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A Semi-Nonparametric Estimator For Counts With An Endogenous Dummy Variable

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dc.creator Romeu, Andrés
dc.creator Vera-Hernández, Angel M.
dc.date 2007-11-08T16:07:41Z
dc.date 2007-11-08T16:07:41Z
dc.date 2000
dc.date.accessioned 2017-01-31T00:58:16Z
dc.date.available 2017-01-31T00:58:16Z
dc.identifier http://hdl.handle.net/10261/1968
dc.identifier.uri http://dspace.mediu.edu.my:8181/xmlui/handle/10261/1968
dc.description Treating endogeneity and flexibility in such a way that efficiency is not sacrified has become a rising point of interest in count data models. We use a polynomial expansion of a Poisson baseline density to compute the full information maximum likelihood (FIML) estimator. In order to test the model we propose measures of goodness of fit, information criteria, likelihood ratio and scores tests for evaluation. We also show how to compute statistics for sensitivity analysis. Then, we test our model using data on number of trips by households and number of physician office visits, finding that low order polynomials may be enough to improve fit significantly.
dc.description We benefitted from financial support of the Comissionat per a Universitats i Recerca de la Generalitat de Catalunya grant no. 1997FI-436, Universitat Autònoma de Barcelona AP92-34967274 and from Spanish Ministry of Education DGICYT PB96-1160.
dc.language eng
dc.relation UFAE and IAE Working Papers
dc.relation 452.00
dc.rights openAccess
dc.subject Polynomial Poisson expansion
dc.subject Flexible functional form
dc.subject Treatment effect
dc.subject Sensitivity analysis
dc.title A Semi-Nonparametric Estimator For Counts With An Endogenous Dummy Variable
dc.type Documento de trabajo


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