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A survey of recent theoretical developments in the econometrics of panel data

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Abstract

This paper surveys some recent developments in panel data analysis. In particular, it focuses on the error component model which is popular in panel data applications, and discusses recent advances in its estimation under heteroscedasticity, serial correlation, and a general variance-covariance matrix. It also surveys the extensions of this model to the seemingly unrelated regressions case, and the simultaneous equations case. The dynamic case and the incomplete panel data case are also considered, as well as a host of other miscellaneous extensions. Prediction with this model is briefly surveyed and alternative tests for this model are reviewed. While the bibliography is not exhaustive, this survey should complement previous surveys and should prove useful for researchers working in this area.

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Authors and Affiliations

  1. Department of Economics, Texas A&M University, 77843-4228, College Station, TX

    B. H. Baltagi

  2. School of Business and Economics, Wilfried Laurier University, N2L 3C5, Waterloo, Ontario, Canada

    B. Raj

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  1. B. H. Baltagi
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The authors would like to thank Terry Dielman, Tom Wansbeek and Marno Verbeek for their helpful comments and suggestions. Raj was supported by the Academic Development Fund, Wilfrid Laurier University, while Baltagi was supported by the Advanced Research Program, Texas Higher Education Board.

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Baltagi, B.H., Raj, B. A survey of recent theoretical developments in the econometrics of panel data. Empirical Economics 17, 85–109 (1992). https://doi.org/10.1007/BF01192477

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  • DOI: https://doi.org/10.1007/BF01192477

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