|Generate QR code
Open Access
Subscription Access
Econometric estimation of the impact of oil prices shock on the Russian economy in VECM model
https://doi.org/10.32609/0042-8736-2017-10-27-49
Abstract
The paper estimates terms of trade shock influence on the Russian output, gross investment and consumption using VECM model with exogenous variables. As a proxy for terms of trade we use oil prices. Empirical results demonstrate that a permanent oil price increase led to a short-run economic boom followed by a negative contribution to economic growth.
Keywords
terms of trade,
oil prices,
economic growth,
Russian economy,
GDP,
consumption,
investment,
vector error correction model
JEL: С22; C51; D58; E32; E52; F41
About the Author
A. Polbin
Gaidar Institute for Economic Policy; Russian Presidential Academy of National Economy and Public Administration
Russian Federation
Russian Federation
References
1. Ayvazyan S. A., Brodskiy B. E. (2006). Macroeconometric modeling: modern trends, problems, an example of the econometric model of the Russian economy. Applied Econometrics, Vol. 2, No. 2, pp. 85—111. (In Russian).
2. Ayvazyan S. A., Brodskiy B.E., Sandoyan E.M., Voskanyan M.A., Manukyan D.E. (2013). Macroeconometric modeling of Russian and Armenian economies. II. Aggregated macroeconometric models of the national economies of Russia and Armenia. Applied Econometrics, Vol. 31, No. 3, pp. 7—31. (In Russian).
3. Vashchelyuk N. V., Polbin A. V., Trunin P. V. (2015). Estimation of the monetary policy shock’s influence on the Russian economy. HSE Economic Journal, No. 2, pp. 169—198. (In Russian).
4. Deryugina E., Ponomarenko A. (2015). A large Bayesian vector autoregression model for Russia. Moscow: Bank of Russia. (In Russian).
5. Drobyshevskiy S., Polbin A. (2015). Decomposition of the structural shocks contribution to the Russian macroeconomic indicators dynamics on the basis of the DSGE model. Ekonomicheskaya Politika, No. 2, pp. 20—42. (In ¬Russian).
6. Dubovskij D. L., Kofanov D. A., Sosunov K. A. (2015). Dating of the Russian business cycle. HSE Economic Journal, Vol. 19, No. 4, pp. 554—575. (In Russian).
7. Zamulin O. A. (2016). Russia in 2015: A supply-side recession. Journal of the New Economic Association, Vol. 29, No. 1, pp. 181—185. (In Russian).
8. Idrisov G., Sinelnikov-Murylev S. (2014). Forming sources of long-run growth: How to understand them? Voprosy Ekonomiki, No. 3, pp. 4—20. (In Russian).
9. Kudrin A., Gurvich E. (2014). A new growth model for the Russian economy. Voprosy Ekonomiki, No. 12, pp. 4—36. (In Russian).
10. Lomivorotov R. V. (2015). Bayesian estimation of monetary policy in Russia. Applied Econometrics, Vol. 38, No. 2, pp. 41—63. (In Russian).
11. Mau V. (2017). The lessons of stabilization and prospects of growth: Russia’s economic policy in 2016. Voprosy Ekonomiki, No. 2, pp. 5—29. (In Russian).
12. Malakhovskaya O. (2016). DSGE-based forecasting: What should our perspective be? Voprosy Ekonomiki, No. 12, pp. 129—146. (In Russian).
13. Pestova A. (2017). Monetary policy regimes in Russia: Guidelines for further quantitative studies. Voprosy Ekonomiki, No. 4, pp. 38—60. (In Russian).
14. Pestova A., Mamonov M. (2016). Estimating the influence of different shocks on macroeconomic indicators and developing conditional forecasts on the basis of BVAR model for the Russian economy. Ekonomicheskaya Politika, No. 4, pp. 56—92. (In Russian).
15. Polbin A. V. (2014). Econometric estimation of a structural macroeconomic model for the Russian economy. Applied Econometrics, No. 1, pp. 3—29. (In Russian).
16. Polbin A. V., Skrobotov A. A. (2016). Testing for structural breaks in the long-run growth rate of the Russian economy. HSE Economic Journal, Vol. 20, No. 4, pp. 588—623. (In Russian).
17. Polbin A. (2017). Modeling the real ruble exchange rate under monetary policy regime change. Voprosy Ekonomiki, No. 4, pp. 61—78. (In Russian).
18. Sinelnikov-Murylev S., Drobyshevsky S., Kazakova M. (2014). Decomposition of Russian GDP growth rates in 1999—2014. Ekonomicheskaya Politika, No. 5, pp. 7—37. (In Russian).
19. Shulgin A. G. (2014). How much monetary policy rules do we need to estimate DSGE model for Russia? Applied Econometrics, Vol. 36, No. 4, pp. 3—31. (In Russian).
20. Aguiar M., Gopinath G. (2007). Emerging market business cycles: The cycle is the trend. Journal of Political Economy, Vol. 115, No. 1, pp. 69-102.
21. Beck R., Kamps A., Mileva E. (2007). Long-term growth prospects for the Russian economy. European Central Bank Occasional Paper Series, No. 58.
22. Blanchard O. J., Kahn C. M. (1980). The solution of linear difference models under rational expectations. Econometrica, Vol. 48, No. 5, pp. 1305-1312.
23. Bruno M., Sachs J. (1982). Energy and resource allocation: A dynamic model of the “Dutch disease”. Review of Economic Studies, 1982, Vol. 49, No. 5, pp. 845-859.
24. Canova F. (2007). Methods for applied macroeconomic research. Princeton University Press.
25. Engle R. F., Granger C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, Vol. 55, No. 2, pp. 251-276.
26. Esfahani H. S., Mohaddes K., Pesaran M. H. (2014). An empirical growth model for major oil exporters. Journal of Applied Econometrics, Vol. 29, No. 1, pp. 1-21.
27. Garratt A., Lee K., Pesaran M. H., Shin Y. (2012). Global and national macroeconometric modelling: a longrun structural approach. Oxford University Press.
28. Gospodinov N., Herrera A., Pesavento E. (2013). Unit roots, cointegration and pretesting in VAR models. Advances in Econometrics, Vol. 32, pp. 81-115.
29. Granger C. W. (1981). Some properties of time series data and their use in econometric model specification. Journal of Econometrics, Vol. 16. No. 1, pp. 121-130.
30. Gylfason T. (2001). Natural resources, education, and economic development. European Economic Review, Vol. 45, No. 4, pp. 847-859.
31. Kilian L. (2009) Not all oil price shocks are alike: Disentangling demand and supply shocks in the crude oil market. American Economic Review, Vol. 99, No. 3, pp. 1053-1069.
32. King R., Plosser C., Stock J., Watson M. (1991). Stochastic trends and economic fluctuations. American Economic Review, Vol. 81, No. 4, pp. 819-40.
33. Kuboniwa M. (2014). A comparative analysis of the impact of oil prices on oil-rich emerging economies in the Pacific Rim. Journal of Comparative Economics, Vol. 42, No. 2, pp. 328-339.
34. Lucas R. E. (1976). Econometric policy evaluation: A critique. Carnegie Rochester Conference Series on Public Policy, Vol. 1, pp. 19-46.
35. MacKinnon J. (2010). Critical values for co-integration tests. Queen’s Economics Department Working Paper, No. 1227.
36. Mehlum H., Moene K., Torvik R. (2006). Institutions and the resource curse. Economic Journal, Vol. 116, No. 508, pp. 1-20.
37. Mendoza E. G. (1995). The terms of trade, the real exchange rate, and economic fluctuations. International Economic Review, Vol. 36, No. 1, pp. 101-137.
38. Phillips P. C. B. (1998). Impulse response and forecast error variance asymptotics in nonstationary VARs. Journal of Econometrics, Vol. 83, No. 1, pp. 21-56.
39. Ramey V. A., Shapiro M. D. (2001). Displaced capital: A study of aerospace plant closings. Journal of Political Economy, Vol. 109, No. 5, pp. 958-992.
40. Rautava J. (2004). The role of oil prices and the real exchange rate in Russia’s economy - a cointegration approach. Journal of Comparative Economics, Vol. 32, No. 2, pp. 315-327.
41. Rautava J. (2013). Oil prices, excess uncertainty and trend growth. Focus on European Economic Integration, No. 4, pp. 77-87.
42. Sachs J. D., Warner A. M. (1995). Natural resource abundance and economic growth. NBER Working Paper, No. 5398.
43. Sachs J. D., Warner A. M. (1997). Fundamental sources of long-run growth. American Economic Review, Vol. 87, No. 2, pp. 184-188.
44. Schmitt-Grohé S., Uribe M. (2011). Business cycles with a common trend in neutral and investment-specific productivity. Review of Economic Dynamics, Vol. 14, No. 1, pp. 122-135.
45. Sims C. A., Zha T. (1999). Error bands for impulse responses. Econometrica, Vol. 67, No. 5, pp. 1113-1155.
46. Solow R. M. (1956). A contribution to the theory of economic growth. Quarterly Journal of Economics, Vol. 70, No. 1, pp. 65-94.
47. Stock J. H., Watson M. W. (1993). A simple estimator of cointegrating vectors in higher order integrated systems. Econometrica, Vol. 61, No. 4, pp. 783-820.
48. Whelan K. (2002). A guide to US chain aggregated NIPA data. Review of Income and Wealth, Vol. 48, No. 2, pp. 217-233.
Review
For citations:
Polbin A. Econometric estimation of the impact of oil prices shock on the Russian economy in VECM model. Voprosy Ekonomiki. 2017;(10):27-49. (In Russ.) https://doi.org/10.32609/0042-8736-2017-10-27-49
Views:
1175
Email this article 
