This paper suggests an improved GMM estimator for the autoregressive parameter of a spatial autoregressive error model by taking into account that unobservable regression disturbances are different from observable regression residuals. Although this difference decreases in large samples, it is...

Most of the estimators suggested for the estimation of spatial autoregressive models are generally inconsistent in the presence of an unknown form of heteroskedasticity in the disturbance term. The estimators formulated from the generalized method of moments (GMM) and the Bayesian Markov Chain...

This paper develops an estimator for higher-order spatial autoregressive panel data error component models with spatial autoregressive disturbances, SARAR(R,S). We derive the moment conditions and optimal weighting matrix without distributional assumptions for a generalized moments (GM)...