New Statistical and Econometric Approaches to Assessing Financial Processes (Banking Sector, Public Debt, Financial Management)

The results of studies on the development of new statistical and econometric approaches to modeling budget policy is presented. The obtained results are applied on the example of tax revenue modeling. The authors note the importance of ensuring transparency and predictability of state financial policy, the realisticness of economic forecasts, because this is the basis of budget modeling. It is also necessary to take into account the various economic cycles that affect the economic dynamics in a particular period of time and in a particular country (or group of countries). Accounting for various factors, including through the use of mathematical methods, will allow to plan reforms with a scientific position. In particular, this is especially true in connection with the introduction of multi-year budget planning. The most important issue of budget policy is the planning of tax revenues (taxes form 90% of budget revenues). To identify the main threats to the tax base, the phenomenon of “tax passes” was used, which is based on an assessment of the effectiveness of a tax credit. The main participants in the formation of the “gross gap” in the value added tax revenues in Ukraine are shown. A correlation and regression analysis of the natural logarithms of the gross domestic product and tax revenues is carried out. This allowed us to determine the elasticity of tax revenues and GDP in Ukraine. A change in GDP directly affects the amount of tax payments to the budget, and the rate of change of indicators is proportional and changes insignificantly. These results allow us to strategically model the reform of discretionary tax policy mechanisms based on a quantitative assessment of tax gaps and the elasticity of tax payments. The authors were able to substantiate some proposals for reforming the budget policy regarding tax revenues