LM tests for spatial correlation in spatial models with limited dependent variables
AbstractModels 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.
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Bibliographic InfoArticle provided by Elsevier in its journal Regional Science and Urban Economics.
Volume (Year): 42 (2012)
Issue (Month): 3 ()
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Web page: http://www.elsevier.com/locate/regec
Spatial econometric models; LM tests; Limited dependent variables;
Find related papers by 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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