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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.

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

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Date of creation: Sep 2011
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Handle: RePEc:udb:wpaper:uwec-2011-14
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  1. James H. Stock & Mark W. Watson, 2001. "Forecasting Output and Inflation: The Role of Asset Prices," NBER Working Papers 8180, National Bureau of Economic Research, Inc.
  2. Søren Johansen & Rocco Mosconi & Bent Nielsen, 2000. "Cointegration analysis in the presence of structural breaks in the deterministic trend," Econometrics Journal, Royal Economic Society, vol. 3(2), pages 216-249.
  3. BAI, Jushan & PERRON, Pierre, 1998. "Computation and Analysis of Multiple Structural-Change Models," Cahiers de recherche 9807, Universite de Montreal, Departement de sciences economiques.
  4. Y.Chen & K. Rogoff, 2003. "Commodity Currencies and Empirical Exchange Rate Puzzles," DNB Staff Reports (discontinued) 76, Netherlands Central Bank.
  5. 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.
  6. 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.
  7. Pindyck, Robert S & Rotemberg, Julio J, 1990. "The Excess Co-movement of Commodity Prices," Economic Journal, Royal Economic Society, vol. 100(403), pages 1173-89, December.
  8. Yu-Chin Chen & Kenneth Rogoff & Barbara Rossi, 2008. "Can Exchange Rates Forecast Commodity Prices?," NBER Working Papers 13901, National Bureau of Economic Research, Inc.
  9. Jeff Fuhrer & George Moore, 1989. "Monetary policy rules and the indicator properties of asset prices," Finance and Economics Discussion Series 89, Board of Governors of the Federal Reserve System (U.S.).
  10. 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.
  11. 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.
  12. 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.
  13. 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.
  14. 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.
  15. Baillie, R.T., 1989. "Commodity Prices And Aggregate Inflation: Would A Commodity Price Rule Be Worthwhile?," Papers 8808, Michigan State - Econometrics and Economic Theory.
  16. Andreou, Elena & Ghysels, Eric & Kourtellos, Andros, 2010. "Regression models with mixed sampling frequencies," Journal of Econometrics, Elsevier, vol. 158(2), pages 246-261, October.
  17. 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.
  18. Ben Bernanke & Mark Gertler, 2000. "Monetary Policy and Asset Price Volatility," NBER Working Papers 7559, National Bureau of Economic Research, Inc.
  19. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
  20. Todd E. Clark & Michael W. McCracken, 1999. "Tests of equal forecast accuracy and encompassing for nested models," Research Working Paper 99-11, Federal Reserve Bank of Kansas City.
  21. 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.
  22. Todd E. Clark & Kenneth D. West, 2005. "Approximately normal tests for equal predictive accuracy in nested models," Research Working Paper RWP 05-05, Federal Reserve Bank of Kansas City.
  23. Paul Cashin & Luis Felipe Céspedes & Ratna Sahay, 2003. "Commodity Currencies and the Real Exchange Rate," Working Papers Central Bank of Chile 236, Central Bank of Chile.
  24. 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.
  25. 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.
  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. Kugler, Peter, 1991. "Common trends, commodity prices and consumer prices," Economics Letters, Elsevier, vol. 37(4), pages 345-349, December.
  28. C. John McDermott & Alasdair Scott & Paul Cashin, 1999. "The Myth of Comoving Commodity Prices," IMF Working Papers 99/169, International Monetary Fund.
  29. Fred Furlong, 1989. "Commodity prices and inflation," FRBSF Economic Letter, Federal Reserve Bank of San Francisco, issue jun16.
  30. 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.
  31. 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.
  32. 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.
  33. 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.
  34. 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.
  35. 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.
  36. Juselius, Katarina, 2006. "The Cointegrated VAR Model: Methodology and Applications," OUP Catalogue, Oxford University Press, number 9780199285679, March.
  37. 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.
  38. Chen, Yu-chin & Rogoff, Kenneth, 2003. "Commodity currencies," Journal of International Economics, Elsevier, vol. 60(1), pages 133-160, May.
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