Economic Analysis: Theory and Practice

Using the neural network method to forecast investment efficiency

Vol. 16, Iss. 8, AUGUST 2017

Received: 5 July 2017

Received in revised form: 13 July 2017

Accepted: 24 July 2017

Available online: 29 August 2017


JEL Classification: О11

Pages: 1438–1454

Khrustalev E.Yu. Central Economics and Mathematics Institute, RAS, Moscow, Russian Federation

Shramko O.G. District Inspectorate of Federal Tax Service No. 7, Kolomna, Moscow Oblast, Russian Federation

Subject The article is dedicated to identifying the areas of investment in the economy of subjects of the Russian Federation.
Objectives The purpose of the study is to develop new comprehensive and accurate tools to assess the potential of regional economic structure to determine the areas of investment.
Methods The proposed methodology and tools for its implementation rest on integrated use of the neural network method as applied to the region's economy.
Results For the purpose of integrated evaluation of investment efficiency, we developed a method that helps obtain quite accurate figures of investment policy efficiency in respect of each subject of the Russian Federation, using a limited number of initial indicators of economic activity in the region. This approach enables to determine the most appropriate areas of investing for socio-economic development of regions, to smooth the spatial polarization that currently tends to increase.
Conclusions and Relevance Our methodological approach makes it possible to assess the expediency of clustering the constituent entities of the Russian Federation and using the neural network modeling to perfect the State investment policy.

Keywords: economic factor, development, investment


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Vol. 16, Iss. 8
August 2017