We examine finite sample properties of estimators for approximate factor models when N is small. Contrary to the “rule-of-thumb”, we find that the principal component analysis estimator and the quasi-maximum likelihood estimator perform well even when N is small.

This article proposes a new stationarity test based on the KPSS test with less size distortion. We extend the boundary rule proposed by Sul et al. (2005) to the autoregressive spectral density estimator and parametrically estimate the long-run variance. We also derive the finite sample bias of...

This paper proposes a new test for factor loading structural change in dynamic factor models. The proposed test is robust to the nonmonotonic power problem that occurs if the factor loadings exhibit structural changes at common dates over cross-sections. To illustrate the usefulness of our test,...