Game Analysis of Strategies for Providing Material Support to the Population
https://doi.org/10.21686/2500-3925-2024-1-57-66
Abstract
The article focuses on the possibilities of game analysis of options for providing material support to the population, implemented in the form of a game with nature – a generalized player, whose inclusion in the game analysis allows us to consider the diverse interaction of economic agents with the socio-economic environment. This set of methods has a number of advantages among the complex of mathematical methods in economics and management in conditions when regression models become irrelevant due to increasing uncertainty or lack of sufficient initial data.
The purpose of the study is to overcome the insufficient use of the potential of game models in the practice of modeling social situations, taking into account the real information conditions that have developed to date.
The research methods are the methods of game theory (construction of a set of active strategies for providing material support to the population; identification of possible variants of states of nature reflecting the possibilities of the number of people who really need material support; determination of the optimal strategy for providing material support, taking into account the selected optimality criterion).
Their use contributes to improving the quality of decisions made in the field of providing material assistance to the population. Among the results of the study, we will indicate the implementation of all the necessary stages of the game analysis of strategies for providing material support to the population. The proposed mechanism for assessing the usefulness of funds, used for material support of the population, takes into account various contributions to the assessment of the final utility of the distribution of funds, arising both in cases of receiving funds by those in need and in cases of non-receipt of funds by those in need, as well as in cases of receiving funds by citizens who do not really need financial assistance. The authors have made calculations and assessed the consequences of strategies, the implementation of which involves reducing the number of citizens who receive financial assistance (with simultaneous dynamics of the amount of financial assistance). The game analysis of strategies for providing material support to the population became possible due to the construction of a game model of a basic level of complexity that takes into account the main scenarios of the development of the social situation under consideration. In the process of studying the constructed game model, a high degree of sensitivity of strategies for providing material assistance to the population to the choice of the optimality criterion, as well as its parameter, was established. This feature requires clarification of the information situation in which the strategy of providing financial assistance is chosen. In conclusion, we note that the material of the article may be useful for consideration with subsequent pilot testing at various levels of state and municipal administration, when developing and adopting legislative initiatives on social support measures aimed at strengthening the targeting of financial assistance to the population. Also, the material and tools of this study can serve in the course of improving existing and developing new academic disciplines, the content of which is related to the quantitative analysis of socio-economic problems and situations.
About the Authors
D. A. VlasovRussian Federation
Dmitry A. Vlasov, Cand. Sc. (Pedagogy), Associate professor
Department of Mathematical methods of Economics
Moscow
P. A. Karasev
Russian Federation
Petr A. Karasev, Cand. Sc. (Economics), Associate professor
Department of Higher mathematics
Moscow
A. V. Sinchukov
Russian Federation
Alexander V. Sinchukov, Cand. Sc. (Pedagogy), Associate professor
Department of Mathematics
Moscow
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Review
For citations:
Vlasov D.A., Karasev P.A., Sinchukov A.V. Game Analysis of Strategies for Providing Material Support to the Population. Statistics and Economics. 2024;21(1):57-66. (In Russ.) https://doi.org/10.21686/2500-3925-2024-1-57-66