### 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 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 language | English |
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Pages (from-to) | 301-310 |

Journal | Econometric Theory |

Volume | 26 |

Issue number | 1 |

Publication status | Published - 2010 |

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## Cite this

Magnus, J. R., & Muris, C. H. M. (2010). Specification of variance matrices for panel data models.

*Econometric Theory*,*26*(1), 301-310.