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In a recent paper Juodis and Reese (2021) (JR) show that the application ofthe CD test proposed by Pesaran (2004) to residuals from panels with latentfactors results in over-rejection and propose a randomized test statistic tocorrect for over-rejection, and add a screening component to achieve power.This paper considers the same problem but from a different perspective andshows 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 tobe asymptotically normal, irrespective of whether the latent factors are weakor strong. This result is shown to hold for pure latent factor models as wellas for panel regressions with latent factors. Small sample properties of theCD* test are investigated by Monte Carlo experiments and are shown to have thecorrect 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 ofpanels with non-Gaussian errors, and have low power against spatial networkalternatives. The use of the CD* test is illustrated with two empiricalapplications from the literature.

A Bias-Corrected CD Test for Error Cross-Sectional Dependence in Panel Data Models with Latent Factors