OLS-based estimation of the disturbance variance under spatial autocorrelation
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Date
2006-11-10T07:46:03Z
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Abstract
We investigate the OLS-based estimator s^2 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 s^2 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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Keywords
Bias, Regression, Spatial error correlation, Variance