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Can Parameter Instability Explain the Meese-Rogoff Puzzle?

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  • Bacchetta, Philippe
  • Beutler, Toni
  • van Wincoop, Eric

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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Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 7383.

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Date of creation: Jul 2009
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Handle: RePEc:cpr:ceprdp:7383

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Keywords: Exchange rate forecasting; exchange rate models;

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  1. Chen, Yu-chin & Rogoff, Kenneth, 2003. "Commodity currencies," Journal of International Economics, Elsevier, vol. 60(1), pages 133-160, May.
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Cited by:
  1. Rossi, Barbara & Sekhposyan, Tatevik, 2011. "Understanding models' forecasting performance," Journal of Econometrics, Elsevier, vol. 164(1), pages 158-172, September.
  2. Rossi, Barbara, 2013. "Exchange Rate Predictability," CEPR Discussion Papers 9575, C.E.P.R. Discussion Papers.
  3. Fratzscher, Marcel & Sarno, Lucio & Zinna, Gabriele, 2012. "The Scapegoat Theory of Exchange Rates: The First Tests," CEPR Discussion Papers 8812, C.E.P.R. Discussion Papers.
  4. 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.
  5. Toni Beutler, 2012. "Forecasting Exchange Rates with Commodity Convenience Yields," Working Papers 12.03, Swiss National Bank, Study Center Gerzensee.
  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. 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.
  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. Travis J. Berge, 2011. "Forecasting disconnected exchange rates," Research Working Paper RWP 11-12, Federal Reserve Bank of Kansas City.
  10. 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.
  11. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.

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