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On the Usefulness of the Diebold-Mariano Test in the Selection of Prediction Models

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Author Info

  • Costantini, Mauro

    (BWZ, University of Vienna, Vienna, Austria)

  • Kunst, Robert M.

    (Department of Economics and Finance, Institute for Advanced Studies, Vienna, Austria and Department of Economics, University of Vienna, Austria)

Abstract

In evaluating prediction models, many researchers flank comparative ex-ante prediction experiments by significance tests on accuracy improvement, such as the Diebold-Mariano test. We argue that basing the choice of prediction models on such significance tests is problematic, as this practice may favor the null model, usually a simple benchmark. We explore the validity of this argument by extensive Monte Carlo simulations with linear (ARMA) and nonlinear (SETAR) generating processes. For many parameter constellations, we find that utilization of additional significance tests in selecting the forecasting model fails to improve predictive accuracy.

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File URL: http://www.ihs.ac.at/publications/eco/es-276.pdf
File Function: First version, 2011
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Bibliographic Info

Paper provided by Institute for Advanced Studies in its series Economics Series with number 276.

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Length: 18 pages
Date of creation: Nov 2011
Date of revision:
Handle: RePEc:ihs:ihsesp:276

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Related research

Keywords: Forecsting; time series; predictive accuracy; model selection!;

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References

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  1. Inoue, Atsushi & Kilian, Lutz, 2003. "On the Selection of Forecasting Models," CEPR Discussion Papers 3809, C.E.P.R. Discussion Papers.
  2. Todd E. Clark & Michael McCracken, 1999. "Tests of Equal Forecast Accuracy and Encompassing for Nested Models," Computing in Economics and Finance 1999 1241, Society for Computational Economics.
  3. Mauro Costantini & Robert M. Kunst, 2011. "Combining forecasts based on multiple encompassing tests in a macroeconomic core system," Journal of Forecasting, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 30(6), pages 579-596, September.
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Cited by:
  1. Luis A. Gil-Alana & Juncal Cuñado & Guglielmo Maria Caporale, 2012. "Modelling Long Run Trends and Cycles in Financial Time Series Data," Faculty Working Papers 13/12, School of Economics and Business Administration, University of Navarra.
  2. Anders Bredahl Kock & Timo Teräsvirta, 2011. "Forecasting Macroeconomic Variables using Neural Network Models and Three Automated Model Selection Techniques," CREATES Research Papers 2011-27, School of Economics and Management, University of Aarhus.
  3. Guglielmo Maria Caporale & Luis A. Gil-Alana, 2012. "Persistence and Cycles in the US Federal Funds Rate," CESifo Working Paper Series 4035, CESifo Group Munich.
  4. Frédérique Bec & Mélika Ben Salem, 2012. "Inventory Investment and the Business Cycle : The usual Suspect," Working Papers, Centre de Recherche en Economie et Statistique 2012-09, Centre de Recherche en Economie et Statistique.

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