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A Spatial Cliff-Ord-Type Model With Heteroskedastic Innovations: Small And Large Sample Results

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

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 multistep GMM/IV-type estimation procedures for the parameters of the model. We also give the limiting distributions for our suggested estimators and consistent estimators for their asymptotic variance-covariance matrices. We conduct a Monte Carlo study to show that the derived large-sample distribution provides a good approximation to the actual small-sample distribution of our estimators. Copyright (c) 2009, Wiley Periodicals, Inc.

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Article provided by Wiley Blackwell in its journal Journal of Regional Science.

Volume (Year): 50 (2010)
Issue (Month): 2 ()
Pages: 592-614

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Handle: RePEc:bla:jregsc:v:50:y:2010:i:2:p:592-614
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  1. Kelejian, Harry H. & Prucha, Ingmar R., 2007. "HAC estimation in a spatial framework," Journal of Econometrics, Elsevier, vol. 140(1), pages 131-154, September.
  2. Luc Anselin & Julie Le Gallo, 2006. "Interpolation of Air Quality Measures in Hedonic House Price Models: Spatial Aspects This paper is part of a joint research effort with James Murdoch (University of Texas, Dallas) and Mark Thayer (San," Spatial Economic Analysis, Taylor & Francis Journals, vol. 1(1), pages 31-52.
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  7. Jeffrey P. Cohen & Catherine J. Morrison Paul, 2004. "Public Infrastructure Investment, Interstate Spatial Spillovers, and Manufacturing Costs," The Review of Economics and Statistics, MIT Press, vol. 86(2), pages 551-560, May.
  8. Harry H. Kelejian & Ingmar R. Prucha, 1995. "A Generalized Moments Estimator for the Autoregressive Parameter in a Spatial Model," Electronic Working Papers 95-001, University of Maryland, Department of Economics, revised Mar 1997.
  9. Holtz-Eakin, Douglas, 1994. "Public-Sector Capital and the Productivity Puzzle," The Review of Economics and Statistics, MIT Press, vol. 76(1), pages 12-21, February.
  10. Badi H. Baltagi & Peter Egger & Michael Pfaffermayr, 2005. "Estimating Models of Complex FDI: Are There Third-Country Effects?," Center for Policy Research Working Papers 73, Center for Policy Research, Maxwell School, Syracuse University.
  11. Harry H. Kelejian & Ingmar R. Prucha, 2008. "Specification and Estimation of Spatial Autoregressive Models with Autoregressive and Heteroskedastic Disturbances," CESifo Working Paper Series 2448, CESifo Group Munich.
  12. Kathleen P. Bell & Nancy E. Bockstael, 2000. "Applying the Generalized-Moments Estimation Approach to Spatial Problems Involving Microlevel Data," The Review of Economics and Statistics, MIT Press, vol. 82(1), pages 72-82, February.
  13. Lung-Fei Lee, 2004. "Asymptotic Distributions of Quasi-Maximum Likelihood Estimators for Spatial Autoregressive Models," Econometrica, Econometric Society, vol. 72(6), pages 1899-1925, November.
  14. Giorgio Topa, 2001. "Social Interactions, Local Spillovers and Unemployment," Review of Economic Studies, Oxford University Press, vol. 68(2), pages 261-295.
  15. Shroder, Mark, 1995. "Games the States Don't Play: Welfare Benefits and the Theory of Fiscal Federalism," The Review of Economics and Statistics, MIT Press, vol. 77(1), pages 183-91, February.
  16. Kelejian, Harry H. & Prucha, Ingmar R., 2004. "Estimation of simultaneous systems of spatially interrelated cross sectional equations," Journal of Econometrics, Elsevier, vol. 118(1-2), pages 27-50.
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