The article investigates the finite sample properties of estimators for spatial autoregressive models where the disturbance terms may follow a spatial autoregressive process. In particular we investigate the finite sample behavior of the feasible generalized spatial two-stage least squares (FGS2SLS) estimator introduced by Kelejian and Prucha (1998), the maximum likelihood (ML) estimator, as well as that of several other estimators. We find that the FGS2SLS estimator is virtually as efficient as the ML estimator.
Finite Sample Properties of Estimators of Spatial Autoregressive Models with Autoregressive DisturbancesDebabrata Das, Harry H. Kelejian, and Ingmar Prucha ,
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Papers in Regional Science
Finite Sample Properties of Estimators of Spatial Autoregressive Models with Autoregressive Disturbances