A Spatial Cliff-Ord-Type Model with Heteroskedastic Innovations: Small and Large Sample Results

By I. Arráiz, D. Drukker, Harry H. Kelejian, Ingmar R. Prucha. Social Science Research Network, 2009

347 citations recorded by the source corpus.

In this paper we specify a linear Cliff and Ord-type spatial model. The model allows for spatial lags in the dependent variable, the exogenous variables, and disturbances. The innovations in the disturbance process are assumed to be heteroskedastic with an unknown form. We formulate a multi-step GMM/IV type estimation procedure for the parameters of the model. We then establish the limiting distribution of our suggested estimators, and give consistent estimators for their asymptotic variance covariance matrices, utilizing results given in Kelejian and Prucha (2007b). Monte Carlo results are given which suggest that the derived large sample distribution provides a good approximation to the actual small sample distribution of our estimators.

Subfields: Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/21822f48427f6984e250ced1a8f460ba104fa562

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In Economics and Econometrics

Citations in the corpus

Forgetting the Flood? An Analysis of the Flood Risk Discount over Time (2013, methodology): “timator could produce inconsistent estimates in the presence of heteroskedasticity (Arraiz et al. 2010).”