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Activity Number: 55
Type: Topic Contributed
Date/Time: Sunday, July 29, 2007 : 4:00 PM to 5:50 PM
Sponsor: IMS
Abstract - #309449
Title: Mis-specified Maximum Likelihood Estimates and Spatial Error Models
Author(s): Jiehua Chen*+ and Paul Switzer
Companies: Stanford University and Stanford University
Address: Statistics Department, Stanford, CA, 94305,
Keywords:
Abstract:

The paper investigates the impact of covariance model misspecification on the estimates of the regression coefficients in a spatial error model. Spatial error models are the regression models which have spatially indexed observations and spatially correlated residuals. Specifically, we evaluate the asymptotic bias for the regression coefficients and estimates of the standard errors of coefficients that results from incorrect assumptions regarding the covariance matrix of the error term. The asymptotic bias is the lower bound of the bias and the paper also tries to shed some lights on the possible upper bound of bias by simulations.

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Revised September, 2007