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2026, Issue 2 (71). Abstracts
The optimal design of elimination tournaments with a superstar Tournament is a widespread tool for organizing competition and identifying the most effective agent. We study single- and double-elimination tournaments with heterogeneous players of two types: several regular players and a unique superstar. Players simultaneously choose efforts in each match, winning with a probability calculated with the Tullock success function, the costs are linear with respect to player’s efforts. We consider well-known designer’s objective functions, i. e. the total efforts associated with the performance of the tournament and the probability of winning the strongest player, and introduce the novel weighted composed function accounting for various related organizer costs. Analysis shows that a double-elimination tournament is less profitable in most cases, except when the tournament organizer is concerned about the probability that the superstar wins the tournament. Special attention is paid to the case of an extremely strong superstar. It is shown that attracting such a player is suboptimal for the organizer, both due to the large payments to this player, which increase with his strength, and due to the strategic demotivation of other tournament participants from exerting high effort, which reduces the overall entertainment value of the tournament. The study is valuable for organizers of various tournaments, as it allows them to choose the optimal tournament format and predict its relationship with future entertainment value. Keywords: single-elimination tournament, double-elimination tournament, tournament design, heterogeneous players, sportsman-superstar Full text
Economic growth and inequality in a model with robot This paper develops an overlapping generations model with altruism and dynasties that vary in their intertemporal preferences and degree of altruism. The paper inves-tigates the effects of robotization on economic growth and inequality. The model assumes that an individual representing a dynasty lives for two time periods and has one heir, to whom a non-zero bequest is left. The size of the bequest is one of the arguments of log-linear utility function. During the first time period, the individual works and receives a wage and also receives some bequest. The technology is described by a three-factor (labor, capital, and robots) Cobb–Douglas production function, in which a robot can fully replace one worker. It is shown that the dynamics of equilibrium paths depend on the price of robots. If robots are too expensive, they will not be produced or used, and the equilibrium path will converge to a certain steady-state equilibrium. As robots become slightly cheaper, the process of automation begins, and the equilibrium path converges toward a new steady-state equilibrium. The transition to a new equilibrium can lead to either an increase or a decline in the welfare of individual dynasties or society as a whole. If robots become even cheaper, the economy will settle on an infinite growth path. However, that does not mean that the welfare of all dynasties will grow infinitely. The income of some dynasties may even decline. In any case, automation will lead to greater inequality in the distribution of income and wealth. Keywords: economics growth; inequality; robotization DOI: 10.31737/22212264_2026_2_36-57 S.K. Tomskii, National Research University Higher School of Economics (HSE University), Saint Petersburg, Russia Elasticity of electricity demand: Account of tariffs by time-of-use7 This article examines the long-run price elasticity of household electricity demand in Russia, taking into account time-of-use (ToU) tariffs. Using panel data for 65 regions over the period 2016–2021, the analysis estimates price elasticity of demand across different time zones. The main findings indicate that daytime and semipeak consumption exhibit statistically significant negative elasticity, while nighttime and peak consumption show no significant response to price changes. These results do not support strong effectiveness of time-based tariff differentiation, except for daytime and semipeak periods. Similar conclusions were observed in China and other countries, often attributed to ineffective price differentials between tariff periods. Enhancing tariff differentiation, introducing better time segmentation, and implementing more complex pricing systems — such as critical peak pricing or its variants — could lead to more efficient load redistribution within the Russian power system. Keywords: pricing, demand elasticity, time-of-use tariffs, electricity, tariff differentiation Full text
.V.E. Vasil’ev, North-Eastern Federal University (NEFU), Yakutsk, Russia Estimates of the impact of railway modernisation in southern Siberia on the geography of the economic activity based on a computable general equilibrium model The article, based on the general equilibrium model, assesses the impact of modernization of transport infrastructure on the well-being of the population and on the spatial proportions of economic activity in the south of Western Siberia. Twenty five relatively large municipalities located in the Novosibirsk, Kemerovo, Tomsk and Omsk regions, Altai Territory and the Altai Republic are considered. Estimates showed that the highest economic returns and welfare gains for the whole territory come from upgrading transport infrastructure and reducing communication costs with the largest urban center, Novosibirsk. The calculations confirmed the role of the city as an integration core of the urban system and transport and logistics center of the south of Western Siberia. But model experiments also showed that centripetal tendencies dominate in the territory under consideration, and the benefits of spatial concentration of business are significantly higher than the costs associated with a higher density of business activity. Reduced communication costs cause a significant redistribution of business to Novosibirsk at the expense of employment and population in most other settlements, although there are exceptions. The implementation of major transport projects should be accompanied by the creation of an extensive network of roads in the surrounding areas, as well as measures to support communities the competitive features of which are significantly impaired. Keywords: computable general equilibrium model, economic activity, spatial proportions, transport infrastructure, southern Siberia Full text
A.V. Krupochkin, Plekhanov Russian University of Economics, Moscow, Russia Bitcoin: From the exchange equation to inverse leverage volatility forecasting This study aims to quantify the impact of Bitcoin’s macro-network metrics — interpreted within a modified Fisher equation of exchange — on its market price, and to build a forecasting model for both the price and conditional volatility of Bitcoin. The empirical base consists of daily data from 2020 to 2024 (1,827 observations) covering total coin supply (TS), velocity of circulation (Vel), U.S.-dollar transaction volume (TV), and market price. Using principal component analysis (PCA), two orthogonal latent factors were extracted from these on-chain indicators, jointly explaining 91.1% of their total variation. The first factor is interpreted as a supply-scarcity factor (dominant loading from TS) and exerts a strong posi-tive effect on price. The second factor, capturing transaction activity (associated with velocity and transaction volume), exhibits a statistically significant negative impact, thereby empirically confirming the «HODL effect» and the primacy of Bitcoin’s investment function over its medium-of-exchange role. To account for temporal dynamics and volatility clustering, a combined SARIMA(1,1,0) (1,1,0)(0,1,0,90)–EGARCH(1,1) model with Student’s t-distribution was applied. Within the EGARCH-t framework, a significant positive «inverse leverage effect» (asymmetry coefficient γ = 0.0317, p-value = 0.041) is identified, indicating that positive price shocks increase future volatility stronger than negative shocks of equal magnitude. The obtained results deepen the understanding of specific market risks of digital assets and offer a theoreti-cally grounded toolkit for their forecasting. Keywords: Bitcoin pricing, macro-network indicators, principal component analysis (PCA), conditional volatility, inverse leverage effect, SARIMA-EGARCH-t models Full text
M.A. Giltman, Tyumen State University, Tyumen, Russia Employment of registered unemployed older people during the period of retirement age increase The increase in the retirement age, which began in 2019, led to the emergence of a number of benefits and advantages that pre-retirees can receive by registering at the Employment center as unemployed. In this paper an attempt is made to find out how successfully older people find employment after being in an episode of registered unemployment. For this purpose, the flows of transition between the formal statuses of «employed», «registered unemployed» and «unemployed» are analyzed in terms of gender, age, education, qualifications at the previous place of work etc. Using multinomial logistic regression the probabilities of being employed with lower, higher, or the same qualifications as in the previous job are estimated. The analysis is based on administrative microdata on registered unemployed for 2019–2023 provided by the Department of Labor and Employment of the Tyumen Region. The results showed that the age of older people moving into employment and unemployment is almost the same, while education is different. The availability of professional education, self-employment, the position of a skilled worker in a previous job and a number of other factors increase the likelihood of employment with the same or higher qualifications. The options for getting out of registered unemployment for older people differ for men and women. Keywords: employment, pensioners, pre-retirees, employment center, employment service, unemployment, multinomial logistic regression, multilogit Full text
P.F. Andrukovich, Central Economics and Mathematics Institute, Russian Academy of Sciences, Moscow, Russia N.D. Kondratiev’s technological waves and GDP dynamics The article begins with an overview of theoretical works on the existence of cycles in the process of economic development and publications describing econometric models of long waves. The article shows that the main trend in GDP dynamics, corresponding to internal economic processes rather than the infl uence of exogenous factors, can be described by a superposition of Kondratiev’s long waves represented by sinusoidal functions. The parameters of each of these waves — the beginning of its origin, the amplitude and two more parameters specifying its dynamics — allow one to “tune” the model to the dynamics of GDP in different countries with different GDP sizes, different beginnings of a particular wave and their different periods. The models for six European countries: Italy, Spain, Portugal, Norway, Finland and Sweden, as well as for the USA, based on GDP values, measured in international dollars, are constructed. Taking into account the generally accepted opinion on the existence of five long waves from the end of the 18th to the end of the 20th century, estimates of the beginning time of each of these waves, the values of their amplitudes, the length of their periods, as well as the characteristics of the entire set of waves as a whole are obtained for each of the specified countries. It is shown that there are both similarities in the structure and dynamics of N.D. Kondratiev’s long waves in these countries, and differences in the moments of their origin, development and withdrawal into the “second” plan. Based on the constructed models, an assessment is given of the magnitude of deviations of GDP values from the model during periods of wars, economic crises, etc. Keywords: Kondratiev’s waves, international comparisons, technological waves, econometric models Full text
E.A. Shenkman, National Research University Higher School of Economics (HSE University), Perm, Russia Comparative analysis of large language models and human behavior in the Dictator Game This article analyzes the behavior of large language models (LLMs) in the Dictator game; the comparison was carried out against the results of previously conducted laboratory behavioral experiments with human participants. The study examines modifi cations of the basic game that is including the possibility of taking resources from the opponent as well as the introduction of a production phase. Ten LLMs were selected for the experiments, including both international and Russian models. The results show that LLMs systematically display greater generosity compared to human participants: the average transfers to the opponent are higher regardless of the game conditions. At the same time, the analysis of the models’ reasoning revealed the use of both fairness- and trust-related categories and arguments oriented toward maximizing self-interest, which makes their decision-making similar to the cognitive foundations observed in humans. Thus, LLMs replicate certain elements of social behavior but exhibit a shift toward “hyper-altruism”, which limits their direct applicability as substitutes for human participants in behavioral experiments. Keywords: large language models (LLM), Dictator Game, behavioral economics, AI agents, social norms Full text
N.V. Ershova, National Research University Higher School of Economics, Moscow, Russia State support of manufacturing fi rms in periods of crisis: Factors for receiving support The paper examines the scale and factors of state support provided to Russian industrial firms with a focus on the period of crisis caused by the COVID-19 pandemic using the data of three waves of enterprise survey (2014, 2018, 2022). Based on 2022 disaggregated data, the dynamics and factors of receipt of financial and organizational support during the crisis were identified. A comparison of three waves of survey showed a decrease in the influence of state participation in the firm’s ownership structure on access to state support. In all periods, factors characterizing the state-business relations such as providing assistance to authorities in regional socio-economic development and participation in business associations remained significant. In 2022, the importance of investment activity of firms increased, and the importance of innovation activity was preserved. During the crisis, there was a significant increase in the share of firms receiving state financial support that peaked in 2020. Also we identified differences in the types of support correlated with different factors based on the 2022 data. Actively investing firms and firms-members of business associations more often received financial support, while enterprises with high innovative activity received mainly organizational support from government authorities. Keywords: government support, Russian manufacturing firms, financial support, organizational support, COVID-19 crisis JEL classification: D22, H25, O25 Full text
P.A. Popova, HSE University, Moscow, Russia The impact of COVID-19 and preferential mortgage lending programs on mortgage lending: Evidence from Russia This study explores the relationship between preferential mortgage programs and regional mortgage lending in Russia during the COVID-19 pandemic and the subsequent recovery period. Using quarterly data from 85 Russian regions, the research examines how preferential mortgage programs — Standard Preferential, Family, Far Eastern, and IT — were associated with lending growth and delinquency rates. The findings underscore the complex interplay between housing policies, regional economic conditions, and mortgage market activity under varying external economic shocks. The study reveals that overall mortgage lending volumes were higher during the pandemic and post-pandemic periods in regions with greater adoption of preferential mortgage programs. This pattern suggests that these programs supported housing market activity, particularly in economically resilient regions. However, regions with higher program utilization also experienced elevated delinquency rates, reflecting the challenges of balancing increased borrowing with financial risks. Program- specific analysis highlights variations in lending dynamics and underscores the importance of tailoring housing policies to regional and demographic needs, offering insights into the design of adaptive support measures that promote mortgage market stability and economic recovery. Keywords: COVID-19 economic shock, mortgage lending, preferential mortgage programs, regional mortgage markets in Russia, financial stability Full text
O.V. Biryukova, Centre for Comprehensive European and International Studies, HSE University, Moscow, Russia Exporting creative goods from China: Government support measures in the 13th and 14th five-year plans The rapid expansion of creative industries plays a pivotal role in fostering sustainable economic development and enhancing the global cultural footprint of exporting nations. Consequently, governments worldwide actively implement targeted mechanisms to stimulate creative exports. As the undisputed global leader in creative goods exports, China’s success stems from both its inherent comparative advantages and systematic state interventions. However, the specifi c quantitative impact of governmental support instruments on China’s creative export performance remains underexplored in existing literature. This study systematically examines the key fiscal and financial support measures implemented during the 13th and 14th five-year plans and assesses their influence on creative goods exports from 2016 to 2023. Utilizing a balanced panel regression approach across regional and product-level datasets, the analysis reveals that both VAT export rebates and direct government budget financing exert a statistically significant positive effect on export volumes. Furthermore, the findings highlight a pronounced geographic and structural concentration of exports, predominantly directed toward the United States and European markets. The study concludes that while current support policies have effectively bolstered export competitiveness, strategic optimization is required to mitigate regional disparities, encourage long-term sectoral diversifi cation, and reduce vulnerability to external market fluctuations. Keywords: creative industries, creative goods, Chinese export, government support, export support Full text
D.Yu. Gorbunov, New Economic School, Skolkovo, Moscow, Russia Human capital, social connections, and firm productivity: Evidence from Russian Old Believers The Old Believers, a persecuted religious minority in the Russian Empire, controlled an over-proportional share of textile firms despite constituting only a small fraction of the population. This article connects the historical entrepreneurial experience of the Old Believers with modern theories of firm productivity and economic development. Drawing on historic and economic literature, the article reviews evidence suggesting that Old Believers’ enterprises often demonstrated higher productivity and better performance than firms owned by the rest of the Orthodox population. The article highlights three main explanations for this success, discussed in the literature: high levels of human capital, dense social and confessional networks, and access to financial resources through mutual lending. Particular attention is given to the mechanisms through which social and financial capital influenced productivity in the context of the late industrialization of the Russian Empire. The article also discusses the opportunities and limitations of applying modern firm-level economic theory to historical data from Imperial Russia. The case of Old Believers’ entrepreneurship provides a valuable historical setting for testing modern theories of firm productivity, social capital, and resource allocation. The article concludes by identifying areas for future empirical research based on available firm level historical datasets. Keywords: economic history of Russia, Russian Old Believers, firm productivity, entrepreneurship, social connections. Full text
E.N. Nikishina, Lomonosov Moscow State University; Institute for National Projects, Moscow, Russia Prospects for integrating behavioral and cultural economics The article argues for the promise of integrating behavioral and cultural economics based on the common premise of bounded rationality. It systematizes empirical evidence on the relationships between cultural characteristics and cognitive biases. It is shown that most of the links between cultural characteristics and cognitive biases are currently established for ?non-standard preferences? (reference-dependent preferences, social preferences, and present-biased intertemporal preferences). Among cultural indicators, the most links have been identified for the individualism-collectivism dimension. From a practical standpoint, the article’s findings highlight the importance of considering cultural context when designing educational programs, as well as the promise of simultaneously accounting for both cultural context and the structure of cognitive biases in institutional design (including nudge). For Russia, this implies, among other things, the importance of considering regional differences on the individualism-collectivism scale and developing culturally-specific tools for mitigating biases associated with high power distance and uncertainty avoidance. Keywords: cognitive biases, values, attitudes, individualism, nudge, the link between culture and cognitive biases Full text
Ph.S. Kartaev, Center for Mathematical Modeling of Economic Processes, IEPI, RANEPA; Lomonosov Moscow State University, Moscow, Russia Sentiment and monetary policy The article provides a survey of the contemporary literature on the role of sentiment in finance, macroeconomics, and monetary policy. It discusses approaches to measuring sentiment, including the construction of sentiment indices based on the analysis of unstructured data of various types (text, audio, and video), and examines the use of sentiment indicators for forecasting macroeconomic variables. The paper demonstrates that the expanding application of sentiment in microeconomic, macroeconomic, and financial analysis is closely linked to recent advances in machine learning methods for processing unstructured data. The survey shows that sentiment is closely related to the mechanisms of expectation formation and can substantially amplify macroeconomic fluctuations. This effect may be explained by the bounded rationality of economic agents: excessive reactions to recent news may arise due to the behavioral representativeness heuristic. In the context of macroeconomic and financial fluctuations, such overreaction is described by the diagnostic expectations hypothesis, which appears to be broadly consistent with Russian data. Particular attention is devoted to models of infl ation expectations and to empirical findings, including estimates for the Russian economy, that support the view that the transmission of monetary policy changes in the presence of behavioral distortions. The paper concludes that sentiment and communication effects should be explicitly taken into account when forecasting the consequences of monetary policy. Keywords: sentiment, monetary policy, inflation expectations, transmission mechanism, unstructured data analysis Full text
A.M. Matevosova, Bank of Russia; Institute of Economics of the Russian Academy of Sciences; Lomonosov Moscow State University, Moscow, Russia Sentiment analysis for monetary policy research The article examines the experience of using sentiment analysis methods in the field of monetary policy for the research of public opinion, central bank communication, macroeconomic analysis and forecasting. Natural language processing (NLP) methods overcome the disadvantages of traditional approaches based on opinion polls in the context of measuring infl ation expectations and trust in the central bank. Sentiment analysis is actively used in the study of various aspects of central bank communication and the assessment of media sentiment. As a tool for quantifying qualitative data, sentiment analysis allows to build high-frequency and operational estimates of indicators. It is noted that thematic indicators based on sentiment analysis can in some cases improve the accuracy of macroeconomic forecasting by enriching information extracted from classical economic variables. The development of machine learning and the emergence of new neural network architectures expand the possibilities of using sentiment analysis, but they also raise the issue of choosing tools. The article provides a comparative analysis of various sentiment analysis methods, including classical machine learning models and neural networks, for the task of building an indicator of trust in the Central Bank. The approach based on fine-tuning of pre-trained Bidirectional Encoder Representations from Transformers (BERT) is recognized as the most effective. It was revealed that fine-tuning large language models can significantly improve the quality of solving the problem of sentiment analysis by adapting to the subject area, which is especially important for research in the field of monetary policy. Keywords: sentiment analysis, monetary policy, central bank, neural networks, large language models, trust, infl ation expectations Full text
A.M. Karminsky, National Research University Higher School of Economics (HSE University), Moscow, Russia Sentiment analysis in the banking sector and finance At present, banks are interested in improving the quality of their own processes and models for decision-making within these processes. Process improvement involves its automation, that is, replacing manual work with automated mechanisms that enhance service quality and reduce banking costs; model improvement involves increasing its accuracy and stability by using additional information. One possible way to achieve this optimisation is sentiment analysis, which allows recognising information from texts and using it both for automating banking processes and for improving the accuracy and stability of the models developed by banks. Currently, many Russian banks are implementing sentiment analysis methods into their internal processes and taking their results into account when developing their own models, thereby gaining competitive advantages in the market. The article examines the essence, methods, objectives, types of classification and examples of sentiment analysis dictionaries in banking. The specifics of applying sentiment analysis in both international and Russian practices are analysed in detail, and the prospects and trends for the development of sentiment analysis in Russia and abroad in the near future are presented. Keywords: banking, sentiment analysis, text tonality, computational linguistics, machine learning, text analysis Full text M.I. Stolbov, Moscow State Institute of International Relations (MGIMO University), Moscow, Russia The role of sentometrics in analysing financial instability The paper traces the evolution of approaches to the analysis of financial stability, ranging from classical prudential indicators and aggregate financial stress indices to sentiment-based indices capturing the mood and expectations of economic agents. Based on the contemporary literature, the paper provides a systematic review of the key methodological issues related to sentometric approach, namely the construction of specialised dictionaries and the aggregation of textual information into a single index. The paper discusses the trade-offs between the interpretability of dictionary-based methods and the flexibility of models based on machine learning and large language models. It is further emphasised that the choice of text corpus and data processing method has a substantial impact on the interpretation and predictive properties of the resulting indicators. Particular attention is paid to a review of empirical studies based on a thematic graph of articles (Connected Papers), which makes possible to identify the main clusters of work at the intersection of sentometrics, financial stability and macroprudential policy. In the concluding part, the paper discusses the limitations and weak points of sentometric indicators, including problems of interpretation, comparability and data quality, and formulates directions for further research required to integrate sentometric indices into the existing standard frameworks for monitoring financial stability. Keywords: sentometrics, financial stability, central bank communication, natural language processing, large language models, financial stress Full text
I.D. Krylov, National Research University Higher School of Economics (HSE University); Bank of Russia, Moscow, Russia The problem of economic interpretation of sentiment indices Modern text-processing methods substantially expand the range of sources through which economists can study unobservable economic phenomena. Researchers use large orpora of textual data to construct sentiment indices, which are then given an economic interpretation. Public texts, however, are a highly specific source of information. They are embedded in a broader social context that cannot always be identified from the text itself, yet may shape the meaning of the statements it contains. For this reason, the technical accuracy of classifying statements, for example the successful detection of irony, is not in itself a sufficient evidence of a link with an economic phenomenon. This transition requires specific justification. The article examines the relationship between an index and an economic phenomenon through the concept of measurement validity. Using sentiment indices of infl ation expectations and consumer sentiment as examples, it shows that validation requirements depend on the researcher’s interpretation of the index. An index may be used as an applied predictor, as a proxy for an existing indicator, or as a measure of economic phenomenon. In each case, a type of evidence is needed to justify the relationship between the indicator and the measured object. The strongest requirements arise when an index is interpreted as a measure of a phenomenon, especially if the phenomenon itself has an uncertain conceptual status. Keywords: sentiment analysis; measurement validity; inflation expectations; consumer sentiment Full text
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