Asymptotics of improved generalized moment estimators for spatial autoregressive error models. (English) Zbl 1338.62062
Summary: This article considers linear models with a spatial autoregressive error structure. Extending M. Arnold and D. Wied [Econ. Lett. 108, No. 1, 65–68 (2010; Zbl 1201.62098)], who develop an improved generalized method of moment (GMM) estimator for the parameters of the disturbance process to reduce the bias of existing estimation approaches, we establish the asymptotic normality of a new weighted version of this improved estimator and derive the efficient weighting matrix. We also show that this efficiently weighted GMM estimator is feasible as long as the regression matrix of the underlying linear model is non stochastic and illustrate the performance of the new estimator by a Monte Carlo simulation and an application to real data.
Citations:
Zbl 1201.62098References:
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