Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/22686
Authors: 
Krämer, Walter
Hanck, Christoph
Year of Publication: 
2006
Series/Report no.: 
Technical Report / Universität Dortmund, SFB 475 Komplexitätsreduktion in Multivariaten Datenstrukturen 2006,42
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.
Subjects: 
regression
spatial error correlation
bias
variance
Document Type: 
Working Paper

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