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

Author

Listed:
  • Irani Arraiz
  • David M. Drukker
  • Harry H. Kelejian
  • Ingmar R. Prucha

Abstract

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.

Suggested Citation

  • Irani Arraiz & David M. Drukker & Harry H. Kelejian & Ingmar R. Prucha, 2008. "A Spatial Cliff-Ord-type Model with Heteroskedastic Innovations: Small and Large Sample Results," CESifo Working Paper Series 2485, CESifo.
  • Handle: RePEc:ces:ceswps:_2485
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    More about this item

    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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