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LM tests for spatial correlation in spatial models with limited dependent variables


  • Qu, Xi
  • Lee, Lung-fei


Models of limited dependent variables are of great interest in econometrics. This paper focuses on the specification and hypothesis test of spatial models which have a Tobit structure. We derive an extended central limit theorem for statistics of a linear–quadratic form with multivariate random variables. We consider the LM statistics for testing spatial correlation and establish their asymptotic distributions. The tests are applied to an empirical example: we detect the presence of competition among school districts on school district income tax in Iowa.

Suggested Citation

  • Qu, Xi & Lee, Lung-fei, 2012. "LM tests for spatial correlation in spatial models with limited dependent variables," Regional Science and Urban Economics, Elsevier, vol. 42(3), pages 430-445.
  • Handle: RePEc:eee:regeco:v:42:y:2012:i:3:p:430-445 DOI: 10.1016/j.regsciurbeco.2011.11.001

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    References listed on IDEAS

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    Cited by:

    1. Heijnen, P. & Samarina, A.. & Jacobs, J.P.A.M. & Elhorst, J.P., 2013. "State transfers at different moments in time," Research Report 13006-EEF, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    2. Ming He & Kuan-Pin Lin, 2015. "Testing in a Random Effects Panel Data Model with Spatially Correlated Error Components and Spatially Lagged Dependent Variables," Econometrics, MDPI, Open Access Journal, vol. 3(4), pages 1-36, November.
    3. Qu, Xi & Lee, Lung-fei, 2013. "Locally most powerful tests for spatial interactions in the simultaneous SAR Tobit model," Regional Science and Urban Economics, Elsevier, vol. 43(2), pages 307-321.
    4. T. Arduini, 2016. "Distribution Free Estimation of Spatial Autoregressive Binary Choice Panel Data Models," Working Papers wp1052, Dipartimento Scienze Economiche, Universita' di Bologna.
    5. Yang, Kai & Lee, Lung-fei, 2017. "Identification and QML estimation of multivariate and simultaneous equations spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 196(1), pages 196-214.
    6. repec:dgr:rugsom:13006-eef is not listed on IDEAS
    7. Anna Gloria Billé & Samantha Leorato, 2017. "Quasi-ML estimation, Marginal Effects and Asymptotics for Spatial Autoregressive Nonlinear Models," BEMPS - Bozen Economics & Management Paper Series BEMPS44, Faculty of Economics and Management at the Free University of Bozen.
    8. He, Ming & Lin, Kuan-Pin, 2013. "Locally adjusted LM test for spatial dependence in fixed effects panel data models," Economics Letters, Elsevier, vol. 121(1), pages 59-63.
    9. Qu, Xi & Lee, Lung-fei, 2015. "Estimating a spatial autoregressive model with an endogenous spatial weight matrix," Journal of Econometrics, Elsevier, vol. 184(2), pages 209-232.
    10. He, Ming & Lin, Kuan-Pin, 2015. "Testing spatial effects and random effects in a nested panel data model," Economics Letters, Elsevier, vol. 135(C), pages 85-91.
    11. Xu, Xingbai & Lee, Lung-fei, 2015. "Maximum likelihood estimation of a spatial autoregressive Tobit model," Journal of Econometrics, Elsevier, vol. 188(1), pages 264-280.
    12. Lei, J., 2014. "Essays on nonlinear panel data models," Other publications TiSEM 302d1ae7-0310-43b0-b253-6, Tilburg University, School of Economics and Management.

    More about this item


    Spatial econometric models; LM tests; Limited dependent variables;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • R50 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - General


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