Hostname: page-component-586b7cd67f-2plfb Total loading time: 0 Render date: 2024-11-26T09:01:55.874Z Has data issue: false hasContentIssue false
  • English
  • Français

DO OIL SHOCKS DRIVE BUSINESS CYCLES? SOME U.S. AND INTERNATIONAL EVIDENCE

Published online by Cambridge University Press:  05 December 2011

Kristie M. Engemann ,
Kevin L. Kliesen  and
Michael T. Owyang
Kristie M. Engemann
Affiliation:
Federal Reserve Bank of St. Louis
Kevin L. Kliesen*
Affiliation:
Federal Reserve Bank of St. Louis
Michael T. Owyang
Affiliation:
Federal Reserve Bank of St. Louis
*
Address correspondence to: Kevin Kliesen, Federal Reserve Bank of St. Louis, P.O. Box 442, St. Louis, MO63166, USA; e-mail: [email protected].
Get access Rights & Permissions [Opens in a new window]

Abstract

Oil prices rose sharply prior to the onset of the 2007–2009 recession. Hamilton [in the Palgrave Dictionary of Macroeconomics (2008)] noted that nine of the last ten recessions in the United States were preceded by a substantial increases in the price of oil. In this paper, we consider whether oil price shocks significantly increase the probability of recessions in a number of countries. Because business cycle turning points generally are not available for other countries, we estimate the turning points together with oil's effect in a Markov-switching model with time-varying transition probabilities. We find that, for most countries, oil shocks do affect the likelihood of entering a recession. In particular, for a constant, zero-term spread, an average-sized shock to WTI oil prices increases the probability of recession in the United States by nearly 50 percentage points after one year and nearly 90 percentage points after two years.

Keywords

Time-Varying Transition ProbabilitiesProbitRecessionOil PricesGibbs Sampler
Type
Articles
Information
Macroeconomic Dynamics , Volume 15 , Supplement S3: Oil Price Shocks , November 2011 , pp. 498 - 517
Copyright
Copyright © Cambridge University Press 2011

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Blanchard, Olivier J. and Galí, Jordi (2008) The Macroeconomic Effects of Oil Price Shocks: Why Are the 2000s So Different from the 1970s? Working paper 07-21, MIT Department of Economics.Google Scholar
Burbidge, John and Harrison, Alan (1984) Testing for the effects of oil-price rises using vector autoregressions. International Economic Review 25 (2), 459–484.Google Scholar
Casella, George and George, Edward I. (1992) Explaining the Gibbs sampler. American Statistician 46 (3), 167–174.CrossRefGoogle Scholar
Clements, Michael P. and Krolzig, Hans-Martin (2002) Can oil shocks explain asymmetries in the US business cycle? Empirical Economics 27 (2), 185–204.CrossRefGoogle Scholar
Cuñado, Juncal and de Gracia, Fernando Pérez (2003) Do oil price shocks matter? Evidence for some European countries. Energy Economics 25 (2), 137–154.Google Scholar
Estrella, Arturo and Mishkin, Frederic S. (1998) Predicting U.S. recessions: Financial variables as leading indicators. Review of Economics and Statistics 80 (1), 45–61.Google Scholar
Filardo, Andrew J. (1994) Business-cycle phases and their transitional dynamics. Journal of Business and Economic Statistics 12 (3), 299–308.Google Scholar
Filardo, Andrew J. and Gordon, Stephen F. (1998) Business cycle durations. Journal of Econometrics 85 (1), 99–123.Google Scholar
Gelfand, Alan E., Dey, Dipak K., and Chang, Hong (1992) Model determination using predictive distributions with implementation via sampling-based methods. In Bernardo, J. M., Berger, J. O., Dawid, A. P. and Smith, A.F. (eds.), Bayesian Statistics 4: Proceedings of the Fourth Valencia International Meeting, pp. 147–159. Oxford, UK: Oxford University Press.CrossRefGoogle Scholar
Gelfand, Alan E. and Smith, Adrian F. M. (1990) Sampling-based approaches to calculating marginal densities. Journal of the American Statistical Association 85 (410), 398–409.Google Scholar
Geweke, John and Keane, Michael (2007) Smoothly mixing regressions. Journal of Econometrics 138 (1), 252–290.Google Scholar
Goldfeld, Stephen M. and Quandt, Richard E. (1973) A Markov model for switching regressions. Journal of Econometrics 1 (1), 3–15.Google Scholar
Hamilton, James D. (1983) Oil and the macroeconomy since World War II. Journal of Political Economy 91 (2), 228–248.CrossRefGoogle Scholar
Hamilton, James D. (1989) A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica 57 (2), 357–384.Google Scholar
Hamilton, James D. (1996) This is what happened to the oil price–macroeconomy relationship. Journal of Monetary Economics 38 (2), 215–220.CrossRefGoogle Scholar
Hamilton, James D. (2003) What is an oil shock? Journal of Econometrics 113 (2), 363–398.Google Scholar
Hamilton, James D. (2008) Oil and the macroeconomy. In Durlauf, Steven N. and Blume, Lawrence E. (eds.), Palgrave Dictionary of Economics, 2nd ed.Palgrave Macmillan.Google Scholar
Hooker, Mark A. (1996) What happened to the oil price–macroeconomy relationship? Journal of Monetary Economics 38 (2), 195–213.Google Scholar
Jiménez-Rodríguez, Rebeca and Sánchez, Marcelo (2005) Oil price shocks and real GDP growth: Empirical evidence for some OECD countries. Applied Economics 37 (2), 201–228.Google Scholar
Kauppi, Heikki and Saikkonen, Pentti (2008) Predicting U.S. recessions with dynamic binary response models. Review of Economics and Statistics 90 (4), 777–791.Google Scholar
Kilian, Lutz (2008a) A comparison of the effects of exogenous oil supply shocks on output and inflation in the G7 countries. Journal of the European Economic Association 6 (1), 78–121.Google Scholar
Kilian, Lutz (2008b) Exogenous oil supply shocks: How big are they and how much do they matter for the U.S. economy? Review of Economics and Statistics 90 (2), 216–240.Google Scholar
Kilian, Lutz (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.Google Scholar
Kilian, Lutz and Vigfusson, Robert J. (2009) Pitfalls in Estimating Asymmetric Effects of Energy Price Shocks. International Finance Discussion Paper, No. 970, Board of Governors of the federal Reserve System.CrossRefGoogle Scholar
Kliesen, Kevin L. (2008) Oil and the U.S. macroeconomy: An update and a simple forecasting exercise. Federal Reserve Bank of St. Louis Review 90 (5), 505–516.Google Scholar
Lee, Kiseok, Ni, Shawn, and Ratti, Ronald A. (1995) Oil shocks and the macroeconomy: The role of price variability. Energy Journal 16 (4), 39–56.Google Scholar
Mork, Knut Anton (1989) Oil and the macroeconomy when prices go up and down: An extension of Hamilton's results. Journal of Political Economy 97 (3), 740–744.Google Scholar
Mork, Knut Anton, Olsen, Oystein, and Mysen, Hans Terje (1994) Macroeconomic responses to oil price increases and decreases in seven oecd countries. Energy Journal 15 (4), 19–35.Google Scholar
Peersman, Gert and Robays, Ine Van (2009) Cross-Country Differences in the Effects of Oil Shocks. Working paper, Ghent University.Google Scholar
Raymond, Jennie E. and Rich, Robert W. (1997) Oil and the macroeconomy: A Markov state-switching approach. Journal of Money, Credit and Banking 29 (2), 193–213.Google Scholar
Wheelock, David C. and Wohar, Mark E. (2009) Can the term spread predict output growth and recessions? A survey of the literature. Federal Reserve Bank of St. Louis Review 91(5, Part 1), 419–440.Google Scholar