IDEAS home Printed from
MyIDEAS: Log in (now much improved!) to save this paper

Forecasting Inflation using Commodity Price Aggregates

  • Yu-chin Chen
  • Stephen J. Turnovsky
  • Eric Zivot

This paper shows that for five small commodity-exporting countries that have adopted inflation targeting monetary policies, world commodity price aggregates have predictive power for their CPI and PPI inflation, particularly once possible structural breaks are taken into account. This conclusion is robust to using either disaggregated or aggregated commodity price indexes (although the former perform better), the currency denomination of the commodity prices, and to using mixed-frequency data. In pseudo out-of-sample forecasting, commodity indexes outperform the random walk and AR(1) processes, although the improvements over the latter are sometimes modest.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL:
Download Restriction: no

Paper provided by University of Washington, Department of Economics in its series Working Papers with number UWEC-2011-14.

in new window

Date of creation: Sep 2011
Date of revision:
Handle: RePEc:udb:wpaper:uwec-2011-14
Contact details of provider: Postal:
Box 353330, Seattle, WA 98193-3330

Web page:

More information through EDIRC

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as in new window
  1. Bent Nielsen, 2000. "Cointegration Analysis in the Presence of Structural Breaks in the Deterministic Trend," Econometric Society World Congress 2000 Contributed Papers 1494, Econometric Society.
  2. Pecchenino, R. A., 1992. "Commodity prices and the CPI: Cointegration, information, and signal extraction," International Journal of Forecasting, Elsevier, vol. 7(4), pages 493-500, March.
  3. James H. Stock & Mark W. Watson, 2007. "Why Has U.S. Inflation Become Harder to Forecast?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 3-33, 02.
  4. 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.
  5. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
  6. Yu-chin Chen & Wen-Jen Tsay, 2011. "Forecasting Commodity Prices with Mixed-Frequency Data: An OLS-Based Generalized ADL Approach," IEAS Working Paper : academic research 11-A001, Institute of Economics, Academia Sinica, Taipei, Taiwan, revised May 2011.
  7. Yu-chin Chen & Kenneth Rogoff & Barbara Rossi, 2008. "Can Exchange Rates Forecast Commodity Prices?," Working Papers UWEC-2008-11-FC, University of Washington, Department of Economics, revised Oct 2009.
  8. Baillie, Richard T., 1989. "Commodity prices and aggregate inflation: Would a commodity price rule be worthwhile?," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 31(1), pages 185-240, January.
  9. Pindyck, Robert S. & Rotemberg, Julio., 1987. "The excess co-movement of commodity prices," Working papers 1969-87., Massachusetts Institute of Technology (MIT), Sloan School of Management.
  10. Todd E. Clark & Michael W. McCracken, 2000. "Tests of Equal Forecast Accuracy and Encompassing for Nested Models," Econometric Society World Congress 2000 Contributed Papers 0319, Econometric Society.
  11. Mahdavi, Saeid & Zhou, Su, 1997. "Gold and commodity prices as leading indicators of inflation: Tests of long-run relationship and predictive performance," Journal of Economics and Business, Elsevier, vol. 49(5), pages 475-489.
  12. Deb, Partha & Trivedi, Pravin K & Varangis, Panayotis, 1996. "The Excess Co-movement of Commodity Prices Reconsidered," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(3), pages 275-91, May-June.
  13. Ben S. Bernanke & Mark Gertler, 2001. "Should Central Banks Respond to Movements in Asset Prices?," American Economic Review, American Economic Association, vol. 91(2), pages 253-257, May.
  14. Ben S. Bernanke & Mark Gertler, 1999. "Monetary policy and asset price volatility," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, pages 77-128.
  15. Hooker, Mark A, 2002. "Are Oil Shocks Inflationary? Asymmetric and Nonlinear Specifications versus Changes in Regime," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 34(2), pages 540-61, May.
  16. Cashin, Paul & Cespedes, Luis F. & Sahay, Ratna, 2004. "Commodity currencies and the real exchange rate," Journal of Development Economics, Elsevier, vol. 75(1), pages 239-268, October.
  17. Clark, Todd E. & West, Kenneth D., 2006. "Using out-of-sample mean squared prediction errors to test the martingale difference hypothesis," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 155-186.
  18. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
  19. C. John McDermott & Alasdair Scott & Paul Cashin, 1999. "The Myth of Comoving Commodity Prices," IMF Working Papers 99/169, International Monetary Fund.
  20. Chen, Yu-chin & Rogoff, Kenneth, 2003. "Commodity currencies," Journal of International Economics, Elsevier, vol. 60(1), pages 133-160, May.
  21. Elena Andreou & Eric Ghysels & Andros Kourtellos, 2007. "Regression Models with Mixed Sampling Frequencies," University of Cyprus Working Papers in Economics 8-2007, University of Cyprus Department of Economics.
  22. Nikolay Gospodinov & Serena Ng, 2013. "Commodity Prices, Convenience Yields, and Inflation," The Review of Economics and Statistics, MIT Press, vol. 95(1), pages 206-219, March.
  23. James H. Stock & Mark W. Watson, 2001. "Forecasting output and inflation: the role of asset prices," Proceedings, Federal Reserve Bank of San Francisco, issue Mar.
  24. Elena Andreou & Eric Ghysels & Andros Kourtellos, 2010. "Forecasting with mixed-frequency data," University of Cyprus Working Papers in Economics 10-2010, University of Cyprus Department of Economics.
  25. Frederick T. Furlong, 1989. "Commodity prices and inflation," FRBSF Economic Letter, Federal Reserve Bank of San Francisco, issue jun16.
  26. Andrew Atkeson & Lee E. Ohanian, 2001. "Are Phillips curves useful for forecasting inflation?," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Win, pages 2-11.
  27. Chunrong Ai & Arjun Chatrath & Frank Song, 2006. "On the Comovement of Commodity Prices," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 88(3), pages 574-588.
  28. Fuhrer, Jeff & Moore, George, 1992. "Monetary policy rules and the indicator properties of asset prices," Journal of Monetary Economics, Elsevier, vol. 29(2), pages 303-336, April.
  29. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-80, November.
  30. Kugler, Peter, 1991. "Common trends, commodity prices and consumer prices," Economics Letters, Elsevier, vol. 37(4), pages 345-349, December.
  31. Kenneth Rogoff & Yu-chin Chen, 2002. "Commodity Currencies and Empirical Exchange Rate Puzzles," IMF Working Papers 02/27, International Monetary Fund.
  32. Baillie, R.T., 1989. "Commodity Prices And Aggregate Inflation: Would A Commodity Price Rule Be Worthwhile?," Papers 8808, Michigan State - Econometrics and Economic Theory.
  33. Charles Engel & Nelson C. Mark & Kenneth D. West, 2008. "Exchange Rate Models Are Not As Bad As You Think," NBER Chapters, in: NBER Macroeconomics Annual 2007, Volume 22, pages 381-441 National Bureau of Economic Research, Inc.
  34. S. Brock Blomberg & Ethan S. Harris, 1995. "The commodity-consumer price connection: fact or fable?," Economic Policy Review, Federal Reserve Bank of New York, issue Oct, pages 21-38.
  35. Juselius, Katarina, 2006. "The Cointegrated VAR Model: Methodology and Applications," OUP Catalogue, Oxford University Press, number 9780199285679, December.
  36. Johansen, Soren & Juselius, Katarina, 1990. "Maximum Likelihood Estimation and Inference on Cointegration--With Applications to the Demand for Money," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 52(2), pages 169-210, May.
  37. James H. Stock & Mark W. Watson, 2007. "Erratum to "Why Has U.S. Inflation Become Harder to Forecast?"," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(7), pages 1849-1849, October.
  38. Stephen G. Cecchetti & Hans Genberg & Sushil Wadhwani, 2002. "Asset Prices in a Flexible Inflation Targeting Framework," NBER Working Papers 8970, National Bureau of Economic Research, Inc.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:udb:wpaper:uwec-2011-14. 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: (Michael Goldblatt)

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 references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link 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 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.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.