Estimation of spatial autoregressive models with boundary specification problem
This article examines the impact of the boundary specification problem upon the estimation of spatial autoregressive models within an instrumental variable (IV) framework. We show the usual IV estimator remains consistent and asymptotically normal, but incurs an asymptotic bias of order Op(n2/ν), where n2 is the number of boundary units and ν is the total sample size. Our results show some promise for IV based inference even in the presence of the boundary problem.
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- Kelejian, Harry H & Prucha, Ingmar R, 1998.
"A Generalized Spatial Two-Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances,"
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- Harry H. Kelejian & Ingmar R. Prucha, 1997. "A Generalized Spatial Two Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances," Electronic Working Papers 97-002, University of Maryland, Department of Economics, revised Aug 1997.
- Manski, C.F., 1991.
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9127, Wisconsin Madison - Social Systems.
- Charles F. Manski, 1993. "Identification of Endogenous Social Effects: The Reflection Problem," Review of Economic Studies, Oxford University Press, vol. 60(3), pages 531-542.
- Lung-fei Lee, 2003. "Best Spatial Two-Stage Least Squares Estimators for a Spatial Autoregressive Model with Autoregressive Disturbances," Econometric Reviews, Taylor & Francis Journals, vol. 22(4), pages 307-335.
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