  In a recent paper Juodis and Reese (2021) (JR) show that the application of
the CD test proposed by Pesaran (2004) to residuals from panels with latent
factors results in over-rejection and propose a randomized test statistic to
correct for over-rejection, and add a screening component to achieve power.
This paper considers the same problem but from a different perspective and
shows that the standard CD test remains valid if the latent factors are weak,
and proposes a simple bias-corrected CD test, labelled CD*, which is shown to
be asymptotically normal, irrespective of whether the latent factors are weak
or strong. This result is shown to hold for pure latent factor models as well
as for panel regressions with latent factors. Small sample properties of the
CD* test are investigated by Monte Carlo experiments and are shown to have the
correct size and satisfactory power for both Gaussian and non-Gaussian errors.
In contrast, it is found that JR's test tends to over-reject in the case of
panels with non-Gaussian errors, and have low power against spatial network
alternatives. The use of the CD* test is illustrated with two empirical
applications from the literature.
