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A simple, robust test for choosing the level of fixed effects in linear panel data models

In: Advances in Applied Econometrics

Author

Listed:
  • Leslie E. Papke

    (Michigan State University)

  • Jeffrey M. Wooldridge

    (Michigan State University)

Abstract

For the panel data case where cross-sectional units are nested within higher-level groups, and there are many such groups, we propose a test that allows one to determine whether controlling for fixed effects at the more aggregate level is sufficient. The alternative is that one should allow for fixed effects at the unit level. The regression-based test is simple to carry out, even for unbalanced panels. In addition, the test is easily made robust to arbitrary heteroskedasticity, serial correlation across time, and even cluster correlation at the group level. We also show how to modify the traditional Hausman test of a single coefficient to be fully robust to serial correlation and cluster correlation. The tests work well in terms of size and power in a small simulation study. We apply the test to choosing between a fixed effects analysis at the school district level and the disaggregated school level.

Suggested Citation

  • Leslie E. Papke & Jeffrey M. Wooldridge, 2024. "A simple, robust test for choosing the level of fixed effects in linear panel data models," Advanced Studies in Theoretical and Applied Econometrics, in: Subal C. Kumbhakar & Robin C. Sickles & Hung-Jen Wang (ed.), Advances in Applied Econometrics, pages 219-237, Springer.
    • Handle: RePEc:spr:adschp:978-3-031-48385-1_9
    DOI: 10.1007/978-3-031-48385-1_9
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    More about this item

    Keywords

    Panel data; Fixed effects; Correlated random effects; Hausman test;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General

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