Vol 60, No 1 (2024)

The first part of the paper presents the results of theoretical and methodological research based on a relatively new view of the processes of knowledge production as a public good and its subsequent transformation into private, meritorious and normative-public goods with individual and social utility, with a focus on one of the branches of this transformation — the publication of scientific articles. An important feature of this process, distinguishing this type of activity, is due to the problems of intellectual property and copyright. This area of modern science determines the institutional conditions of transformation of knowledge into products of market exchange. The protection of intellectual property realized by the legislation on copyright gave rise to many theoretical and practical problems related to the known consequences of the development of this institution, which limits the dissemination of knowledge and reduces its availability. A special role here belongs to the developing contractual practice of transferring copyrights to publishers, including issues of publication ethics, and the peculiarities of economic relations arising in such a situation, the expedient component of which is the payment of royalties and labor remuneration to reviewers.

Developing country currencies experienced strong fluctuations during the pandemic. In order to clarify the reasons of the high volatility of the Russian ruble, the Brazilian real and the Indian rupee we investigate the impact of COVID-19, its coverage in the social media and inquire about the coronavirus in Google on the exchange rates of the currencies in the study on the dollar during the period of high volatility from 01.01.2020 to 30.04.2020. Based on the works on crowd psychology, and behavioural finance, we theorise about the effects of coronavirus attention and hysteria (hype) around it on currency markets. Based on the developed GARCH models, we empirically prove that an increase in the number of publications on coronavirus in the national segment of Facebook and Instagram was accompanied by a rise in the volatility of national currencies. Such results were observed for the exchange rates of the rouble, the real and the rupee. We proved the presence of a hype-effect around COVID-19 in case of the USD/RUB exchange rate. With heightened interest in the coronavirus, the effect manifested itself in an increase in the degree to which COVID-19 coverage in social media affected the volatility of the ruble exchange rate.

The problem of employment in the informal sector of the economy escalated during the pandemic, post-covid recovery and, especially, in the period of sanctions. As an interdisciplinary field of research in the humanitarian, socio-economic, information and mathematical spheres, issues of employment, unemployment, social benefits are increasingly resonating in modern publications. The global framework of the research subject often makes difficult to formalize the processes, especially in the shadow economy. The authors used the panel data analysis to assess the dynamics of employment in the informal sector and the causes of negative trends in the post-pandemic period. The number of model explanatory variables for the period 2010–2021 was 84 with subsequent cutoff and reduction to 32 parameters. To compile a panel data the authors used the official information from Rosstat and information obtained by expert surveys. During the study the scientists create the models of combined regression, model with fixed effects, and model with individual, including random, effects. As a result the authors obtained the ratio “employment in the informal sector — the level of hidden economic activity”. The important applied relevance of the research is the possibility to generate control, both at the state and economic level, in terms of the identified reasons for the growth of employment in the informal sector in order to reduce their negative impact.

The article deals with the design and development of scientific tools for evaluating investment projects in the Arctic zone of Russia, taking into account the specific features of their application in the region. The necessity is substantiated and a mechanism is proposed for a comprehensive assessment of the effectiveness of investment projects implemented in the Arctic zone to select the highest priority projects, which is based on specific indicators that allow taking into account the peculiarities of the development of the Arctic regions. The system of component indicators for evaluating the effectiveness of projects is proposed. It is based on federal methods and supplemented with special indicators characterizing the regions of the Arctic zone, which allows describing the economic, social, environmental components of efficiency, ensuring state income, regional development, contribution to the national project and the country’s defence capability. The recommended set of indicators can be adjusted, which will not affect the developed algorithm for assessing the priority of projects. The authors developed a mechanism for determining the comparative effectiveness of projects based on their cost characteristics and expert assessments that allow determining the developed set of indicators. Experts’ assessments in the form of interval numbers are used for calculations. An algorithm for such an assessment of the effectiveness of development projects in the Arctic regions is proposed, including calculation of indicators that make up the assessment of the comparative effectiveness of the projects, determination of the integral assessment of such projects, as well as calculation of the comparative effectiveness of the analyzed projects. A numerical example is given, which makes possible to implement the developed mechanism for calculating the comparative effectiveness of projects in the Arctic zone of the country, taking into account environmental, social, ecological and other factors. The scientific results of the study include the development of economic and mathematical tools for ranking and selecting projects in assessing comparative efficiency in the industrial development of the Arctic. An approach to accounting and evaluating ethnological aspects in determining the effectiveness of projects in the Arctic is proposed.

In the literature on forecasting electricity spot prices, it is noted that the empirical distribution of the growth rates of equilibrium prices for electricity is characterized by the presence of heavy ‘tails’, so they can be described as a jump-diffusion process. However, electricity prices are associated with a variety of observable factors that can be included in the model. Within the framework of this article, a flexible model, that allows taking into account statistical features of electricity prices (multilevel seasonality, stochastic volatility), as well as fundamental price factors that directly or indirectly affect equilibrium price indices (weather factors, resource prices, industrial production index, or IPI), was developed. Using methods of Bayesian inference, it was shown that the developed two-level specification of the stochastic volatility model, which separates the factors influencing the deterministic and stochastic components of the series, fits the data best, among the considered alternatives. As a result, differences in the price dynamics between the European and Siberian price zones were revealed: the influence of the weather factor in the price zones is not the same; there are also differences in the weekly price dynamics and the effect of holidays. The effect of low-frequency economic factors (resource prices, IPI) on prices was not revealed. This model is a useful tool for analyzing short-term and long-term electricity price dynamics, building scenario forecasts, and it also can potentially be used in risk-management and electricity derivatives pricing.

Solving the problem of effective management of labor productivity of company employees, taking into account many heterogeneous factors, often of a stochastic, non-stationary and non-linear nature, embedded in complex chains of cause-and-effect interactions in the context of digital transformation of the economy presents certain difficulties. The paper proposes a technology that ensures, with a high degree of certainty, the establishment of causal relationship between the implementation of alternative management decisions and the productivity of company employees, and is designed to select solutions based on an assessment of the effect of their impact on labor productivity. The novelty of the proposed technology is based on a hybrid approach to modeling the object of study and combines two models. First model – a structural model built on the basis of a priori knowledge of the laws of functioning and development and providing a causal understanding of the object and capable of predicting the effect of factors (explicit and indirect). Second model – a model based on data, which is tuned (adapted) taking into account empirical data obtained as a result of observation (measurement) of an object. The developed technology uses heterogeneous research methods —a randomized controlled experiment to obtain information about the tested activities, statistical data analysis —descriptive data analysis, correlation and regression analysis, the difference-difference method to establish a causal relationship between the implemented event and the growth of labor productivity, a Bayesian network of causality for building and analyzing a structural model of an object and explaining the causal relationships of explicit and hidden factors that affect labor productivity in the context of the implementation of measures. Of practical significance are the results of testing the proposed theoretical provisions, methods and technologies on actual data on the activities of a food service company. The results obtained will contribute to the effective use of the developed technology aimed at ensuring the growth of labor productivity under uncertainty in the external and internal environment and will contribute to the sustainable development of companies and the growth of its profitability.

Sequential truel is a duel-like game between three players. Each players is endowed with his own marksmanship. At each turn, a player whose turn is to shoot can target any of the remaining alive opponents or abstain from shooting. The game ends when there is only one player alive or when all alive players abstained from shooting one after another. The single survivor obtains the “survivor” prize 1, while the payoff of all other players is 0. In the case the truel ends due to “inactivity”, all the players receive the payoff of 0. It is a deeply studied game with paradoxical finding that the weakest player has the highest probability of surviving in many settings, especially when the player can abstain from shooting. Here we present an explicit construction that contradicts this finding. There exists a mixed strategy subgame perfect equilibrium in which the strongest player has the highest probability of survival. This equilibrium exists for a specific order of play, in which the two stronger opponents act before the weakest one. When it exists, there are multiple subgame-perfect equilibria, including the existing stationary construction, in which two stronger opponents target each other.