Estimation of Models of the Effect of Taxes on the Economic Growth of the Regions of Russia
- https://doi.org/10.2991/aebmr.k.200312.292How to use a DOI?
Subject of article is the assessment of descriptive and optimization models of the effect of taxes on economic growth. Work purpose is based on the analysis of the basic models of economic growth (taking into account the tax factor) of foreign and domestic authors to identify the features, advantages and disadvantages of the latter on the basis of the approach considered taxes as a factor of economic growth. The hypothesis of the study is based on the assumption that the accumulation of funds to state is necessary in order to further redistribute them t achieve a high level of socio-economic development, which implies the use of simulation modeling, which is an experimental and applied methodology and allows describing the behavior of the corresponding systems, form a theory and test hypotheses that can explain this behavior, as well as about establish concrete recommendations for reforming the tax system with the aim of accelerating economic growth. Methodological foundations of a systems approach and economic and mathematical modeling are used: comparative method — in identifying features of economic growth models that take taxes into account; statistical analysis - in the study of dependencies between macroeconomic indicators; economic and mathematical modeling and mathematical statistics - in the construction of economic growth model, taking into account the tax factor. The proposed approach can be used by public institutions to assess the reform of the structure of the tax system, which will contribute to stable growth rates of production of goods and the provision of services.
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Cite this article
TY - CONF AU - A A Mambetova AU - E P Peshkova PY - 2020 DA - 2020/03/17 TI - Estimation of Models of the Effect of Taxes on the Economic Growth of the Regions of Russia BT - Proceedings of the International Scientific Conference "Far East Con" (ISCFEC 2020) PB - Atlantis Press SP - 2093 EP - 2106 SN - 2352-5428 UR - https://doi.org/10.2991/aebmr.k.200312.292 DO - https://doi.org/10.2991/aebmr.k.200312.292 ID - Mambetova2020 ER -