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

Mohammad Pesaran and Yimeng Xie

No 2022-06-10, Working Papers from Wang Yanan Institute for Studies in Economics (WISE), Xiamen University

Abstract: 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 overrejection, 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.

Keywords: Latent factor models; strong and weak factors; error cross-sectional dependence; spatial and network alternatives (search for similar items in EconPapers)
JEL-codes: C18 C23 C55 (search for similar items in EconPapers)
Date: 2022-06-10
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Working Paper: A Bias-Corrected CD Test for Error Cross-Sectional Dependence in Panel Data Models with Latent Factors (2021)
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