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Estimation and Testing in a Fixed Effects Panel Data Model with Serially Correlated Error Component Disturbances

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Abstract

This paper revisits the fixed effects panel data model with AR(1) remainder disturbances and provides a bias corrected estimator for the serial correlation coefficient based on first differencing the panel regression to get rid of the fixed effects. This bias corrected estimator builds upon the estimator proposed by Han and Phillips (2010). Asymptotic properties as well as Monte Carlo results are provided that show the better performance of this new proposed bias corrected estimator. This is extended to the unbalanced panel data case and also illustrated using the empirical application in Donohue and Levitt (2001).

Suggested Citation

  • Badi H. Baltagi & Long Liu, 2025. "Estimation and Testing in a Fixed Effects Panel Data Model with Serially Correlated Error Component Disturbances," Center for Policy Research Working Papers 267, Center for Policy Research, Maxwell School, Syracuse University.
    • Handle: RePEc:max:cprwps:267
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    File URL: https://surface.syr.edu/cpr/499/
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    More about this item

    Keywords

    Panel Data; Serial Correlation; Generalized Least Squares; Fixed Effects; First Difference; Nonstationarity;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models

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