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The Incidental Parameters Problem in Testing for Remaining Cross-section Correlation

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  • Arturas Juodis
  • Simon Reese

Abstract

In this paper we consider the properties of the Pesaran (2004, 2015a) CD test for cross-section correlation when applied to residuals obtained from panel data models with many estimated parameters. We show that the presence of period-specific parameters leads the CD test statistic to diverge as length of the time dimension of the sample grows. This result holds even if cross-section dependence is correctly accounted for and hence constitutes an example of the Incidental Parameters Problem. The relevance of this problem is investigated both for the classical Time Fixed Effects estimator as well as the Common Correlated Effects estimator of Pesaran (2006). We suggest a weighted CD test statistic which re-establishes standard normal inference under the null hypothesis. Given the widespread use of the CD test statistic to test for remaining cross-section correlation, our results have far reaching implications for empirical researchers.

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  • Arturas Juodis & Simon Reese, 2018. "The Incidental Parameters Problem in Testing for Remaining Cross-section Correlation," Papers 1810.03715, arXiv.org, revised Feb 2021.
  • Handle: RePEc:arx:papers:1810.03715
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    8. Antonio Musolesi & Giada Andrea Prete & Michel Simioni, 2022. "Is infrastructure capital really productive? Non-parametric modeling and data-driven model selection in a cross-sectionally dependent panel framework," SEEDS Working Papers 0522, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Mar 2022.
    9. Michael D. Plante, 2023. "Investing in the Batteries and Vehicles of the Future: A View Through the Stock Market," Working Papers 2314, Federal Reserve Bank of Dallas, revised 25 Mar 2024.

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