Abstract: The article is devoted to the quantitative assessment of the tax sensitivity of particular sectors of the economy. The subject of the study is a system of indicators characterizing the sectors of the economy at the macro and micro levels. The purpose of the study is to analyze the dependence of economic sectors on the tax burden. The paper focuses on the importance of taxes for the economic growth of the country's economy and sectoral differences caused by the level of technological development, regional conditions, as well as government regulation. A methodological approach developed by the author allowed to assess the tax sensitivity of individual industries, tested on the most important sectors for the Russian budget. The author analyzes the tax burden and revenues to the consolidated budget, identifies the industries that have the greatest impact on the budget and builds models for them that allow quantifying tax sensitivity across a set of organizations. Modern machine learning methods such as decision tree, gradient boosting, nearest neighbor method, as well as the classical linear regression method were used as analysis methods. The scientific novelty of the study lies in the possibility of using the developed methodological approach to assess differences in the tax sensitivity of individual sectors of the economy for making managerial decisions differentially for each individual sector. As a result of the conducted research, the high tax sensitivity of the extractive industry, manufacturing and construction industries has been revealed. The average level of tax sensitivity is typical for wholesale and retail trade; repair of motor vehicles and motorcycles. Low tax sensitivity was found in financial and insurance activities. Based on the results of the assessment, recommendations are proposed for the introduction of tax instruments into the activities of individual industries and a conclusion is made about the need to specialize tax incentive mechanisms by economic sectors in order to increase economic growth and optimize tax revenues.

Abstract: The tax burden of the regions is influenced by a whole range of factors, among which it is necessary to take into account the natural and climatic conditions. After all, the specialization of the regions, production capabilities, production volumes and, accordingly, the level of tax revenues to the consolidated budget of the Russian Federation depend on them. The article analyzes the tax potential of regions depending on the climatic factor. The subject of this study is a system of statistical indicators characterizing the natural and climatic conditions of the regions (temperature and precipitation in July and January for three years) and the economic results of their activities, including tax revenues to budgets. The aim of the work is to assess the influence of the climatic factor on the tax potential of the regions using the grouping method of cluster analysis.  The research method is cluster analysis (k-means method), implemented using the R programming language and its packages, which allows combining regions according to the similarity in climatic conditions, while minimizing variation within groups and maximizing intergroup differences. The results of the study can be applied in the development of recommendations at the state level on optimizing the tax burden of regions for regions with similar conditions. The novelty of the study lies in the possibility of assessing and comparing the characteristics of regions with similar climatic conditions in terms of tax potential, which is necessary to develop measures for the development of regions and increase their tax potential. As a result of the study, the influence of the climatic factor on the tax potential of the regions and the need to take it into account in combination with other factors is proved.