The paper examines the impact of the COVID-19 pandemic on the economy and the corresponding atypical economic crisis, the role of the economic ability of the government during this crisis, aspects of financial support for the economy and the peculiarities of the zombie economy. The aim of the study is to research the actions of the economic ability of the government as an independent factor of production in the context of the COVID-19 pandemic, contributing to the unfolding of the process of zombie-ing the economy. The research uses the methods of deduction and induction, analysis and synthesis, analogy and abstraction. The special functions of the government are considered within the context of the economic crisis caused by the COVID-19 pandemic; particularly, we refer to the recognition of the fifth factor of production of the economic ability of the government. The main features of this atypical crisis are characterized. It is shown that the process of deglobalization during the COVID-19 pandemic characterizes the deglobalization of the economic ability of the government and that this process is temporary, since overcoming the global phenomenon of the pandemic and the economic crisis caused by it requires exclusively global efforts and measures. Particular attention is focused on the financial support of the economy from the economic ability of the government within the context of this economic crisis. The conclusion is that this support contributes to the process of zombie-ing the economy which took on a global character during the global financial and economic crisis of 2007–2009 and continued after its completion. Zombie-ing the economy is the result of a conflict between the political interests of the government and its economic ability when the latter is not able to overcome the barrier created by the former. A solution to this problem is possible through changes in bankruptcy legislation when its main principle of avoiding the unwanted bankruptcy of firms will be replaced by the principle of liquidation of unviable firms. Such a change in bankruptcy legislation can be implemented only during the economic upswing.

The paper illustrates an approach to GDP growth in the context of an ecological economy. The subject of the research is the establishment of the interdependence of the state of the ecology of the environment and the results of human activity. The aim of the study is to determine the presence or absence of a relationship between pollutants in each type of environmental pollutants and the level of economic development of the country, represented by GDP per capita indicators. The relevance of the study is due to the ecologically unbalanced growth of GDP, which is accompanied by an increase in disproportions between the volume of pollutants emitted by the extractive, processing, processing, agricultural and infrastructure sectors of the economy, and the conditions of human life due to the deterioration of the “ecological quality” of the environment, which limits the possibilities for further development of human capital. The scientific novelty of the research lies in the development of economic and mathematical models, methods, and numerical algorithms for assessing and analyzing the state of air, water, and environmental pollution under the influence of the country’s economic growth. Methods used: empirical and statistical analysis, building regression models, algorithmic and predictions, building time trends, etc. The authors based the methodology of substantiating the method for assessing the environmental constraints on GDP growth on an empirical study of the state of the environment and the state of the Russian economy in 2000–2018. Results: the authors have determined a set of indicators reflecting the state and trends of changes in environmental pollutants in Russia (carbon dioxide emissions, wastewater, production, and consumption waste) and their interdependence with economic development, which predetermine long-term social, environmental, and energy consequences. An algorithm has been developed to substantiate environmental restrictions on Russia’s GDP growth in the period 2000–2018. The algorithm is based on a modified Kaya equation, through which the relationship between each type of pollutant and indicators of GDP per capita, energy resources, and industrial production is checked. In accordance with GDP growth, the forecast of environmental restrictions was developed according to scenarios of 10–40% and showed the inevitability of implementing a plan to prevent environmental pollution in Russia. It is concluded that Russia must promote environmental and low-carbon policies, reduce emissions, waste, and energy consumption over the next few decades to achieve sustainable development. The country is faced with the task of moving away from a nature-destroying economy, thereby saving natural capital, minimizing the costs of eliminating the negative environmental consequences of technogenic economic development in the future.

This paper analyses a new concept presented in the works of B. Eichengreen, A.J. Mehl, L. Chitu “Mars or Mercury? The Geopolitics of International Currency Choice”, according to which the state’s possession of nuclear weapons is linked to its possession of reserve currency. The paper aims to provide a detailed assessment of how gaining reserve currency status depends on the military and political potential of the state issuer. The research method is an analysis of the historical material and the current state of the issue under discussion. The study shows the relationship between the global military and political leadership and control over the global financial infrastructure, which increases its importance as a space for interstate conflicts. It has been proven that neither the presence of military power nor the ability and willingness to provide partners with security guarantees do not predetermine the acquisition of the reserve status by the national currency. This status is acquired as a result of control over global investment processes, in the implementation of which military power plays a significant, but not exclusive role. This power, as the potential for economic and financial dominance, is a derivative of the scale and level of development of the national economy, with a key factor in its deep involvement in international trade. From the point of view of practical forecasting of economic, military and political development, the authors conclude that in the foreseeable future, despite the strengthening of its military potential, the PRC will not be able and, most likely, will not try to obtain the status of the yuan as a reserve currency. The United States, in turn, will increasingly use its dominance in the capital market and control over the global financial infrastructure as a tool to maintain global leadership. Further study of the considered issues will significantly increase the efficiency of forecasting economic processes in relation to the military and political situation.

The subject of the research is trends in the implementation of digital technologies in the banking sector. The relevance of the paper is due to the objective processes of global digital intervention of technologies in all spheres of human life and society. The research aims to identify, systematize and generalize key trends and regulations in the development of digital business models of banking services in Industry 4.0. For the first time, the authors identified and systematized modern trends and regulations in the development of digital business models of banking services in Industry 4.0, offered their own conceptual vision of the concept of “digital business model of banking services”. The authors apply general scientific, philosophical, analytical, statistical, problem chronological and historical-genetic methods, as well as methods of expert assessments. The article summarizes the main stages of the evolution of business models of the banking sector, reveals substantive and methodological differences between traditional remote banking services and digital banking, highlights the main business models for organizing digital banking; provides up-to-date data on the level of development of digital banking in the main geographic zones of the world; shows the dynamics and key areas of investment in the fintech industry in 2014–2019 and provides a critical analysis of their conditions; identifies problematic aspects of the development of digital business models of banking; describes the functionality of the main digital business models of Russian banks with the author’s assessment of their capabilities and examples of their use in Russian practice. The authors conclude that the main drivers of digitalization of the banking sector are stable growth of non-cash payments in the world and in Russia; stable growth of the global digital banking market; the impact of the COVID-19 pandemic on the active demand of consumers of remote financial services; increased competition in the retail banking market; and a significant decrease in margins for traditional banking products. Identification and systematization of trends and regulations in the implementation of digital business models of banking services can form the basis for further analysis of the specifics of digitalization and personalization of digital banking in Industry 4.0 for the sustainable socio-economic development of the country in terms of possible advantages and threats to the security of financial resources and personal data of customers.

The authors study the development of the oil and gas industry and assess the financial efficiency of the use of renewable energy sources, which determine the relevance of the research topic. The purpose of this work is to study the effectiveness of the development of the Russian energy sector and its contribution to the world economy. The main question to which this article should give an answer is that how the Russian power industry will develop in corresponding to the global trends in energy consumption. This paper uses a method for finding the parameters of the efficiency of renewable energy sources using exponential smoothing. The paper uses data from the analytical report of British Petroleum and the Bloomberg system for the period from January 2012 to December 2019. The result of the study shows an improvement in the accuracy of the predicted values, while previous models had higher standard error estimates. The novelty of the study is to achieve accurate results of the forecast of fossil-fuel consumption for 3 years ahead (the forecast accuracy is 80.5). The article concludes that while Russian oil and gas projects are very important for the Russian economy until now, renewable energy projects are more beneficial. In addition, Russia does not seem to support the global trend towards a renewable and sustainable economy. Although oil and gas prices remain acceptable, unforeseen changes in the behavior of real buyers can hinder the efficiency of the Russian economy and lead to a disruption of Russia’s economic growth if Russia does not decisively steer towards renewable energy from now on. The growth of the Russian power industry corresponds to the global trends in fossil energy consumption (while fossil prices, thus incomes keep worsening), and thus innovative solutions for enhancing renewable energies must be adopted. The article proves that many pipeline projects (South Stream, Turkish Stream, Nord Stream 2) move the Russian energy sector back to the past because they just contradict existing trends.

The subject of the research is the financial mechanism of the modern venture investment market under conditions of uncertainty and the requirements of accelerated innovative development. The study aims to analyze the impact of the pandemic on the sustainability of the institutional behavior of venture capital investment in the global and Russian markets. The authors apply such scientific methods as sampling, grouping, comparison, analogy, analysis, generalization, systemic-structural approach to assessing the development of the subject of research. The paper analyses the role of venture investment in the successful promotion of innovations using the example of the world’s leading companies in 2016–2021. Successful examples of venture investment are presented. The study investigates the impact of the pandemic and lockdown on the level of volatility, composition and dynamics of venture capital investments in 2020– 2021. The authors conclude that the pandemic has an impact on the sectoral redistribution of investments in favor of venture investments in medicine, biotechnology, the sector of information and communication technologies and solutions for business, education, healthcare, on market polarization (covid-negative, covid-positive, covid-neutral), on reducing the role of state funds and Russian accelerators, while increasing the interest and scale of participation of private institutions (foreign investors, business angels, syndicated angel investment), to increase of the volume of the Russian venture capital market by increasing the average ticket size despite the reduction in their number, to strengthen the practice reproduction of their own ecosystems by corporate institutions, to popularize venture capital investment deals in terms of mergers and acquisitions. Prospects for researching the venture capital market are associated with the constant attention to high-tech covid-positive projects, with the growth of transactions in the early stages, due to the increase in the number of professional communities, with the pinpoint development of specific tasks of an investor or corporation by accelerators, with venture investment of companies with the subsequent entry of the project into their own ecosystem, with the improvement of the state’s restrictive measures aimed at a clear institutionalization of professional activities and increasing the financial stability of participants in the investment and innovation markets, with the stimulation of mechanisms for regional innovative development to attract capital to high-risk projects in the regions.

The Global Depository Receipt (“GDR” or “DR”) is a structured financial instrument denominated in foreign currency and Indian companies issue equity shares/securities underlying the GDR to international investors. Many companies have used GDRs for manipulative and fraudulent practices and the Indian regulator, SEBI has penalised them. This paper aims to evaluate the legitimacy of the GDRs and malpractices associated with them and to find if there is any need for reform in the GDR Scheme, to see if the GDRs are beneficial to the economy or are inherently manipulative instruments and looks at the need to reform the laws governing GDR. The authors have employed the methods, literature review and empirical research. The authors have conducted empirical research of the participants in the Indian GDR industry in April and May of 2021 by way of an online Questionnaire and unstructured telephonic interviews. The study results in the author’s conclusion that the GDRs are legitimate instruments but the participants abused the Scheme and led to malpractices. The authors failed to conclude about the need for reforms in the GDR laws. The paper recommends the suitable amendment of the DR scheme with an intention to plug its loopholes and allow it in foreign jurisdictions with the highest compliance requirements while keeping in mind the cost of such compliance.

This research discusses various issues associated with central bank digital currency that is identified as a new form of money. This paper aims to identify the key prerequisites for the issuance of central bank digital currencies, to discuss the key characteristics of central bank digital currencies and analyze the possible impact of central bank digital currencies on the financial system. The author uses the methods of synthesis, analysis, logical method, comparison, induction, deduction. The research highlights the key principles that should be considered when making decisions on the issuance of central bank digital currency. The paper emphasizes that the issuance of central bank digital currency can be successful if it has competitive advantages over existing forms of fiat money. The research identifies the main characteristics of central bank digital currencies. The paper discusses whether central banks should pay interest on fiat digital currencies. The author notes that the impact of central bank digital currencies on the financial system is expected to vary in different periods of time depending on the phase of the economic cycle and the level of interest rates in the economy. The research shows that central bank digital currency will stimulate the digitalization of the financial system while at the same time it will not create additional risks to financial stability. Introducing central bank digital currency is primarily aimed at promoting the efficient payment system. Further research is needed into mechanisms for the technical implementation of digital currency issuance, taking into account the possible risks associated with introducing fiat digital money.

The cryptocurrency market debate resumed in 2020 with renewed vigour as the price of Bitcoin surpassed late 2017 highs. This study aims to analyse possible factors of Bitcoin’s pricing at various cryptocurrency market development stages — before the 2017 price bubble, after and during the COVID-19 pandemic. The main method of analysis is a generalized autoregressive conditional heteroskedasticity model with conditional generalized error distribution (GARCHGED). Two groups of indicators are used as possible factors related to the Bitcoin dynamics. The first group consists of various quantitative indicators directly related to Bitcoin (the so-called internal factors) — the volume of exchange trade, the volume of transactions in the Bitcoin blockchain, the number of new and active wallets, hash rate, the sum of fees paid in the blockchain, as well as the dynamics of Google Trends search queries. The second group is the return on various financial assets — stock and bond indexes, commodities, and currency markets. The results of the analysis demonstrate the absence of a stable correlation between any of the factors under consideration and Bitcoin returns in all the periods that we focus on. In the period before the 2017 price bubble, the internal factors and Bitcoin returns showed generally co-directional dynamics, but the situation changed in 2018. In early 2021, the correlation between Bitcoin and traditional financial assets returns has increased significantly. We can conclude that Bitcoin is becoming a popular means of diversification as a high-risk asset, which, however, follows the pattern of a speculative bubble at the beginning of 2021. The increased demand for the need to invest in Bitcoin using various exchange-traded instruments (ETFs for cryptocurrencies) may soon lead to a further increase in the price of this cryptocurrency if such instruments are registered on the exchange.

The export of timber can be used by unscrupulous taxpayers in illegal schemes to reimburse VAT from the budget to obtain an unjustified tax benefit by overstating the amount of tax deductions, which confirms the relevance of the research. The subject of the paper is the economic relations between the exporting country and the importer of goods, works or services and their impact on VAT taxation. The aim of the study is to identify the vulnerabilities of the current tax legislation in the field of value-added tax reimbursement and analyze the improvement and optimization of the mechanism for administering value-added tax to ensure national economic security and preserve federal budget revenues as a result of reducing the amount of budget funds reimbursed to taxpayers. The author applies such methods as abstract-logical, analysis and synthesis, induction and deduction. As a result, the study reveals the problems of illegal VAT refunds in the export of timber associated with the use of new methods by taxpayers to minimize tax liabilities and the complication of the form of contractual relations. The author makes a conclusion about a possible solution to the problems of tax administration when taxpayers carry out export operations with exported products, using the experience of the functioning of the Charter of the agro-industrial complex. The novelty of the study lies in the proposal to adopt a ban on multi-stage sales and purchases by the tax authority as the basis for regulating the export of products outside the territory of the EAEU. This will exclude artificial price increases. The results obtained can be used in the further development of the tax administration system, in the analytical work of state bodies authorized to control and supervise taxes and fees.

In the field of financial monitoring, it is necessary to promptly obtain objective assessments of economic entities (in particular, credit institutions) for effective decision-making. Automation of the process of identifying unscrupulous credit institutions based on machine learning methods will allow regulatory authorities to quickly identify and suppress illegal activities. The aim of the research is to substantiate the possibilities of using machine learning methods and algorithms for the automatic identification of unscrupulous credit institutions. It is required to select a mathematical toolkit for analyzing data on credit institutions, which allows tracking the involvement of a bank in money laundering processes. The paper provides a comparative analysis of the results of processing data on the activities of credit institutions using classification methods — logistic regression, decision trees. The author applies support vector machine and neural network methods, Bayesian networks (Two-Class Bayes Point Machine), and anomaly search — an algorithm of a One-Class Support Vector Machine and a PCA-Based Anomaly Detection algorithm. The study presents the results of solving the problem of classifying credit institutions in terms of possible involvement in money laundering processes, the results of analyzing data on the activities of credit institutions by methods of detecting anomalies. A comparative analysis of the results obtained using various modern algorithms for the classification and search for anomalies is carried out. The author concluded that the PCA-Based Anomaly Detection algorithm showed more accurate results compared to the One-Class Support Vector Machine algorithm. Of the considered classification algorithms, the most accurate results were shown by the Two-Class Boosted Decision Tree (AdaBoost) algorithm. The research results can be used by the Bank of Russia and Rosfinmonitoring to automate the identification of unscrupulous credit institutions

Accounts receivable, being both a sales and financial category, is a key aspect of the development of modern market relations. At the same time, accounts receivable has become a complex object of only microeconomic research. Insufficient knowledge of accounts receivable at the macro level determined the relevance of the research. The subject area of the research is the total accounts receivable of Russian organizations. The aim of the study is to group Russian regions and types of economic activities depending on the conditions of conducting sales and payment activities. The methodology consists of a systematic approach, which allowed a comprehensive review of the object of research and macroeconomic analysis, which ensured the reliability and validity of the conclusions of the work. As a result, the author defines the total accounts receivable of organizations in the economy as an independent object of macroeconomic research. Based on the results of the analysis for 2000–2019, the author concludes that there is a high degree of correlation between sales revenue and accounts receivable of Russian organizations, as well as the presence of trends in the increasing importance of accounts receivable in sales and the reduction of its overdue part in the finances of organizations. The share of accounts receivable in the total sales revenue of organizations is taken as a generalized characteristic of the conditions for doing business in the sales activities of organizations, and in payment activities — the share of overdue total accounts receivable of organizations. The author’s matrix for express assessment of the conditions for conducting sales and payment activities of organizations in the economy constitutes the scientific novelty of the study. It made it possible to group the types of activities, regions and districts of the Russian Federation, depending on the specified conditions. The prospect for future research of the total accounts receivable of organizations in the economy is the search for tools to determine its optimal volume and structure to timely identify the factors of the upcoming crises of non-payment and overproduction, both in the economy as a whole and in individual commodity markets.

This paper aims to develop a theory of statistical observation in terms of scientific and methodological approaches to processing big data and to determine the possibilities of integrating information resources of various types to measure complex latent categories (using the example of social comfort) and to apply this experience in practice through the use of the financial situation indicators in forecasting. The authors have built a social comfort model in which the choice of weights for its components is based on a modified principal component analysis. The assessment is based on Google Trends data and official statistics. Google Trends data analysis methods are based on the development of an integrated approach to the semantic search for information about the components of social comfort, which reduces the share of author’s subjectivity; methodology of primary processing, considering the principles of comparability, homogeneity, consistency, relevance, description of functions and models necessary for the selection and adjustment of search queries. The proposed algorithm for working with big data allowed to determine the components of social comfort (“Education and Training”, “Safety”, “Leisure and free time”), for which it is necessary to directly integrate big data in the system of primary statistical accounting with further data processing and obtaining composite indicators. The authors conclude that a stable significant correlation has been found for the “Financial Situation” component, which makes it possible to use it for further calculations and extrapolation of financial indicators. The scientific novelty lies in the development of principles and directions for the integration of two alternative data sources when assessing complex latent categories. The findings and the results of the integral assessment of social comfort can be used by state statistics authorities to form a new type of continuous statistical observation based on the use of big data, as well as by executive authorities at the federal, regional and municipal levels in terms of determining the priorities of socio-economic policy development.