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Useful matrix transformations for panel data analysis: a survey

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Abstract

This paper surveys some useful matrix transformations which simplify the derivation of GLS as WLS in an error component model. This is particularly important for large panel data applications where brute force inversion of large data matrices may not be feasible. This WLS transformation is known in the literature as the Fuller and Baltese (1974) transformation and its extension to error component models with heteroscedasticity, serial correlation, unbalancedness as well as a set of seemingly unrelated regressions are considered.

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Authors and Affiliations

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

    B. H. Baltagi

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  1. B. H. Baltagi
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Baltagi, B.H. Useful matrix transformations for panel data analysis: a survey. Statistical Papers 34, 281–301 (1993). https://doi.org/10.1007/BF02925550

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  • DOI: https://doi.org/10.1007/BF02925550

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