Spatial approach in forecasting tax revenues

Study of tax revenue forecasting accuracy is an integral part of the planning and analysis of the tax system indicators as well as one of the central functions of the State Fiscal Service of Ukraine (SFS). This process is complicated by the lack of development of complex statistical apparatus that can be applied for forecasting purposes taking into account the size of tax data available in SFS of Ukraine. The purpose of this article is to demonstrate the advantages of using panel regressions of various fit in forecasting tax revenues at the regional level. To analyze the advantages and disadvantages of usage panel data structure in forecasting tax revenues by region, the authors employ econometric tools, including univariate time series models for each region, spatial and dynamic panel regression. The scientific result is that, on the basis of the analysis, the authors prove the feasibility of using panel regressions with the purpose of forecasting taxes in cases with limited time series data. These developments in modeling and forecasting tax revenues also have practical value, because they can be used directly in the analytical activities of SFS of Ukraine at the regional level.