Improving the value added tax forecasting tools

Abstract

The value added tax (VAT) prediction is one of the essential tools to form the Russian Federation federal budget. Presently, there are various methods and tools to forecast taxes, including VAT. This research proposes to enhance the estimation of VAT inflow into the federal budget singling out certain formation factors in the GDP structure. The dynamics of the federal budget income in the period 2010-2019 has been examined. It has been stated that VAT refers to non-oil and gas revenues, while the structural analysis of this tax enables to single out domestic production VAT and import related VAT. This tax sum division has become a basis for building federal budget VAT income forecasting models. The primary model takes into account the GDP dynamics in the given period, as well as the GDP to federal budget incomes ratio and their main elements. To develop a more accurate VAT forecasting model the above mentioned tax has been divided into two components - imports VAT and domestic consumption VAT. The imports VAT evaluation is done via the share of projected imports, which in its turn is calculated by the marginal propensity to imports. The domestic consumption VAT is done via the GDP share previously stripped off the import value. During research the excellences and faults of each model have been highlighted. The conclusion about the expediency of models based on separating imports VAT and domestic consumption VAT application for VAT forecasting has been made.