IDEAS home Printed from https://ideas.repec.org/a/bla/ecinqu/v46y2008i4p528-539.html
   My bibliography  Save this article

Should Oil Prices Receive So Much Attention? An Evaluation Of The Predictive Power Of Oil Prices For The U.S. Economy

Author

Listed:
  • LANCE BACHMEIER
  • QI LI
  • DANDAN LIU

Abstract

"This paper evaluates the potential gains from using oil prices to forecast a variety of measures of inflation, economic activity, and monetary policy-related variables. With a few exceptions, oil prices do not have any predictive content for these variables. This finding is robust to the use of rolling forecast windows, the use of industry-level data, changes in the forecast horizon, and allowing for nonlinearities. "("JEL "Q43, E37, C32) Copyright (c) 2007 Western Economic Association International.

Suggested Citation

  • Lance Bachmeier & Qi Li & Dandan Liu, 2008. "Should Oil Prices Receive So Much Attention? An Evaluation Of The Predictive Power Of Oil Prices For The U.S. Economy," Economic Inquiry, Western Economic Association International, vol. 46(4), pages 528-539, October.
  • Handle: RePEc:bla:ecinqu:v:46:y:2008:i:4:p:528-539
    as

    Download full text from publisher

    File URL: http://www.blackwell-synergy.com/doi/abs/10.1111/j.1465-7295.2007.00095.x
    File Function: link to full text
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Corradi, Valentina & Swanson, Norman R., 2002. "A consistent test for nonlinear out of sample predictive accuracy," Journal of Econometrics, Elsevier, vol. 110(2), pages 353-381, October.
    2. Chao, John & Corradi, Valentina & Swanson, Norman R., 2001. "Out-Of-Sample Tests For Granger Causality," Macroeconomic Dynamics, Cambridge University Press, vol. 5(04), pages 598-620, September.
    3. Richard Clarida & Jordi Galí & Mark Gertler, 2000. "Monetary Policy Rules and Macroeconomic Stability: Evidence and Some Theory," The Quarterly Journal of Economics, Oxford University Press, vol. 115(1), pages 147-180.
    4. McCracken, Michael W., 2007. "Asymptotics for out of sample tests of Granger causality," Journal of Econometrics, Elsevier, vol. 140(2), pages 719-752, October.
    5. Hamilton, James D., 1996. "This is what happened to the oil price-macroeconomy relationship," Journal of Monetary Economics, Elsevier, vol. 38(2), pages 215-220, October.
    6. Swanson, Norman R., 1998. "Money and output viewed through a rolling window," Journal of Monetary Economics, Elsevier, vol. 41(3), pages 455-474, May.
    7. Peter Ferderer, J., 1996. "Oil price volatility and the macroeconomy," Journal of Macroeconomics, Elsevier, vol. 18(1), pages 1-26.
    8. Kilian, Lutz & Taylor, Mark P., 2003. "Why is it so difficult to beat the random walk forecast of exchange rates?," Journal of International Economics, Elsevier, vol. 60(1), pages 85-107, May.
    9. John Y. Campbell & Samuel B. Thompson, 2005. "Predicting the Equity Premium Out of Sample: Can Anything Beat the Historical Average?," NBER Working Papers 11468, National Bureau of Economic Research, Inc.
    10. Hamilton, James D, 1988. "A Neoclassical Model of Unemployment and the Business Cycle," Journal of Political Economy, University of Chicago Press, vol. 96(3), pages 593-617, June.
    11. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    12. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003. "Modeling and Forecasting Realized Volatility," Econometrica, Econometric Society, vol. 71(2), pages 579-625, March.
    13. Hamilton, James D, 1983. "Oil and the Macroeconomy since World War II," Journal of Political Economy, University of Chicago Press, vol. 91(2), pages 228-248, April.
    14. Clark, Todd E. & McCracken, Michael W., 2001. "Tests of equal forecast accuracy and encompassing for nested models," Journal of Econometrics, Elsevier, vol. 105(1), pages 85-110, November.
    15. Chao Wei, 2003. "Energy, the Stock Market, and the Putty-Clay Investment Model," American Economic Review, American Economic Association, vol. 93(1), pages 311-323, March.
    16. Inoue, Atsushi & Kilian, Lutz, 2006. "On the selection of forecasting models," Journal of Econometrics, Elsevier, vol. 130(2), pages 273-306, February.
    17. West, Kenneth D, 1996. "Asymptotic Inference about Predictive Ability," Econometrica, Econometric Society, vol. 64(5), pages 1067-1084, September.
    18. Clark, Todd E. & McCracken, Michael W., 2006. "The Predictive Content of the Output Gap for Inflation: Resolving In-Sample and Out-of-Sample Evidence," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(5), pages 1127-1148, August.
    19. Hamilton, James D., 2003. "What is an oil shock?," Journal of Econometrics, Elsevier, vol. 113(2), pages 363-398, April.
    20. Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2006. "A comparison of direct and iterated multistep AR methods for forecasting macroeconomic time series," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 499-526.
    21. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    22. Stock, James H & Watson, Mark W, 1996. "Evidence on Structural Instability in Macroeconomic Time Series Relations," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(1), pages 11-30, January.
    23. Ben S. Bernanke, 1983. "Irreversibility, Uncertainty, and Cyclical Investment," The Quarterly Journal of Economics, Oxford University Press, vol. 98(1), pages 85-106.
    24. Kiseok Lee & Shawn Ni & Ronald A. Ratti, 1995. "Oil Shocks and the Macroeconomy: The Role of Price Variability," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 39-56.
    25. Valentina Corradi & Norman R. Swanson, 2007. "Nonparametric Bootstrap Procedures For Predictive Inference Based On Recursive Estimation Schemes," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 48(1), pages 67-109, February.
    26. Leduc, Sylvain & Sill, Keith, 2004. "A quantitative analysis of oil-price shocks, systematic monetary policy, and economic downturns," Journal of Monetary Economics, Elsevier, vol. 51(4), pages 781-808, May.
    27. Jones, Charles M & Kaul, Gautam, 1996. " Oil and the Stock Markets," Journal of Finance, American Finance Association, vol. 51(2), pages 463-491, June.
    28. Fan, Yanqin & Li, Qi, 1996. "Consistent Model Specification Tests: Omitted Variables and Semiparametric Functional Forms," Econometrica, Econometric Society, vol. 64(4), pages 865-890, July.
    29. Lee, Kiseok & Ni, Shawn, 2002. "On the dynamic effects of oil price shocks: a study using industry level data," Journal of Monetary Economics, Elsevier, vol. 49(4), pages 823-852, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Fan, Qinbin & Jahan-Parvar, Mohammad R., 2012. "U.S. industry-level returns and oil prices," International Review of Economics & Finance, Elsevier, vol. 22(1), pages 112-128.
    2. Alquist, Ron & Kilian, Lutz & Vigfusson, Robert J., 2013. "Forecasting the Price of Oil," Handbook of Economic Forecasting, Elsevier.
    3. Marc Joëts & Valérie Mignon & Tovonony Razafindrabe, 2015. "Does the volatility of commodity prices reflect macroeconomic uncertainty?," EconomiX Working Papers 2015-7, University of Paris Nanterre, EconomiX.
    4. Ziesemer, Thomas, 2009. "Growth with imported resources: On the sustainability of U.S. growth and foreign debt," MERIT Working Papers 028, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    5. repec:eee:eneeco:v:68:y:2017:i:c:p:313-326 is not listed on IDEAS
    6. Lutz Kilian & Robert J. Vigfusson, 2013. "Do Oil Prices Help Forecast U.S. Real GDP? The Role of Nonlinearities and Asymmetries," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(1), pages 78-93, January.
    7. Francesco Ravazzolo & Philip Rothman, 2013. "Oil and U.S. GDP: A Real‐Time Out‐of‐Sample Examination," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 45(2-3), pages 449-463, March.
    8. Jacint Balaguer & Manuel Cantavella-Jordá, 2014. "The Effect of Economic Growth and Oil Price Variations on CO2 Emissions: Evidence from Spain (1874-2011)," Working Papers 2014/22, Economics Department, Universitat Jaume I, Castellón (Spain).
    9. Kilian, Lutz & Vigfusson, Robert J., 2011. "Nonlinearities In The Oil Price–Output Relationship," Macroeconomic Dynamics, Cambridge University Press, vol. 15(S3), pages 337-363, November.
    10. Ravazzolo Francesco & Rothman Philip, 2016. "Oil-price density forecasts of US GDP," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(4), pages 441-453, September.
    11. Atems, Bebonchu & Kapper, Devin & Lam, Eddery, 2015. "Do exchange rates respond asymmetrically to shocks in the crude oil market?," Energy Economics, Elsevier, vol. 49(C), pages 227-238.
    12. Marc Joëts & Valérie Mignon & Tovonony Razafindrabe, 2017. "Does the volatility of commodity prices reflect macroeconomic uncertainty?," Post-Print halshs-01683788, HAL.

    More about this item

    JEL classification:

    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:ecinqu:v:46:y:2008:i:4:p:528-539. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum) or (Christopher F. Baum). General contact details of provider: http://edirc.repec.org/data/weaaaea.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.