Estimation of the Spatial Autoregressive Parameter by Two Stage Least Squares Procedures: A Serious Problem
Harry H. Kelejian and Ingmar Prucha ,
2
( 20 )
International Regional Science Review
103-111
April
1997
Abstract

Time series regression models that have autoregressive errors are often estimated by two-stage procedures which are based on the Cochrane-Orcutt (1949) transformation. It seems natural to also attempt the estimation of spatial regression models whose error terms are autoregressive in terms of an analogous transformation. Various two-stage least squares procedures suggest themselves in this context, including an analog to Durbin's (1960) procedure.

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