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Can Parameter Instability Explain the Meese-Rogoff Puzzle?

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  • Philippe Bacchetta
  • Eric van Wincoop
  • Toni Beutler

Abstract

The empirical literature on nominal exchange rates shows that the current exchange rate is often a better predictor of future exchange rates than a linear combination of macroeconomic fundamentals. This result is behind the famous Meese-Rogoff puzzle. In this paper we evaluate whether parameter instability can account for this puzzle. We consider a theoretical reduced-form relationship between the exchange rate and fundamentals in which parameters are either constant or time varying. We calibrate the model to data for exchange rates and fundamentals and conduct the exact same Meese-Rogoff exercise with data generated by the model. Our main finding is that the impact of time-varying parameters on the prediction performance is either very small or goes in the wrong direction. To help interpret the findings, we derive theoretical results on the impact of time-varying parameters on the out-of-sample forecasting performance of the model. We conclude that it is not time-varying parameters, but rather small sample estimation bias, that explains the Meese-Rogoff puzzle.

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Bibliographic Info

Paper provided by Université de Lausanne, Faculté des HEC, DEEP in its series Cahiers de Recherches Economiques du Département d'Econométrie et d'Economie politique (DEEP) with number 09.08.

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Length: 34 pages + figures
Date of creation: Jul 2009
Date of revision:
Publication status: Published in NBER International Seminar on Macroeonomics 2009, 2010, pp. 125-173
Handle: RePEc:lau:crdeep:09.08

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Postal: Université de Lausanne, Faculté des HEC, DEEP, Internef, CH-1015 Lausanne
Phone: ++41 21 692.33.64
Fax: ++41 21 692.33.05
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Web page: http://www.hec.unil.ch/deep/publications/cahiers/series
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Keywords: exchange rate forecasting; time-varying coefficients;

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References

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  1. 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.
  2. Nelson Mark & Donggyu Sul, 1998. "Norminal Exchange Rates and Monetary Fundamentals: Evidence from a Small Post-Bretton Woods Panel," Working Papers 98-19, Ohio State University, Department of Economics.
  3. Groen, Jan J J, 2005. "Exchange Rate Predictability and Monetary Fundamentals in a Small Multi-country Panel," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 495-516, June.
  4. Todd E. Clark & Kenneth D. West, 2004. "Using out-of-sample mean squared prediction errors to test the Martingale difference hypothesis," Research Working Paper RWP 04-03, Federal Reserve Bank of Kansas City.
  5. Eric van Wincoop & Philippe Bacchetta, 2003. "Can Information Heterogeneity Explain the Exchange Rate Determination Puzzle?," NBER Working Papers 9498, National Bureau of Economic Research, Inc.
  6. Rossi, Barbara, 2006. "Are Exchange Rates Really Random Walks? Some Evidence Robust To Parameter Instability," Macroeconomic Dynamics, Cambridge University Press, vol. 10(01), pages 20-38, February.
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  12. Philippe Bacchetta & Eric van Wincoop, 2009. "On the Unstable Relationship between Exchange Rates and Macroeconomic Fundamentals," NBER Working Papers 15008, National Bureau of Economic Research, Inc.
  13. Molodtsova, Tanya & Papell, David H., 2009. "Out-of-sample exchange rate predictability with Taylor rule fundamentals," Journal of International Economics, Elsevier, vol. 77(2), pages 167-180, April.
  14. Cheung, Yin-Wong & Chinn, Menzie & Garcia Pascual, Antonio, 2003. "Empirical Exchange Rate Models of the Nineties: Are Any Fit to Survive?," Santa Cruz Center for International Economics, Working Paper Series qt5fc508pt, Center for International Economics, UC Santa Cruz.
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  19. Kenneth S. Rogoff & Vania Stavrakeva, 2008. "The Continuing Puzzle of Short Horizon Exchange Rate Forecasting," NBER Working Papers 14071, National Bureau of Economic Research, Inc.
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  21. Philippe Bacchetta & Eric van Wincoop, 2009. "Tacit On the Unstable Relationship between Exchange Rates and Macroeconomic Fundamentals," Cahiers de Recherches Economiques du Département d'Econométrie et d'Economie politique (DEEP) 09.07, Université de Lausanne, Faculté des HEC, DEEP.
  22. Richard Meese & Kenneth Rogoff & Jacob Frenkel, . "The Out-of-Sample Failure of Empirical Exchange Rate Models: Sampling Error or Misspecification?," Working Paper 32044, Harvard University OpenScholar.
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Citations

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Cited by:
  1. Cheolbeom Park & Sookyung Park, 2013. "Exchange Rate Predictability and a Monetary Model with Time-varying Cointegration Coefficients," Discussion Paper Series 1302, Institute of Economic Research, Korea University.
  2. Rossi, Barbara, 2013. "Exchange Rate Predictability," CEPR Discussion Papers 9575, C.E.P.R. Discussion Papers.
  3. Philippe Bacchetta & Eric van Wincoop, 2009. "On the Unstable Relationship between Exchange Rates and Macroeconomic Fundamentals," Working Papers 272009, Hong Kong Institute for Monetary Research.
  4. Marcel Fratzscher & Lucio Sarno & Gabriele Zinna, 2013. "The Scapegoat Theory of Exchange Rates: The First Tests," Discussion Papers of DIW Berlin 1290, DIW Berlin, German Institute for Economic Research.
  5. Travis J. Berge, 2011. "Forecasting disconnected exchange rates," Research Working Paper RWP 11-12, Federal Reserve Bank of Kansas City.
  6. Joseph P. Byrne & Dimitris Korobilis & Pinho J. Ribeiro, 2014. "Exchange Rate Predictability in a Changing World," Working Paper Series 06_14, The Rimini Centre for Economic Analysis.
  7. Barbara Rossi & Tatevik Sekhposyan, 2010. "Understanding Models' Forecasting Performance," Working Papers 10-56, Duke University, Department of Economics.
  8. Philippe Bacchetta & Eric van Wincoop, 2011. "Modeling Exchange Rates with Incomplete Information," Cahiers de Recherches Economiques du Département d'Econométrie et d'Economie politique (DEEP) 11.03, Université de Lausanne, Faculté des HEC, DEEP.
  9. Toni Beutler, 2012. "Forecasting Exchange Rates with Commodity Convenience Yields," Working Papers 12.03, Swiss National Bank, Study Center Gerzensee.
  10. Christophe Amat & Tomasz Michalski & Gilles Stoltz, 2014. "Forecasting exchange rates better than the random walk thanks to machine learning techniques," Working Papers halshs-01003914, HAL.
  11. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.

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