arXiv subjects

Ovidijus Stauskas

Publications and source records attributed to Ovidijus Stauskas.

3 recordsLinked to original sources

arXiv2025

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.

econ.EM↗

arXiv2025

New Tests of Equal Forecast Accuracy for Factor-Augmented Regressions with Weaker Loadings

We provide the theoretical foundation for the recent tests of equal forecast accuracy and encompassing by Pitarakis (2023) and Pitarakis (2025), when the competing forecast specification is that of a factor-augmented regression model. This should be of interest for practitioners, as there is no theory justifying the use of these simple and powerful tests in such context. In pursuit of this, we employ a novel theory to incorporate the empirically well-documented fact of homogeneously/heterogeneously weak factor loadings, and track their effect on the forecast comparison problem.

econ.EM↗

arXiv2025

On Selection of Cross-Section Averages in Non-stationary Environments

Information criteria (IC) have been widely used in factor models to estimate an unknown number of latent factors. It has recently been shown that IC perform well in Common Correlated Effects (CCE) and related setups in selecting a set of cross-section averages (CAs) sufficient for the factor space under stationary factors. As CAs can proxy non-stationary factors, it is tempting to claim such generality of IC, too. We show formally and in simulations that IC have a severe underselection issue even under very mild forms of factor non-stationarity, which goes against the sentiment in the literature.

econ.EM↗