Apal'kova T.G., Levchenko K.G. —
Statistical analysis of the differentiation of regions of the Russian Federation by tax revenues of consolidated budgets using the R language
// Taxes and Taxation. – 2024. – ¹ 3.
– P. 1 - 11.
DOI: 10.7256/2454-065X.2024.3.70590
URL: https://en.e-notabene.ru/ttmag/article_70590.html
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Abstract: The subject area of this article is the application of descriptive statistics and multidimensional classification methods to describe the regional features of the formation of tax components of revenues of consolidated budgets of the Russian Federation. The aim of the work is to demonstrate the simplicity and effectiveness of using mathematical and statistical methods and the functionality of the open source language R to solve problems of structural analysis of tax revenues, identify regional specifics, and comparative analysis of regions from the point of view of tax revenues. The apparatus of mathematical statistics implemented in the R language, in particular, opens up wide opportunities for classifying tax subjects, including multidimensional ones, significantly facilitating the procedures of analysis, ranking and planning. The functionality described in the article can be used in the process of forming and adjusting tax policy at different levels. The possibilities of the mathematical statistics apparatus in combination with the instrumental methods of the R language are revealed by the example of the classification analysis of the regions of the Russian Federation. At the same time, the absolute and relative values of tax revenues in the revenues of regional budgets are selected as classification features. The classification by belonging to the federal district and the study of the "natural" stratification by the method of cluster analysis are considered. The apparatus of mathematical statistics and, especially, the tools of the R language are used unreasonably rarely in research of this kind, despite the ease of use and the absence of the need for special training, these circumstances determine the relevance of this article. Aggregation by federal districts made it possible to identify: the Ural Federal District as the leader in terms of the average regional share of tax revenues in the revenue part of the budget and the North Caucasus Federal District, characterized by the lowest average regional contributions of tax payments to regional budgets. The analysis of the natural stratification of the regions of the Russian Federation by their relative tax contributions to consolidated budgets made it possible to identify groups: the most typical regions, subsidized regions, donor regions and regions in which the most expensive assets of enterprises of the Russian Federation are concentrated