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

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  • Qu, Xi
  • Lee, Lung-fei

Abstract

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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    as
    1. Robert Jong & Ana María Herrera, 2011. "Dynamic Censored Regression and the Open Market Desk Reaction Function," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(2), pages 228-237, April.
    2. Amemiya, Takeshi, 1973. "Regression Analysis when the Dependent Variable is Truncated Normal," Econometrica, Econometric Society, vol. 41(6), pages 997-1016, November.
    3. Lambert, Dayton M. & Brown, Jason P. & Florax, Raymond J.G.M., 2010. "A two-step estimator for a spatial lag model of counts: Theory, small sample performance and an application," Regional Science and Urban Economics, Elsevier, vol. 40(4), pages 241-252, July.
    4. H. Kelejian, Harry & Prucha, Ingmar R., 2001. "On the asymptotic distribution of the Moran I test statistic with applications," Journal of Econometrics, Elsevier, vol. 104(2), pages 219-257, September.
    5. William A. Brock & Steven N. Durlauf, 2001. "Discrete Choice with Social Interactions," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 68(2), pages 235-260.
    6. Pinkse, Joris & Slade, Margaret E., 1998. "Contracting in space: An application of spatial statistics to discrete-choice models," Journal of Econometrics, Elsevier, vol. 85(1), pages 125-154, July.
    7. Joris Pinkse & Margaret E. Slade, 2010. "The Future Of Spatial Econometrics," Journal of Regional Science, Wiley Blackwell, vol. 50(1), pages 103-117, February.
    8. Bhat, Chandra R. & Sener, Ipek N. & Eluru, Naveen, 2010. "A flexible spatially dependent discrete choice model: Formulation and application to teenagers' weekday recreational activity participation," Transportation Research Part B: Methodological, Elsevier, vol. 44(8-9), pages 903-921, September.
    9. Amemiya, Takeshi, 1974. "Multivariate Regression and Simultaneous Equation Models when the Dependent Variables Are Truncated Normal," Econometrica, Econometric Society, vol. 42(6), pages 999-1012, November.
    10. Corinne Autant‐Bernard & James P. LeSage, 2011. "Quantifying Knowledge Spillovers Using Spatial Econometric Models," Journal of Regional Science, Wiley Blackwell, vol. 51(3), pages 471-496, August.
    11. Smirnov, Oleg A., 2010. "Modeling spatial discrete choice," Regional Science and Urban Economics, Elsevier, vol. 40(5), pages 292-298, September.
    12. Olsen, Randall J, 1978. "Note on the Uniqueness of the Maximum Likelihood Estimator for the Tobit Model," Econometrica, Econometric Society, vol. 46(5), pages 1211-1215, September.
    13. Laurent Davezies & Xavier D'Haultfoeuille & Denis Fougère, 2009. "Identification of peer effects using group size variation," Econometrics Journal, Royal Economic Society, vol. 12(3), pages 397-413, November.
    14. Klier, Thomas & McMillen, Daniel P, 2008. "Clustering of Auto Supplier Plants in the United States," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 460-471.
    15. Jan K. Brueckner, 2003. "Strategic Interaction Among Governments: An Overview of Empirical Studies," International Regional Science Review, , vol. 26(2), pages 175-188, April.
    16. Lee, Lung-fei, 2007. "Identification and estimation of econometric models with group interactions, contextual factors and fixed effects," Journal of Econometrics, Elsevier, vol. 140(2), pages 333-374, October.
    17. Langyintuo, Augustine S. & Mekuria, Mulugetta, 2008. "Assessing the influence of neighborhood effects on the adoption of improved agricultural technologies in developing agriculture," African Journal of Agricultural and Resource Economics, African Association of Agricultural Economists, vol. 2(2), pages 1-19, August.
    18. Gourieroux, Christian & Monfort, Alain & Renault, Eric & Trognon, Alain, 1987. "Generalised residuals," Journal of Econometrics, Elsevier, vol. 34(1-2), pages 5-32.
    19. Corinne Autant-Bernard & James Lesage, 2011. "Quantifying knowledge spillovers using spatial econometric tools," Post-Print halshs-00617709, HAL.
    20. Lung-fei Lee & Xiaodong Liu & Xu Lin, 2010. "Specification and estimation of social interaction models with network structures," Econometrics Journal, Royal Economic Society, vol. 13(2), pages 145-176, July.
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    More about this item

    Keywords

    Spatial econometric models; LM tests; Limited dependent variables;
    All these keywords.

    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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