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Title:Specification and estimation of spatial autoregressive models with autoregressive and heteroskedastic disturbances PDF Logo
Authors:Kelejian, Harry H.
Prucha, Ingmar R.
Issue Date:2008
Series/Report no.:CESifo working paper 2448
Abstract:One important goal of this study is to develop a methodology of inference for a widely used Cliff-Ord type spatial model containing spatial lags in the dependent variable, exogenous variables, and the disturbance terms, while allowing for unknown heteroskedasticity in the innovations. We first generalize the generalized moments (GM) estimator suggested in Kelejian and Prucha (1998, 1999) for the spatial autoregressive parameter in the disturbance process. We prove the consistency of our estimator; unlike in our earlier paper we also determine its asymptotic distribution, and discuss issues of efficiency. We then define instrumental variable (IV) estimators for the regression parameters of the model and give results concerning the joint asymptotic distribution of those estimators and the GM estimator under reasonable conditions. Much of the theory is kept general to cover a wide range of settings. We note the estimation theory developed by Kelejian and Prucha (1998, 1999) for GM and IV estimators and by Lee (2004) for the quasi-maximum likelihood estimator under the assumption of homoskedastic innovations does not carry over to the case of heteroskedastic innovations. The paper also provides a critical discussion of the usual specification of the parameter space.
Subjects:Spatial dependence
heteroskedasticity
Cliff-Ord model
two-stage least squares
generalized moments estimation
asymptotics
JEL:C21
C31
Document Type:Working Paper
Appears in Collections:CESifo Working Papers, CESifo Group Munich

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