Testing non-nested semiparametric models: An application to engel curves specification

Juan Mora () and Miguel A. Delgado González
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Miguel A. Delgado González: Universidad Carlos III de Madrid

Working Papers. Serie AD from Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie)

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 nonlinear part are discrete and then no smoothing is required on estimating the nonparametric components. We also consider the general case where continuous and discrete regressors are present. The performance of the test in finite samples is 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.

Keywords: Engel curves; non-nested models; semiparametric estimation (search for similar items in EconPapers)
Pages: 40 pages
Date: 1996-12
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http://www.ivie.es/downloads/docs/wpasad/wpasad-1996-21.pdf Fisrt version / Primera version, 1996 (application/pdf)

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Journal Article: Testing non-nested semiparametric models: an application to Engel curves specification (1998)
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Persistent link: https://EconPapers.repec.org/RePEc:ivi:wpasad:1996-21

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