Highly profitable oil and gas companies are key taxpayers in the federal and regional budgets. The purpose of this study is to develop a flowchart of priority conditions and prospective results for the innovative development of oil and gas regions in the Volga Federal District. The framework is based on effective budget policy and tax administration strategies. Institutional mechanisms for improving the financial performance of developing a changing resource base and hardtop-recover oil reserves are examined. The innovation-based resource path of industrial development in the region is examined. Issues of technological sovereignty and the transition to a new industrial paradigm are analyzed. Particular attention is paid to financial innovation, concession agreements, and the policies of subfederal public-law entities. A regression analysis of the dynamics of the percentage component of tax deductions to the regional consolidated budget is conducted. Taxes on profits, personal income, and property of organizations in oil and gas regions are examined. A statistical analysis was conducted of the level of innovation activity, the share of organizations implementing technological innovations, innovation expenditures, and the volume of innovative goods, works, and services in oil and gas regions. The results of the study are presented as an equilibrium system of interdependent input and output, direct and intermediate elements of a flowchart for the innovative development of an oil and gas region. The diagram is based on budget policy and tax administration strategies.

The emergence and active use of the rotational method of organizing work in Russia is associated with the vast spaces and low population density of the Arctic zone of the Russian Federation, Siberia and the Far East. The shift method continues to be actively used at present by both large and medium-sized enterprises that pay corporate income tax. The Tax Code of the Russian Federation includes local government bodies of municipalities in the scheme for determining the costs of maintaining rotational and temporary camps. An analysis of the law enforcement practice of municipalities, aimed at determining these expenses, shows its inconsistency with the norms of tax legislation, which determines the relevance of the study. The purpose of this study is to develop scientifically sound and legally compliant approaches to determining the costs of maintaining rotational and temporary camps for the purposes of taxing the profits of organizations, as well as methodological recommendations for use by municipalities. The main research methods are systemic, logical, theoretical knowledge, scientific abstraction. The article outlines legal approaches to calculating the costs of maintaining rotational and temporary camps for tax purposes of organizations operating on a rotational basis in accordance with the norms of the Tax Code of the Russian Federation, as well as economic approaches to calculating the costs of maintaining similar rotational facilities and services of municipalities. The result of the study was the development of methodological recommendations for the formation by local governments of cost standards for the maintenance of facilities and services similar to rotational services and the procedure for determining the costs of maintaining housing, communal and social facilities, subsidiary farms and other similar services.

Reforming pension systems amid demographic aging and rising fiscal pressure necessitates robust tools for the quantitative assessment of their socio-economic consequences. The purpose of the study is to develop and test a comprehensive methodology for the retrospective evaluation of pension reform, integrating coefficient, factor, variance, and regression analyses within an enhanced analysis of covariance (ANCOVA) framework, supplemented by graphical validation. The methodology is applied to the 2018 Russian pension reform, which introduced a gradual increase in the statutory retirement age. Official statistical data from Rosstat and the Social Fund of Russia for the period 2001–2023 are used as the empirical basis. The analysis reveals that, during the interim implementation phase of the reform (2019–2023), the financial sustainability of the pension system improved. This improvement is partially attributable to a demographic shock–namely, the reduction in the number of elderly citizens due to excess mortality in 2020–2021. At the same time, a decline in the earnings replacement rate was observed, indicating a deterioration in the relative level of pension provision. Crisis events, including forced medium-term shifts in budgetary policy priorities, further diminished the effectiveness of the reform. The results demonstrate a statistically significant association between the implementation of the reform and changes in key performance indicators of the pension system; however, they do not confirm the achievement of the stated objective–namely, an improvement in the level of pension adequacy. Under conditions of persistently high rubledenominated inflation, the study recommends continuing to develop the non-state pension system.

The current discussions on the definition and development of the state’s payment sovereignty in the context of geopolitical instability and fragmentation of the global economy determine the relevance of theoretical and empirical analysis of payment sovereignty. The purpose of the study is to develop theoretical and practical foundations for assessing the state’s payment sovereignty using Russia as an example. To achieve this goal, the study used theoretical methods of analysis and synthesis, the systematization method, as well as empirical methods: the comparison method, the method of analyzing the dynamics of time series, the structural method. The study found that the concept of «payment sovereignty» is not limited to the independence of the state from the payment card systems of other countries, but is a system that integrates technological, infrastructural, monetary and energy components for the purpose of economic growth based on the implementation of the potential of sustainable financial development of the state. The study proposes a methodology for assessing the payment sovereignty of the state, which suggests systematizing the existing statistical indicators of the development of the payment sphere by the components of payment sovereignty: technological, infrastructural, monetary and energy. Based on the results of the study conducted using the proposed methodology, it was concluded that the development of the payment sovereignty of the state as a system of interrelated elements is based on the disclosure of the potential of each of its components and implies the need for further formation of financial market institutions. The study may be useful both for specialists in this field and for regulatory and supervisory authorities. Further research on this topic may focus on a broader analysis of indicators of technological, infrastructural, monetary and energy components of payment sovereignty as the existing statistical base expands.

The relevance of this study stems from the need to enhance the accuracy of forecasting tools in determining future budget revenues for the Russian Federation, given the dynamic macroeconomic environment shaped by sanctions. In the current situation, it is essential to respond quickly to the changes taking place. This requires the use of various frequency data in predictive models and the search for new, more accurate forecasting methods. The object of the study is the dynamics of federal budget revenues. The subject of the research is to examine the applicability of reservoir computing in forecasting federal budget revenues in the Russian Federation. The purpose of the study is to identify the feasibility of using reservoir computing models in forecasting federal budget revenues in the Russian Federation. Empirical and theoretical methods were employed in the research process. These methods allowed us to understand the essence of reservoir computing, interpret the predictive results obtained, and select the best hyperparameters. As a result, a model based on reservoir computing was proposed by the author, taking into account the dynamics of monthly and daily factors in the development of the Russian economy. It is concluded that the world’s first experience in using reservoir computing in forecasting federal budget revenues in the Russian Federation has improved the quality of the model. The characteristics of the resulting model are significantly better than analogues calculated using other methods. The high fragmentation of the Russian data and the short length of the time series have also been revealed, which was eliminated by shortening the time period for training models and imputing missing values in the data.

This paper focuses on examining the interaction between investment and financing strategies in a dynamic model with existing assets and a growth option where the investment cost can be financed either by contingent convertible leaseequity or by convertible debt-equity. It aims to study the impact of these two models as a financing instrument on conversion timing, conversion rate and the optimal value of the firm in different scenarios. The difference between CoColease and CoCodebt contracts from a modeling point of view is explored by examining the company’s closed solutions using the real options approach and risk-free price theory. The results reveal that the convertible lease with low amortization value and sufficiently high conversion rate has less severe inefficiencies resulting from risk transfer and debt overhang than those caused by convertible debt. In particular, with a high landlord tax rate equal to τ_ι = 0,3, shareholders will experience a distortion of debt overhang and will have strong incentives to transfer risks. The conversion time may be delayed with conditional convertible lease financing instead of convertible debt. The research work concludes that financing through convertible leasing contracts with a low amortization value is more advantageous than that of CoCo debt, but if the lessor’s tax rate is high, the opposite may be true.

This study aims to develop a model to determine the optimal financing required for the development of an information control system (ICS). The model will be based on monitoring and dynamically adjusting certain parameters to solve the task. The model will describe the dynamic development of the IMS (information management system) in a situation center using a system of nonlinear differential equations. An original approach to formalizing the process of financing IMS development is presented, accounting for budget planning and compliance with financial milestones. The model provides an analytical and visual representation of the current state of IMS development, useful for operational management purposes. The development process is managed under conditions of uncertainty and incompleteness of data on the readiness of IUS components, including their manufacturing technologies. The effectiveness of a modified «soft computing» method for handling poorly formalized uncertainty is investigated. It has been shown that implementation of «soft management» of financing can reduce the development risks and create a promising decision-making system within budgetary constraints. A mathematical three-dimensional model can be applied to other areas where it is necessary to monitor the state of an object over time. This model is also interesting from the perspective of mathematical control theory, an interdisciplinary tool for developing alternatives to traditional control methods.

The paper is a result of a comprehensive and systematic approach to reviewing the growing opportunities for BRICS countries in introducing artificial intelligence into a mutual financial platform. The subject of the study is the AI as a factor of BRICS cooperation and its growth in finance. The purpose of the study is to identify measures that stimulate the introduction of AI into a shared public financial infrastructure platform by implementing the methodological combination of structured and reproducible guidelines, incorporating elements of the PRISMA method in particular. The task of the research team is to search for scientific answers to the urgent questions of current artificial intelligence inequality between nations and to come to the conclusion that BRICS nations should develop and implement a shared public AI platform to enhance accessibility to general and specialized information as well as equity for marginalized communities in all member countries. It is pointed out that such AI platform have to be organized in a way that enshrines principles of data sovereignty. Mechanisms and international AI strategies for meeting the challenges are introduced. The developed proposal is unique. Other initiatives have not yet received adequate justification. The project of such a scale demands not only funding, but also dedicated professionals as well as open-source software development instruments. These issues represent promising areas for further research.

The implementation of the new strategy for the scientific and technological development of Russia requires monitoring structural changes in the economy as an information basis for justifying structural modernization. This information is needed to form economic growth models and stimulate investment activity in industries of new technological structures, which will ensure the development of all related sectors of the economy and the technological independence of the country. In this regard, the objective of the study was to assess structural changes in the economy and their forecasts for the medium term, taking into account the priorities of Russia’s scientific and technological development. The study is based on the calculation and assessment of qualitative changes in the structure of the economy, focusing on the identified priority sectors and industries. It also evaluates the quality of these changes. Based on the EMISS data for 2017–2023, we have constructed trends that meet the criteria of approximation reliability, and correctly reflect the established patterns in the changes in indicators. We have also made a forecast for 2024–2026 in the context of the identified sectors and industries. An improved approach to grouping priority sectors and industries is of theoretical significance, as it allows us to assess structural changes in the economy from the perspective of the priorities of Russia’s scientific and technological development. The practical significance of the obtained results consists in the possibility of their use for monitoring the implementation of the strategy for scientific and technological development, as well as in supporting investment projects aimed at the technological advancement of companies in the industries of new technological structures that are essential for future economic growth. The research methodology may be of interest to strategic development centers and investment funds that support industry and entrepreneurship.

The primary purpose of the study is to evaluate the impact of research output in finance, both in terms of quantity and quality, on the development of the financial sector. The study analyzed data from 2000 to 2017, including 15 countries in the Middle East, employing a two-step SYS-GMM method. The empirical findings reveal a significant correlation between the quantity of research output in finance and the overall activity and stability of the financial sector. However, when it comes to the quality of research output in finance, it only positively influences the activity while negatively and significantly affecting the stability of the financial sector. This noteworthy result suggests that highly regarded research in finance may recommend taking greater risks for national reforms, operating under the belief of «no pain, no gain». High-quality research in finance often offers valuable insights, minimizes risk and uncertainty, and helps inform policies and reform strategies for successful implementation. It is crucial for Middle Eastern policymakers to prioritize improving both the quantity and quality of finance research and provide support to researchers. This will enable them to achieve the desired economic growth and impact the development of the financial sector. Furthermore, policymakers can also consider recommendations from well-respected economists to mitigate instability in the financial sector while pursuing necessary, albeit risky, initiatives for successful reform. To date, no other research has investigated the influence of research output in the field of finance on financial development, both in terms of quantity and quality.

Environmental sustainability and climate change have been considered as two of the burning issues across the globe and require an inclusive approach to manage the same. Regulators and policymakers are constantly pressurizing business corporations to adopt emission management practices to control their carbon footprint. To respond to this, corporate houses have progressively institutionalized internal carbon pricing (ICP) as a climate management strategy to control carbon footprints in operations and business models. The purpose of the study is to examine the firm-specific determinants of adopting ICP among companies operating in an emerging economy context. Current research takes a three-dimensional look at the reasons behind the use of ICP by combining factors related to finances, corporate governance, and the environment. Using panel data from 107 firms for 10 years (2013–2022), the study employs binary logistic regression analysis. Further, the study also uses the generalized method of moments (GMM) to control for potential endogeneity. Findings indicate that profitability, firm size, leverage, board size, and environmental sensitivity are the significant factors affecting the adoption of ICP among the sample firms. Further, the results also depict that even though the number of firms using ICP has increased, the current mean adoption rate is only 23%. The present study contributes to the scarce literature on carbon management practices in emerging contexts and describes several important implications for managers and policymakers.

This article analyzes dividend income taxation across Russian federal subjects using statistical data from the Federal Tax Service of Russia and Rosstat for 2012–2023. The purpose of the study is to identify federal subjects exhibiting signs of personal income tax base erosion related to dividend income. This objective predetermined the following research tasks: to develop a regression model for structural and dynamic analysis of dividend income; to identify federal subjects with significant deviations from nationwide indicators; to determine potential tax optimization schemes that may cause these deviations; and to develop a risk-oriented model for identifying federal subjects where non-residents and individual entrepreneurs may potentially utilize «dividend» tax evasion schemes. The research employs econometric modeling (panel regression model with fixed effects), comparative analysis, and statistical analysis. The study establishes a statistically significant relationship between the share of dividends in total individual income and corporate profit dynamics, as well as a strong influence from the proportion of non-residents and individual entrepreneurs receiving dividends. The analysis controls for macroeconomic shocks and time-invariant regional factors such as industry structure and investor profiles. Federal subjects exhibiting signs of personal income tax base erosion related to dividend income were identified, and key factors that tax authorities should consider during tax audits were highlighted. The novelty of this research lies in constructing a regression model for structural and dynamic analysis of dividend income, as well as developing a risk-oriented model for identifying federal subjects where non-residents and entrepreneurs may potentially employ «dividend» tax evasion schemes. The practical significance stems from enabling tax authorities to use the proposed models to identify potential centers of systematic tax evasion scheme usage and facilitate their prompt suppression. The proposed research methodology allows for decomposition at to the municipal level, enabling more precise identification of sources of potential personal income tax base erosion.

The article is dedicated to the tax burden on small and medium-sized businesses (SMEs). The authors compare the level of tax burden depending on the scale of entrepreneurial activity. The aim of this article is to assess the perception of SMEs regarding the level of tax burden in order to ensure adequate fulfillment of their tax obligations. The research aims to compare the level of tax burden on small and medium-sized enterprises (SMEs) depending on their size, and to identify behavioral patterns that may affect business fragmentation. The research methodology is based on the use of comparative analysis methods, tabular data visualization, and graphical representation. Based on the comparative analysis, we have found that SMEs have a much lower tax burden compared to other enterprises. However, the subjective perception of the tax burden level, especially among microenterprises, significantly differs from the actual situation. This indicates their opportunistic approach to taxation. The novelty of this study lies in the fact that there has not yet been a comparison of the tax burdens of micro, small, and medium-sized businesses that use the general tax system to assess the accuracy of their tax liability. An element of scientific novelty and the significance of the obtained results lies in the mutual connection between the problem of assessing the tax burden in relation to the size of SMEs, and the issues of their tax behavior. The practical value of this study lies in its ability to objectively assess the level of tax burden on small and medium-sized enterprises (SMEs) and to determine the degree of impact that taxation has on entrepreneurial decisions.

The «Futures & Options» (F&O) course is a major for financial students to learn to identify and recognize risks, master the skills and methods of risk management, and shape risk-oriented thinking. The purpose of the study is to identify the impact of the F&O course on the professional thinking, life and future work of students. This study used a survey on finance students (n = 534) of Tongling University of China who have studied F&O course over the past two years. Research questions: (1) How do students currently perceive the F&O course? (2) What factors influence the current perception of F&O students? (3) Does the impact of the F&O course on life/future employment and student development vary by gender? (4) Does the impact of the F&O course on life/future employment and student development vary depending on their knowledge of futures and options? (5) Does the impact of the F&O course on the life/future work and development of students vary depending on their participation in equity and fund investments? (6) Will the impact of the F&O course on the life/future employment and development of students vary depending on their participation in futures and options investments? The results of the study showed that the level of knowledge of male students was slightly higher than that of female students, and there were no gender differences in the impact of the F&O course on the life/future employment and development of students. Students who identified themselves with higher value of usefulness and ability of risk management did not participate in investing F&O. Students with higher knowledge level perform better than the others. It was concluded that, in general, the level of knowledge of students is better within the current educational model, the readiness of students to participate in practice is low, and the cultivation of risk awareness is not ideal.

The article explores one of the main trends in modern financial transformation, namely the impact of decentralized finance (DeFi) on the banking sector. The author goes beyond conventional discussions about banks’ responses to DeFi and proposes a different vision for their role and function in the digital economy and Web 3.0. The aim of the study is to identify and analyze changes brought about by the rise of DeFi, as well as to propose possible strategies for banks to adopt in light of technological advancements. Unlike traditional approaches that focus on the conflict between banks and DeFi platforms, this work emphasizes the analysis of future models of financial intermediation. Concepts such as «5.0 banks», «metabanks», and autonomous digital ecosystems are explored, where banking functions are implemented in a more programmable manner. The research methods include a comparative analysis of the structural and functional differences between the traditional banking system and decentralized finance (DeFi), an analytical review of recent scientific publications, and an assessment of potential future developments for banks in the face of decentralized technology. Based on this research, we found that banks remain an important part of the financial system, despite increasing pressure from decentralized finance. However, banks must adapt to technological change in order to maintain their relevance. We identified three possible paths for the future of banking: the integration of DeFi features into existing banking products, the creation of hybrid models that combine DeFi and traditional banking, and the transition to fully autonomous algorithmic systems powered by smart contracts and artificial intelligence. While all three scenarios are possible, we believe that the hybrid model that combines DeFi innovation with customer protection and regulation is the most likely to succeed in the long term. The novelty of this work lies in its conceptual approach to how banks can adapt to decentralized technologies and forecast their future evolution within the context of Web3. Its practical significance lies in the potential for using these findings to develop digital transformation strategies for banks.

The subject of the research is the economic and socio-psychological aspects of investment behavior in the stock market, which is the most volatile segment of the stock market. The purpose of the study is to develop a methodology for assessing deviations in stock market prices from their rational (fundamental) values. Objectives: to reveal the essence of the market value of shares and its irrational component, which is a set of heuristic estimates of the future benefits of the share owner; to describe the stages of development of behavioral economics considering irrationality in consumer choice models; to analyze research in the field of irrational stock pricing and propose an algorithm for solving the problem. Relevance: Irrational valuation of financial assets can become a catalyst for economic crises. This is why distortions in consumer behavior require government supervision and regulation. Methodology: The authors employed Discounted Cash Flow Model, Logit model, the Least Squares Method, and Lasso Regularization. Research result: The author’s approach to assessing financial heuristics, including a set of indicators that reflect distortions in consumer behavior in the stock market. Based on the results of the study, we concluded that the market value can deviate significantly from rational expectations. We proved that there is a relationship between cognitive distortions and quotation dynamics. However, we found that the methods we considered do not allow us to determine the duration of irrational assessments. Scientific novelty: A new approach to modeling the irrational valuation of stocks has been developed based on the relationship between the deviation of stock prices from their fair values and indicators can be used to make heuristic estimates of future benefits from owning a particular stock. The practical significance: The use of the developed methodology can be beneficial for investors to accurately assess the fair value of their portfolios. Businesses can use it to create models of consumer behavior when developing of financial products. Mega-regulators can use it to analyze investment behavior factors and respond to market distortions in a timely manner.

Delving into the intricacies of investor psychology, this research engages in an extensive systematic literature review to illuminate the intricate relationship between behavioral biases and investment decisions in the stock market. The study progresses through meticulous stages: research identification, literature search, document evaluation, synthesis, analysis, and reporting, encompassing 101 articles. It reveals a clear positive trend in financial decision-making research, starting in 2016 and peaking in 2022. Furthermore, the research also found that there are two journals domiciled in Switzerland, where there are 56,482 citations related to investment decision-making articles. One of these covered journals is Frontiers in Psychology, which has 11 articles with a total of 55,251 citations, placing it among the top 10 journals with the highest citations. This trajectory exposes various biases in the stock market, including overconfidence, availability, and herding. Previous research has examined overconfidence and its relationship with anchoring bias, availability, and herding, especially in emerging markets. However, a significant shift occurred in 2019 when researchers began investigating gambler’s fallacy and regret aversion bias. This momentum continued in 2021, with a surge in decision bias research, encompassing areas such as prospect theory and financial literacy. The findings of this research urge future research to explore conservatism, confirmation bias, regret aversion, framing, status-quo, and bias towards the familiar in investment choices, as these aspects offer rich research opportunities. Moreover, this encourages a deeper understanding of contributory factors, including financial literacy, income, education, gender, and age, in shaping and influencing investment decisions.

The aim of this study is to develop a conceptual model for treasury cash management in the public sector. The model is based on a centralized approach integrating digital management tools and predictive analytics within the framework of a single treasury window paradigm. Research Methodology: A combination of theoretical and empirical methods was used to achieve the research goal. The theoretical part includes analysis and synthesis, induction and deduction, modeling and abstraction. Empirical research is conducted through observation. This combination allowed for a retrospective analysis, identifying current issues and systemic trends in the evolution of treasury cash management in the Russian Federation over the entire period of its institutionalization (2008–2025). Interpretive (generalization and structural) research methods were used to develop the conceptual model. Conclusions: The prerequisites for effective cash management have been substantiated and the problems of managing cash have been systematized. This has revealed the internal structure of the current state of the public financial management system as well as providing a theoretical and methodological platform for further development. A new model for public cash management has been developed, which aims to improve the adaptability, sustainability, and effectiveness of budgetary regulation through the use of digital technology.