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Semi-parametric estimation of the sample selection model

TLDR
In this article, the authors compare three types of nonparametric Maxfmum Zikelíhood estimators: Semt-nonparametrc MaxfmUM Zikellíhood, Semtnonparameter Zikeller estimators, and SingZe-equatton estimators.
Abstract
Esttmatfng a uxtge equatfon, account must be taken of the jact that ruages oj non-i,iorkers are not observed. For thts purpose, Heckman (1979) fntroduced the sample seLectfon modeL, consiating of troo equatíons: A(Línear) arage equatfon, explafning the potenttal Zog t,iage rate of every índívídual, incZudfng non-morkers, and a bfnary choice equatton, indícatíng ~uhether or not someone fs employed and the axige fa observed. TradíttonaL ML-eatfmatfon requfres a parametric specfftcatfon of the dtstributfon of the error terms, such as bivarfate normaZíty. Recently, a number of aemt-parametric estfmators have been developed mhích onZy requfre fndependence of the errors from the regressora ín both equations. We conatder three types o1 them: Semt-nonparametrtc Maxfmum Zikelíhood, ín mhich the parametera of interest and the densíty oJ the errors are eatimated afmuLtaneouaZy; 1}uo atage estfmators, generalizing the traditfonal Heckman ttoo step eatimator, míth semf-parametric estfmates o~ the bfnary chotce equatfon and a noriparametrfc correctton term added to the axige equatfon; and singZe-equatton estimators, neglecting irlJormation on non-raorkers. The estimators conaídered are asymptotícaZly normal, and aZZom Jor fnference. We preaent reaulta ,~or a sample of Dutch jemales and compare ~ith parametric !(L-estimatea. " We are grateful to the Netherlends Central Bureau of Statiatics (CBS) for providing the data. The views expressed i n this paper do not necessarily reflect the policies of the CBS. Financial support by the Netherlands Organisation of Scientific Research (NWO) and the Royal Netherlands Academy of Arts and Sciences (KNAW) is gratefully acknowledged by the first and second author, respectively. We are grateful for valuable commenta to Arie Kapteyn and seminar participants at CORE, (ironingen University, Tilburg University, and the Free University of Amsterdam.

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Journal ArticleDOI

Estimating Models with Sample Selection Bias: A Survey

TL;DR: In this paper, a survey of the available methods for estimating models with sample selection bias is presented, including semi-parametric and fully parameterized models, and the ability to tackle different selection rules generating the selection bias.
Report SeriesDOI

Endogeneity in nonparametric and semiparametric regression models

TL;DR: In this article, the authors consider the nonparametric and semiparametric methods for estimating regression models with continuous endogenous regressors and identify the "average structural function" as a parameter of central interest.
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Chapter 41 Estimation of semiparametric models

TL;DR: Semi-parametric models as mentioned in this paper combine a parametric form for some component of the data generating process (usually the behavioral relation between the dependent and explanatory variables) with weak nonparametric restrictions on the remainder of the model, usually the distribution of the unobservable errors.
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The public and private sector pay gap in Pakistan: a quantile regression analysis

TL;DR: In this article, the authors examined the magnitude of public/private wage differentials in Pakistan using data drawn from the 2001-02 Pakistan National Labour Force Survey and found that about two-fifths of the raw wage differential in average hourly wages between the two sectors is accounted for by differentially in average characteristics.
Journal ArticleDOI

Testing the normality assumption in the sample selection model with an application to travel demand

TL;DR: In this article, a test for the normality assumption in the sample selection model is introduced, based on a flexible parametric specification of the density function of the error terms in the model.
References
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Posted Content

Varieties of selection bias

Journal ArticleDOI

Semi-nonparametric maximum likelihood estimation

A. Ronald Gallant, +1 more
- 01 Mar 1987 - 
TL;DR: In this paper, an approche basee sur une innovation due a Phillips (1983) sur les approximations des fonctions de densite is proposed. But this approche is based on a different approach.
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An efficient semiparametric estimator for binary response models

Roger Klein, +1 more
- 01 Mar 1993 - 
TL;DR: In this article, an estimator for discrete choice models that makes no assumption concerning the functional form of the choice probability function, where this function can be characterized by an index, is proposed.
Journal ArticleDOI

Testing for normality.

TL;DR: The procedure of making confidence intervals is based on the assumption that the data is a random sample from a population with a normal population frequency curve, and different ways to check if this is true are discussed.
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Chapter 13 The economic analysis of labor market discrimination: A survey

TL;DR: A survey on the economics of labor market discrimination, motivated by two fundamental problems associated with income and wage differences among groups classified by sex, race, ethnicity, and other characteristics is presented in this article.
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