Acta Univ. Agric. Silvic. Mendelianae Brun. 2017, 65(1), 299-310 | DOI: 10.11118/actaun201765010299

The Success of Economic Policies in Russia: Dependence on Crude Oil vs. Export Diversification

Elena Kuzmenko1, Lubo¹ Smutka1, Mikhail Pankov2, Nadezhda Efimova3
1 Department of Economics, Faculty of Economics and Management, Czech University of Life Sciences Prague; Kamycka 129, 165 21 Prague-6 Suchdol, Czech Republic
2 Department of Statistics and Econometrics, Faculty of Economics and Finance, St. Petersburg State University of Economics; Sadovaya street 21, 191023 St. Petersburg, Russian Federation
3 Department of Corporate Finance and Business Valuation, Faculty of Economics and Finance. St. Petersburg State University of Economics; Sadovaya street 21, 191023 St. Petersburg, Russian Federation

In the light of numerous debates around Russia's dependence on crude oil and the necessity to diversify the Russian economy, the present paper investigates how closely federal budget revenues, structure of export basket and GDP growth in Russia are tied up with crude oil prices (POIL) on the one hand and the real effective exchange rate of ruble (REER) on the other. The study covers the period from 2000:Q1 till 2014:Q4 and employs index analysis along with vector error correction model (VECM) based on Johansen co-integration technique. The calculated REER revealed its significant appreciation, that together with a high share of mineral products in total Russian exports points to Dutch disease presence. The constructed econometric models revealed the existence of long-run relationships among the analyzed indicators. Post-estimation tests proved the validity of the VECMs. According to the obtained results, in order to stimulate "non-oil" exports monetary authorities should depreciate national currency, whilst fiscal burden should be mild towards "non oil" producers. However, the observed dynamics of macroeconomic indicators points to the fact that the Russian economy is still substantially influenced by POIL and this influence is much more stronger than it is exerted by fiscal and monetary regulators. It allows us to conclude that crude oil will continue to play, at least in foreseeable future, a dominant role in further development of the Russian economy.

Keywords: Russia, GDP, fiscal revenues, crude oil price, REER, VECM, co-integration
Grants and funding:

This article was prepared on the materials of the research project "Is there any possibility for functional co-operation of the post-soviet countries?" performed within the internal grant No. 20161014, provided by the Internal Grant Agency of the Faculty of Economics and Management, Czech University of Life Sciences Prague.

Prepublished online: February 28, 2017; Published: March 1, 2017  Show citation

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Kuzmenko, E., Smutka, L., Pankov, M., & Efimova, N. (2017). The Success of Economic Policies in Russia: Dependence on Crude Oil vs. Export Diversification. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 65(1), 299-310. doi: 10.11118/actaun201765010299
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    References

    1. ALL-RUSSIAN MARKET RESEARCH INSTITUTE. Foreign exchange policy and the exchange rate performance. [Online]. Available at: http://www.afrocom.ru/en/russia_outlook/economy [Accessed: 2015, August 8].
    2. BANNIKOV, V. 2006. Vector autoregressive models and correction of the regression residuals (Eviews) [In Russian: Vektornye modeli avtoregressii i korrekcii regressionnyh ostatkov (Eviews)]. Prikladnaya ekonometrika, 3: 96-129.
    3. BAUM, C. F. 2013. VAR, SVAR and VECM models. Materials for lecture EC 823: Applied Econometrics. Boston College. [Online]. Available at: http://fmwww.bc.edu/EC-C/S2013/823/EC823.S2013.nn10.slides.pdf [Accessed: 2015, August 18].
    4. BLANCHARD, O. and PEROTTI, R. 2002. An Empirical Characterization of the Dynamic Effects of Changes in Government Spending and Taxes on Output. Quarterly Journal of Economics, 107(4): 1329 - 1368. DOI: 10.1162/003355302320935043 Go to original source...
    5. BORDOFF, J. and HOUSER, T. 2014. American gas to the rescue? The impact of US LNG exports on European security and Russian foreign policy. Center on Global Energy Policy and Columbia SIPA. [Online]. Available at: http://energypolicy.columbia.edu/sites/default/files/energy/CGEP_American%20Gas%20to%20the%20Rescue%3F.pdf [Accessed: 2015, August 15].
    6. ENGLE, R. F. and GRANGER, W. J. 1987. Co-integration and error correction: representation, estimation, and testing. Econometrica: journal of the Econometric Society, 55(2): 251 - 276. DOI: 10.2307/1913236 Go to original source...
    7. FEDERAL STATE STATISTICS SERVICE. c1999 - 2016. Official Statistic [in Russian: Официальная статистика]. [Online]. Available at: http://www.gks.ru/wps/wcm/connect/rosstat_main/rosstat/ru/statistics/accounts/# [Accessed: 2015, August 13].
    8. GIORDANO, R., MOMIGLIANO, N. S. and PEROTTI, R. 2008. The effects of fiscal policy in Italy: Evidence from a VAR model. European Journal of Political Economy, 23: 707 - 733. DOI: 10.1016/j.ejpoleco.2006.10.005 Go to original source...
    9. HYLLBERG, S. et al. 1990. Seasonal integration and cointegration. Journal of econometrics, 44(1): 215 - 238. DOI: 10.1016/0304-4076(90)90080-D Go to original source...
    10. INTERNATIONAL MONETARRY FUND. 2015. IMF Data: International Financial Statistic of IMF. [Online]. Available at: https://www.imf.org/external/data.htm [Accessed: 2015, August 13].
    11. JOHANSEN, S. 1988. Statistical analysis of cointegration vectors. Journal of economic dynamics and control, 12(2): 231 - 254. DOI: 10.1016/0165-1889(88)90041-3 Go to original source...
    12. JOHANSEN, S. 1995. Likelihood-based inference in cointegrated vector autoregressive models. OUP Catalogue. Oxford University Press. Go to original source...
    13. JUSELIUS, K. 2014. The Co-integrated VAR Model: Methodology and Applications. Oxford University Press.
    14. KANTOROVICH, G. 2003. Time series analysis (a course of lectures) [In Russian: Analiz vremennyh ryadov (kurs lekciy)]. Moskva: Ekonomicheskiy zhurnal Vysshey shkoly ekonomiki.
    15. KILIAN, L. 2001. Impulse Response Analysis in Vector Autoregressions with Unknown Lag Order. Journal of Forecasting, 20: 161-179. DOI: 10.1002/1099-131X(200104)20:33.0.CO;2-X Go to original source...
    16. KOÈENDA, E. and CERNÝ, A. 2007. Elements of Time Series Econometrics: An Applied Approach, Praha: Karolinum Press, Charles University.
    17. KUDRIN, A. 2006. The real effective course of rouble: the problems of growth [In Russian: Realniy effektivniy kurs rublya: problemy rosta]. Voprosy ekonomiki, 10: 4-18. Go to original source...
    18. KUISMANEN, M. and KÄMPPI, V. 2010. The Effects of Fiscal Policy on Economic Activity in Finland. Economic Modeling, 27(5): 1315 - 1323. DOI: 10.1016/j.econmod.2010.01.010 Go to original source...
    19. KUWORNU, J. K. M. 2012. Effect of Macroeconomic Variables on the Ghanaian Stock Market Returns: A Co-integration Analysis. Agris on-line Papers in Economics and Informatics, 4(2): 15 - 26. [Online]. Available at: http://online.agris.cz/files/2012/agris_on-line_2012_2.pdf [Accessed: 2015, August 8].
    20. LÜTKEPOHL, H. and KRÄTZIG, M. 2004. Applied Time Series Econometrics. Cambridge: Cambridge University Press. Go to original source...
    21. MAITAH, M., HAYAT, A., MALEC, K. and ELDEEB, O. 2014. The impact of foreign direct investments on employment in the Czech Republic. Reserach Journal of Applied Sciences, 9(12): 1001 - 1008.
    22. MAITAH, M., KUZMENKO, E. and SMUTKA, L. 2016. Real Effective Exchange Rate of Rouble and Competitiveness of Russian Agrarian Producers. Economies, 4(3): 12. DOI: 10.3390/economies4030012 Go to original source...
    23. MAITAH, M., SALEEM, N., MALEC, K, BOUBAKER, M. and GOUDA, S. 2015. Economic value added and stock market development in Egypt. Asian Social Science, 11(3): 126 - 134. Go to original source...
    24. MAITAH, M., SMUTKA, L., PULKRÁBEK, J., BENE©OVÁ, I. and BELOVÁ, A. 2013. Sugar production and consumption in Egypt in 1995 - 2009. Listy Cukrovarnické a Øepaøské, 129(9 - 10): 300 - 304.
    25. BANKK OF MOSCOW. Moscow Interbank Currency Exchange. [Online]. Available at: https://www.micex.ru/marketdata/quotes?group=currency_selt&data_type=history/ [Accessed: 2015, August 15].
    26. NELSON, C. R. and KANG, H. 1984. Pitfalls in the Use of Time as an Explanatory Variable in Regression. Journal of Business & Economic Statistics, 2(1): 73 - 82. Go to original source...
    27. PANILOV, M. 2009. Calculation and the analysis of the real effective rouble exchange rate dynamics [In Russian: Raschet i analiz dinamiki realnogo effektivnogo kursa rublya]. Audit i finansoviy analiz, 2 [Online]. Available at: http://www.auditfin.com/fin/2009/2/Panilov/Panilov%20.pdf [Accessed: 2015, August 13].
    28. POLTEROVICH, V., POPOV, V. and TONIS, A. 2008. Mechanisms of resource curse, economic policy and growth. Working Paper WP/2008/000. Moscow: New Economic School, 34. [Online]. Available at: http://mpra.ub.uni-muenchen.de/20570/ [Accessed: 2015, August 5]. Go to original source...
    29. RAUTAVA, J. 2002. The role of oil prices and the real exchange rate in Russia's economy. BOFIT Discussion Papers, No. 3. [Online]. Available at: http://www.suomenpankki.fi/pdf/103007.pdf [Accessed: 2015, August 5]. Go to original source...
    30. RUMÁNKOVÁ, L. 2012. Examination of existence of the law of one price at Czech meat markets. Agris on-line Papers in Economics and Informatics, 4(1): 39 - 47.
    31. SIMS, C. A. 1980. Macroeconomics and Reality. Econometrica, 48(1): 1 - 48. DOI: 10.2307/1912017 Go to original source...
    32. STATBUREAU. © 2007 - 2016. Eurozone Inflation Rate at 2015. [Online]. Available at: https://www.statbureau.org/ru/eurozone/inflation/2015 [Accessed: 2015, August 14].
    33. STATBUREAU. © 2007 - 2016. Inflation rate in Russia. [Online]. Available at: https://www.statbureau.org/en/russia/inflation [Accessed: 2015, August 14].
    34. SUKATI, M. 2013. Cointegration Analysis of Oil Prices and Consumer Price Index in South Africa using STATA Software. MPRA Paper 49797. Munich: University Library of Munich.
    35. THE FEDERAL TREASURY OF RUSSIA. [Online]. Available at: http://datamarts.roskazna.ru/index.php/2013-razdely/dokhody [Accessed: 2015, August 12].
    36. WELFE, W. 2013. Macroeconomic models. Vol. 47 of the series Advanced studies in Theoretical and Applied Econometrics. Springer-Verlag Berlin Heidelberg. Go to original source...
    37. ZIVOT, E. and WANG, J. 2007. Modelling Financial Time Series with S-PLUS, Second Edition, Springer Science & Business Media.

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