Macroeconomic Effects of Oil Price Fluctuations in Colombia
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Resumen
This research aims to study the effects of oil price changes on the Colombian economy during 2001:Q1 to 2016:Q2. A structural vector auto-regression model in the spirit of Blanchard and Galí (2010) is estimated under a recursive identification scheme, where unexpected oil price variations are exogenous relative to the contemporaneous values of the remaining variables. Drawing on impulse-response estimates, a 10% increase in the oil price generates the following accumulated orthogonalized responses: i) a contemporaneous 0.4% increase in GDP growth, later on the effect reaches its maximum in the first quarter (1.7% increase) and starts to decay after two quarters; ii) a contemporaneous 1.2% decrease in unemployment, then the effect remains slightly negative and reaches its maximum after ten quarters (5.1% decrease); iii) a contemporaneous 0.9% decrease in inflation, followed by an 0.2% increase by quarter three, and thereafter the effect remains slightly negative.
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Referencias
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Kwiatkowski, D., Phillips, P., Schmidt, P. & Shin, Y. (1992). Testing the null hypothesis of stationarity against the alternative of unit root: How sure are we that economic time series have unit root?. Journal of Econometrics, 54, 159- 178.
Lorde, T., Jackman, M., Thomas, C. (2009). The macroeconomic effects of oil price fluctuations on a small open oil-producing country: The case of Trinidad and Tobago. Energy Policy, 37(7), 2708–2716
Lütkepohl, H., Krätzig, M. (2005). Applied Time Series Econometrics. Cambridge, UK: Cambridge University Press, pp. 210-215.
Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Berlin, Germany: Springer, pp. 30-367.
Lütkepohl, H. (2011). Vector Autorregresive Models. Woking Paper ECO-2011/30. European University Institute.
Newey, W., West, K. (1994). Automatic Lag Selection in Covariance Matrix Estimation. Review of Economic Studies, 61(4), 631-653.
Sims, C. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1-48.
Sims, C. (1986). Are Forecasting Models Usable for Policy Analysis?. Quarterly Review of the Federal Reserve of Minneapolis, 10(1), 1-16.
The World Bank. (2016). World Development Indicators. Sourced from: http://data.worldbank.org/data-catalog/world-development-indicators. Accessed on October 16th, 2016.
Rotemberg, J., Woodford, M. (1996). Imperfect Competition and the Effects of Energy Price Increases on Economic Activity. Journal of Money, Credit and Banking, 28(4), 549-577.
U.S. Energy Information Administration. (2016). Country Analysis Brief: Colombia.
Baker Hughes. (2016). International Rig Count. Sourced from: http://phx.corporate- ir.net/phoenix.zhtml?c=79687&p=irol-rigcountsintl. Accessed on November 26th, 2016.
Blanchard, O. & Galí, J. (2010). The Macroeconomic Effects of Oil Price Shocks. Why are the 2000s so different from 1970s?. In Gali, J. & Gertler, M. (Eds.), International Dimensions of Monetary Policy (pp. 373-421). National Bureau of Economic Research. University of Chicago Press.
Banco de la República de Colombia. (2016). Statistics. Sourced from: http://www.banrep.gov.co/en/data-and-statistics. Accessed on October 16th, 2016.
BP. (2016). BP Statistical Review of World Energy – data workbook. Sourced from: http://www.bp.com/en/global/corporate/energy-economics/statistical-review-of- world-energy/downloads.html. Accessed on October 16th, 2016.
Ecopetrol S.A. (2016). Reporte Integrado de Gestión Sostenible 2015. Sourced from: www.ecopetrol.com.co/documentos/Ecopetrol_IA_2015_29marzo.pdf. Accessed on September 20th, 2016.
Farzanegan, M.R. & Markwardt, G. (2009). The effects of oil price shocks on the Iranian economy. Energy Economics, 31(1), 134-151.
Hamilton, J. (1983). .Oil and the Macroeconomy since World War II. Journal of Political Economy, 91(2), 228-248
Hamilton, J. (1996). This is What Happened to the Oil Price Macro-economy Relationship. Journal of Monetary Economics, 38(2), 215-220.
International Monetary Fund. (2016). Global price of WTI Crude. Sourced from: https://fred.stlouisfed.org/series/POILWTIUSDQ. Accesed on October 16th, 2016.
Kilian, L. (2013). Structural Vector Autoregressions. In Hashimzade, N., & Thornton, M. (Eds.), Handbook of Research Methods and Applications in Empirical Macroeconomics (pp. 515-554). Edward Elgar Publishing Limited.
Kilian, L. (2009). Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market. American Economic Review, 99(3), 1053-1069.
Kwiatkowski, D., Phillips, P., Schmidt, P. & Shin, Y. (1992). Testing the null hypothesis of stationarity against the alternative of unit root: How sure are we that economic time series have unit root?. Journal of Econometrics, 54, 159- 178.
Lorde, T., Jackman, M., Thomas, C. (2009). The macroeconomic effects of oil price fluctuations on a small open oil-producing country: The case of Trinidad and Tobago. Energy Policy, 37(7), 2708–2716
Lütkepohl, H., Krätzig, M. (2005). Applied Time Series Econometrics. Cambridge, UK: Cambridge University Press, pp. 210-215.
Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Berlin, Germany: Springer, pp. 30-367.
Lütkepohl, H. (2011). Vector Autorregresive Models. Woking Paper ECO-2011/30. European University Institute.
Newey, W., West, K. (1994). Automatic Lag Selection in Covariance Matrix Estimation. Review of Economic Studies, 61(4), 631-653.
Sims, C. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1-48.
Sims, C. (1986). Are Forecasting Models Usable for Policy Analysis?. Quarterly Review of the Federal Reserve of Minneapolis, 10(1), 1-16.
The World Bank. (2016). World Development Indicators. Sourced from: http://data.worldbank.org/data-catalog/world-development-indicators. Accessed on October 16th, 2016.
Rotemberg, J., Woodford, M. (1996). Imperfect Competition and the Effects of Energy Price Increases on Economic Activity. Journal of Money, Credit and Banking, 28(4), 549-577.
U.S. Energy Information Administration. (2016). Country Analysis Brief: Colombia.