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Performance Evaluation of the Mechanisms Strengthening the State Sovereignty of Russia

https://doi.org/10.26794/2587-5671-2018-22-5-6-26

Abstract

In this article, the authors present a quantitative assessment of the consequences of a number of government decisions aimed at achieving accelerated economic growth, namely: 1) diversifcation of the economy; 2) reduction of the differentiation of regions; 3) increase of social protection of the population; 4) stimulation of the domestic demand. The authors used for calculations the modifed model complex developed in CEMI RAS. The complex includes a set of Computable General Equilibrium models (CGE models) and Agent-Based Models (ABMs). The author’s calculations showed, as compared with other industries, that the increase in fnancing of the sectors of the new economy leads for 7 years to the growth of GDP by 4.45 percentage points in relation to the basic version of the economy. We also established that due to tax preferences and differentiated investment policy in relation to the “problem” regions, it is possible to equalize the level of development of the subjects of the Russian Federation. The authors conclude that the process of inter-regional smoothing is time-consuming and a signifcant effect is possible after fve years from the beginning of the implementation of the relevant mechanisms. The results of the calculations showed that the increase in benefts as a whole leads to GDP growth and has a positive impact on the economic system. We also concluded that the reduction of the refnancing rate leads to an increase in GDP and lower inflation. With the help of the model complex, we calculated the influence of a number of illegal fnancial transactions on the main macro indicators. Quantitative assessment was carried out in three scenarios: 1) withdrawal of budget funds; 2) tax evasion by individuals and legal entities; 3) withdrawal of fnancial assets abroad. The unrealized GDP growth potential for the six years compared to the initial period was 11.107, 21.323, and 31.976 percentage points for the three scenarios, respectively. The calculations also show that almost any cash infusion into the real sector of the economy leads to GDP growth due to signifcant demonetization of the Russian economy.

About the Authors

V.  L.  Makarov
Central Economic and Mathematical Institute of the Russian Academy of Sciences, Moscow
Russian Federation
Dr. Sci. (Phys.­Math.), Academician of RAS, scientifc supervisor



A.  R. Bakhtizin
Central Economic and Mathematical Institute of the Russian Academy of Sciences, Moscow
Russian Federation
Dr. Sci. (Econ.), the corresponding member of RAS, Director



B.  R.  Khabriev
Central Economic and Mathematical Institute of the Russian Academy of Sciences, Moscow
Russian Federation
Manager for transaction support at LLC “RT­Development of Business”, a post­graduate student



References

1. Yakunin V.I., Bagdasaryan V.E., Sulakshin S.S. A trap: New technologies to combat Russian statehood. Moscow: Eksmo, Algoritm; 2010. 432 p. (In Russ.).

2. Yakunin V.I., Sulakshin S.S., Bagdasaryan V.E. et al. The national idea of Russia: My country must be, and must always be! In 6 vols. Moscow: Nauchnyi ekspert; 2012. 4440 p. (In Russ.).

3. Aganbegyan A.G. 25 years of new Russia. Economic and social level: Trampling on the spot. Ekonomicheskie strategii = Economic Strategies. 2018;20(1):6–21. (In Russ.).

4. Bakhtizin A.R. Agent­oriented models of the economy. Moscow: Ekonomika; 2008. 280 p. (In Russ.).

5. Makarov V.L., Bakhtizin A.R. Social modelling — a new computer breakthrough (agent­oriented models). Moscow: Ekonomika; 2013. 295 p. (In Russ.).

6. Makarov V.L., Bakhtizin A.R. Modern methods of forecasting the consequences of administrative decisions. Upravlencheskoe konsul’tirovanie = Administrative Consulting. 2015;(7):12–24. (In Russ.).

7. Makarov V.L., Losev A.A., Afanas’ev A.A. Computable simulation model for money circulation in the Russian economy. Ekonomika i matematicheskie metody = Economics and Mathematical Methods. 2011;47(1):3–27. (In Russ.).

8. Makarov V.L., Sushko E.D., Bakhtizin A.R. Situational modelling — the effective tool for strategic planning and management. Upravlencheskoe konsul’tirovanie = Administrative Consulting. 2016;(6):26–39. (In Russ.).

9. Makarov V.L., Bakhtizin A.R., Sulakshin S.S. The application of computable models in public administration. Moscow: Nauchnyi ekspert; 2007. 304 p. (In Russ.).

10. Harberger A. The incidence of the corporation income tax. Journal of Political Economy. 1962;70(3):215–240. DOI: 10.1086/258636

11. Scarf H. The computation of economic equilibria. New Haven, London: Yale University Press; 1984. 249 p.

12. Taylor L., ed. Socially relevant policy analysis: Structuralist computable general equilibrium models for the developing world. Cambridge, MA: The MIT Press; 1990. 389 p.

13. Dixon P.B., Jorgenson D.W., eds. Handbook of computable general equilibrium modelling. Vols. 1A, 1B. Oxford: North Holland; 2013.

14. Johansen L. A multi­sectoral study of economic growth. Amsterdam: North­Holland; 1960. 177 p. (Contributions to economic analysis. Vol. 21).

15. Berck P., Golan E., Smith B. Dynamic revenue analysis in California: An overview. State Tax Notes. 1996;11:1227–1237.

16. Thissen M. A classification of empirical CGE modelling. University of Groningen. SOM Research Report. 1998;(99C 01). URL: https://www.rug.nl/research/portal/fles/3182311/99c01.pdf (accessed 07.09.2018).

17. Burfsher M.E. Introduction to computable general equilibrium models. Cambridge: CUP Publ.; 2011. 368 p.

18. Coutts K., Gudgin G., Buchanan J. How the economics profession got it wrong on Brexit. Centre for Business Research. University of Cambridge. Working Paper. 2018;(493). URL: https://www.cbr.cam.ac.uk/fleadmin/user_upload/centre­for­business­research/downloads/working­papers/wp493.pdf (accessed 07.09.2018).

19. Aguiar A., Carrico C., Hertel T., Hussein Z., McDougall R., Narayanan B. Extending the GTAP framework for public procurement analysis. GTAP Working Paper. 2016;(82). URL: https://www.gtap.agecon.purdue.edu/resources/download/8351.pdf

20. Giesecke J.A., Madden J.R. Regional computable general equilibrium modelling. In: Handbook of computable general equilibrium modelling. Vol. 1A. Oxford: North Holland; 2013:379–475.

21. Dixon P.B., Rimmer M.T. Dynamic general and equilibrium modelling for forecasting and policy: A practical guide and documentation of MONASH. Amsterdam: Elsevier; 2002. 338 p. (Contributions to economic analysis. Vol. 256).

22. Peter M.W., Horridge J.M., Meagher G.A., Naqvi F., Parmenter B.R., Adams P.D. MONASH­MRF: A multisectoral, multi­regional model of the Australian economy. Melbourne: Centre of Policy Studies, Monash University; 2001.

23. Brooke A., Kendrick D., Meeraus A., Raman R. GAMS: A user’s guide. Washington, DC: GAMS Development Corp.; 1998. 262 p.

24. Rutherford T.F. Applied general equilibrium modelling with MPSGE as a GAMS subsystem: An overview of the modelling framework and syntax. Boulder: Department of Economics, University of Colorado; 1997. 49 p. URL: http://www.mpsge.org/mpsge/syntax.pdf (accessed 07.09.2018).

25. Harrison W., Pearson K. An introduction to GEMPACK. Melbourne: Center of Policy Studies and Impact Project, Monash University; 2000.

26. Bussieck M., Meeraus A. General algebraic modelling system (GAMS). In: Modelling languages in mathematical optimization. Dordrecht: Kluwer Academic Publ.; 2004:137–157. DOI: 10.1007/978–1–4613–0215–5_8.

27. Horridge M., Meeraus A., Pearson K., Rutherford T.F. Solution software for computable general equilibrium modelling. In: Handbook of computable general equilibrium modelling. Vol. 1B. Amsterdam: Elsevier; 2013:1331–1382.

28. Bakhtizin A.R., Kol’chugina A.V., Bukhval’d E.M. Ranking the subjects of the Russian Federation based on their potential and rates of socio­economic development. Region: ekonomika i sotsiologiya = Region: Economics and Sociology. 2016;(2):3–22. (In Russ.). DOI: 10.15372/REG20160201

29. Bakhtizin A.R., Bukhval’d E.M., Kol’chugina A.V. Economic differentiation of regions of Russia: New estimates and patterns. ETAP: ekonomicheskaya teoriya, analiz, praktika = ETAP: Economic Theory, Analysis, and Practice. 2017;(1):41–56. (In Russ.).

30. Valentei S. D., Bakhtizin A. R., Kol’chugina A.V. Trends of economic development of the subjects of the Russian Federation in conditions of a decline in oil prices and economic sanctions. Federalizm = Federalism. 2017;(3):113–132. (In Russ.).

31. Valentei S.D., Bukhval’d E.M., Kol’chugina A.V., Bakhtizin A.R. Grouping of regions of federal districts of the Russian Federation by development trends. Federalizm = Federalism. 2015;(4):131–138. (In Russ.).

32. Abe K., Wilson J.S. Governance, corruption, and trade in the Asia Pacifc Region. The World Bank. Policy Research Working Paper. 2008;(4731). URL: https://openknowledge.worldbank.org/bitstream/handle/10986/6961/WPS 4731.pdf?sequence=1&isAllowed=y (accessed 04.09.2018).

33. Helble M., Shepherd B., Wilson J.S. Transparency and trade facilitation in the Asia Pacifc: Estimating the gains from reform. Washington, DC: The World Bank; 2007. 84 p. URL: http://siteresources.worldbank.org/INTRES/Resources/Transparency­APEC­Study­Fin.pdf (accessed 04.09.2018).


Review

For citations:


Makarov V.L., Bakhtizin A.R., Khabriev B.R. Performance Evaluation of the Mechanisms Strengthening the State Sovereignty of Russia. Finance: Theory and Practice. 2018;22(5):6-26. (In Russ.) https://doi.org/10.26794/2587-5671-2018-22-5-6-26

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