Out-of-Sample Forecast Tests Robust to the Choice of Window Size

This article proposes new methodologies for evaluating economic models' out-of-sample forecasting performance that are robust to the choice of the estimation window size. The methodologies involve evaluating the predictive ability of forecasting models over a wide range of window sizes. The stu...

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Bibliographic Details
Published inJournal of business & economic statistics Vol. 30; no. 3; pp. 432 - 453
Main Authors Rossi, Barbara, Inoue, Atsushi
Format Journal Article
LanguageEnglish
Published Alexandria Taylor & Francis Group 01.07.2012
American Statistical Association
Taylor & Francis Ltd
Subjects
Consistent estimators
Critical values
Economic forecasting models
Economic models
Empirical evidence
Estimation window
Forecast evaluation
Forecasting models
Forecasting techniques
Modeling
Null hypothesis
Parametric models
Predictive ability testing
Significance level
Statistical forecasts
Studies
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Summary:This article proposes new methodologies for evaluating economic models' out-of-sample forecasting performance that are robust to the choice of the estimation window size. The methodologies involve evaluating the predictive ability of forecasting models over a wide range of window sizes. The study shows that the tests proposed in the literature may lack the power to detect predictive ability and might be subject to data snooping across different window sizes if used repeatedly. An empirical application shows the usefulness of the methodologies for evaluating exchange rate models' forecasting ability.
ISSN:0735-0015
1537-2707
DOI:10.1080/07350015.2012.693850