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Identification and QML estimation of multivariate and simultaneous equations spatial autoregressive models

Listed author(s):
  • Yang, Kai
  • Lee, Lung-fei
Registered author(s):

    This paper investigates a simultaneous equations spatial autoregressive model which incorporates simultaneity effects, own-variable spatial lags and cross-variable spatial lags as explanatory variables, and allows for correlation between disturbances across equations. In exposition, we also discuss a multivariate spatial autoregressive model that can be treated as a reduced form of the simultaneous equations model. We study parameter spaces, parameter identification, asymptotic properties of the quasi-maximum likelihood estimation, and computational issues. Monte Carlo experiments illustrate the advantages of the QML, broader applicability and efficiency, compared to instrumental variables based estimation methods in the existing literature.

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    File URL: http://www.sciencedirect.com/science/article/pii/S0304407616301683
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    Article provided by Elsevier in its journal Journal of Econometrics.

    Volume (Year): 196 (2017)
    Issue (Month): 1 ()
    Pages: 196-214

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    Handle: RePEc:eee:econom:v:196:y:2017:i:1:p:196-214
    DOI: 10.1016/j.jeconom.2016.04.019
    Contact details of provider: Web page: http://www.elsevier.com/locate/jeconom

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