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A tax method to calculate the value of the shadow economy of Russian regions

Fedotov D.Yu. Baikal State University, Irkutsk, Russian Federation ( fdy@inbox.ru )

Nevzorova E.N. Baikal State University, Irkutsk, Russian Federation ( nevzorova_kat@mail.ru )

Orlova E.N. Baikal State University, Irkutsk, Russian Federation ( OrlovaEN@bgu.ru )

Journal: Regional Economics: Theory and Pactice, #11, 2017

Importance So far, a variety of methods to measure the shadow economy have been developed. However, most of researchers investigate shadow economy at the national level, and far fewer works address the issue at the regional level.
Objectives The objective of the study is to develop a methodology for calculating the value of the shadow economy of Russian regions.
Methods Econometric methods helped develop a methodology to measure the shadow economy in Russian regions based on the comparison of statistical data and tax reporting. Methodological tools involve mathematical methods for statistical data processing.
Results The study solves the problem of calculating the value of the shadow economy in Russian regions. To verify the reliability of obtained results, we performed a correlation analysis of association between the size of the shadow economy in Russian regions and the indicators of socio-economic development of the regions, which relate to the level of the regional shadow economy.
Conclusions and Relevance The study made it possible to calculate the value of the shadow economy in Russian regions over 2010–2013. The findings may be useful for the State socio-economic policy implementation at the regional level.


A tax method to calculate the value of the shadow economy of Russian regions

Fedotov D.Yu. Baikal State University, Irkutsk, Russian Federation ( fdy@inbox.ru )

Nevzorova E.N. Baikal State University, Irkutsk, Russian Federation ( fdy@inbox.ru )

Orlova E.N. Baikal State University, Irkutsk, Russian Federation ( fdy@inbox.ru )

Journal: Finance and credit, #15, 2016

Importance So far, a variety of methods to measure the shadow economy have been developed. However, most of researchers investigate shadow economy at the national level, and far fewer works address the issue at the regional level.
Objectives The objective of the study is to develop a methodology for calculating the value of the shadow economy of Russian regions.
Methods Econometric methods helped develop a methodology to measure the shadow economy in Russian regions based on the comparison of statistical data and tax reporting. Methodological tools involve mathematical methods for statistical data processing.
Results The study solves the problem of calculating the value of the shadow economy in Russian regions. To verify the reliability of obtained results, we performed a correlation analysis of association between the size of the shadow economy in Russian regions and the indicators of socio-economic development of the regions, which relate to the level of the regional shadow economy.
Conclusions and Relevance The study made it possible to calculate the value of the shadow economy in Russian regions over 2010–2013. The findings may be useful for the State socio-economic policy implementation at the regional level.


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