Modern Approaches to Forecasting Corporate Income Tax Revenues in the Russian Federation
( Pp. 225-229)

More about authors
Datkaayim R. Dekanova
Financial University under the Government of the Russian Federation
Moscow, Russian Federation Valery I. Khoruzhy
Financial University under the Government of the Russian Federation
Moscow, Russian Federation
Abstract:
The purpose of the study. The purpose of the study is to determine the optimal model for forecasting corporate income tax revenues. The subject of the study is modern methods of forecasting income tax revenues to the budgets of the subjects of the Russian Federation, based on mathematical and statistical, regression and autoregressive models with a moving average. The article identifies the advantages and disadvantages of existing approaches to forecasting tax revenues, as well as defines the conditions for the applicability of the considered models in conditions of high dynamics of changes in market conditions and macroeconomic uncertainty. The results of the study are presented, which make it possible to establish the optimal methodology for forecasting corporate income tax receipts, taking into account the statistical limitations of the planning horizon, as well as to identify a forecasting mechanism available for use in long-term planning. Conclusions. Based on the results of the study, it was concluded that it is advisable to combine tax forecasting models to achieve optimal predictive and analytical indicators, as well as to apply this approach only within the framework of short-term planning. The final forecast indicator can be identified on the basis of expert assessments, the average value of the indicators obtained, or through a combination of these approaches: an expert assessment of the weighting coefficients to calculate the weighted average value of the forecast indicator.
How to Cite:
Dekanova D. R., Khoruzhy V. I. Modern Approaches to Forecasting Corporate Income Tax Revenues in the Russian Federation // ECONOMIC PROBLEMS AND LEGAL PRACTICE. 2024. Vol. 20. № 1. P. 225-229. (in Russ.) DOI: 10.33693/2541-8025-2024-20-1-225-229. EDN: NSPOMW
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Keywords:
tax forecasting, mathematical forecasting models, regression forecasting models, autoregressive and integrated moving average models, corporate income taxes, tax revenues of the budgets of the constituent entities of the Russian Federation..


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