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Comparing Predictive Accuracy, Twenty Years Later: A Personal Perspective on the Use and Abuse of Diebold-Mariano Tests

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  • Francis X. Diebold

Abstract

The Diebold-Mariano (DM) test was intended for comparing forecasts; it has been, and remains, useful in that regard. The DM test was not intended for comparing models. Unfortunately, however, much of the large subsequent literature uses DM-type tests for comparing models, in (pseudo-) out-of-sample environments. In that case, much simpler yet more compelling full-sample model comparison procedures exist; they have been, and should continue to be, widely used. The hunch that (pseudo-) out-of-sample analysis is somehow the "only," or "best," or even a "good" way to provide insurance against in-sample over-fitting in model comparisons proves largely false. On the other hand, (pseudo-) out-of-sample analysis may be useful for learning about comparative historical predictive performance.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 18391.

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Date of creation: Sep 2012
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Handle: RePEc:nbr:nberwo:18391

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  1. Lutz Kilian & Mark P. Taylor, 2001. "Why is it so difficult to beat the Random Walk Forecast of Exchange Rates?," Tinbergen Institute Discussion Papers 01-031/4, Tinbergen Institute.
  2. Inoue, Atsushi & Kilian, Lutz, 2006. "On the selection of forecasting models," Journal of Econometrics, Elsevier, Elsevier, vol. 130(2), pages 273-306, February.
  3. Clark, Todd E. & McCracken, Michael W., 2001. "Tests of equal forecast accuracy and encompassing for nested models," Journal of Econometrics, Elsevier, Elsevier, vol. 105(1), pages 85-110, November.
  4. Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, Econometric Society, vol. 57(2), pages 307-33, March.
  5. Inoue, Atsushi & Rossi, Barbara, 2011. "Out-of-Sample Forecast Tests Robust to the Choice of Window Size," CEPR Discussion Papers 8542, C.E.P.R. Discussion Papers.
  6. Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
  7. Todd E. Clark & Michael W. McCracken, 2011. "Advances in forecast evaluation," Working Papers 2011-025, Federal Reserve Bank of St. Louis.
  8. Clark, Todd E. & McCracken, Michael W., 2009. "Tests of Equal Predictive Ability With Real-Time Data," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 27(4), pages 441-454.
  9. Li, Tong, 2009. "Simulation based selection of competing structural econometric models," Journal of Econometrics, Elsevier, Elsevier, vol. 148(2), pages 114-123, February.
  10. Atsushi Inoue & Lutz Kilian, 2005. "In-Sample or Out-of-Sample Tests of Predictability: Which One Should We Use?," Econometric Reviews, Taylor & Francis Journals, Taylor & Francis Journals, vol. 23(4), pages 371-402.
  11. David E. Rapach & Jack K. Strauss & Guofu Zhou, 2010. "Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy," Review of Financial Studies, Society for Financial Studies, vol. 23(2), pages 821-862, February.
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  1. My "Must Read" List
    by Dave Giles in Econometrics Beat: Dave Giles' Blog on 2012-09-27 01:33:00
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Cited by:
  1. Rachidi Kotchoni & Dalibor Stevanovic, 2013. "Probability and Severity of Recessions," CIRANO Working Papers 2013s-43, CIRANO.
  2. Elliott, Graham & Gargano, Antonio & Timmermann, Allan, 2013. "Complete subset regressions," Journal of Econometrics, Elsevier, Elsevier, vol. 177(2), pages 357-373.
  3. Hajo Holzmann & Matthias Eulert, 2014. "The role of the information set for forecasting - with applications to risk management," Papers 1404.7653, arXiv.org.
  4. J. Isaac Miller, 2014. "Simple Robust Tests for the Specification of High-Frequency Predictors of a Low-Frequency Series," Working Papers, Department of Economics, University of Missouri 1412, Department of Economics, University of Missouri.

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