Purpose of the study – to determine the spatial structure and concentration of tax revenues from the activities of small and medium enterprises (SMEs) in municipal entities of the resource-type region (based on materials from the Kemerovo Region – Kuzbass), to characterize their compliance with the needs of local budgets.
Materials and methods. The data on total tax revenues from SMEs, specific revenues per small and medium enterprise, in relation to population indexes, the total number of SMEs, the presence or absence of coal mining in the municipality were used. The coefficients of variation and oscillation, Atkinson index, the coefficient of paired correlation, Gatev coefficient, and the paired Student t-test were applied. The calculations were performed in the SPSS 19.0 program and the free software “R”.
Results. The Kemerovo region – Kuzbass is characterized by high levels of spatial concentration of revenues from SMEs by municipalities, spatial inequality for this index. This is explained by not only the differences in the level of economic and business development between the centers and the periphery, but also by a large gap between municipalities in terms of population (10 times or more). The concentration and inequality of tax potential by municipalities in 2023 increased compared to 2021. The absolute values of revenues from special tax regimes and the population of municipalities have a very high level of correlation. Gatev coefficient (where another calculation method related to specific weights is used) showed a moderate degree of difference in the structures of these indexes. The center is ahead of the periphery in terms of the share of SMEs in the tax potential. Spatial inequality in revenues per one SME entity is moderate; in 2023, compared to 2021, a tendency towards an increase in this index was revealed. The leading positions are occupied by the Novokuznetsk municipal district (which is partly explained by the agglomeration effect of Novokuznetsk), Tashtagolsky municipal district (rapid development of the national resort of Sheregesh). The largest urban centers (Kemerovo, Novokuznetsk urban districts) occupy only third and fourth place. The absolute value of the tax potential of SMEs, as well as specific revenues from special tax regimes per one SME entity do not depend on the presence of a developed coal industry in the municipality.
Conclusion. The study demonstrates spatial proportions and spatial inequality of municipalities in terms of SME tax potential, taking into account the specifics of resource-type regions. The presented methodological approach can be used to study a similar subject area in other regions dependent on mineral extraction. The findings of the study demonstrate the potential of SMEs in ensuring budget balance at the local level in the face of risks of declining coal production.

Purpose of the study. The purpose of the study is to analyze the socio-economic factors of employment in the urban districts of the Russian Federation. Within the framework of the study, a cluster analysis of cities is carried out in two variants: (1) based on factor indexes of employment and (2) using both performance and factor indexes of employment. In both cases, a statistical justification is provided for taking into account the lags of the delayed impact of factor indexes on performance ones. The use of this variable approach in clustering allows us to identify statistically homogeneous groups of cities, respectively, without taking into account and taking into account the individual effects of the factor influence on employment and, on this basis, to justify the indexes of employment regulation in the cities of the Russian Federation.
Materials and methods. To achieve this goal, a system of indexes was developed based on the data of municipal statistics provided by the Federal Plan of Statistical Work, including quantitative and qualitative assessments of the level of socio-economic factors of employment. The study conducted a cluster analysis using the hierarchical method (Ward’s method) and the iterative method (k-means).
Results. As a result of the cluster analysis, statistically homogeneous subgroups of cities were identified that differ in the level of employment, administrative composition, set and nature of the influence of factor indexes on employment. Based on a comparative analysis of two clustering options, it was proven that identifying significant employment factors at the municipal level (by urban municipalities) is possible with clustering using both performance and factor indexes, as well as taking into account the time lags of their relationship. Clustering of cities only by factor indexes does not provide for taking into account the individual characteristics of interdependence of the studied indexes in cities, which leads to rough statistical estimates and the concealment of latent interrelations, the consideration of which is necessary for regulating employment.
Conclusion. The study revealed that statistically homogeneous clusters of cities have specific administrative composition, which predetermines the characteristics of multifactor regression models of employment, the parameters of which are recommended for use in developing measures to regulate employment and the socio-economic development of cities.

The purpose of the study. The purpose of the study is to model a generalized system of indicators of economic security of the regions of the Russian Federation. The topic of the study is relevant, since the prevention of crisis situations, the organization of stable functioning of regional economies, the development of territories and the growth of the standard of living of the population necessitate constant monitoring of the economic security of the regions of Russia, which is based on the modeling of a system of indicators, because socioeconomic development is a complex system of interconnections, various components of the economy.
Data and methods. The normative and legal documents of the government bodies of the Russian Federation, official data of the Federal State Statistics Service, the Unified Interdepartmental Information and Statistical System and the Ministry of Finance of the Russian Federation were used as the information and empirical base of the study. The indicators were selected based on the works of Russian scientists and Decree of the President of the Russian Federation dated May 13, 2017 No. 208 “On the Strategy of Economic Security of the Russian Federation for the period up to 2030”. The method of factor analysis - principal component analysis was used in the formation and modeling of a generalized system of indicators of economic security of regions.
Solutions and results. To achieve this goal, at the initial stage of the study, a system of indicators was formed, consisting of 26 indicators characterizing the production, financial, social and other aspects of the life of the regions that determine economic security. The information compression method, the principal component analysis, were applied to the selected indicator system. When choosing the number of principal components (factors), we relied on the eigenvalues of the principal components (Kaiser Criterion) and their contribution to the overall variance of the initial features. Seven principal components were identified. At the same time, their total contribution to the total variance was 78.45%, which is a sufficient condition for the formation of components. The best interpretation of the principal components was achieved without subjecting factor loads to any rotations. Thus, the components were obtained: f_1 (financial security), f_2 (demographic security), f_3 (social security), f_4 (food security), f_5 (scientific and technical security), f_6 (degree of depreciation of fixed assets), f_7 (industrial safety). The information content coefficients for all principal components are in the range from 0.70 to 0.95; therefore, their composition is significant. The constructed regression model in a standardized form made it possible to determine the impact of the selected generalized factors on the level of economic security of the regions of the Russian Federation.
Conclusion. Having a high level of economic security is important for the activities of each region, therefore it is necessary to conduct high-quality monitoring of the degree of economic security, which allows you to identify weaknesses and strengths in the economy. The results of the study made it possible to form the main generalized factors of economic security of the regions: financial, demographic, social, food, scientific and technical, industrial safety and the degree of depreciation of fixed assets - the subjects of the Russian Federation can be assessed from the point of view of their economic stability, and, consequently, their competitiveness at the national level.

The use of statistical methods and econometric modeling has its own specifics when analyzing data obtained from agrobiological studies. When studying such an index as crop yield and selecting factors that influence it, the analyst faces the problem of the need to include explanatory variables in the regression model that have a nonquantitative form of expression, associated with the use of various microbiological preparations for seed treatment. Such a problem can be solved by using dummy variables in the models.
The purpose of the research – development of methodological approaches to constructing a regression multifactorial model, including both quantitative and qualitative explanatory variables, describing quantitatively the dependence of the feed mix yield for cows on these factors.
Materials and methods. The methodology for solving this research problem is based on fundamental approaches published in scientific papers by scientists covering the problems of using econometric models with dummy variables. The basis of the study is an integrated approach to the use of mathematical and statistical methods for analyzing dependencies between variables, modeling and forecasting, as well as experimental results of studying the level of dry mass yield of the feed mix depending on the nitrogen content in the soil and the use of microbiological preparations “Bisolbi-T” and “Extrasol”, obtained for four mowings carried out in the summer period of 2023.
Results. The study and quantitative description of the effect of microbiological preparations “Bisolbi-T” and “Extrasol” at different concentrations of nitrogen in the soil on the yield of dry mass of the feed mix allowed us to obtain econometric two-factor models, in which the factor - the use of the preparation for preliminary treatment of seed material, was included as a dummy variable. Based on the statistically significant regression models obtained during the study, taking into account the periods and cycles of mowing the feed mix, the expected values of its yield at the standard concentration of nitrogen in the soil were calculated, a comparative assessment of the effectiveness of the studied preparations was performed.
Conclusion. The use of statistical data analysis methods with the construction of regression models in agrobiological research has certain specifics. The possibility of including dummy explanatory variables in the regression model allows us to study and quantify the impact of nonquantitative factors on crop yields. Obtaining statistically significant models is the basis for forecasting the yield level and making decisions when choosing optimal options for applying fertilizer concentrations, determining preferences for microbiological additives used to increase crop productivity, calculating prospective values of the yield of the feed mix depending on the period of its mowing. All this is of strategic importance when planning the volumes of feed production for farm animals and the amount of expenses of enterprises for their activities, in particular for drawing up a budget for feed costs.

The purpose of the study. Development of a methodology for the estimated value of shares of issuing companies on the stock market based on the values of their investment criteria and indexes of net profit per share.
Materials and methods. The study uses analytical and statistical data for the time period 1881-2022 on the market quotations of the S&P500 index and indexes of net profit of companies in terms of E, E6 and E10 shares (E6 and E10 are the moving average of E for the previous 6 and 10 years) for companies included in the calculation of the S&P500 index. Similar data for the time period 1998-2022 of the index-forming Russian companies Gazprom, Nornickel and Rosneft are also used. The research methodology includes statistical methods, methods of comparative analysis, comparison and generalization.
Results. Based on the obtained data of regression dependence of the market quotations of the S&P500 index from 1881 to 2022 on the investment criteria of American companies S&P500/E and S&P500/E10, as well as on their net profit indexes in terms of E and E10 shares, it is shown that the objective financial and economic characteristics of companies mainly determine the market price of its shares. The regression dependence of the S&P500 on the E, E10 indexes and on the S&P/E10 investment criterion is characterized as high and very high. The presented S&P/E6 investment criterion, along with the S&P500/E10, has a very high impact on the S&P500 in comparison with other criteria and indexes (data from regression statistics during the dotcom crises from 2000 to 2005 and global crisis phenomena from 2007 to 2010). In most cases, it was revealed: high and very high dependence of the market value of shares of US and Russian issuing companies on the investment criteria P/E6 and P/E10; medium and weak dependence on the indexes E, E6 and E10; weak and very weak dependence on the investment criterion P/E.
Conclusion. The results obtained show that to assess the reliable value of shares of issuing companies on the stock market, it is advisable to use the values of investment criteria P/E6 and P/E10. The practical significance of the study lies in testing the developed methodology for estimating the value of shares of issuing companies on the stock market. Stock market participants in choosing preferred investment strategies can use the results of the study. Based on the data obtained on a reliable assessment of the value of shares of issuing companies of the Russian stock market, regulatory organizations have the opportunity to formulate effective management of it in the context of existing negative geopolitical events.

The purpose of the study is to determine the trends of regional development and the peculiarities of population behavior in the context of modern challenges. The relevance of the study of the specific behavior of the population of the regions is associated with the problems of reflecting economic development trends which affect the actions and deeds of people and the quality of their lives. At the same time, liberal approaches to the definition of behavioral strategies of the population do not allow to objectively reflect the peculiarities of regional development. The methodology is used from the point of view of substantiating digital meters reflecting the processes of interaction of needs, consumption, production and behavior of the population, their impact on the peculiarities and trends of regional development.
Methods: Rosstat methodology, including the balance method, a method of comparative assessments of regional development trends and analysis of the degree of satisfaction of the needs of the population.
Results. The peculiarities of the formation of the population behavior of the subsidized border region, which is directly related to the living conditions and the degree of satisfaction of people’s needs, are revealed. The unpredictable behavior of the population was used to assess the relationship between needs and the production of goods that affect the characteristics and well-being of people. It is established that the population of the Kurgan region is in a constant state of stress due to management miscalculations in inter-budgetary relations, the imbalance of interests of employers with employees who artificially underestimate the value of labor and knowledge of employees. All this affects the deterioration of demographic and migration behavior of the population, the quality of life of people.
Conclusion. Official statistics allow us to truthfully determine the trends of regional development and the peculiarities of population behavior in the face of modern challenges. The results obtained allowed us to reveal the actual problems of the development of the subsidized region, which affect the behavioral strategies of the population. Also, when developing state measures to ensure people’s savings, maintaining a balance of interests of the population and employers with government authorities in order to reduce the negative impact of unpredictable behavior of people on the future.