Publications

The paper discusses interregional differentiation in the distribution of electronic purchases among the population in Russia. The empirical base of the study is open regional data collected by statistical agencies and authorized government agencies, which were studied using panel regression methods. The aim of the work is to find out what factors are primarily responsible for the interregional spread in the level of online channel use in consumer retail purchases. The study focuses on regional drivers and barriers for the spread of e-commerce. The results show that shares of users of stationary computers and smartphones, as well as gross regional product per capita are the main positive factors, and lack of trust in e-commerce channels is the main obstacle, whereas Internet infrastructure, age structure, educational level, urbanization, aggregated regional preferences for personal purchases and physical availability of retail trade outlets were found to be irrelevant.

The paper contains a retrospective analysis of macroeconomic policy and macroeconomic reforms in post-Soviet countries in 1992-2021, that is, after obtaining political and economic independence at the end of 1991. A special attention is given to problems of macroeconomic stabilization and economic growth. As a result of structural distortions inherited from the Soviet economy and slow pace of economic and institutional reforms, countries of the former Soviet Union suffered from the long and deep output decline in the 1990s, and their post-transition growth recovery in the 2000s did not last long. Furthermore, they remain vulnerable to both domestic and external economic shocks. Given a limited predictability of post-COVID global economic trends, this vulnerability will continue, most likely, in the next couple of years.

We currently see a large increase in e-commerce sector; it is becoming a central trend in the banking industry. Fraudsters keep up with modern technologies, and use weak points in human psychology and security systems to steal money from regular users. To ensure the required level of security, banks began to apply artificial intelligence in their anti-fraud systems. Fraud detection can be formulated as a classification problem with a case-based reasoning or knowledge extraction task with unbalanced classes. In this paper we present a framework of models based on various approaches of artificial intelligence, such as neural networks, decision trees, copula models and others to recognize payment behavior of fraudster. The considered framework is evaluated with different metrics and implemented in an actual anti-fraud system, which leads to an improvement of the system performance. Finally, the interrelation between the anti-fraud system indicators and banks operational risks is discussed in this paper.

Book review of the monograph by Julius Horvath published by Palgrave Springer in 2020.

Performance evaluation enables decision makers (DMs) to have a better view about the weaknesses and strengths of leading units to improve efficiencies as a crucial goal. Data envelopment analysis (DEA) is the most popular technique to measure performance efficiency of decision making units (DMUs). However, conventional DEA is unable to consider uncertainty of input and output data in the evaluations. In this study, in order to address uncertainty in data, a robust credibility DEA (RCDEA) model has been introduced. First, a fuzzy credibility approach is used to construct fuzzy data. Then, a robust optimization approach is applied to consider uncertainty in constructing fuzzy sets. Moreover, perturbation level is considered as exact and fuzzy values. To illustrate the capability of the proposed model, 28 hospitals are evaluated in northwestern region of Iran and results are analyzed. According to the results, as perturbation degree increases, DMUs get normalized lower efficiencies and vise-versa.

An explanation of the Dunning–Kruger effect is provided which does not require any psychological explanation, because it is derived as a statistical artifact. This is achieved by specifying a simple statistical model which explicitly takes the (random) boundary constraints into account. The model fits the data almost perfectly

Internal-Ratings Based (IRB) approach is one of the founding blocks in the modern credit risk management and regulation. Its implementations by the banks world-wide incentivizes researchers, central bankers and investors to evaluate the outcome versus the non-IRB banks, i.e., the treatment effect. However, there are obstacles in such evaluation. From one side, all the banks may transit to IRB for a relatively modest economy (like Greece). From another side, there is no single IRB transition point (like in the EU where the transition is voluntarily; a single point exists for the USA where the transition was mandatory for the largest banks). That is why we discuss the problem of the ‘control’ group depletion (attrition) in the Difference-in-Differences method. We provide two ways to replicate data using python language. The first code is based on the matrix structure (object * time), the second – panel data structure. Comparing both ways of the data replication (resampling) we choose the second algorithm due to it versality and faster computing results, than the first one.

Many datasets used in the social sciences have a hierarchical structure, where lower units of aggregation are ‘nested’ in higher units. In many disciplines, such data are analyzed using multilevel modeling (MLM, also known as hierarchical linear modeling). However, MLM as a framework is relatively unknown in economics. Instead, economists use a range of separate econometric methods, including cluster-robust standard errors, fixed effects models, models with cross-level interactions, and estimated dependent variable models. Relying on an extensive literature review, this paper describes this methodological divide and provides a detailed comparison between MLM and ‘economic methods’ in their abilities to deal with three methodological challenges inherent in multilevel data ‒ clustering, omitted variables, and coefficients' heterogeneity across groups. We unfold the comparative advantages of these two methodological approaches and provide practical recommendations about which of them should be used, why, and in what settings.

В данной работе поднимается вопрос о том, как персональные характеристики СЕО, под воздействием наличия у СЕО власти, могут оказывать влияние на ее/его отношение к риску. Согласно агентской теории, менеджеры имеют неизменные предпочтения к риску, причем, менеджеры либо не склонны к риску, либо имеют риск-нейтральные предпочтения. Тем не менее, на практике встречаются случаи, когда СЕО берут на себя избыточный риск, а власть таких директоров оказывается положительно связанной с принятием избыточного риска. Таким образом, целью данной работы является анализ взаимосвязи между властью СЕО и ее/его персональными предпочтениями к риску. Опираясь на исследования в области поведенческих финансов и психологии, мы пришли к выводу, что власть может выступать как источником развития определенных черт характера (в случае с самоуверенностью и высокомерием), так и их бустером (в случае с нарциссизмом). В свою очередь, результаты существующих исследований показывают, в зависимости от черт характера человека, мы можем наблюдать разные поведенческие паттерны в том числе в вопросах, касающихся принятия риска. Таким образом, мы делаем гипотезу о том, что, оказывая влияние на характеристики персоны СЕО и на его поведение, уровень власти в руках СЕО может выступать фактором, объясняющим разные паттерны отношения к риску. Данная связь вносит вклад в существующие теории по поведенческим корпоративным финансам и корпоративному управлению и, тем самым, улучшает наше представление о том, каким образом разные характеристики СЕО (черты характера и власть) могут влиять на корпоративные решения.

Offering employment in the public sector in exchange for electoral support (patronage politics) and vote-buying are clientelistic practices frequently used by political machines. In the literature, these practices are typically studied in isolation. In this paper, we study how the interaction between these two practices (as opposed to having just one tool) affects economic development.

This paper investigates how corporate governance of unlisted firms in an emerging market economy affects financing constraints, measured by the sensitivity of investment to cash flow. In order to evaluate the quality of corporate governance, we develop two corporate governance indices based on a large-scale survey of Russian enterprises – one for shareholder protection and one for transparency. We estimate standard investment regressions where the cash flow variable is interacted with our corporate governance indices and variables capturing the ownership structure. The central result is that better shareholder protection diminishes the cash flow sensitivity of investment, particularly in firms with an outside controlling owner. In contrast, we do not find such an effect for transparency, which can be partially explained by the threat of hostile takeovers. We address the problem of the endogeneity of corporate governance by using fixed-effects regressions and a novel instrumental variable based on particular legal provisions for corporate governance in Russia depending on the number of shareholders.

Among the factors of court performance—a crucial element of the institutional environment for a well-functioning market economy—productivity (disposition time) and adjudicatory quality (minimum legal errors) are significant. This paper investigates presumed quantity-quality tradeoff in Russian commercial courts when considering claims to annul administrative infringement decisions, on the example of antitrust cases. Using a dataset of the first instance court decisions regarding claims to annul decisions of Russian competition authority during 2008–2015, we explore the influence of extra efforts by a judge to assess the evidence on the probability of appealing and annulling her decision. The effect is not found to be statistically significant which means the absence of adjudicatory quantity-quality tradeoff. We discuss then the implications of the finding to the rules for additional evidence presented in the courts when considering a case. We conclude, first, that in Russia the rules on reasonable disposition time and the motivation of judges to prevent backlog do not increase the probability of legal errors. Second, new evidence acquired during judicial review does not statistically improve the legal quality of court decisions. The policy implication is that the recent initiative of the Supreme Court of the Russian Federation to limit additional evidence when considering claims to annul administrative antitrust decisions is reasonable.

The study explores how wages grow with experience in the Russian Federation. In all available cross-sectional data, the trajectory of the observed wage–experience profile is flat, peaks early, and declines sharply afterwards. This shape looks puzzling since it differs starkly from that observed in both developed and developing countries. We show that a proper interpretation of the wage–experience profile is hindered by the APC problem, when the effects of time, cohort, and experience are mixed. Our study uses data from the RLMSHSE household survey covering the years 2000-2019. Relying on human capital theory, we apply a procedure suggested by Heckman et al. (1998) and advanced in Lagakos et al. (2018) to disentangle the APC effects. With certain assumptions concerning human capital depreciation due to aging, our results show that Russian wages do grow monotonically with experience. However, this growth is partially offset by the cohort effect that that proceeds in the opposite direction, thus reflecting massive depreciation of the human capital of workers from older cohorts. Meanwhile, the time effect mirrors the general GDP path as well as all booms and busts over the period.

This article explores the interrelation between economic growth and foreign direct investments (FDI) in the countries of the Commonwealth of Independent States (CIS) in 1993–2019. The research focuses on the impact of new FDI inflows per capita, as well as the influence of accumulated foreign capital (FDI stock per capita) on GDP growth per capita. This article has aimed to find the causal link between GDP growth and FDI inflows, as well as between GDP growth and FDI stock per capita in the CIS countries.

The research methods include: empirical and statistical research, synthesis of practical and theoretical matters, methods of mathematical modelling. Discussion. FDI in the CIS countries are often determined by market size and market growth potential, which ensure a favourable business environment for foreign investors. Data obtained during the analysis suggest that the CIS countries mainly attract market-oriented FDI, which is consistent with the findings of the authors. Thus, the accumulated foreign capital stock has positive impact on economic growth in the CIS countries.

Results. Foreign direct investments for economic growth act through such factors as gross domestic product, interest rate, average wages, exchange rate, consumer price index, political stability. The corona- virus pandemic factor is assessed by the authors as negatively affecting the investment attractiveness of countries; the use of digital technologies in handling FDI, according to the authors, is debatable issue.

This special issue presents a selection from the papers presented at the conference on “Experiences and Challenges in Measuring Income and Wealth in CIS Countries and Eastern Europe”, jointly organized by the International Association for Research in Income and Wealth (IARIW) and National Research University Higher School of Economics (HSE University) in Moscow on 17–18, September 2019. This conference marks a significant event being the first IARIW conference held on the territory of the former Soviet Union.

             The IARIW has historical roots in Eastern Europe. The first IARIW chairman, Simon Kuznets (1901-1985), was born in Pinsk (Belarus today). He started his academic training here in Eastern Europe, at the Kharkov Commercial Institute (Ukraine) and published his first paper “Money wages of factory employees in Kharkov in 1920” (in Russian), just before his emigration to the United States. The debates on Soviet industrialization in the early 1920s; his teachers in the institute and early experience of the analysis of the Soviet economy in the turmoil years of the Russian Revolution and the Civil War; as well as professional contacts and reading of economic literature in Russian in the 1920s and early 1930s contributed to his professional outlook (Syrquin, 2021). These topics and debates are echoed in this IARIW Conference Program. Two major themes, the risk of the middle-income trap, and the causes and consequences of inequality run through the papers in this issue.

This paper aims to study the perspectives of sustainable development amid the COVID-19 pandemic and crisis in 2021, backed by financial risk management and corporate social responsibility. To achieve this goal, the authors use the methods of regression analysis, horizontal and trend analysis, and variation analysis. As a result, it is proven—for the first time—that in isolation, investments and corporate social responsibility do not contribute positively to sustainable development. In addition, the authors determine the absence of the outflow of investments from the world economy during crises. Based on this, a new approach to crisis management of sustainable development is developed—it is based on stimulating corporate social responsibility, for which the complex recommendations in the sphere of state management are offered. The theoretical significance of the conclusions made consists in specifying the essence of financial risk management of sustainable development, which has to be conducted with a strict connection to and based on corporate social responsibility. The practical significance of the developed new approach and offered recommendations on its practical implementation consists of strengthening the scientific and methodological provision of economic crisis management of COVID-19 and the maximization of its contribution to sustainable development to support the Decade of Action.

National journals represent an important part of the landscape in almost any academic system. Their role may vary from being mere outlets for publishing country-specific studies in local languages to hosting global research. With the process of globalization in recent decades, such journals (as well as their authors) have increasingly gained opportunities to become internationally visible and to be read worldwide. Suggesting the definition of a national journal as being exogenous and with unaltered characteristics with respect to any changes in the journal’s content and policy, we provide the first up-to-date analysis of national output in post-Soviet countries, at the levels of both journal and article, for the period 2010–2019. In general, publications in local journals (associated in Scopus with the countries under consideration) constitute a substantial proportion of the national research output, with the most numerous representations of national journals found in Russia, Ukraine, Lithuania, and Estonia. The journals in the countries under consideration differ in their disciplinary composition, quality, language policy and visibility, reflecting the divergence of the countries in the decades since their independence. Although analysis of these journals suggests they are not true vehicles for communication with a global community providing international visibility for their authors, the demand for publication in internationally indexed, national journals is high and the number of journals (and articles published) has grown substantially in the last decade.

Global value chains (GVCs) generate significant effects on participating firms. But can GVCs affect other companies in the host economies? We propose a conceptual framework for GVC spillovers and test it using data for Russian manufacturing firms in 2009–2015. Using a panel estimation technique with random and fixed effects, we find that firms in industries that are intensively integrated into GVCs, on average, have higher total factor productivity (TFP), controlling for firm heterogeneity, industry and region fixed effects. TFP gains in GVCs are unequally distributed and depend on (i) the industry’s position in the GVC, (ii) the industry’s technological intensity and (iii) the firm’s TFP level. We relate the findings to the evidence of the “optimal” technological gap that maximizes productivity spillovers for national companies. The results are highly relevant for policymakers as they prove that trade policy and foreign direct investment attraction policy should not go hand in hand but should be incorporated into GVC-oriented policy to encourage the full range of TFP improvements in local (non-GVC-included) firms. To fully benefit from GVC-oriented policy, State policy should encourage the development of inter-firm links. In addition, our results support the importance of evolutionary structural changes in economic upgrading in GVCs and the strength of the role of policies oriented towards medium-technology industries as drivers of technological development.

This paper examines the impact of the Global Financial Crisis (GFC) on wealth inequality. We investigate this question, using data for 143 countries for the period 2010–2018. We find no significant impact of the occurrence of the crisis on wealth inequality. We show limited evidence that the severity of the banking crisis affects the change in wealth inequality. Furthermore, the impact of the GFC on the change in wealth inequality is influenced by the country characteristics: the GFC has more enhanced wealth inequality in countries with higher levels of economic and financial development as well as lower initial levels of wealth inequality. We therefore contribute to a better understanding of the real effects of banking crises by providing evidence of the distributional effects of the GFC.