This article examines the thermal power industry as a crucial component of the national energy system and part of the natural monopoly sector, with a focus on its institutional framework shaped by incomplete structural and behavioral reforms. As a strategically important sector, the thermal power industry plays a dual role: ensuring energy security and stable supply, while also contributing to climate change mitigation as one of Russia's major greenhouse gas emitters. The study analyzes the course and consequences of deregulation, identifying institutional constraints that hinder modernization of energy and utility infrastructure and limit company involvement in climate initiatives. It advances proposals to align the regulatory framework with structural reform principles in natural monopolies, while integrating contemporary adaptations and behavioral economics. Special attention is given to regional climate policy implementation, highlighting best practices and successful cases. Based on a comparative analysis of Russian and international experiences, and with due regard to sectoral and regional specificities, the study confirms the hypothesis that effective modernization of the regulatory regime must be completed, accompanied by fine-tuning of climate policy instruments to meet current energy and climate challenges. The hypothesis is further expanded by demonstrating the importance of strengthening regional climate policies and encouraging proactive local authorities to support business-led initiatives - an essential condition for balanced, long-term socio-economic development. The results may be applied by academics and educators, federal and regional authorities in charge of antimonopoly, energy and climate policies, as well as by large businesses in developing competitive strategies in the face of current challenges.
To develop decisions on foreign trade and macroeconomic policy, it became necessary to assess the impact of anti-Russian sanctions on Russia's reorientation of trade flows to neighboring post-Soviet countries, as this procedure has become a primary task for adapting to the sanctions. Using the difference-in-differences method, we assessed the impact of the reorientation of export and import flows to several post-Soviet countries in 2022 and 2023 in response to anti-Russian and secondary sanctions imposed by unfriendly countries, including for individual partner countries. The assessment yielded a number of results describing the dynamics of changes in foreign trade flows for 2022-2023. Specifically, in 2022, Russian firms managed to reorient their exports to Azerbaijan and Tajikistan, while reorienting their imports to none of the countries under consideration (excluding Tajikistan, Turkmenistan, and Uzbekistan, for Russian imports from which the impact of sanctions was insignificant). In 2023, Russian firms adapted better to the sanctions: they managed to reorient exports to Azerbaijan, Tajikistan, and Turkmenistan, while imports were unaffected, with the exception of Kyrgyzstan. The study also found that a net negative impact of secondary sanctions on Russia's trade with post-Soviet countries was observed only in 2023, which is consistent with statements by unfriendly countries about the limited effect of anti-Russian sanctions and the tightening of secondary sanctions in 2023. The study's results can be used to describe foreign economic flows and formulate appropriate export-import policies.
To conduct effective monetary policy, central banks require comprehensive and timely information on the state of economic and consumer activity, as well as the ability to predict their future dynamics to build an effective strategy. Typically, economic analysis relies on data from state statistical agencies, which often have significant time lags. To enhance the analysis and forecasting of economic indicators, international practice also involves using data from business tendency surveys conducted by central banks or specialized agencies. This data can serve as predictors for conventional statistical indicators and help forecast their dynamics. In this paper, the authors first summarize international and Russian experience in forecasting economic activity using business survey data. Second, using pairwise and multiple linear regression models, as well as dynamic factor models, the authors examine the forecasting accuracy of economic indicators both without and with the inclusion of data from the Bank of Russia's business surveys. The initial hypothesis - that indicators derived from business surveys significantly improve the forecast quality of economic and consumer activity indicators for the Russian Federation calculated by Rosstat - is generally confirmed. The authors conclude that the Bank of Russia's enterprise monitoring indicators indeed substantially enhance the quality of economic forecasts. The findings of this study can be utilized in shaping the forecast values for monetary policy.
According to a number of studies, as well as the experience of developed and most developing countries, the Russian insurance market currently has significant growth potential. The purpose of this article is to identify possible tools for increasing demand for insurance services that differ from existing traditional growth drivers. The study hypothesizes that sources of growth in collected insurance premiums may include not only traditional increases in insurance rates or the expansion of the range of loan-related insurance options, but also insurance products atypical for the Russian market. The article proposes the active use of a product new to the Russian market - specifically, the possibility of introducing elements of social microinsurance, combining features of microinsurance and social deposits and accounts, into insurance companies' product lines. In this study, the authors develop a possible mechanism for implementing these microinsurance products, taking into account regional differentiation and defining a possible list of covered risks. Based on the conducted research, using methods of generalization and comparative analysis, the authors also identify potential segments for promoting increasingly popular short-term insurance contracts, as well as the conditions for their implementation. These measures are aimed at increasing demand for insurance products and developing the Russian insurance market amid stagnation in the country's insurance system. The research results can be used to formulate appropriate insurance market policies, including product and industry-specific ones.
The study aims to understand whether the use of the data from the Monitoring of Enterprises of the Bank of Russia improves the accuracy of the inflation forecast for Russia as a whole on a short-term horizon of 1, 2, 3 and 6 months. The relevance of the study is determined by the high value of the correctness of the inflation forecast for the correct use of the monetary policy tools available to the mega-regulator. Potentially, monitoring data have strong predictive properties due to their connection to the forecasting power of economic entities. Also, studies using the forecasting of inflation indicators using machine learning methods instead of classical econometric models are becoming increasingly important. The current work verifies the predictive power of enterprise monitoring data by comparing the errors of the out-of-sample Consumer Price Index forecast in pseudo-real time using a set of econometric analysis and machine learning models with different information sets: with and without monitoring indicators. Comparison of model errors with different information sets allowed us to estimate the overall contribution of monitoring data to the predictive power of the models. The Die-bold - Mariano test adjusted for small samples was used as a formal test when comparing the accuracy metrics of the models. The modeling yielded empirical arguments supporting the presence of useful predictive properties of monitoring indicators for Consumer Price Index forecast models. Adding monitoring indicators to the models usually leads to a decrease in the out-of-sample forecast error, especially when forecasting for a horizon of up to three months. This result depends on the choice of model; on average, direct forecast models with regularization better reveal the predictive properties of monitoring data. The Consumer Price Index forecast by components also works well when using industry monitoring statistics. In general, indicators from enterprise monitoring can be considered as leading indicators and used at the stage of short-term forecasting.
This paper demonstrates the potential application of artificial intelligence - specifically, clustering algorithms and related data visualization techniques - in the context of digitalization of public finance. The analysis is conducted of the possibility of introducing central bank digital currencies as a new instrument of monetary policy. The research proposes a methodological approach based on the adaptation of the Cross-Industry Standard Process for Data Mining framework to cluster analysis, specifically for clustering countries to evaluate their readiness for Central bank digital currencies implementation. The data preprocessing stage included handling missing values, outlier detection, feature scaling, and correlation analysis. Subsequently, clustering algorithms requiring a predefined number of clusters were employed, including Hierarchical Clustering, K-Means, K-Medoids, Spectral Clustering, and Balanced Iterative Reducing and Clustering using Hierarchies (with the number of clusters determined using the elbow method, dendrogram analysis, and theoretical justification). Additionally, clustering algorithms that do not require a predefined number of clusters were applied, such as Affinity Propagation, Mean Shift, Density-Based Spatial Clustering of Applications with Noise, Hierarchical Density-Based Spatial Clustering of Applications with Noise. To evaluate the clustering results, the following quality metrics were calculated: Silhouette Score, Davies - Bouldin Index, and Calinski - Harabasz Index. The application of cluster analysis revealed the possibility of identifying countries with similar characteristics and conditions and grouping them in terms of their readiness to implement Central bank digital currencies. The theoretical contribution lies in substantiating the applicability of clustering and visualization techniques for the analysis of public finance, including the identification of cross-country similarities and differences in the context of Central bank digital currencies deployment. The practical significance of the study is in the development of an approach for assessing the conditions necessary for the successful implementation of Central bank digital currencies, which may assist central banks in designing optimal deployment strategies.
The article presents an analysis of the manifestation of opportunistic behavior of insurance organizations in Russia, highlights the stages and forms of opportunistic behavior, its causes and main manifestations. A hypothesis is put forward that in modern Russia the nature of opportunistic behavior of insurance organizations has changed from supported by owners to a more common form in the world - misselling and actions of employees of insurance organizations and insurance intermediaries. The purpose of the study is to show the significance for the Russian insurance market, to study the causes and consequences of opportunistic behavior of insurance companies, their owners, management and personnel, options for their manifestation and prevalence throughout the development of the Russian insurance market and, on this basis, to give recommendations for minimizing the consequences of such behavior. The current practice of opportunistic activity of insurance organizations is more associated with the actions or inactions of insurers' employees and is implemented through an increase in the cost of insurance services due to incomplete disclosure of information about the insurance program and unfair actions of employees when concluding an insurance contract, as well as through limiting payments at the settlement stage. The change of initiators of opportunistic behavior from owners and management of insurance organizations to personnel, insurance agents and intermediaries is proven. Today, the most vulnerable are directly employees of insurance companies themselves, whose motivation is objectively more associated with solving short-and medium-term problems.
In environmentally sensitive industries, ESG ratings play a crucial role in shaping a company's reputation and its ability to gain access into capital markets. The lack of standardized criteria can create disparities, potentially disadvantaging businesses in specific political or geographic areas. This research investigates the correlation between ESG ratings and market capitalization, while also examining the impartiality of these ratings for publicly traded energy companies, considering their regional location. Employing regression analysis, multivariate analysis with non-parametric tests, and a composite ESG rating model, the study reveals statistically significant findings that confirm the impact of ESG ratings on a company's capitalization, with variations based on regional residency. A study also reveals a bias in ESG ratings, favoring larger companies and regions that are net consumers of hydrocarbon energy, while regions of net energy suppliers face stricter assessments. This bias diminishes investor confidence in ESG ratings and encourages the search for alternative evaluation methods. The study concludes that leading agencies do not ensure sufficient reliability and objectivity in ESG ratings, which negatively impacts the promotion of sustainable investments and the ESG agenda. The results of the study can be used to develop mechanisms to minimize reputational risks for net suppliers of energy resources.
The objective of this article is to conduct an in-depth analysis of the potential trade implications arising from the entry into force of the Free Trade Agreement between the Eurasian Economic Union Member States and Indonesia, focusing on its impact on Russia - Indonesia economic cooperation. The study aims to provide a nuanced and realistic assessment of how Russia's participation in the Eurasian Economic Union, on the one hand, and Indonesia's involvement in ASEAN and other trade agreements, on the other, may influence trade relations following the establishment of the Free Trade Agreement. The hypothesis is that the development of economic relations with Indonesia will provide Russia not only with long-term economic benefits by increasing cooperation with ASEAN but also with a strengthened legally established trade framework within the 'Turn to the East' policy. An empirical analysis of the existing trade relations between Russia and Indonesia was conducted by calculating three trade indices. The paper identifies product groups with the highest potential for trade growth between the two countries. A partial equilibrium model, which considers the specifics of both parties' participation in Free Trade Agreement agreements, is employed to determine the effects of trade liberalization between countries under the Eurasian Economic Union - Indonesia Free Trade Agreement. The study concludes that, despite a relatively modest impact on trade flows, the agreement holds significant economic, and political importance. The findings provide valuable practical insights for the ongoing negotiations on the establishment of a free trade agreement between the Eurasian Economic Union and Indonesia and can be utilized by both policymakers and researchers in this field.
The article systematizes, synthesizes, and compares the results of studies aimed at modeling and assessing the effectiveness of macroprudential policy both at the level of individual countries and in a cross-country context. It provides an interdisciplinary review that integrates empirical findings with theoretical frameworks of macroprudential regulation, offering a novel analytical perspective on its effectiveness and unintended consequences. The research question addresses whether a universal approach exists for evaluating the effectiveness of macroprudential policy. The paper discusses methodological opportunities and barriers in constructing a comprehensive indicator of macroprudential policy stringency and quantifying its impact on various financial stability metrics. A systematic analysis of contemporary theoretical and empirical approaches to quantifying the intensity of prudential supervision reveals a lack of consensus and a universal methodology for evaluating the policy's effectiveness across different countries. The observed heterogeneity in results is linked to the unintended consequences of the policy, which are given special attention in the study. Moreover, the paper emphasizes the coordination of macroprudential and monetary policies. It describes key transmission mechanisms that may conflict and significantly reduce the effectiveness of both policies. The study demonstrates that their complementarity is best captured through dynamic stochastic general equilibrium models, where macroprudential regulation can be implemented via various channels systematically outlined in the research. The scientific novelty of the article lies in identifying and systematizing key methodological and empirical approaches to evaluating macroprudential policy, as well as in highlighting underexplored aspects of its effectiveness in diverse institutional and economic contexts. This analysis not only consolidates existing findings but also identifies directions for future research. This underscores the academic value of the paper, highlighting its originality not only as a synthesis of existing data but also as a foundation for new perspectives in their analysis.
Restrictive economic measures by unfriendly states have become a new normal for the Russian economy. This paper assesses the impact of information about sanctions on the exchange rate. The following news feeds were used as a source of information: RBC, Interfax, Vedomosti, containing more than 225 thousand news items of a corresponding nature. More than 58 thousand texts were selected from the Vedomosti news feed, 67 thousand texts from the Inter-fax feed, and 100 thousand texts from the RBC feed. Based on the application of topic modeling, such topics about sanctions as "anti-sanctions policy", "sanctions of unfriendly states", "sanctions circumvention" and "industry sanctions" were identified. In this study, an algorithm based on the BERT neural network model was used, which allows for topic modeling taking into account the semantics of the text and identifying more complex topics. In particular, the BERTopic algorithm automatically determines the number of topics in the text and highlights the frequency of words in each topic. The paper proposes author's sanction indices that allow assessing the level of sanctions based on a "bag of words". Using a 2-level methodology ("random forest" and GARCH modeling), the relationship between the obtained sanction indices and the exchange rate (dollar to ruble) was identified. In general, the constructed models allow us to draw a conclusion about the significance of sanction indices and their relationship with the exchange rate. At the same time, the anti-sanction policy index developed by the authors is of particularly high importance, revealing the state's efforts to counter sanctions directed against Russia and strengthen the domestic economy.
At the crossroads of the 20th-21st centuries, the issues of the international industrial fragmentation have received new impulses for development. External shocks such as global crises, the COVID-19 pandemic and sanctions have changed the architecture of business structures. The modern transformation of global value chains (GVCs) in response to economic and geopolitical challenges needs to be understood and evaluated. Methodological approaches based on the decomposition of world production activity are used to determine the significance of key countries and regions. The objects of the research became the countries that are the leaders in the global ranking of the trade in value-added for 2020. The subject is macroeconomic indicators that evaluate the international fragmentation of business under the growing technological shifts, and basic changes in the world trade. The primary goal of this study is to identify to what extent trade in value-added (TiVA) makes it possible to determine the country's position in the international division of labor. In the course of the study, it was revealed that the volume of trade in value-added has a significant impact on national GDP, the country's foreign trade indicators and investing stocks. As for the indicators characterizing net exports, net outbound investments, as well as employment, there is no single answer. The countries demonstrated multidirectional dynamics and even the absence of any impact. It has been found that the significant part of the goods produced within the GVCs is consumed in the country where enterprises are located, and commodities operated under international cooperation agreements are traded between partners.
The article presents an analysis of the development of the infrastructure of checkpoints in the Eurasian Economic Union in comparison with the best international practices. Based on the study of international experience, the importance of modernizing the existing infrastructure and the need to introduce various compensation mechanisms to mitigate and offset the growing negative effects of armed conflicts and unilateral sanctions for the development of international economic relations is substantiated. In this regard, the subject of the article is the study of border infrastructure tools, the use of which will contribute to such development. Examples of the world's best practices in using breakthrough technologies in the activities of regulatory authorities at customs borders to organize effective control over the movement of goods, vehicles and individuals are presented. Individual successful technological solutions implemented by the customs authorities of the member states of the Eurasian Economic Union at checkpoints on the customs border of the Eurasian Economic Union are demonstrated. A comprehensive solution is proposed to amend the law of the Eurasian Economic Union, which will form common mandatory requirements for the establishment of checkpoints on the entire customs border of the Eurasian Economic Union. The results of the study demonstrated that a systematic approach to improving the infrastructure of checkpoints through the introduction of breakthrough technologies and ensuring their integration into a single information system will help simplify customs and border formalities, accelerate the movement of goods and, as a result, lead to positive effects for the economic development of the EAEU.
The development of the digital and data economy has actualised a new cross-section of research into the development and improvement of business models of companies. The research is devoted to the systematisation of approaches to the analysis of business models of Russian high-tech companies and identification of their main types. The study formulated the criteria for classifying companies as high-tech, the features of innovative business models, and the trends of the digital economy that directly affect business models. The theory of characteristic features of business models was used as a methodological basis, which allowed us to collect and capture key attributes, refine them using factor analysis, and cluster companies based on the similarity of these characteristics. The study covered 75 companies from different sectors of the economy. As a result, a number of business models characteristic of Russian high-tech business were identified. For each model, the specifics of their functioning were examined, and the key factors influencing their development were identified, including the availability of venture capital funding, the level of digitalisation of customers and regulatory support from the government. Business models are formed at the intersection of advanced technologies, corporate and government demand, and specific economic conditions. The originality of the work lies in the development of a typology that clarifies the conceptual framework of hightech business, which is confirmed by expert validation. The scientific novelty of the article lies in the systematisation and typology of business models of Russian high-tech companies, taking into account the impact of technological trends and the digital economy, which made it possible to identify the key attributes and factors that should be considered for the development, modernisation and design of new business models. The results are applicable for managerial decisions to support innovation and adaptation strategies in the context of digital transformation and the data economy. The prospects of the research are related to analysing the dynamics of models under the influence of global trends, changes in economic policy, as well as the development of new technologies such as artificial intelligence, robotics and sensorics, wireless communication and a number of others.
Tax control is the main fiscal and regulatory instrument of the country's current economy. In modern realities, the modernization of tax processes is explained by the active use of digital technologies in tax administration through the use of various tools. The company's tax policy is directly related to the continuous optimization of tax expenditures and minimization of tax risks. This policy is implemented through digital technologies, platforms, and services. This article examines in detail the digital control tool, the tax monitoring program. The mechanism of the "tax monitoring" program is described, statistical data, criticism and opinions of scientists and business representatives are presented, the conditions for joining the "tax monitoring" program, its advantages, disadvantages and problems leading to its further improvement are considered, as well as the experience of joining the program of the country's largest banks. The options for developing the attractiveness of using this tax program among large busi-nesses are proposed. In addition to Russian practice, foreign experience in the application of tax monitoring is also considered. The conducted analysis allows us to conclude that this tax control program attracts an increasing number of taxpayers every year and is recognized by them as effective in reducing tax risks and optimizing financial, labor, and time resources. But for several years since the launch of this program, one of the main issues for discussion among the largest business representatives has been the need to participate in this program. To make an appropriate informed decision, a comprehensive comparative assessment of the effective-ness of the program is necessary. In addition, the most important debatable issue is the at-tribution of tax monitoring to one of the classes of the tax sphere - tax administration or tax planning, on which the functions and interaction of subjects of tax monitoring depend. The results of the research can be used in the practical activities of business entities, in the work of tax authorities, and in teaching financial and tax courses in higher educational institutions.
In this article, the students of Leonid Solomonovich Blyakhman attempted to analyze his contribution to the creation of the theory of industrial management at the Faculty of Economics of St. Petersburg State University, the development and entry into the modern level of one of the leading departments of the faculty - the Department of Enterprise Economics, Entrepreneurship and Innovation. Leonid Solomonovich took part in the foundation of our department together with the war veteran A. A. Markin, whose close friend he was from the first to the last days. The pedagogical activity of L. S. Blyakhman, who for several decades headed the topic of industrial management and organization management at the department, taught the main courses in these areas, and shared his perception theory of management with his colleagues, is characterized. It is demonstrated that he managed to make management, along with enterprise economics, the locomotive of the educational program of the Department of Enterprise Economics, Entrepreneurship and Innovation. It is shown that in the early 90s. In the 20(th) century, he met perestroika as a natural stage in the development of Russia, and links to his textbooks written during this period are given, which are full of enthusiasm. With the help of his books, many heads of Russian enterprises and government officials became familiar with the basics of the market economy. Persistent, purposeful, and at the same time benevolent attitude towards his graduate students allowed Leonid Solomonovich to prepare a large number of candidates of economic sciences. The article examines the distinctive feature of professor Blakhman, who was always aware of the latest advanced scientific achievements, emerging innovative ideas, developed scientific methods, but proposed to apply them in Russian conditions not mechanically, but through creative processing, taking into account the specifics of Russian culture and traditions of the country's development. He was a real generator of ideas, the relevance of which remains to this day, in particular, the program of the "second industrialization" of Russia, developed in detail by L. S. Blakhman, is finally beginning to be implemented.
The article is devoted to the study of the economic content of new economic categories - digital currencies of central banks (CBDCs) and tokenized deposits (TDs), determining the forms and models of issuance, establishing possible areas of use and integration options. The study analyzes the risks associated with the implementation of CBDCs and TDs, and proposes a risk management system in the process of circulation of digital currencies of central banks and tokenized deposits of commercial banks. The study found that CBDCs are a digital form of central bank money represented by a direct digital obligation of the regulator. CBDCs can be used for both retail payments and wholesale/value settlement, both domestically and internationally. TDs are a digital form of private issuers' money, represented by digital liabilities of commercial banks or other credit institutions that they use in retail payments. A promising mechanism of interlinking or integration between CBDCs and TDs is a programmable platform that allows to settle transactions and guarantee uniformity of different forms of money related to minimization of transaction costs and atomic settlement. The implementation of CBDCs and TDs generates new types of financial and non-financial risks that can be analyzed, identified and managed through the development of a digital currency risk management system. The creation of such a system is one of the key conditions for the active use of digital currencies, which also contributes to rethinking the target mandates of the & scy;entral bank's monetary policy.
The article is devoted to the problems of justifying risk decisions and managing risks over a long planning period, taking into account strategic indicators of future results of the planning period and changes in the conditions for project implementation in the current situation. The amount of capital at the end of the planning period is considered as the future business result. The strategic indicator of capital at the end of the planning period is defined as the expected value of this capital depending on the planned scenarios for the implementation of each project. It is a guideline for making long-term risk decisions taking into account future results at the end of the planning period. To model the capital at the end of the planning period for each considered sequence of implementation of individual risk projects, the method of the full financial plan is used. It is assumed that each risk project is implemented only according to one scenario, depending on which the capital is estimated at the end of the period, and a comparison of the obtained result with the established value of the indicator allows obtaining information for making additional decisions depending on the current situation of business development. The models of the complete financial plan for determining the capital at the end of the planning period for a given sequence of implementation scenarios for each considered risky project are formulated. Experimental calculations of the strategic indicator at the end of a six-year period are performed depending on the entire set of specified sequences and the risk of its achievement. Attention is drawn to the possibilities of business management based on its diversification under the assumption that all projects are implemented according to pessimistic scenarios based on the termination of implementation and liquidation of projects, investing the received funds in the business and reducing payments to owners, which allows bringing the expected capital at the end of the planning period closer to the selected value of the strategic indicator and reducing the risk. It is shown that, taking into account the given value of the selected strategic indicator of future results when making risky decisions and implementing risky investment projects, it is possible to ensure business development that to one degree or another corresponds to the established indicators.
Human capital is a fundamental determinant of economic growth, and health deterioration as a component of human capital reduces labor productivity, increases absenteeism, and raises mortality rates. Global crises not only worsen public health but also amplify health inequalities, as vulnerable groups are disproportionately affected by these shocks. Understanding the factors that drive health inequality is essential for mitigating the impacts of future crises. This study identifies the socioeconomic and demographic factors contributing to health inequalities using survey data from employed residents of St. Petersburg collected during the peak of COVID-19 containment measures. Econometric analysis was conducted using binary choice and generalized ordered choice models to identify factors influencing workability and vaccination rates. Despite free vaccine availability and extensive government-led promotion, individuals with lower education, lower income, and self-employment status were particularly vulnerable to vaccination disparities. In contrast, older adults - facing higher health risks - had markedly higher vaccination rates, suggesting limited success in encouraging vaccination among younger people based on intergenerational solidarity. Disparities in workability based on income and education were also observed: lower-income and less-educated individuals were more likely to experience declines in workability during the pandemic. Notably, self-assessed health status emerged as a significant predictor of workability, highlighting the role of subjective health perceptions over objective health metrics. These findings can inform policies aimed at reducing health inequalities and increasing the resilience of vulnerable populations.
The article is devoted to the problem of substantiation and effective implementation of the climate policy of Russia by involving Russian business in its implementation in the form of manda tory and voluntary climate projects (CP), which is classified as a priority in a number of official documents of strategic importance for the country. Among the various aspects of this problem, taking into account the level of its elaboration in regulatory and legal documentation, specialized literature, as well as reflection in business practice, the following tasks come to the fore: clarification of the methodology and methods for assessing climate projects, consistent with international approaches and taking into account the specifics of the modern socio-economic and geopolitical situation; determination of framework conditions that contribute to the payback of CPs and their positive impact on the competitive positions of the country as a whole and individual enterprises, in particular. In this context, the authors form a list of the highest priority climate projects for their implementation by Russian businesses on a mandatory and voluntary basis, taking into account their economic feasibility and achievement of carbon neutrality goals. Along with this, they calculate the commercial effectiveness of the implementation of climate projects, briefly assess the sanctions risks associated with the international recognition of their climate effect, and develop recommendations for the regulator on appropriate financial support and stimulation of wider involvement of enterprises in their implementation. The article reveals the position of the authors on a number of actively discussed issues, including the following: methods of economic justification of business climate projects and the prerequisites for their commercial feasibility; a comprehensive assessment of the full effect of the relevant projects, not limited only to their role in reducing carbon intensity; the advisability of rethinking the priorities of climate policy taking into account these results; target tasks for fine-tuning the regulatory mechanism and methods of financial incentives for more active involvement of Russian businesses in the implementation of climate projects.
