Semiparametric estimation of a heteroskedastic sample selection model

dc.contributor.author

Chen, S

dc.contributor.author

Khan, S

dc.date.accessioned

2010-06-28T18:49:45Z

dc.date.issued

2003-12-01

dc.description.abstract

This paper considers estimation of a sample selection model subject to conditional heteroskedasticity in both the selection and outcome equations. The form of heteroskedasticity allowed for in each equation is multiplicative, and each of the two scale functions is left unspecified. A three-step estimator for the parameters of interest in the outcome equation is proposed. The first two stages involve nonparametric estimation of the "propensity score" and the conditional interquartile range of the outcome equation, respectively. The third stage reweights the data so that the conditional expectation of the reweighted dependent variable is of a partially linear form, and the parameters of interest are estimated by an approach analogous to that adopted in Ahn and Powell (1993, Journal of Econometrics 58, 3-29). Under standard regularity conditions the proposed estimator is shown to be √n-consistent and asymptotically normal, and the form of its limiting covariance matrix is derived.

dc.format.mimetype

application/pdf

dc.identifier.issn

0266-4666

dc.identifier.uri

https://hdl.handle.net/10161/2541

dc.language.iso

en_US

dc.publisher

Cambridge University Press (CUP)

dc.relation.ispartof

Econometric Theory

dc.relation.isversionof

10.1017/S0266466603196077

dc.title

Semiparametric estimation of a heteroskedastic sample selection model

dc.type

Journal article

pubs.begin-page

1040

pubs.end-page

1064

pubs.issue

6

pubs.organisational-group

Duke

pubs.organisational-group

Economics

pubs.organisational-group

Trinity College of Arts & Sciences

pubs.publication-status

Published

pubs.volume

19

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