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Forecasting Inflation using Commodity Price Aggregates

Author

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

Abstract

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.

Suggested Citation

  • Yu-chin Chen & Stephen J. Turnovsky & Eric Zivot, 2011. "Forecasting Inflation using Commodity Price Aggregates," Working Papers UWEC-2011-14, University of Washington, Department of Economics.
  • Handle: RePEc:udb:wpaper:uwec-2011-14
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. Yu-Chin Chen & Kenneth S. Rogoff & Barbara Rossi, 2010. "Can Exchange Rates Forecast Commodity Prices?," The Quarterly Journal of Economics, Oxford University Press, vol. 125(3), pages 1145-1194.
    6. Kenneth Rogoff & Yu-chin Chen, 2002. "Commodity Currencies and Empirical Exchange Rate Puzzles," IMF Working Papers 02/27, International Monetary Fund.
    7. 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.
    8. 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.
    9. 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 540-561, May.
    10. 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.
    11. 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.
    12. Pindyck, Robert S & Rotemberg, Julio J, 1990. "The Excess Co-movement of Commodity Prices," Economic Journal, Royal Economic Society, vol. 100(403), pages 1173-1189, December.
    13. Chen, Yu-chin & Rogoff, Kenneth, 2003. "Commodity currencies," Journal of International Economics, Elsevier, vol. 60(1), pages 133-160, May.
    14. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    15. Paul Cashin & C John McDermott & Alasdair Scott, 1999. "The myth of co-moving commodity prices," Reserve Bank of New Zealand Discussion Paper Series G99/9, Reserve Bank of New Zealand.
    16. 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.
    17. 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, February.
    18. 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.
    19. 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.
    20. 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.
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    Cited by:

    1. repec:spr:annopr:v:260:y:2018:i:1:d:10.1007_s10479-017-2659-0 is not listed on IDEAS
    2. Afees A. Salisu & Ahamuefula Ephraim Ogbonna, 2017. "Improving the Predictive ability of oil for inflation: An ADL-MIDAS Approach," Working Papers 025, Centre for Econometric and Allied Research, University of Ibadan.
    3. Balcilar, Mehmet & Katzke, Nico & Gupta, Rangan, 2017. "Do precious metal prices help in forecasting South African inflation?," The North American Journal of Economics and Finance, Elsevier, vol. 40(C), pages 63-72.
    4. repec:eee:intfor:v:33:y:2017:i:3:p:679-693 is not listed on IDEAS
    5. repec:sbe:breart:v:36:y:2016:i:2:a:52273 is not listed on IDEAS
    6. Moses Tule & Afees A. Salisu & Charles Chimeke, 2018. "You are what you eat: The role of oil price in Nigeria inflation forecast," Working Papers 040, Centre for Econometric and Allied Research, University of Ibadan.
    7. Mandalinci, Zeyyad, 2017. "Forecasting inflation in emerging markets: An evaluation of alternative models," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1082-1104.
    8. Byrne, Joseph P & Ibrahim, Boulis Maher & Sakemoto, Ryuta, 2017. "Carry Trades and Commodity Risk Factors," MPRA Paper 80789, University Library of Munich, Germany.
    9. repec:taf:applec:v:50:y:2018:i:4:p:407-425 is not listed on IDEAS
    10. repec:ebl:ecbull:eb-17-00609 is not listed on IDEAS
    11. repec:eee:ecolet:v:158:y:2017:i:c:p:41-46 is not listed on IDEAS
    12. Afees A. Salisu & Kazeem Isah, 2017. "Predicting US Inflation: Evidence from a New Approach," Working Papers 039, Centre for Econometric and Allied Research, University of Ibadan.

    More about this item

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E61 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Policy Objectives; Policy Designs and Consistency; Policy Coordination
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • F47 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Forecasting and Simulation: Models and Applications

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