Purpose of the study. Analysis of changes in the dynamics and structure of the balance of payments to develop preventive anti-crisis measures is one of the important and most difficult tasks of regulating the economy at the state level. The growing number of scientific papers devoted to modeling dynamics, studying the relationship of the balance of payments with various endogenous and exogenous factors indicates the importance and growing interest in this topic.

Materials and methods. The original time series are nonstationary. When moving to time series with differences, information corresponding only to short-term changes is stored in these series. And all other information covering long-term changes in dynamics is lost when moving to differences. The situation that has arisen requires a correct approach to the process of modeling the time series under consideration. The observation period of the study covers annual data from 1995 to 2023. To solve the problem and to provide a characteristic description of the dynamics of the development of the balance of payments, the paper first carried out an economic analysis of the dynamics of the balance of payments for its individual articles, from 2012 to 2021, in particular for 2020-2021. Subsequent steps for advanced econometric analysis of time series were devoted to the determination of stationarity, the transition to differences, and the construction of vector error correction models. When performing the cointegration test, its combination with the stationarity test was revealed. All necessary tests were performed and analyzed. Critical values for these statistics were obtained and analyzed.

Results. This article develops a vector error correction model that allows the analysis and modeling of more than two – time statistical series in a specified time period. VECM limits the dynamics of endogenous factors and directs them to a cointegration relationship. The paper examines the relationship between the current account of the balance of payments of Azerbaijan and world prices for West Texas Intermediate and Brent oil.

Conclusion. Using the constructed VECM, it is possible to measure deviations from equilibrium and the rate of its restoration. The very slow recovery after the disruption from the shock reactions of changes in world oil prices allows us to conclude that there is a stable, longterm, equilibrium relationship between the time series under study.

Purpose of the study. Infant mortality is included in the list of indexes for assessing the performance of executive authorities of the regions of the Russian Federation. Its reduction serves as target indicators for the implementation of the national projects «Healthcare» and «Family». The article presents the results of statistical analysis and forecasting of the main trends in the infant mortality rate in the Russian Federation to assess the possibility of achieving the planned values of the target indexes for the implementation of national projects.

Materials and methods. The theoretical basis of the study was the works of foreign and domestic authors devoted to the study of infant mortality and factors for its reduction. Methods of descriptive statistics, groupings, and the forecasting method based on the ARIMA model were used as the methodological basis of the study. The information base of the study is data from the Federal State Statistics Service.

The results of the study allowed us to identify the dynamics and structure of infant mortality for the period under review. An analysis of the dynamics of the infant mortality rate in Russia shows a decrease from 8.6 in 2012 to 4.2 per 1000 live births in 2023. Infant mortality among boys exceeds that among girls. The infant mortality rate in rural areas is higher than in urban areas: on average, infant mortality in the city is 5.5‰, in rural areas – 6.9‰. The presence of territorial differentiation in the level of infant mortality by regions of the Russian Federation. The results of grouping the regions of the Russian Federation made it possible to identify regions with low, medium, high and very high characteristics of infant mortality. The vast majority of Russian regions are characterized by an average infant mortality rate. Regions with low infant mortality rates include regions of the Far North (Nenets autonomous area, Khanty-Mansi autonomous area), central Russia (Kaluga district) and southern territories (Sevastopol city). Subjects with high infant mortality rates include the republics of the North Caucasus federal district (Karachay-Cherkess Republic, Chechen Republic, Republic of Dagestan), Siberia, and the Far East (Krasnoyarsk, Primorsky, Kamchatka and Zabaykalsky territories). The fourth group with very high infant mortality rates includes only the Chukotka autonomous area, where the index reaches an abnormal value of 19.1‰. Forecasting infant mortality rates based on the ARIMA model made it possible to assess the probability of achieving the target indexes for its reduction set by the national project «Healthcare» and the federal project «Maternity and Childhood Protection». According to the forecast, the infant mortality target index will be reached by 2027. With a probability of 95%, the infant mortality will be 3.9 cases per 1000 live births.

Conclusions. The analysis shows that achieving the target indexes for reducing infant mortality is realistic if current trends are maintained. To achieve the set goals, it is necessary to continue implementing state and regional programs and national projects aimed at increasing the birth rate, protecting motherhood and childhood, the availability and quality of medical care for children, developing children’s health care and stabilizing the demographic situation in the country.

The purpose of the study is to analyze and identify the structure of the parameters of resource provision of the population in the field of healthcare and the efficiency of using hospital stock in the regions of the Russian Federation. Such structuring will allow classifying both the regions of the Russian Federation and identifying among the analyzed parameters the factors that largely determine regional differences and interregional disparities in order to prioritize these factors when developing the main directions of state regulation of interregional differences in the regions of the Russian Federation in the field of healthcare.

Materials and methods. To achieve this purpose, a cluster analysis of the regions of the Russian Federation was carried out on the basis of data from the Unified Interdepartmental Information and Statistical System using the iterative k-means method implemented in the Statistica software package.

Results. As a result of the cluster analysis of the regions of the Russian Federation by six features, nine clusters were identified and their profile characteristics were determined. The main results of the multivariate statistical analysis include: analysis of variance parameters; values of total intra-cluster variances; values of intercluster sums of squared distances; a graph of average values for six features for each of the nine clusters, as well as descriptive statistics for each object within the selected clusters. Based on the results of the variance analysis for all clustering options, the magnitude (and significance level) of the F-values and the magnitude of the empirical coefficient of determination revealed a high significance for the distribution of objects into clusters of the following features: provision of hospital beds per 10 thousand population; provision of the population with mid-level medical workers working in state and municipal medical organizations (people per 10 thousand population) and provision of the population with doctors working in state and municipal medical organizations (people per 10 thousand population).

Conclusion. Descriptive statistics for each Russian region within the nine selected clusters showed that there is a relatively low variability of feature values within the clusters. This indicates a high degree of homogeneity and compactness of the constructed clusters. The obtained clustering results allow us to determine the resource profiles of Russian regions and formulate the main priorities of the regional healthcare development policy in Russia, aimed at increasing the degree of homogeneity of the country’s regions in terms of quality and accessibility of medical care. The practical significance of the study is that its results will allow us to more effectively develop regional policies and carry out state regulation of the healthcare sector in the Russian Federation, as well as to determine measures to support the industry in regions with low indexes of hospital stock efficiency.

The purpose of the study is to establish and describe the trends in the development of insurance in Russia as a type of market activity, redistributive financial relationships and phenomena of social life in inseparable connection with the most important parameters of economic and social development. The most important segment of the market economy is subject to statistical research, which unites specific institutional units that are market producers of financial services of a redistributive nature, namely, the entire set of insurance organizations operating in the economic territory of the Russian Federation and considered as resident units according to the methodology of the system of national accounts. The study was conducted to identify and quantify the impact of socio-economic factors such as the standard of living of the population, housing construction, and road traffic conditions on the cost results of the Russian insurance sector, and to establish patterns and correlations of these features over a long period of time.

Data and methods. To achieve this goal, a set of tasks related to the use of mathematical and probabilistic tools has been solved, which has become an integral part of the statistical methodology for processing numerical arrays to study mass phenomena occurring in society. Methods of analytical alignment, trend forecasting, regression of dynamic series, visual representation of systematized data, namely graphical and tabular, applied software applications of statistical analysis have been applied directly to study the results of insurance organizations.

Decisions and results. The processing of numerical information generated into an array of source data led to the construction of a dynamic regression model reflecting the patterns of formation of the financial result of insurance organizations, predetermined by the level of income of the population, insurance payments, housing construction, and road transport discipline. The forecast values of the risk factors were calculated, which made it possible to predict the index of insurance premiums for the entire set of insurance organizations for the period up to 2026.

Conclusion. Based on the results of statistical modeling, an economic interpretation of the parameters of the constructed models and the relative values describing the elasticity of the relationships was carried out. The directions of relations have been established, and their modern particularity has been substantiated. The results obtained can be used by government statistical agencies and experts in monitoring financial and insurance markets in the Russian economic space.

Purpose of the study. The purpose of the study is to determine the possibilities of using dispersion analysis as a tool for increasing business profitability by obtaining and providing clients in real estate agencies with objective criteria information when they provide intermediary and consulting services.

Materials and methods. The information base of the study was statistical data on the real estate market of the city of Yaroslavl. Quantitative indexes were assessed for compliance with the normal distribution using the Kolmogorov-Smirnov and Shapiro-Wilk tests. When presenting the results of descriptive statistics, the median (Me), lower and upper quartiles (Q1-Q3) were used. Two-factor analysis of variance, nonparametric Kruskal-Wallis tests and Mann-Whitney U-test were used as statistical tools for the study. Dunn’s test with Bonferroni correction was used for performing posteriori comparisons. The exclusion method was used to select data for multiple linear regression. Statistical data processing was performed on a personal computer using the SPSS Statistics v. 27.0 program (SPSS Inc., USA). The significance level was taken to be 0.05.

Results. The necessity of using dispersion analysis to improve the efficiency of real estate agencies in providing professional services is substantiated. The concept of criterion information is formulated as a necessary and sufficient volume of data obtained by objective methods to reduce the risk of errors in selecting apartments for clients. The cost per square meter of housing is compared depending on various

factors influencing the choice of a professional solution. A multiple linear regression equation is constructed to predict the cost of housing.

Conclusion. The author’s model of using the possibilities of dispersion analysis as a tool for forming the necessary criterion information for clients allows increasing the profitability of business in real estate agencies.

The article presents new approaches to the development of the strategic management system for the socio-economic and scientifictechnological spheres of Russia, as well as to the development of the respective strategic goals in view of new challenges associated with the rapid S&T progress, comprehensive digitalization of society, which, in turn, inevitably brings new, unpredictable risks. The need to improve the management of socio-technological development in the changing world is shown, which is especially relevant for Russia in view of the current confrontation with the united West and the intensification of the competition for the Russia’s future. The article explores the role of the Q-methodology in selecting scientifically based strategic management goals. It demonstrates its potential to combine qualitative and quantitative approaches, determine the internal structure of attitudes and opinions, identify their similarities and differences, and reduce them to a few «significant Factors» reflecting the common ways of thinking. Relying on modern understanding of the two key issues – scientific research for management and scientific expertise in management – an attempt is made to rethink the interaction and mutual trust between science and public management.

The purpose of the research. Substantiation of the need to use new approaches and scientific instruments for the strategic management of socio-technological development and the formation of socially agreed and scientifically based goals for such development in the new multipolar intellectual world, where digital innovations shape the most important of evolutions – the evolution of human beings. Strategic visions, goals, and decisions developed by different teams and organizations are often based on differing values, methodologies, approaches, models, and methods. Recommended development paths and problem solutions typically differ and represent conflicting points of view. The difference in subjective assessments makes it difficult to reach consensus and take strategic decisions. This research aims to improve strategic management and scientific expertise.

Materials and methods. The research was carried out based on the study of the results of the relevant scientific research; a review of systematic studies, conditions and factors influencing the development of scientific research; the framing theory and the frame analysis. The authors carried out the generalization of the obtained local results on the example of forming scientifically based development goals.

Results. The authors carried out an analysis of the feasibility to apply the new approach in making scientifically grounded decisions and in formulating strategic goals for innovation development, given existing constraints and expert opinions. Using the Q-methodology to improve mutual understanding of the participants’ positions and professional cultures the authors examined the possibility of grouping the proposed solutions with respect to key opinions on the existing problems of all participants of the strategic goals forming system.

Conclusion. The proposed approach to organizing strategic development management and formulating scientific grounded goals facilitates the process of forming a consensus of decisions by using the comparison of conservative and innovative options for formulating strategic goals. The application of the Q-methodology allows the improvement of the quality of strategic management in conditions of high uncertainty, diversity of approaches and assessments, delays in making research of complex systems, as well as of innovative technologies and processes. This expands the potential for using science for the development of public policy, stimulating improvements in its quality, and clarifying the directions of necessary scientific research.