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Testing Long-Horizon Predictive Ability With High Persistence, And The Meese-Rogoff Puzzle

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Barbara Rossi

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Abstract

A well-known puzzle in international finance is that a random walk predicts exchange rates better than economic models. I offer a potential explanation. When exchange rates and fundamentals are highly persistent, long-horizon forecasts of economic models are biased by the estimation error. When this bias is big, a random walk will forecast better, even if the economic model is true. I propose a test for equal predictability in the presence of high persistence. It shows that the poor forecasting ability of economic models "does not" imply that the models are "not" good descriptions of the data. Copyright 2005 by the Economics Department Of The University Of Pennsylvania And Osaka University Institute Of Social And Economic Research Association.

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Article provided by Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association in its journal International Economic Review.

Volume (Year): 46 (2005)
Issue (Month): 1 (02)
Pages: 61-92
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Handle: RePEc:ier:iecrev:v:46:y:2005:i:1:p:61-92

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  1. Chevillon, Guillaume, 2007. "Inference in the Presence of Stochastic and Deterministic Trends," ESSEC Working Papers DR 07021, ESSEC Research Center, ESSEC Business School. [Downloadable!]
  2. Jin Lee, 2007. "Fractionally Integrated Long Horizon Regressions," Studies in Nonlinear Dynamics & Econometrics, Berkeley Electronic Press, vol. 11(1). [Downloadable!]
  3. Erik Hjalmarsson, 2006. "New methods for inference in long-run predictive regressions," International Finance Discussion Papers 853, Board of Governors of the Federal Reserve System (U.S.). [Downloadable!]
  4. Valerie Cerra & Sweta Chaman Saxena, 2008. "The Monetary Model Strikes Back: Evidence from the World," IMF Working Papers 08/73, International Monetary Fund. [Downloadable!]
  5. Todd E. Clark & Michael W. McCracken, 2007. "Tests of equal predictive ability with real-time data," Research Working Paper RWP 07-06, Federal Reserve Bank of Kansas City. [Downloadable!]
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  6. Sarno, Lucio & Valente, Giorgio, 2008. "Exchange Rates and Fundamentals: Footloose or Evolving Relationship?," CEPR Discussion Papers 6638, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
    Other versions:
  7. Jin Lee, 2005. "Long horizon regressions with moderate deviations from a unit root," Economics Bulletin, Economics Bulletin, vol. 3(52), pages 1-11. [Downloadable!]
  8. Jian Wang & Jason J. Wu, 2008. "The Taylor rule and forecast intervals for exchange rates," Globalization and Monetary Policy Institute Working Paper 22, Federal Reserve Bank of Dallas. [Downloadable!]
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  9. David Peel & Ivan Paya & E Pavlidis, 2009. "Forecasting the Real Exchange Rate using a Long Span of Data. A Rematch: Linear vs Nonlinear," Working Papers 006075, Lancaster University Management School, Economics Department. [Downloadable!]
  10. Geetesh Bhardwaj & Norman Swanson, 2004. "An Empirical Investigation of the Usefulness of ARFIMA Models for Predicting Macroeconomic and Financial Time Series," Departmental Working Papers 200422, Rutgers University, Department of Economics. [Downloadable!]
    Other versions:
  11. Rime, Dagfinn & Sarno, Lucio & Sojli, Elvira, 2009. "Exchange Rate Forecasting, Order Flow and Macroeconomic Information," CEPR Discussion Papers 7225, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
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