Specification of variance matrices for panel data models

J.R. Magnus, C.H.M. Muris

Research output: Contribution to journalArticleScientificpeer-review


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 x 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
JournalEconometric Theory
Issue number1
Publication statusPublished - 2010


Dive into the research topics of 'Specification of variance matrices for panel data models'. Together they form a unique fingerprint.

Cite this