The relevance of the study lies in the fact that at present, information flows, often based on “falsification” of data, are having an increasing influence. And statistics act as such a tool.
Purpose of the study. The purpose of this paper is to study opinions and approaches to the use of statistics to conduct information wars.
Materials and methods. The study examined the main directions of statistics as a tool for working with data. The most common and practically justified is the use of statistics as a tool of knowledge, management, propaganda and control. The result of interpreting statistical data primarily depends on the degree of objectivity and level of literacy of those who work with the data: both at the initial stage of the original data array, and at the stage of explaining the resulting values.
Results. It was revealed that the same parameters (proportions) can be interpreted in completely different ways. Such differences arise both from the subjectivity of the perception of these data and from the degree of elaboration of the material. As a result, a field for discrepancies and discussion arises.
Conclusion. Statistics have already become an integral component of wars of a new format, where the battle for people’s worldview becomes the basis for further presence in many spheres of life. But with competent, properly structured and timely statistical information, it is possible to suppress falsely generated data and inflict damage on the enemy that significantly exceeds direct military clashes on the battlefield.

The purpose of the study is to substantiate the documentation for assessing the dynamics of structural changes in the socio-economic environment and their typology. The relevance of the study is related to the problems of reflecting the socio-economic environment, which affect the efficiency of economic activity. To address these issues, many regions of the country have adopted regional development strategies for the period up to 2030, which correspond to the national development goals of the Russian Federation. Various approaches of scientists to determining the essence and significance of the socio-economic environment, which is defined as a set of conditions and factors that influence all sectors of the economy, are studied.
Methods: structural, index, comparative estimates and methodology of the system of national accounts.
Results: the article uses a digital meter as a reproduction of the population and gross regional product (GRP), which objectively reflect the structural changes and typologies of the regions. GRP is calculated by types of economic activity, at the stages of: production, income generation and final consumption of households 2012-2021. Typologies of the Ural regions have been developed according to the following criteria: specialization of the economy, the position of the region in production, by types of primary income and final consumption of households per capita.
Conclusion: the advantage of the statistical approach of studying the assessment of the dynamics of structural changes in the socio-economic environment and their typology allows us to get a more objective idea of the prevailing trends and the state of the regional economy. The results obtained made it possible to formulate a methodological basis for future scientific research in the field of structural changes in the meso-environment and socio-economic behavior of the population. They can also be used as a methodological basis for the development of public policy measures and strategies for sustainable development of territories in the future.

The purpose of research. The increasing rate of Russian economy digitalization has ambiguous proportions by industries and regions. Russian regions are characterized by uneven levels of Internet adoption, as well as organizations applying computer networks, servers and electronic documentation systems. This creates territorial differentiation of opportunities for organizations to use digital services and online platforms created by commercial banks to attract and service loans.
Overview and analysis of literary sources have led to the conclusion that quantitative assessment of interplay between digitalization of organizations and their credit activity has not been sufficiently developed at the regional level. The purpose of this study is to develop statistical indexes to assess the impact of digitalization of organizations on their credit activity by Russian regions, and to analyze interdependence of suggested indexes to find out the patterns of such an impact.
Methods. The source data array is a set of values of statistical indexes, proposed for the purposes of the study, published by Rosstat. This array is processed by imputation of missing values knn – k nearest neighbors to eliminate missing part of the original data. The tightness of statistical relationship between the analyzed variables was assessed by calculating the paired correlation coefficients. The average and median values of the analyzed effective variables were calculated across several years. The regional distribution by clusters per effective variable values was made using the hierarchical cluster analysis. The impact of factor variables on the effective variables was assessed using the panel regression modelling.
Results. Based on the system of regional statistics indexes formed by the author, the territorial peculiarities of the dependence of credit capacity on the factors of digitalization of organizations in groups of Russian regions were analyzed, and the parameters of the “response” of credit capacity indexes to changes in individual technological components of digitalization of organizations in regional clusters were obtained.
Conclusion. It was concluded that the results of the study could be used to develop business lending programs for commercial banks and determine the priorities of regional digital development programs by government bodies.

This article is devoted to the influence of a number of macroeconomic indexes on the amount of reserves for possible losses in the Azerbaijan banking sector.
The purpose of research. The purpose of the research to analyze the stability of the banking sector to the impact of macroeconomic shocks in the economy, study what the concept of financial stability of the banking sector includes, and what methods are used in the process of its analysis and assessment, investigate the dependence of a number of variables characterizing the state of the banking sector on various macroeconomic shocks inherent in the economy, analyze how the Central Bank is involved in regulating and monitoring the financial stability of the banking sector, as well as through what measures it supports banks in times of crisis.
Materials and мethodology. The practical stage of the work is to create a multiple regression model that will reveal the degree of impact of macroeconomic shocks on the position of the Azerbaijan banking sector. To carry out the analysis and construct regression equations, quarterly data for the period 2012-2023 were used. Information was taken from a number of sources: 1) Official website of the Central Bank of Azerbaijan; 2) Official website of Ministry of Finance; 3) Official website of Azerbaijan State Statistics Committee; 4) Reports on the development of the banking sector and banking supervision. To analyze and estimating the values of the dependent variables of provisions for possible losses and return on assets, values for the banking sector as a whole are taken from annual reports on the development of the banking sector and banking supervision.
Since the source data in the work is quarterly, our model will be a time series estimated using the ordinary least squares (OLS) method. Lagged variables may be included in the time series. The lags in the explanatory variables take into account the degree of possible lag with which macroeconomic shocks affect banks. In other words, changes in the values of macroeconomic factors do not have an immediate impact on the position of banks, but appear after some time and are delayed [7]. Such lags need to be identified and taken into account in order to form a more accurate and complete picture of the impact of macroeconomic fluctuations on the banking sector.
During preliminary diagnostics of the data, the presence of heteroscedasticity and first-order autocorrelation was revealed. To eliminate it, Newey-West corrections are applied, adjusting the variation-covariance matrix to obtain more consistent estimates of regression coefficients.
Results. When selecting indexes to study the degree of impact of macroeconomic factors on the stability of the banking sector, we took into account the peculiarities of the economy of our country. The fact is that Azerbaijan is a raw materials country, the export of which consists of almost 70% of fuel and energy products [30]. This means that the size of export revenues, the financial position of companies and the stability of the economy are highly dependent on the price situation in the global energy market, namely the price of oil.
In addition, Azerbaijan belongs to a number of countries with an emerging market, which is characterized by increased volatility of exchange rates and instability of financial markets and high interest rates and spreads. Therefore, our country is characterized by the risk of a sharp outflow of capital in the event of a crisis in the world, as investors seek to withdraw their funds from countries that are most vulnerable to the influence of macroeconomic shocks.
GDP dynamics are one of the important indicators of the economic activity of the state. Its fall during the crisis negatively affects various spheres of economic and social life [8].
The Baku stock exchange index reflects the state of the stock market of large companies, which are the most important for the country’s economy [9]. The collapse of the index means a deterioration in the position of companies, a decrease in the market value of their assets and shares, and increases problems with paying external debt and obtaining new loans to ensure the functioning of their activities. In addition, the collapse of quotes on the stock market leads to large losses as a result of their negative revaluation.
Conclusion. When conducting a research of the sustainability of the banking sector in Azerbaijan based on an econometric model, it is necessary to take into account certain limitations. First, the availability and reliability of data is an important aspect that can affect the accuracy of the study results. Secondly, to fully understand the issues under study, it is necessary to take into account the context and specifics of the banking system of Azerbaijan. Finally, this study does not examine social and political factors that may also influence the sustainability of the banking system. Limitations of the study should be considered when interpreting the results and making recommendations.

The purpose of the study is to form an effective tool for classifying the regions of the Russian Federation in the context of innovation activity under technological constraints.
Materials and methods. The information and empirical base of the research consists of Decrees of the President of the Russian Federation, normative legal acts of the Government of the Russian Federation, and open set of statistical data provided by the Federal State Statistics Service. The study provides a multidimensional classification of Russian regions using an indicative analysis of the innovative potential of territories and their socio-economic development, clustering by the Ward method and the Euclidean distance metric, as well as analysis, comparison and illustration of the results obtained using methods of visualizing information in tabular, graphical form, including the usage of cartograms.
Results. While creating a model of typologization of Russian regions, a system of indicative indexes with both qualitative and quantitative characteristics was formed. Based on them, cluster analysis identifies five clusters of regions according to the level of innovation activity and socio-economic development, which is based on the final weighted average index (Iiv) of development. The results of the study determine the effectiveness of the author’s approach to the issue of typologization of regions, and emphasize the visibility and interactivity of the tools used within the framework of the model. The use of cluster and comparative analysis using weighted average indexes makes it possible to identify non-obvious patterns between the innovative activity of the region and its level of development, as well as to emphasize intuitively expected connections. All this can form a practical basis for developing effective strategies for regional development and improving the quality of life of the population.
Conclusion. The study highlights the importance of analyzing the innovative activity of regions in modern conditions of sanctions wars and restrictions on technological imports. The developed model is a comprehensive tool for analyzing the innovative potential and level of development of regions, which allows identifying key factors of innovation activity and potential growth points, and thereby helping to form the basis for the development of strategies and programs for regional development aimed at improving the standard of living of the population.

The economic policy pursued has turned China into a major trading power. In terms of GDP, the Chinese economy has been the first economy in the world for a number of recent years; China’s rapidly growing trade flows have made it the largest trading partner for many countries. Over the past twenty years there has been rapid growth in exports and imports. The article puts forward a hypothesis about the presence of structural instability in the dynamics of Chinese exports for the period from 2000 to 2020. The hypothesis was confirmed and two periods were identified in the dynamics of exports and imports with different natures of the main development trend: from 2000 to 2008 and from 2009 to 2020. For each stage, trend equations were selected that describe the dynamics of exports and imports and an interval forecast of indexes for 2021 was made.
Materials and methods. During the work, dynamic, structural analysis of analytical and statistical information was used; methods of analytical, logical, systemic, correlation and regression analysis were used, as well as analysis of structural changes. The analysis was carried out using the Statistica 10.0 program.
Results. A change in the value of the import coverage ratio by exports was revealed before and after structural changes in the dynamics of the main foreign economic indexes and an assessment of their statistical significance was given. An analysis of the influence of export dynamics on GDP dynamics was carried out and it was found that before structural changes, the influence of export dynamics on GDP dynamics was statistically insignificant, and after a structural change, export dynamics began to have a direct impact on changes in China’s GDP.
Conclusion. Analysis of official statistical data on the main indexes of China’s foreign economic activity for the period from 2000 to 2020 allowed us to note that the volume of Chinese exports increased over the period 2010-2019 from $1.58 trillion in 2010 (10.34% of global exports), to $2.50 trillion in 2019 (12.81% of global exports). In 2019, China continued to rank first in terms of export value among all countries in the world. Despite the challenging year of 2020, China’s exports reached almost 2.6 trillion US dollars and increased by 4% compared to 2019.
China also occupies a leading position in the export of high-tech goods - their volume is 731.9 billion US dollars, the share of exports in the global volume is 25%. At the same time, the dynamics of Chinese exports for the period from 2000 to 2020 was heterogeneous and characterized by structural instability. Two stages can be distinguished with different characteristics of the main development trend: from 2000 to 2008 and from 2009 to 2020. Based on this, the authors came to the conclusion that to describe the main trend in the development of export and import dynamics for the period from 2000 to 2008, the exponential model is best suited. To describe the main trend in the development of export and import dynamics in the period from 2009 to 2020 - logarithmic model. A study of the consistency of changes in export and import volumes showed that in the period from 2009 to 2020 was characterized by greater consistency in China’s main foreign trade flows than the period from 2000 to 2008. In the period before the structural change in the dynamics of exports and imports, the coverage ratio varied from 105.7% to 127.6%; in the period after the structural change, the coverage ratio changed from 108.9% to 135.4%.
Checking the statistical significance of the differences in the coefficient of coverage of imports by exports before and after the structural change showed that the differences are not statistically significant. In the period from 2000 to 2008 the dynamics of China’s exports did not have a statistically significant impact on the dynamics of the country’s GDP. From 2009 to 2020 after structural changes in the nature of the dynamics of the main indexes of China’s foreign trade, changes in exports began to have a statistically significant impact on the dynamics of GDP. A 1% increase in China’s exports now results in a 0.25% increase in GDP.
The practical significance of the paper is determined by the developed methodology for analyzing structural changes in the dynamics of exports and imports, examined using the example of China.

Purpose of the study. The purpose of the study is to confirm or refute the environmental determinism of the occurrence of socially significant diseases among the population of Moscow based on the analysis of data on environmental and health indexes in the context of municipal units of the city.
Materials and methods. The article analyzes Russian and foreign bibliography on the research problem. Based on collected and processed open data on environmental indexes and population morbidity in various districts of Moscow, various types of analysis were carried out to identify the relationship between these data. To classify socially significant diseases based on environmental indexes of the place of residence, machine learning models were designed. The mathematical basis of machine learning methods is the k-nearest neighbors’ method, multilayer perceptron, and gradient boosting. To create the models, the Jupyter Notebook software tool, which supports the Python programming language, was used.
Results. Correlation and regression analysis showed that there is a statistically significant correlation between some selected environmental indexes and the occurrence of socially significant diseases. This result indicates a possible relationship, which is one of the main conclusions of this paper. A web interface has been developed to automate the analysis of new data using constructed machine learning models used to conduct regression analysis to create a binary logistic model (prediction based on collected data of people with socially significant diseases) and a multiclass classification models (prediction based on collected data, which it is the disease that can be detected in a person). The machine learning models used were analyzed and the best model for classifying socially significant diseases was determined.
Conclusion. As a result of the study, it was possible to collect comprehensive information about various environmental indexes and the presence or absence of various objects that have an impact on the environment. These data were used not only in machine learning models, but also to form an objective assessment of the environmental situation of municipal units of Moscow city. Since automatic updating of the rating for dynamic data was implemented, this result can be used by ordinary users who do not have sufficient qualifications in ecology and medicine for independent analysis of the ecological state of areas. We believe that such research will certainly lead to effective practical solutions in this area.

The sphere of public procurement and the disbursement of budget funds in all countries is an environment that attracts not only respectable entrepreneurs who want to make guaranteed money, but also various “criminal white-collar elements.” According to various estimates, the volume of financing for public procurement in the Russian Federation occupies up to one third of the total GDP. A large number of labor and financial resources are involved in this area, while regularly changing legislation in this area, as well as the complexity of procurement procedures for different categories of goods, works, and services create favorable conditions and allow unscrupulous bidders, as well as corrupt customer representatives, to obtain unjustified profits and illegal remuneration. In the current situation, the introduction of new control measures becomes vital to ensure fair competition and efficient use of budget funds. That is why additional research and measures aimed at eliminating these problems and the preconditions for their occurrence are an integral part of ensuring the effectiveness of the public procurement system and protecting public interests.
Purpose of the research is to study the genesis of cartel agreements in public procurement and their impact on the implementation of national projects in the Russian Federation, as well as the impact of cartel agreements on the presence of healthy competition and the efficiency of spending budget funds. As part of the paper, the state of crime in this area was examined; the signs of cartel agreements, methods for identifying cartels, as well as signs of collusion between the customer and the participant in public procurement were identified.
Methods and materials. The author in his paper applies a comprehensive methodological approach, including analysis of statistical data, methods of the general theory of statistics, as well as methods of synthesis and analysis. The main attention is paid to the analysis of the current legal regulation in the field of public procurement. Graphical and tabular methods were used to visualize statistical data. The study is based on data provided by the Ministry of Internal Affairs of Russia, the Federal Antimonopoly Service of Russia, the Federal Treasury of the Russian Federation, the Prosecutor General’s Office of the Russian Federation and the Judicial Department of the Supreme Court.
Results of the study. The paper made a quantitative assessment of the scope of public procurement in recent years, and assessed the work carried out by law enforcement officials and the antimonopoly service. Typical violations of antimonopoly legislation during public procurement are given and methods for identifying them are proposed. The illegal schemes used by cartel participants in electronic trading are analyzed, as well as problematic issues and ways to resolve them that arise in practice. The paper proposes various approaches to increasing the efficiency of law enforcement and control agencies. An analysis of law enforcement practice revealed problems associated with proving crimes in this area, and noted an insufficient level of interaction between law enforcement agencies and the Federal Antimonopoly Service of the Russian Federation.
Conclusion. In the study, the author analyzed the main features of cartels, proposed methods for identifying them, as well as ways to improve the verification activities carried out. The presented measures do not exhaust the topic of the study, and to effectively combat cartels, a systematic approach is recommended, including not only improving the quality of work of law enforcement and control agencies, but also improving the software and hardware used in carrying out inspections. Cartels in public procurement are a relatively new phenomenon for Russia; statistical data obtained from the Russian Ministry of Internal Affairs and the Judicial Department of the Supreme Court of the Russian Federation indicate that law enforcement and control authorities are just beginning their work to counter the criminal behavior of participants in cartel agreements. Only the fruitful joint work of law enforcement and control agencies will ensure the economic security of the state and protect the national interests of the Russian Federation.