New tests of equal forecast accuracy for factor-augmented regressions with weaker loadings
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.
Fields of Study & Subjects
Psychometric Methodologies and Testing
Statistical Methods and Inference
Advanced Statistical Methods and Models
Publication details
- Journal / source
- International Journal of Forecasting
- Publisher
- Elsevier BV
- Volume
- 42
- Issue
- 3
- Pages
- 776–795
- Publication date
- 20 January 2026
- Language
- EN