SPECIFICATION OF VARIANCE MATRICES FOR PANEL DATA MODELS

Jan Magnus () and Chris Muris

Econometric Theory, 2010, vol. 26, issue 1, 301-310

Abstract: 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.

Date: 2010
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