Title: Ways of corporate tax optimisation for cluster entities

Authors: Irina Gashenko; Irina Orobinskaya; Andrey Orobinskiy; Neonila Shiryaeva; Yuliya Zima

Addresses: Department of Taxes and Taxation, Rostov State University of Economics (RINH), Rostov-on-Don, Russia ' Department of Taxes and Taxation, Voronezh State Agrarian University, Voronezh, Russia ' Department of Taxes and Taxation, Voronezh State Agrarian University, Voronezh, Russia ' Department of Taxes and Taxation, Rostov State University of Economics (RINH), Rostov-on-Don, Russia ' Department of Taxes and Taxation, Rostov State University of Economics (RINH), Rostov-on-Don, Russia

Abstract: The purpose of the article is to verify the offered hypothesis and to determine the perspectives of optimisation of taxation for cluster entities using the example of modern Russia. As evidence base of existence of necessity for tax optimisation in Russia, this article offers determination of connection between tax revenues of the state budget and tax burden on organisations with the help of regression analysis. The authors perform characteristics and determine perspectives of optimisation of tax system of modern Russia, substantiate the necessity for tax optimisation of cluster entities and view corporate tax as a perspective direction of tax optimisation for cluster entities. As a result of the research, the authors come to the conclusion that there is a strong dependence between increase in tax burden on Russian enterprises and reduction of tax revenues into the state budget. High tax burden is one of the barriers of clustering in Russia, as participation in cluster entities reduces possibilities for income concealment and shadow business. Tax optimisation is a perspective direction for solving the problem of shadow economy.

Keywords: cluster entity; corporate tax; modern Russia; shadow economy; tax burden; tax optimisation.

DOI: 10.1504/IJTGM.2017.086079

International Journal of Trade and Global Markets, 2017 Vol.10 No.2/3, pp.151 - 159

Received: 15 May 2016
Accepted: 10 Sep 2016

Published online: 22 Aug 2017 *

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