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Specification Of Variance Matrices For Panel Data Models


  • Magnus, Jan R.
  • Muris, Chris


Many regression models have two dimensions, say time ( t = 1,…, T ) and households ( i = 1,…, N ), as in panel data, error components, or spatial econometrics. In estimating such models we need to specify the structure of the error variance matrix Ω , which is of dimension T N × T N . If T N is large, then direct computation of the determinant and inverse of Ω is not practical. In this note we define structures of Ω that allow the computation of its determinant and inverse, only using matrices of orders T and N , and at the same time allowing for heteroskedasticity, for household- or station-specific autocorrelation, and for time-specific spatial correlation.

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  • Magnus, Jan R. & Muris, Chris, 2010. "Specification Of Variance Matrices For Panel Data Models," Econometric Theory, Cambridge University Press, vol. 26(01), pages 301-310, February.
  • Handle: RePEc:cup:etheor:v:26:y:2010:i:01:p:301-310_09

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    References listed on IDEAS

    1. Hsiao, Cheng & Hashem Pesaran, M. & Kamil Tahmiscioglu, A., 2002. "Maximum likelihood estimation of fixed effects dynamic panel data models covering short time periods," Journal of Econometrics, Elsevier, vol. 109(1), pages 107-150, July.
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