Improving the effectiveness of Russia’s investment and industrial policy

Publication type Article
Status Published
Occupation: Associate Professor at the Department of Economics
Affiliation: Plekhanov Russian University of Economics
Address: Moscow, Russian Federation
Occupation: Professor; Department of Mathematics and Statistics, Faculty of Natural Sciences
Affiliation: Regina University, Canada
Address: Canada
Occupation: Expert
Affiliation: All-Russia People’s Front in the Republic of Bashkortostan
Address: Russian Federation
Occupation: Department Director
Affiliation: Department of Industry, Entrepreneurship, Environmental Management, Tourism and Information Technologies of the Republic of Bashkortostan Government
Address: Russian Federation
Occupation: Principal Scientific Researcher
Affiliation: Institute of Social and Economic Research of the Russian Academy of Sciences, Ufa Federal Research Center RAS
Address: Russian Federation
Occupation: Director
Affiliation: Institute of Strategic Studies of the Republic of Bashkortostan
Address: Russian Federation
Journal nameEkonomika i matematicheskie metody
EditionVolume 56 Issue 1

sanction pressure on Russian enterprises and taking into account the key role of industry in providing national economic security, the question of improving the efficiency of the country’s investment-industrial policy has become topical. The aim of the article is to elaborate an economic-mathematical model that will make it possible to make quick and effective managerial decisions in Russia’s investment-industrial sphere. The article considers a multi-model based on three methods: dynamic programming, Cobb–Douglas production function, and interindustry balance. The hypothesis made during the empirical study of the possibility of constructing one production function for several Russian industries, was confirmed. That is why, in our case, based on the general Cobb–Douglas production function, production capacity (gross production output) of several sectors of the national industrial complex are evaluated objectively. The first and second models are based on data from, respectively, seven and six industries of Russia for 2011–2016. Dynamic programming makes it possible to form an optimal plan (securing a maximum possible additional gross production output) of distributing the limited public investment resources among the sectors of the national industrial complex. The maximum possible growth of Russian industries’ gross value added is determined by means of the interindustry balance method. The study is the scientific basis for updating the provisions of the Russian investment and industrial policy.

Keywordsinvestment-industrial policy, dynamic programing, production function, labor, capital, resource productivity, clustering, interindustry balance, output, gross value added.
Publication date20.03.2020
Number of characters28681
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1. Afanasyev A.A., Ponomareva O.S. (2014). The Aggregate Production Function of Rus-sian Economy in 1990–2012. Economics and Mathematical Methods, 4, 21–33 (in Russian).

2. Bellman R., Dreyfus S. (1965). Applied Dynamic Programming. Moskow: Nauka (in Russian).

3. Berezinskaya O. (2016). Investment Break in the Russian Economy: Structural Character-istics and Turnaround Perspectives. Economic Polic, 3, 30–45 (in Russian).

4. Cobb Ch., Douglas P. (1928). A Theory of Production. American Economic Review, 18, 139–165.

5. Evstratov A.A., Kalinin A.M., Parsegov S.G. (2016). The Use of Input–Output Tables to Forecast the Effects of Demand Stimulation State Policy. Studies on Russian Economic Devel-opment, 1, 8–17 (in Russian).

6. Fal’tsman V.K. (2016). Problems of Structural, Investment, and Innovation Policy in the Crisis Period. Studies on Russian Economic Development, 4, 14–23 (in Russian).

7. Garipov F.N., Gizatullin Kh.N., Garipova Z.F. (2016). The Main Directions to Over-come the Challenges of the 21st Century in Agriculture. Economy of Region, 1, 105–116 (in Russian).

8. Gil’mundinov V.M. (2017). Åstimation of the Production Function with the Variable Uti-lization of Capital Assets in the Russian Economy. Studies on Russian Economic Development, 4, 34–43 (in Russian).

9. Glazyev S.Yu. (2015). On the External and Internal Threats to Economic Security of Rus-sia in Conditions of the American Aggression. Management and Business Administration, 1, 4–20 (in Russian).

10. Gorbatkov S.A., Polupanov D.V., Farkhieva S.A., Korotneva M.V. (2012). Economet-rics. Ufa: RITS BashGU (in Russian).

11. Grinberg R.S., Akhunov R.R., Volodin A.I., Gubarev R.V., Dzyuba E.I. (2018). Per-formance-Based Pay — a New (Mixed) Payment Scheme for Russian Civil Servants. Economic and Social Changes: Facts, Trends, Forecast, 6, 163–183 (in Russian).

12. Ivanter I.I., Porfir’ev B.N., Shirov A.A., Shokin I.N. (2017). Basis of Structural-Investment Policy in Modern Conditions of Russian Economy. The Bulletin of the Financial University, 1, 6–15 (in Russian).

13. Kleyner G.B. (2017). System Modernization of Domestic Enterprises: Theoretical Back-ground, Motives, Principles. Economy of Region, 1, 13–24 (in Russian).

14. Kolodnaya E.M. (2014). Mathematical Programming. Minsk: UO VGKS (in Russian).

15. Makarov V.L., Aivazyan S.H., Afanasiev M.Yu., Bakhtizin A.R., Nanavyan A.M. (2014). The Estimation of the Regions’ Efficiency of The Russian Federation Including the Intel-lectual Capital, the Characteristics of Readiness for Innovation, Level of Well-Being, and Quali-ty of life. Economy of Region, 4, 9–30 (in Russian).

16. Manturov D.V., Nikitin G.S., Os’makov V.S. (2017). Government Regulation of Russian Industry in the 2010s. Public Administration Issues, 1, 50–70 (in Russian).

17. Okrepilov V.V., Makarov V.L., Bakhtizin A.R., Kuz’mina S.N. (2015). Application of Supercomputer Technologies for Simulation of Socio-Economic Systems. Economy of Region, 2, 301–313 (in Russian).

18. Savitskaya G.V. (2003). Economic Analysis. Moscow: Novoe znanie (in Russian).

19. Suvorov N.V. (2015). Ñurrent Trends and Problems of Improving Model Tools of Macro-economic Analysis. Studies on Russian Economic Development, 5, 25–39 (in Russian).

20. Svetunkov S.G. (2016). The Possibility Using the Power Production Function of Complex Variable for Economic Forecasting. Economy of Region, 3, 966–976 (in Russian).

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