OLS-based estimation of the disturbance variance under spatial autocorrelation

Walter Krämer and Christoph Hanck

No 2006,42, Technical Reports from Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen

Abstract: 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.

Keywords: regression; spatial error correlation; bias; variance (search for similar items in EconPapers)
Date: 2006
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Working Paper: OLS-based estimation of the disturbance variance under spatial autocorrelation (2006)
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:sfb475:200642

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