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

Margaritella, Luca LU and Stauskas, Ovidijus (2026) In International Journal of Forecasting
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.
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author
and
organization
publishing date
type
Contribution to journal
publication status
epub
subject
keywords
Forecast accuracy, Factor-augmented regressions, Weak loadings, Principal component analysis (PCA), Nested models
in
International Journal of Forecasting
publisher
Elsevier
ISSN
0169-2070
language
English
LU publication?
yes
id
19b6fc21-af2a-4302-9eb5-d67b7195d85d
alternative location
https://authors.elsevier.com/sd/article/S0169-2070(25)00107-4
date added to LUP
2026-01-20 14:33:02
date last changed
2026-01-20 15:05:18
@article{19b6fc21-af2a-4302-9eb5-d67b7195d85d,
  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.}},
  author       = {{Margaritella, Luca and Stauskas, Ovidijus}},
  issn         = {{0169-2070}},
  keywords     = {{Forecast accuracy; Factor-augmented regressions; Weak loadings; Principal component analysis (PCA); Nested models}},
  language     = {{eng}},
  month        = {{01}},
  publisher    = {{Elsevier}},
  series       = {{International Journal of Forecasting}},
  title        = {{New tests of equal forecast accuracy for factor-augmented regressions with weaker loadings}},
  url          = {{https://authors.elsevier.com/sd/article/S0169-2070(25)00107-4}},
  year         = {{2026}},
}