OLS-based estimation of the disturbance variance under spatial autocorrelation

We investigate the OLS-based estimator s2 of the disturbance variance in the standard linear regression model with cross section data when the disturbances are homoskedastic, but spatially correlated. For the most popular model of spatially autoregressive disturbances, we show that s2 can be severely biased in finite samples, but is asymptotically unbiased and consistent for most types of spatial weighting matrices as sample size increases.

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Authors:	Krämer, Prof. Dr. Walter ; Hanck, Dr. Christoph
Institutions:	Institut für Wirtschafts- und Sozialstatistik, Universität Dortmund
Subject:	regression \| spatial error correlation \| bias \| variance

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Series:	Working Papers.
Type of publication:	Book / Working Paper
Notes:	Published in Recent Advances in Linear Models and Related Areas, 2008, pages 357-366 11 pages
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005549263