Inference on semiparametric models with discrete regressors

Delgado, Miguel A.; Mora, Juan

Publication:
Inference on semiparametric models with discrete regressors

dc.affiliation.dpto	UC3M. Departamento de Estadística	es
dc.contributor.author	Delgado, Miguel A.
dc.contributor.author	Mora, Juan
dc.contributor.editor	Universidad Carlos III de Madrid. Departamento de Estadística
dc.date.accessioned	2009-02-18T10:42:12Z
dc.date.available	2009-02-18T10:42:12Z
dc.date.issued	1993-02
dc.description.abstract	We study statistical properties of coefficient estimates of the partially linear regression model when some or all regressors, in the unknown part of the model, are discrete. The method does not require smoothing in the discrete variables. Unlike when there are continuous regressors. when all regressors are discrete independence between regressors and regression errors is not required. We also give some guidance on how to implement the estimate when there are both continuous and discrete regressors in the unknown part of the model. Weights employed in this paper seem straightforwardly applicable to other semiparametric problems.
dc.format.mimetype	application/pdf
dc.identifier.uri	https://hdl.handle.net/10016/3700
dc.language.iso	eng
dc.relation.ispartofseries	UC3M Working Papers. Statistics and Econometrics;
dc.relation.ispartofseries	1993-03-03
dc.rights	Atribución-NoComercial-SinDerivadas 3.0 España
dc.rights.accessRights	open access
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.eciencia	Estadística
dc.subject.other	Semiparametric partially linear model
dc.subject.other	Discrete regressors
dc.subject.other	Empirical conditional expectation estimate
dc.subject.other	Semiparametric efficiency bound
dc.subject.other	Higher order kernels
dc.title	Inference on semiparametric models with discrete regressors
dc.type	working paper	*
dspace.entity.type	Publication