On the Usefulness of the Diebold-Mariano Test in the Selection of Prediction Models: Some Monte Carlo Evidence

Costantini, Mauro and Kunst, Robert M. (November 2011) On the Usefulness of the Diebold-Mariano Test in the Selection of Prediction Models: Some Monte Carlo Evidence. IHS Economics Series 276

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Abstract or Table of Contents

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.;

Item Type: IHS Series
Keywords: 'Forecasting' 'Time series' 'Predictive accuracy' 'Model selection!'
Classification Codes (e.g. JEL): C22, C52, C53
Status: Published
Date Deposited: 26 Sep 2014 10:39
Last Modified: 24 Jul 2017 16:40
URI: http://irihs.ihs.ac.at/id/eprint/2097

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