The article explains the current methodological approaches to the analysis of the export conjuncture (on the example of Russian ma nufacturing enterprises), including a new methodology for its integral assessment. This assessment is made by modeling the global demand for domestic products and their price competitiveness in the international market.

The importance of the analysis of the current phase of Russia's economic development is emphasized, when a structural transformation of industrial and export policy is taking place and a new contour of foreign economic activity is being formed. This necessitates the improvement of methods for export climate assessment. The author underlines the relevance of using not only qualitative and quantitative indicators, but also their hybrid modifications in the economic and statistical analysis of export trends. The article presents a new hybrid measure – the Export Climate Index (ECI), which aggregates the indicators of demand for domestic manufactured goods and their price competitiveness in the international market. The methodology for its calculation is based on theoretical developments, adapted to the specifics of the Russian economy, and the best world practices for measuring and analyzing export trends.

The quantified results of business and consumer surveys in the countries that are Russia's main trading partners, as well as the real effective exchange rate of the ruble according to the Bank of Russia, are used for empirical calculations.

The calculations results revealed a significant leading correlation between the ECI dynamics and the dynamics of the referent – the indicator of export of goods in value terms, confirming the possibility of using the new index not only for an integral assessment of the export climate in Russia, but also as a short-term predictor that effectively supplements statistical measures.

The article presents some results of the study of problems of improving the secure use of digital technologies in the new stage of the development of information and communication technologies (ICT). The relevance is explained by the fact that the use of ICT in the current conditions of the development of the information society and the digital transformation of the economy not only leads to the known positive socio-economic effects but also presupposes the inevitable negative impacts. The objective of protecting the interests of an individual, society, and the state from internal and external information threats is related to the concept of information security. The expansion of its boundaries – from low-level technical measures for the protection of information systems (computer security and cybersecurity) to the strategic management of economic production in this context – has created a new relevant category, digital security, and dictates the expediency of combining these terms into a general concept of «secure use of digital technologies».

The author analyzed the existing methodological approaches to the statistical study of the problems under consideration and developed several proposals for improving the corresponding system of statistical indicators. Methods of descriptive statistics, correlation-regression analysis, and machine learning methods (in particular, various variants of classification algorithms based on decision trees) were used in the analysis to achieve this goal.

While studying information and methodological sources which are indirectly related to statistical resources (a well-known web platform that brings together researchers in the field of data science and machine learning, Kaggle, was examined), the author analyzed the results of a thematic survey of companies. As a result of modeling the influence of the «secure use of digital technologies» factor on the efficiency of economic activity, it was established that its variation by about a third determines the level of economic efficiency of the company within the presented population. The application of machine learning techniques has resulted in acceptable quality predictive models for classifying companies by economic activity in the same factor context.

From a practical point of view, according to the author, the application of the proposed approach to the formation of a system of statistical indicators shall be beneficial for managing processes that ensure the security of the use of digital technologies at the enterprise, region, and country level as a whole.

The article discusses the results of the socio-economic development of Russia in 2022 and highlights trends and forecasts of the dy namics of macroeconomic indicators for 2023–2024. At the same time, the main challenges and threats are analyzed, including production, trade, economic, financial, monetary, infrastructural, logistical and other restrictions that have become the main instruments of the West’s sanctions wars against Russia in the new geopolitical reality associated with Russia’s conducting a special military operation  (SMO).

The main objects of analysis are the current state, trends, risks and threats to the Russian economy, the dynamics of industrial production, prices, inflation and foreign trade. It is noted that, despite the toughening of challenges, sanctions and threats in 2022, the macroeconomic results of 2022 turned out to be higher than official forecasts and experts' expectations. This made it possible to substantiate the main conclusion of the study that the Russian economy managed to prevent a collapse and find additional opportunities to better unlock the potential of economic growth and social progress in the current three-year period of 2023–2025 and in the long term. According to the authors, the need to further transform and improvethe efficiency of the Russian economy is predetermined not only by current but also, possibly, future challenges.

Building on state statistics, the authors analyzed the situation with providing housing opportunities for residents of the Far Eastern Federal District (FEFD). The objective of the study is to define the housing stock characteristics of the macroregion. Based on the methods of statistical analysis applied by the authors, the following parameters of the FEFD housing stock are identified: differentiation of regions – constituent entities of the Russian Federation in terms of housing provision and housing improvement, the degree of housing satisfaction according toresident surveys, debt on housing loans and affordability of rental housing. The paper demonstrates differences in the positions of FEFD regions. The article concludes that additional funding of the FEFD regions through state programs since 2014 has not affected the growth of the FEFD housing stock, which in terms of specific indicators of housing provision, is below the Russian average (2018–2020). The authors argue that for several FEFD regions, there is a dire need to improve housing quality (this applies particularly to the Republic of Buryatia and the Trans-Baikal Territory).

The authors analyze the dynamics of infected and deceased from the coronavirus pandemic over 148 weeks in the «large economies» (24 countries). According to the authors, a large economy is a country that, at least within one year from 1980 to 2019, produced more than 1% of the global GDP. Although the organization of the health care system in these countries is different, only the general requirements of WHO could provide information on the spread of the pandemic in comparable formats. The change from daily data on the number of infected and deceased to weekly data on these indicators (per 1 million persons of the country's population) made it possible, firstly, to exclude insignificant daily fluctuations of these indicators and, secondly, to obtain information in comparable values for countries with widely differing populations.

The paper demonstrates that the frequently used comparison of countries by such integral indicators as the number of infected and deceased at a particular time is not very informative. It is due to the fact that, over time, country-specific circumstances change dramatically. Nevertheless, it was precisely the introduction for analytical purposes of such characteristics as weekly increment peaks of infected people and weekly increment peaks of deceased that made it possible to identify the four features. First, the number of those peaks is small for all countries: from 5 to 9 over 148 weeks. Second, these peaks cover between 70 and 90 percent of the totals of the integral number of infected and deceased in a given country. Third, most peaks of the infected are accompanied by peaks of the deceased with some delay: from zero to six weeks, but in most cases by two weeks, which is consistent with clinical observations. Fourth, the peaks of infected people in all 24 countries exhibit the statistical property of being quasi-synchronous (the so-called property of the maximums of these peaks to fall within predetermined intervals of weeks with probabilities that are the same for all countries). This fact is proved using the mathematical homogeneity criterion χ2.

In this article, building on the data of official Russian statistics, the author analyzes the development of the organization of scientific activity over the last decade, including compared to 2014 – the initial period of anti-Russia sanctions and compared to 2018 – the year before theCOVID-19 pandemic. The paper describes sanctions imposed by a number of unfriendly countries, namely, the refusal to cooperate inmany spheres, including the economy, science, and education. The article considers initial measures to neutralize sanctions. In particular, Russia proposed to create educational «hubs» in the Asia-Pacific region based on the association of the leading universities and scientific institutions for the training of a skilled workforce to implement priority directions of the development of the economy in Russia and the countries of South-East Asia, taking into account their relevance in the real economy sector. The paper analyses issues of integration of science, higher education, and industry, which contributes to the increase of efficiency and effectiveness of research, quality of education, and training of scientific and technical personnel, as well as the inflow of youth in the research and development sphere.

The author outlines the directions for the development of the global information/digital society concerning the demand for new digital technologies, which, year after year, are being revised, updated, and improved. High emphasis is placed on the processes of digital transformation, which have a widespread influence on scientific activities, so much so that 2022–2031 were proclaimed as the Decade of Science and Technology. For instance, by 2024, as part of this program, a series of works will be performed covering the transfer of all state information systems to a unified digital GosTech platform, which in the current complicated conditions will better the quality of public services provided to businesses and citizens.

The paper analyses alcohol consumption patterns among working residents of Russia, depending on their professional and social statuses, using statistical methods. The study is based on data from the Russian Longitudinal Monitoring Survey of the National Research University Higher School of Economics for the period of 2013–2019. Sampling included working women aged 16 to 55 and men aged 16 to 60.

The introductory part of the article covers the main trends in alcohol consumption among working Russians with different professional and social statuses. The main part of the article presents the results of an empirical study of the statistical relationship between the characteristics of an employee's professional and social statuses and indicators characterizing the probability and volume of consumption of specific alcoholic beverages (beer, wine, vodka, etc.) and alcohol in general. An econometric analysis of the relationships was carried out based on a random effect panel logistic model and an individual random effect Tobin model. Statistical estimates were made separately for men and women. The regression analysis helped the authors find an increase in the probability of consuming alcohol in general, as well as wine and spirits (cognac, whiskey, liqueurs) for workers with the highest professional status (legislators; high-ranking officials; senior and mid-level executives), as well as women with mid-level qualifications compared to unskilled workers. At the same time, the authors recognized a downward trend in the probability of vodka consumption for the respondents of both gender groups with the growth of their professional status (most pronounced for women). In addition, with an increase in the professional status of an individual, there was a trend towards a decrease in the volume of alcohol consumption in general and by specific beverages except for wine. The volume of wine consumption by men from the categories of "clerks and workers in trade and services" and "mid-level professionals; officials" exceeded the value of the corresponding indicator for unskilled workers. An analysis of the statistical relationship between the social status of working Russians and their predisposition to consume alcoholic beverages revealed an increase in the probability of consumption of selected alcoholic beverages among representatives of both gender groups and the probability of alcohol consumption in general (among men) with an increase in the social status of an individual with more moderate consumption compared to workers with lower social status (for men).

According to the authors, the results of this study can be relevant to the elaboration of specific alcohol policy measures aimed at reducing alcohol consumption among the employed population of our country.

The article considers the results and methods of international comparisons of national income carried out in the CMEA from 1959 to1988. It is noted that the results of these comparisons were used for solving problems related to the organization of economic cooperation within the CMEA. This goal was consistent with the methodology of bilateral comparisons of the national income of the USSR with each other CMEA countries. The final results for each bilateral comparison were computed using the Fisher index formula. This procedure did not secure the transitivity of the results. Considerable attention was paid to selecting commodity representatives with prices for calculating purchasing power parities (PPPs). For this purpose, meetings of experts, who were well-versed in the technical characteristics of the selected commodity representatives, were convened: in some cases, commodity prices were adjusted to ensure their comparability. The biggest challenges emerged while securing price comparability for the following commodity representatives: machinery, equipment, and construction projects.

The paper presents characteristics of GDP based on PPP comparison methodology carried out within the UN ICP framework. It ensured the comparison of UN ICP and the CMEA comparison methods. In particular, it is noted that GDP comparisons were carried out using multilateral methods of comparison, securing the transitivity of the computed indices. In addition to national income indicators of industrial and agricultural output, capital investments and consumption of the population were compared. The article contains two tables with results of comparisons of national income of the CMEA countries, which were initially classified.