Predictability and Specification in Models of Exchange Rate Determination

Chapter

Abstract

We examine a class of popular structural models of exchange rate determination and compare them to a random walk with and without drift. Given almost any set of conditioning variables, we find parametric specifications fail. Our findings are based on a broad entropy function of the whole distribution of variables and forecasts. We also find significant evidence of nonlinearity and/or “higher moment” influences which seriously questions the habit of forecast and model evaluation based on mean-variance criteria. Taylor rule factors may improve out of sample “forecasts” for some models and exchanges, but do not offer similar improvement for in-sample (historical) fit. We estimate models of exchange rate determination nonparametrically so as to avoid functional form issues. Taylor rule and some other variables are smoothed out, being statistically irrelevant in sample. The metric entropy tests suggest significant differences between the observed densities and their in- and out- of sample forecasts and fitted values. Much like the Diebold-Mariano approach, we are able to report statistical significance of the differences with our more general measures of forecast performance.

References

  1. Berger, David W. and Chaboud, Alain P. and Chernenko, Sergey V. and Howorka, Edward and Jonathan H. Wright (2008). “Order Flow and Exchange Rate Dynamics in Electronic Brokerage System Data”, Journal of International Economics, Elsevier, vol. 75(1), pages 93–109, May.Google Scholar
  2. Berkowitz, Jeremy (2001). “Testing Density Forecasts with Applications to Risk Management”, Journal of Business and Economic Statistics, 19, 465–474.CrossRefGoogle Scholar
  3. Cheung, Yin-Wong & Chinn, Menzie D. & Antonio G. Pascual (2005).“Empirical Exchange Rate Models of the Nineties: Are any Fit to Survive?” Journal of International Money and Finance, Elsevier, vol. 24(7), pages 1150–1175, November.Google Scholar
  4. Chinn, Menzie D. & Michael J. Moore (2011).“Order Flow and the Monetary Model of Exchange Rates: Evidence from a Novel Data Set”, Forthcoming in Journal of Money, Credit and Banking.Google Scholar
  5. Clark, Todd E. & Michael W. McCracken (2001).“Tests of Equal Forecast Accuracy and Encompassing for Nested Models”, Journal of Econometrics, Elsevier, vol. 105(1), pages 85–110, November.Google Scholar
  6. Clark, Todd E. & Kenneth D. West (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.Google Scholar
  7. Clements, Michael P. & Jeremy Smith (2000). “Evaluating the Forecast Densities of Linear and Non-Linear Models: Applications to Output Growth and Unemployment”, Journal of Forecasting, 19, 255–276.CrossRefGoogle Scholar
  8. Corradi, Valentina & Norman R. Swanson (2006). “Predictive Density Evaluation”, in: Handbook of Economic Forecasting, eds. Clive W.J. Granger, Graham Elliot and Allan Timmerman, Elsevier, Amsterdam, pp. 197–284.Google Scholar
  9. Diebold, Francis X & Gunther, Todd A. & Anthony S. Tay (1998).“Evaluating Density Forecasts with Applications to Financial Risk Management”, International Economic Review, vol. 39(4), pages 863–83, November.Google Scholar
  10. Diebold, Francis X & Roberto S. Mariano (1995).“Comparing Predictive Accuracy”, Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253–63, July.Google Scholar
  11. Diebold, Francis X & James A. Nason (1990).“Nonparametric Exchange Rate Prediction?” Journal of International Economics, Elsevier, vol. 28(3–4), pages 315–332, May.Google Scholar
  12. Engel, Charles & Mark, Nelson C. & Kenneth D. West (2007).“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.Google Scholar
  13. Engel, Charles & Kenneth D. West (2005). “Exchange Rates and Fundamentals”, Journal of Political Economy, vol. 113(3), pages 485–517, June.Google Scholar
  14. Evans, M.D.D. & Richard K. Lyons (2002). “Order Flow and Exchange Rate Dynamics”, Journal of Political Economy, vol. 110(1), 170–180.CrossRefGoogle Scholar
  15. Evans, M.D.D. & Richard K. Lyons (2005). “Meese and Rogoff Redux: Micro-Based Exchange Rate Forecasting”, American Economic Review, vol. 95(2), pages 405–414, May.Google Scholar
  16. Faust, Jon & Rogers, John H. & Jonathan H. Wright (2003).“Exchange Rate Forecasting: The Errors We’ve Really Made”, Journal of International Economics, Elsevier, vol. 60(1), pages 35–59, May.Google Scholar
  17. Giannnerini, Simone & Dagum, Estela B. & Esfandiar Maasoumi (2011).“A Powerful Entropy Test for Linearity Against Nonlinearity in Time Series”, Working Paper Series.Google Scholar
  18. Gourinchas, Pierre-Olivier & Helene Rey (2007).“International Financial Adjustment”, Journal of Political Economy, vol. 115(4), pages 665–703.Google Scholar
  19. Granger, Clive W. J. & Maasoumi, Esfandiar & Jeff Racine (2004).“A Dependence Metric For Possibly Nonlinear Processes”, Journal of Time Series Analysis, 25, Issue 5, pp. 649–669.Google Scholar
  20. Hayfield, Tristen & Jeffrey S. Racine (2008). “Nonparametric Econometrics: The np Package”, Journal of Statistical Software, Volume 27 (5).Google Scholar
  21. Hsiao, Cheng & Li, Qi & Jeffrey S. Racine (2007).“A Consistent Model Specification Test with Mixed Discrete and Continuous Data”, Journal of Econometrics, Elsevier, vol. 140(2), pages 802–826, October.Google Scholar
  22. Li, Qi & Jeffrey S. Racine (2007). Nonparametric Econometrics: Theory and Practice, Princeton University Press, ISBN: 0691121613, 768 Pages.Google Scholar
  23. Maasoumi, Esfandiar & Jeff Racine (2002).“Entropy and Predictability of Stock Market Returns”, Journal of Econometrics, Elsevier, vol. 107(1–2), pages 291–312, March.Google Scholar
  24. Mark, Nelson C. (1995).“Exchange Rates and Fundamentals: Evidence on Long-Horizon Predictability”, American Economic Review, American Economic Association, vol. 85(1), pages 201–18, March.Google Scholar
  25. Meese, Richard A. & Kenneth Rogoff (1983).“Empirical Exchange Rate Models of the Seventies : Do They Fit out of Sample?” Journal of International Economics, Elsevier, vol. 14(1–2), pages 3–24, February.Google Scholar
  26. Meese, Richard A & Andrew K. Rose (1991).“An Empirical Assessment of Non-linearities in Models of Exchange Rate Determination”, Review of Economic Studies, Wiley Blackwell, vol. 58(3), pages 603–19, May.Google Scholar
  27. Molodtsova, Tanya & David H. Papell (2009).“Out-of-sample Exchange Rate Predictability with Taylor Rule Fundamentals”, Journal of International Economics, Elsevier, vol. 77(2), pages 167–180, April.Google Scholar
  28. Nikolsko-Rzhevskyy, Alex & Ruxandra Prodan (2011).“Markov Switching and Exchange Rate Predictability”, Forthcoming in International Journal of Forecasting.Google Scholar
  29. Rogoff, Kenneth S. & Vania Stavrakeva (2008).“The Continuing Puzzle of Short Horizon Exchange Rate Forecasting”, NBER Working Papers 14071, National Bureau of Economic Research, Inc.Google Scholar
  30. Skaug, H. & Dag Tjøstheim (1996). “Testing for Serial Independence Using Measures of Distance Between Densities”, in P. Robinson & M. Rosenblatt, eds, Athens Conference on Applied Probability and Time Series, Springer Lecture Notes in Statistics, Springer.Google Scholar
  31. Su, Liangjun & Halbert White (2008). “Nonparametric Hellinger Metric Test for Conditional Independence”, Econometric Theory, vol. 24, pages 829–864.CrossRefGoogle Scholar
  32. Wang, Jian & Jason J. Wu (2010).“The Taylor Rule and Forecast Intervals for Exchange Rates”, Forthcoming in Journal of Money, Credit and Banking.Google Scholar
  33. West, Kenneth D. (1996).“Asymptotic Inference about Predictive Ability”, Econometrica, Econometric Society, vol. 64(5), pages 1067–84, September.Google Scholar
  34. White, Halbert (2000). “A Reality Check for Data Snooping”, Econometrica, Econometric Society, vol. 68(5), pages 1097–1126, September.Google Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Arts and Sciences Distinguished Professor of EconomicsEmory UniversityAtlantaUSA
  2. 2.Visiting Assistant Professor of EconomicsAndrew Young School of Policy Studies, Georgia State UniversityAtlantaUSA

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