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

Publikation: Working paper/Preprint Working paperForskning


  • rp19_04

    Forlagets udgivne version, 804 KB, PDF-dokument

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.
UdgiverInstitut for Økonomi, Aarhus Universitet
Antal sider59
StatusUdgivet - 28 mar. 2019
SerietitelCREATES Research Paper


  • Panel data, predictability, long-range dependence, Diebold-Mariano test, encompassing test

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