Juan M. Rodriguez-Poo
;
Stefan Sperlich
;
Ana I. Fernández

semiparametric three-step estimation methods for simultaneous equation systems (replication data)

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.

Data and Resources

Suggested Citation

Rodriguez-Poo, Juan M.; Sperlich, Stefan; Fernández, Ana I. (2005): Semiparametric three-step estimation methods for simultaneous equation systems (replication data). Version: 1. Journal of Applied Econometrics. Dataset. http://dx.doi.org/10.15456/jae.2022319.0710358837