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Testing Non-nested Semiparametric Models: An Application to Engel Curves Specification

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dc.affiliation.dptoUC3M. Departamento de Economíaes
dc.contributor.authorDelgado, Miguel A.
dc.contributor.authorMora, Juan
dc.date.accessioned2009-11-11T13:34:49Z
dc.date.available2009-11-11T13:34:49Z
dc.date.issued1998
dc.description.abstractThis paper proposes a test statistic for discriminating between two partly non-linear regression models whose parametric components are non-nested. The statistic has the form of a J-test based on a parameter which artificially nests the null and alternative hypotheses. We study in detail the realistic case where all regressors in the non-linear part are discrete and then no smoothing is requiered on the estimating the non-parametric components.We also consider the general case where continuous and discrete regressors are present. The performance of the test in finite samples and discussed in the context of some Monte Carlo experiments. The test is well motivated for specification testing of Engel curves. We provide an application using data from the 1980 Spanish Expenditure Survey.
dc.description.statusPublicado
dc.format.mimetypetext/plain
dc.format.mimetypeapplication/pdf
dc.identifier.bibliographicCitationJournal of Applied Econometrics. 1998, vol. 13, p. 145-162
dc.identifier.issn0883-7252
dc.identifier.urihttps://hdl.handle.net/10016/2438
dc.language.isoeng
dc.publisherJohn Wiley & Sons
dc.relation.publisherversionhttp://links.jstor.org/sici?sici=0883-7252%28199803%2F04%2913%3A2%3C145%3ATNSMAA%3E2.0.CO%3B2-N
dc.rights.accessRightsopen access
dc.subject.ecienciaEconomía
dc.titleTesting Non-nested Semiparametric Models: An Application to Engel Curves Specification
dc.typeresearch article*
dc.type.reviewPeerReviewed
dspace.entity.typePublication
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