A Spatial Cliff-Ord-type Model with Heteroskedastic Innovations: Small and Large Sample Results
AbstractIn 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.
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Bibliographic InfoPaper provided by CESifo Group Munich in its series CESifo Working Paper Series with number 2485.
Date of creation: 2008
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Find related papers by JEL classification:
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
- C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
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