New tests of equal forecast accuracy for factor-augmented regressions with weaker loadings

Luca Margaritella and Ovidijus Stauskas

International Journal of Forecasting, 2026, vol. 42, issue 3, 776-795

Abstract: 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 to practitioners, as there is no theory justifying the use of these simple and powerful tests in such a 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.

Keywords: Forecast accuracy; Factor-augmented regressions; Weak loadings; Principal component analysis (PCA); Nested models (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:42:y:2026:i:3:p:776-795

DOI: 10.1016/j.ijforecast.2025.11.005

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