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Semiparametric three‐step estimation methods for simultaneous equation systems
Author(s) -
RodríguezPóo Juan M.,
Sperlich Stefan,
Fernández Ana I.
Publication year - 2005
Publication title -
journal of applied econometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.878
H-Index - 99
eISSN - 1099-1255
pISSN - 0883-7252
DOI - 10.1002/jae.796
Subject(s) - nonparametric statistics , estimation , econometrics , wage , work (physics) , maximum likelihood , parametric statistics , function (biology) , likelihood function , econometric model , mathematics , estimating equations , generalized method of moments , structural equation modeling , economics , structural estimation , statistics , panel data , engineering , market economy , mechanical engineering , management , evolutionary biology , biology
This paper proposes a new method for estimating a structural model of labour supply in which hours of work depend on (log) wages and the wage rate is considered endogenous. The main innovation with respect to other related estimation procedures is that a nonparametric additive structure in the hours of work equation is permitted. Though the focus of the paper is on this particular application, a three‐step methodology for estimating models in the presence of the above econometric problems is described. In the first step the reduced form parameters of the participation equation are estimated by a maximum likelihood procedure adapted for estimation of an additive nonparametric function. In the second step the structural parameters of the wage equation are estimated after obtaining the selection‐corrected conditional mean function. Finally, in the third step the structural parameters of the labour supply equation are estimated using local maximum likelihood estimation techniques. The paper concludes with an application to illustrate the feasibility, performance and possible gain of using this method. Copyright © 2005 John Wiley & Sons, Ltd.