk People’s Republic and establishes that its size ranges between 30 and 40 %. The debatable issues of applying the suggested algorithm for calculating the size of the shadow economy in an industrial region are outlined.

Conclusion. It is often not the irresponsibility of the entrepreneurs themselves that leads to the shadowing of the economy, but the difficulties with the business legalization and exorbitant taxes. The measures of minimizing the level of the shadow economy in the Donetsk People’s Republic are described. The suggested information will be useful for those who determine the economic policy of the region.

Keywords: regional economy, industrial region, shadow economy, ease of doing business, calculation algorithm

For citation

Polovyan A. V., Sinitsina K. I. Assessing the size of the shadow economy in an industrial region (case study of the Donetsk People’s Republic). Perm University Herald. Economy, 2023, vol. 18, no. 4, pp. 409–422. DOI 10.17072/1994-9960-2023-4-409-422. EDN QIAJJG.

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