Specification of variance matrices for panel data models

Jan R. Magnus, Chris Muris

Research output: Contribution to journalArticle (Academic Journal)peer-review

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.

Original languageEnglish
Pages (from-to)301-310
Number of pages10
JournalEconometric Theory
Volume26
Issue number1
DOIs
Publication statusPublished - 1 Feb 2010

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