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Robust Tests for Factor-Augmented Regressions with an Application to the Novel EA-MD-QD Dataset
We present four novel tests of equal predictive accuracy and encompassing à la Pitarakis (2023, 2025) for factor-augmented regressions, where factors are estimated using cross-section averages (CAs) of grouped series. Our inferential theory is asymptotically normal and robust to an overspecification of the number of factors. Our tests are empirically relevant as they accommodate for different degrees of predictor persistence and remain invariant to the location of structural breaks in the loadings. Monte Carlo simulations indicate that our tests exhibit excellent local power properties. Finally, we apply our tests to the novel EA-MD-QD dataset by Barigozzi et. al. (2024) – which covers the Euro Area as a whole and its primary member countries – and show that factors estimated by CAs offer substantial predictive power.
Date:
20 February 2026, 14:15
Venue:
Manor Road Building, Manor Road OX1 3UQ
Venue Details:
Seminar Room C
Speaker:
Ovidijus Stauskas (BI Norwegian Business School)
Organising department:
Department of Economics
Part of:
Nuffield Econometrics Seminar
Booking required?:
Not required
Audience:
Members of the University only
Editor:
Edward Valenzano
