The current study demonstrates an approach of analyzing the returns of Russian issuers’ stocks by taking into account the behavior of individual investors based on the application of metrics of divergence of users’ opinions of online investment platforms and the attention of investors themselves. These opinions, i.e. text messages, were collected using machine learning and deep learning algorithms. The statistics of search queries on economic-political and investment topics is used as a proxy for the attention of private investors to analyze stock returns. The text database consists of more than 4.3 million messages on Tinkoff Pulse, SmartLab and MFD platforms. Stock price behavior is also analyzed by accounting for the attention of retail market participants. The purpose of the paper is to assess the impact of divergence in opinions and attention of private investors to the returns of shares of issuers under consideration on the Russian stock market. The research methodology includes textual and econometric analysis. The author applies augmentation of training text array and training machine learning and underlying deep learning models for automatic classification. Two econometric methods of estimating regressors are used to analyze stock price behavior: generalized method of moments and generalized least squares method. The findings show: (1) divergence of opinions has an impact on stock returns only on the days of discussions; (2) private investors’ attention to economic-political and investment topics has an impact only on the future behavior of stock prices; (3) depending on the level of volatility (risk) of stocks, there are some unstable patterns of the correlation between disagreements among the users of analysed platforms and stock returns.

The subject matter of the study is to determine the tax base of property taxes and to evaluate the results of cadastral value reassessment in autumn 2023, which took place in the regions of the Russian Federation. The purpose of the article is to study methodological approaches to the definition and tax base of real estate taxes and the prospects for applying the results of the cadastral value reassessment in autumn 2023 as a tax base for corporate property tax and personal property tax. In this regard, the tasks of the study are, firstly, to accumulate information contained in regional regulatory documents on the cadastral value of capital construction objects in the regions after reevaluation, and secondly, to present this information in terms of types of objects and functional groups in those regions where possible. This detailed approach is necessary to understand whether a particular capital construction object forms the tax base for corporate property tax or for individual property tax. The relevance of the research lies in the fact that the personal property tax is fully calculated on the basis of cadastral value, while the corporate property tax is partially calculated, and a complete transition to the calculation of corporate property tax is one of the prospective directions of the tax policy on this tax. The scientific novelty of the research consists in the analysis of a totality of regional normative-legal acts, consolidating the results of capital construction objects cadastral value assessment. The main method of the study is the approximation method. As a result, for each region the amount of the total cadastral value of all capital construction objects and their quantity became available. Based on this information, the paper estimates the potential tax base and tax revenues for corporate property tax and personal property tax. The major findings include the approximation of the reassessment results distribution on the tax base for corporate property tax and corporate property tax depending on the types of objects, functional groups and labelling the objects into residential and non-residential in the documents reporting the reassessment results.

Since 2022, against the unprecedented international sanctions pressure, the Russian equity capital market has changed significantly the demand for new IPO transactions has become represented exclusively by domestic investors (the so-called “new reality”). At the same time, the initial public offering of shares on the stock exchange has become more accessible for Russian issuers and has gained even greater popularity among retail investors who have become a new driving force in the stock market. Moreover, the relevance of studying the IPO valuation process transactions in Russia is confirmed by recent government initiatives to stimulate the Russian IPO market, as well as plans to privatize a number of state-owned enterprises through initial public offerings. Thus, the purpose of the study is to identify the key features of the valuation process of IPO transactions of the “new reality” (since 2022). The methodological basis of the study is represented by the analysis of relevant international and domestic scientific publications, resulting in the analysis of the application features for various equity valuation methods on developed and developing stock markets, as well as a qualitative and quantitative study of IPO transactions of the “new reality” based on information on the feedback of key institutional investors and reports of underwriters’ research teams. In the article, the author offers the interpretation of the “fair value” definition (as a result of a multi-level company’s analysis, combining qualitative and quantitative approaches, since it sets valuations expectations for both the issuer and investors) and the application methodology for the “IPO discount”. Finally, the author provides recommendations on qualitative characteristics for reducing the IPO discount, which can be useful for new issuers planning an IPO, as well as for the scientific community studying the problems of the Russian equity capital market.

In conditions when 90% of drugs illegally traded in the Russian Federation are produced abroad, new guidelines are needed to reduce the profitability of drug business in Russia and reduce the attractiveness of its market for transnational criminal groups supplying drugs to the country. Such guideline is an assessment of money laundering scale in the drug business. In this paper, the assessment was carried out using the input-output method, which allows to obtain a sectoral structure of income from various types of criminal activity. The statistics of the Ministry of Internal Affairs of Russia are used as a database, taking into account the latency of drug crime in the country. The results of the assessment show that in 2022 drugs of illegal origin in the amount of 137.9 billion rubles to 491.7 billion rubles were not seized in Russia, in 2023 – 272.9-354.3 billion rubles, of which 96.5-344.2 billion rubles were laundered in 2022, in 2023 – 191.0-248.0 billion rubles, 86.9-309.8 billion rubles were withdrawn abroad in 2022, 171.9–223.2 billion rubles in 2023. Comparison of the calculated indicators with estimates of suspicious transactions for the withdrawal of funds abroad published by the Central Bank of the Russian Federation is not advisable, since laundered drug proceeds are not sensitive to anti-laundering tools. We assume that the author’s observations concerning the persistent seasonality of drug crime in Russia will help in the further adjustment of antilaundering measures. The revealed seasonality is not explained in terms of economic theories of supply and demand. Presumably, the real reasons for seasonality are related to the logistics of transnational criminal groups that ensure the traffic of illegal substances to Russia. This can be confirmed by the concentration of drug crime in the country identified during the study, which is accompanied by an increase in risks in the drug market.

The present article, employing the methods of economic analysis of law (law and economics), explores three specific practices of law enforcement and criminal punishment characteristic of early modern Russia. The study examines the institutions that, from the standpoint of contemporary society, seem controversial and often ineffective in the light of humanitarian standards and human rights, yet were prevaling during the historical period under consideration. Specifically, the article analyzes: (1) the judicial interpretation of alcohol intoxication as a mitigating circumstance—a notion that appears striking from the perspective of modern criminal law, where intoxication typically aggravates liability; (2) the use of torture not only against the accused but also against witnesses during interrogations, which today constitutes a clear violation of rights and freedoms; and (3) the substitution of corporal punishments with others, less radical yet still severe forms. The formal and institutional analysis demonstrates that such practices, within the context of the early modern period, could have been justified and effective from the standpoint of the state, as they served the purposes of deterring recidivism and maintaining public order. The findings emphasize the importance of historical context and institutional environment in understanding the effectiveness and origins of particular law enforcement mechanisms.

In 2024 the Nobel prize was awarded to three American economists associated with New Institutional Economics (NIE): D.Acemoglu, S.Johnson and J. A. Robinson. At the same time, contrary to their predictions, the role of countries such as China, India, and Russia in the world economy is increasing as the world is moving towards multipolarity. The article contains critical analysis of theoretical approaches used by the new Nobel prize-winners and of some of their anti-Russian comments, in particular, on relations between Russia and Ukraine. According to D.Acemoglu, S.Johnson and J. A. Robinson, China, India, and Russia are in an «institutional trap» due to inefficient institutions. In fact in 2017-2024 their economy manifested relatively good performances as it was confirmed in 2024 by the International Comparison Programme (ICP) сarried out by the World Bank. Also, the article examines current trends and pressing problems of Foreign Direct Investments (FDI). However, the author concludes that although FDI flows in the world are positively affected by the decrease of central banks interest rates in many countries, growing uncertainty about the future of the world economy and international trade is creating many new risks for global value chains and FDI. In addition, UNCTAD in April 2025 pointed out that new customs tariffs introduced by US President D.Trump are pushing the world economy towards a recession. Under these conditions the author suggests to recall some ideas about the role of the state on both national and international levels by the Nobel prize-winner in 1974 G.Myrdal (associated with Old Institutional Economics). The article provides certain recommendations for the Russian economic policy.

Throughout the development of any country, there are socio-economic crises that have to be resolved through reforms of varying depth and drama. At the same time, practices of transformation in socio-economic sphere serve as a material for testing existing theoretical concepts. The paper examines the consequences of “shock therapy”, implemented in Argentina since 2023 by the team of the libertarian President H. Miley. The purpose of the research is to forecast socio-economic prospects for Argentina from the viewpoint of Russia’s experience of the 1990s. The assessment of the latter is still largely influenced by the subjective political and philosophical views of scholars. In this regard, a less emotionally burdened, and therefore more objective discussion of the situation in Argentina is useful for domestic Russian scientific discourse. The methodological basis of the study is a comparative economic analysis, though the comparison of different countries is always debatable, especially as different as Argentina and Russia. Nevertheless, certain parallels in their socio-economic development cannot but attract attention. The work is based on publicly available information resources: research by domestic specialists and media materials, as well as data from international statistical databases used in comparing indicators. The study of the transformations taking place in Argentina is relevant theoretically for the development of economics itself, in particular, its ability to indicate the most painless way out of a crisis situation. In a practical sense, this is important from the perspective of combining universality and specificity in the formation of economic policy and determining the tactics of socio-economic reforms.

Macroeconomic instability in the period of 2020–2024 has revived discussions about its impact on economic convergence processes and methods for assessing the convergence of developing and developed countries. This paper presents a systematic analysis of modern econometric approaches and existing limitations in testing the convergence hypothesis. The methodological framework is based on classical Solow economic growth models and their extensions by R. Barro, which take into account institutional and socioeconomic factors in an open economy. However, the β-convergence identified in Barro’s cross-country models remains weak, indicating a slow process of economic convergence across countries. Over the past decade, econometrics has made significant advances, making it possible to analyze convergence using complex mathematical models such as cointegration analysis and the ARFIMA model. However, the findings are heterogeneous, making it difficult to draw a general conclusion regarding economic convergence across countries. Nevertheless, if the convergence hypothesis is accepted, this article proposes calculating the rate of convergence between countries in two ways: through average economic growth rates, by calculating the number of years required to double GDP, and using a time lag method. Although, according to the first approach, developing countries (clusters 3-5) demonstrate higher average annual growth rates than developed countries (clusters 1-2), the poorest countries (clusters 6-7) are characterized by low economic growth rates. Moreover, in a number of countries, the convergence process may slow down or completely break up due to economic and social crises. This emphasizes the importance of considering not only general trends but also the specific national characteristics of each country. Using the second method, drawing on the BRICS countries as an example, the author demonstrates an increasing economic divergence of developing countries from developed ones in the period since 1990.

Socially responsible human resource management (SRHRM) is one of the most frequently discussed concepts in Russian and international literature. However, researchers have yet to develop a unified approach to defining this phenomenon. The primary objective of this article is to conduct a comprehensive review of existing definitions and then propose a new, more relevant definition that reflects current trends and practices in this field. The applied methodology is the analysis of existing literature, as well as the comparison of various definitions and approaches to SRHRM, identifying their strengths and weaknesses. The author argues that socially responsible management not only contributes to improving corporate culture and increasing employee motivation but also plays a key role in achieving sustainable development for organizations and influencing employee engagement and job satisfaction. The study resulted in the development of a new definition of socially responsible human resource management. Its scope encompasses the theory and practice of human resource management in organizations across various sectors, including businesses, government agencies, nonprofit organizations, and educational institutions, as well as the development of strategies and programs aimed at implementing socially responsible human resource management. This study emphasizes the need to adapt theoretical foundations to modern business challenges and requirements. Socially responsible human resource management is an important tool for creating value for both organizations and society as a whole, promoting harmonious development and social responsibility at all levels.

In Russia, a lot of attention is paid to non-financial reporting of a company, investors pay attention to a comprehensive disclosure of non-financial reporting in the annual reports of companies. The purpose of the study is to assess the impact of social aspect disclosure of non-financial corporate reporting on the value of company shares in the periods before and after the coronavirus pandemic. The research methodology includes panel regression, textual analysis, and quantitative analysis indicators of the social content of companies’ annual reports. Drawing on the results of machine learning and LDA, the author compiled main “topics” of words, selected during the study of Russia’s peculiarities and mentality of investors: what is the primary attention of investors while studying the social policy of a company. The glossary incorporates 110 words and phrases recurrent in the text of annual reports and devoted to social policy. These words are subdivided into separate topics (employee health, labor conditions, social network for personnel, employee development, social activity). The findings show that in the period of 2021-2022, social factors began to play a more important role in the process of shaping investment attractiveness. Evaluation of indicators for two periods, referred to as “pre-Covid” and “post-Covid”, made it possible to prove an increase in the number of significant social factors on the value of company’s shares. Thus, if in 2018-2019 only 3 significant indicators were identified, then in 2020-2021 the number of significant social variables increased to 9, which confirms hypothesis 3. It was found that social policy indicators have a direct relationship (working conditions, average number of training hours) and the reverse (ATS, injuries, social investments). We confirm the theoretical contribution of the signaling theory, since the signals associated with social policy influence investors and the decisions they make.

The article focuses on developing the solution to address the crucial issue of ensuring the fairness of external corporate ESG assessments. The research justifies the importance of financial metrics for assessing non-financial business aspects and the applicability of the KRESG index model, which reflects the level of a company’s exposure to technogenic ESG risks based solely on data from its financial statements. The proposed methodology aims to increase the objectivity and independence of ESG assessments conducted by external parties. The study is based on primary data aggregated by the author, including the values of financial reporting metrics and ratings from leading international ESG agencies (S&P and Sustainalytics), for 55 prominent public companies operating in the global energy sector and located in 20 different jurisdictions. The research methodology is based on regression and multivariate analysis, utilizing non-parametric testing and econometric modeling techniques. The study is based on an independent sample and verifies its components with validated statistical analysis tools, which ensures the authenticity and reliability of conclusions and judgments derived. The scientific novelty of the findings lies in evaluating the applicability of a proposed index model for assessing the degree of corporate exposure to ESG risks for companies operating in the international hydrocarbon energy market, based on companies’ financial data. The findings of this study expand and enhance the body of empirical knowledge, increasing the practical applicability and objectivity of third-party rating assessments of a company’s ability to withstand risks related to technogenic ESG issues. The findings will be of value for socially responsible investors in their decision-making process while selecting sustainable financing options, as well as to economists seeking to develop optimal algorithms for third-party ratings that ensure reliable and objective analysis results that may form the basis for futher research in this field.

Issues related to supporting investment process, which is the foundation of regional socioeconomic development, are currently highly relevant due to the search for new investment opportunities in the context of limited financial resources and changing conditions for traditional economic lending. Assessing the investment attractiveness of regions plays a key role in addressing this challenge, as this assessment is a foundation for managerial decisions by external investors. This research focuses on the scientific and practical basis of a methodology for assessing the investment attractiveness of regions as a key tool for increasing their socioeconomic potential. The objective of the paper is to describe the results of a study examining the methodological foundations for assessing the investment attractiveness of a region based on data from the Samara Region. Mathematical modeling serves as a methodological basis for the study, incorporating a regression analysis technique into the development of a model aimed at assessing the investment attractiveness of a region, creating the mathematical basis for achieving this goal. This author describes the content and applicability of a mathematical model for assessing the integrated indicator of a region’s investment attractiveness, which is synthesized from three group indices. Their calculation is based on a specific set of local statistical indicators that are most informative in characterizing the socioeconomic status of Russian regions. The results of this study can be used in investment decision-making and in developing investment strategies for regional development. The proposed methodological approach improves the objectivity of assessments that provide the basis for conclusions regarding the level of investment attractiveness of regions and ensures more robust decision-making by active investors (investment funds) that pool the financial resources of passive investors to invest in the development of a particular region. This, taken together, will contribute to further development of individual industries and economic sectors in the regions, increasing their export potential, and improving the socioeconomic status of the country’s regions.

Ensuring sustainable supply in all food markets, including the regional market of eggs and egg products, is fundamental to achieving food security in the region, which contributes to the implementation of key government objectives in the field of substitution of imported products and providing the population with high-quality food. The purpose of the study is to assess the state of reproduction and the regional market of eggs and egg products in the context of ensuring food security in the Irkutsk region. The object of the research is the own production of eggs and egg products on the regional market of the Irkutsk region. The author applies statistical methods: descriptive statistics, comparative analysis, dynamic series analysis and other research methods. At the first stage of the study, the analysis of data on the number of chickens, production volumes and egg production allows us to determine the type of reproduction as expanded due to extensive factors. The analysis of production output by category of producers shows that the main category of egg producers in the Irkutsk region are agricultural organizations. Analyzing the level of egg self–sufficiency in the region, a fairly high level of 154% was revealed, but not a sufficient level of economic accessibility 95%, which indicates that the population consumes eggs less than the established rational consumption rate. The assessment of import/export ratio shows that the region does not depend on imports and that both exports and imports are developing quite well in the region. To increase the level of consumption, development directions are proposed for both producers and government agencies. The results of the state of reproduction assessment and the regional egg market in the context of ensuring food security can be applied by government agencies to develop a strategy for the development of the poultry industry and optimize government support, as well as by producers to regulate their production activities in order to increase its economic efficiency.

The article explains the link between birth year and mortality levels across Russian cohorts. Life expectancy in Russia did not increase since the 1960s until the early 2000s. However, even taking into consideration its growth over the past two decades, the indicator still lags behind the values in European countries. Slow growth may be partly explained by cohort effects in mortality: some cohorts are disadvantaged compared to their predecessors and successors. Using an age-period-cohort (APC) model, the article identifies Russian cohorts with the strongest cohort effects in mortality across six cause-of-death classes (circulatory diseases, respiratory diseases, neoplasms, infectious diseases, digestive diseases, and external causes). The study draws on age-specific mortality rates by 5-year and single-year age intervals from the Russian Births and Deaths Database (RosBRiS) of the Center for Demographic Research at the New Economic School for the period of 1959–2022. For mortality from respiratory diseases and neoplasms, the largest cohort effects are found among those born in the late 1950s to early 1960s. Cohorts born in 1975–1985 show the strongest cohort effects for mortality from circulatory diseases, external causes, digestive diseases, and infectious diseases. The elevated cohort effects in these cohorts may be restraining gains in life expectancy, as these individuals are still in ages that contribute substantially to overall life expectancy levels.

“What do you think is a ‘genius’?”
“Well, it’s the ability to see things that others don’t see.
Or, more precisely, the invisible connections of things.”
Vladimir Nabokov

The problem of developing a systematic approach in educational and methodological work is considered. At the same time, the emphasis is not on traditional data analysis, but on the use of narrative in decision-making processes. Applied system analysis is used as a basic approach. Analyzed the ability to combine the narrative approach and applied systems analysis in complex management situations that require unique information and decisions based on personal discretion or judgment, rather than strict rules or procedures. A narrative is a value–oriented statement, the clarity and persuasiveness of which depends on the messages it contains about the causality of events that are important for understanding the situation and making decisions. Applied system analysis is an algorithmically structured sequence of steps, starting with the general formulation of a problem and ending with the justification of a project to solve it. The similarity between these two approaches is that the results of understanding and analyzing complex situations are presented in terms of spoken or descriptive professional language. It is shown that the combined use of these two approaches can be effective in solving large-scale problems that require significant amounts of information and time. The provisions discussed in the article have been tested in the educational process of the Faculty of Economics and the medical university.