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Estimation of spatial autoregressive models with boundary specification problem

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  • Zhang, Zhengyu
  • Tao, Ji
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    Abstract

    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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    File URL: http://www.sciencedirect.com/science/article/pii/S0165176512005447
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    Bibliographic Info

    Article provided by Elsevier in its journal Economics Letters.

    Volume (Year): 118 (2013)
    Issue (Month): 1 ()
    Pages: 130-134

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    Handle: RePEc:eee:ecolet:v:118:y:2013:i:1:p:130-134

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    Web page: http://www.elsevier.com/locate/ecolet

    Related research

    Keywords: Spatial autoregression; Social network; Missing data; Instrumental variable;

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    1. Manski, Charles F, 1993. "Identification of Endogenous Social Effects: The Reflection Problem," Review of Economic Studies, Wiley Blackwell, vol. 60(3), pages 531-42, July.
    2. 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.
    3. Kelejian, Harry H & Prucha, Ingmar R, 1998. "A Generalized Spatial Two-Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 99-121, July.
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