2 papers
stat.ME2025
An alternative bootstrap procedure for factor-augmented regression models
Peiyun Jiang, Takashi Yamagata
In this paper, we propose a novel bootstrap algorithm that is more efficient than existing methods for approximating the distribution of the factor-augmented regression estimator f…
stat.ME2025
Bias Correction in Factor-Augmented Regression Models with Weak Factors
Peiyun Jiang, Yoshimasa Uematsu, Takashi Yamagata
In this paper, we study the asymptotic bias of the factor-augmented regression estimator and its reduction, which is augmented by the factors extracted from a large number of $…