Assessing predictive accuracy in panel data models with long-range dependence

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This paper proposes tests of the null hypothesis that model-based forecasts
are uninformative in panels, allowing for individual and interactive fixed effects
that control for cross-sectional dependence, endogenous predictors, and
both short-range and long-range dependence. We consider a Diebold-Mariano
style test based on comparison of the model-based forecast and a nested nopredictability benchmark, an encompassing style test of the same null, and a
test of pooled uninformativeness in the entire panel. A simulation study shows
that the encompassing style test is reasonably sized in finite samples, whereas
the Diebold-Mariano style test is oversized. Both tests have non-trivial local
power. The methods are applied to the predictive relation between economic
policy uncertainty and future stock market volatility in a multi-country analysis.
Original languageEnglish
Place of publicationAarhus
PublisherInstitut for Økonomi, Aarhus Universitet
Number of pages59
Publication statusPublished - 28 Mar 2019
SeriesCREATES Research Paper

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