Development of a methodological approach to medium-term forecasting of the regional economic growth based on the decomposition of macro-forecast indicators for Russia

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The article presents a methodological approach to the development of a medium-term forecast of GRPgrowth rates in regions (subjects of the Russian Federation and Federal districts) in the context of the main types of economic activity based on the decomposition of macroeconomic forecast indicators for Russia. The key factors that have a significant impact on the dynamics of the current regional economic growth, including macroeconomic, territorial and external ones, should be taken into account in forecasts of regional development. The author mentions examples of domestic practices of scientific research in the field of forecasting in the regions of Russia according to the main macroeconomic indicators, including GRP. The paper states the methodological basis and fundamental principles of forecasting of regional indicators of the economic growth according to the main types of economic activity. As a keyfactor an indicator determining the dynamics of production in the sectors of regional economy, the growth rate of investments into fixed capital is used which is determined by the presence of a functional relationship between these characteristics on the basis of the multiplier ratio. On the basis of the developed methodological approach, the author estimates the growth rate of GRP of Russian regions according to the main types of economic activity for the period until 2024. The paper presents the results of the GRP forecast for Federal districts, as well as the share of GRP investments in them. The article shows the regions of the Russian Federation with the highest GRP growth rates in the medium term and trends of changes in the levels of interregional differentiation in investment and economic activity in Russia from 2000 to 2017 and for the forecasted period until 2024.

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Medium-term forecast, growth rates, grp, types of economic activity, forecasting algorithm, methodological approach

Короткий адрес: https://sciup.org/149131965

IDR: 149131965   |   DOI: 10.15688/re.volsu.2020.1.6

Статья научная