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

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dc.contributor.author Delgado, Miguel A.
dc.contributor.author Mora, Juan
dc.date.accessioned 2009-11-11T13:34:49Z
dc.date.available 2009-11-11T13:34:49Z
dc.date.issued 1998
dc.identifier.bibliographicCitation Journal of Applied Econometrics. 1998, vol. 13, p. 145-162
dc.identifier.issn 0883-7252
dc.identifier.uri http://hdl.handle.net/10016/2438
dc.description.abstract This 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.format.mimetype text/plain
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher John Wiley & Sons
dc.title Testing Non-nested Semiparametric Models: An Application to Engel Curves Specification
dc.type article
dc.type.review PeerReviewed
dc.description.status Publicado
dc.relation.publisherversion http://links.jstor.org/sici?sici=0883-7252%28199803%2F04%2913%3A2%3C145%3ATNSMAA%3E2.0.CO%3B2-N
dc.subject.eciencia Economía
dc.rights.accessRights openAccess
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