Русский
EnglishCite this article as:
Tsypin A. P. Econometric Modelling of Influence of Factors on GDP of the Post-Soviet Countries. Izv. Saratov Univ., Economics. Management. Law, 2018, vol. 18, iss. 4, pp. 407-412. DOI: https://doi.org/10.18500/1994-2540-2018-18-4-407-412
Econometric Modelling of Influence of Factors on GDP of the Post-Soviet Countries
Introduction. The processes proceeding in turbulent economy demand continuous monitoring and the analysis, it is possible to refer to those safely formation of gross domestic product in the Post-Soviet countries. A set of external and internal factors exert impact on this formation of this indicator, it is possible to measure this influence perhaps having resorted to econometric methods.
Theoretical analysis. As a method of identification and measurement of dependence between variables the correlation and regression analysis is used, also in the course of the research we addressed tabular and graphic methods.
Empirical analysis. The carried-out analysis of reaction of GDP on political and socio-economic factors, allows us to draw a number of conclusions: first, it is possible to state coinciding reaction of economy of the considered countries, on the crisis situations caused by political decisions (collapse of the USSR) or economic factors (world crises of 1998 and 2009); secondly, drift of set of factors of the Post-Soviet countries exerting impact on GDP (per capita) is observed; thirdly, the more time passes from the beginning of market reforms, the values of macroeconomic indicators of the countries which entered the European Union differ from other Post-Soviet countries stronger; fourthly, in all four time slices, agriculture makes the constraining impact on economic growth, and the farther from 1991, the influence of such factor as the index of human potential is shown stronger that indirectly indicates preparation for transition to digital economy.
Results. Econometric modeling of difficult economic systems, in the conditions of turbulent economy is rather difficult task and it is necessary to approach it with extra care, considering all features of the Post-Soviet countries. In the research we made an attempt to create such econometric models, the received results can serve as a starting point in further researches, and the revealed regularities make a certain contribution to the theory of transitional economies.
1. Kartayev F. S. Econometric Simulation of the Correlation between Rouble Exchange Rate and Russian GDP Dynamics. Vestnik Moskovskogo universiteta. Ser. 6. Ehkonomika [The Moscow University Herald. Ser. 6. Economics], 2009, no. 2, pp. 57–67 (in Russian).
2. Lisin V. S. Problemy modelirovaniya vosproizvodstva VVP Rossii [Problems of modeling of reproduction of GDP of Russia]. Moscow, TEIS Publ., 2004. 232 p. (in Russian).
3. Mansurova T. G. Modeling of Dependence of GDP Growth on Income Gained from Export of Hydrocarbons. In: Nauka, tekhnologii i kommunikacii v sovremennom obshchestve [Science, technologies and communications in modern society. Materials of the Republ. sci. and pract. conf.]. Naberezhnye Chelny, 2008, pp. 124–127 (in Russian).
4. Filimonenko I. V. The Modeling of the Relationship between GDP Growth and Structural Change of Employment in the Economy of Russia. Vestnik Novosibirskogo gosudarstvennogo universiteta. Ser. Social’no-ekonomicheskie nauki [Bulletin of Novosibirsk State University. Ser. Social and economic sciences], 2011, vol. 11, iss. 1, pp. 16–25 (in Russian).
5. Shabelnikova E. V. Econometric Modeling as a Mean of the Depedence of GDP Value from the Size of Taxes on Production and Imports. Mezhdunarodnyi studencheskii nauchnyi vestnik [International Student’s Scientifi c Bulletin], 2017, no. 4–7, pp. 1111–1113 (in Russian).
6. Ayvazyan S. A., Brodskiy B. E., Sandoian E. M., Voskanian M. A., Manukian D. E. Macroeconometric Modeling of Economies of Russia and Armenia. Applied Econometrics, 2013, no. 3 (31), pp. 7–31 (in Russian).
7. Novikov M. M. Statistical Modeling and the Analysis of Tendencies of Macroeconomic Dynamics (on the example of GDP of Republic of Belarus). Bukhgalterskiy uchet i analiz [Accounting and the analysis], 2016, no. 8 (236), pp. 26–35 (in Russian).
8. Gisin V. B., Dzhagitian E. P. Scenario Modeling of Infl uence of Capital Adequacy Ratio on the Relation of Total Assets of the Banking Sectors to GDP of Member States of EEU. Ehkonomika i upravlenie: problemy, resheniya [Economy and management: problems, decisions], 2017, vol. 4, no. 3, pp. 59–63 (in Russian).
9. Hlopin D. A. Research GDP of Member Countries of EEU by Methods of Econometric Modeling. Nauchnye zapiski molodykh issledovatelei [Scientifi c notes of young researchers], 2014, no. 3, pp. 27–30 (in Russian).
10. Pobegayeva D. B. Econometric Modeling GDP Loudspeakers per capita BRICS Member Countries. Intellekt. Innovatsii. Investitsii [Intelligence. Innovations. Investments], 2016, no. 5, pp. 43–46 (in Russian).
11. Tsypin A. P. Statisticheskiy analiz transformatsii ekonomiki Rossii [Statistical analysis of transformation of economy of Russia]. Diss. Cand. Sci. (Econ.). Orenburg, 2005. 199 p. (in Russian).
12. World Bank Open Data. Available at: https://data.worldbank.org (accessed 12 September 2018).
13. Tsypin A. P., Faizova L. R. Statistical Research of Infl uence of Factors on Dynamics of Macroeconomic Indicators of Ex-member of the Soviet Union. Azimut nauchnykh issledovaniy: ekonomika i upravlenie [Azimuth of scientifi c research: economy and management], 2017, vol. 6, no. 4 (21), pp. 259–263 (in Russian).
14. Somov V. L., Tolmachev M. N. Methods for Determining the Coeffi cients of Weight of Dynamic Integral Indicators. Voprosy statistiki, 2017, no. 6, pp. 74–79 (in Russian).
