Abstract
The article addresses the following issues: development of the methods for calculating the effectiveness of the investment process, taking into account the delay in putting the assets into operation; creation of a program for the development of а subsidized region and determination of the necessary volume of investment in the innovative development of industries by the method of simulation modeling; building of macroeconomic models, taking into account the innovative component for estimating and forecasting the GDP of the Russian Federation and the GRP of Federal Regions and the Russian Federation regions on the basis of multiplicative production functions, considering the delay in putting the assets into operation; economic analysis of the statistical estimates of the parameters of the built models; and the most widespread R. Solow’s model in which the rate of the labor force size growth is an exogenous magnitude, the technological level is unchanged, and the return from the two factors of production – labor and capital – is constant. An algorithm for choosing an optimal macroeconomic model for a particular region has been developed. It is planned to build macroeconomic models, taking into account the innovative component for estimating and forecasting the GDP of the Russian Federation and GRP over Federal Regions and the Russian Federation regions on the basis of multiplicative production functions, taking into consideration the delay in putting the assets into operation; it is also planned to analyze the statistical estimates of the built models.
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Acknowledgments
The research is supported by the Russian Science Foundation Grant № 16-18-10017 “A Complex of Programs for Forecasting Regional Economic Development.”
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Kulalaeva, I., Tsaregorodtsev, E. (2018). Effectiveness of Assessment Methodology for Forecasting Sustainable Development of Russian Regions. In: Strielkowski, W., Chigisheva, O. (eds) Leadership for the Future Sustainable Development of Business and Education. Springer Proceedings in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-319-74216-8_53
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DOI: https://doi.org/10.1007/978-3-319-74216-8_53
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