Semiparametric estimation of a heteroskedastic sample selection model
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.
Type
Journal articlePermalink
https://hdl.handle.net/10161/2541Published Version (Please cite this version)
10.1017/S0266466603196077Publication Info
Chen, S; & Khan, S (2003). Semiparametric estimation of a heteroskedastic sample selection model. Econometric Theory, 19(6). pp. 1040-1064. 10.1017/S0266466603196077. Retrieved from https://hdl.handle.net/10161/2541.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
Collections
More Info
Show full item recordScholars@Duke
Shakeeb Khan
Professor of Economics
Professor Khan is on leave at Boston College for the 2016-17 academic year.Professor
Khan specializes in the fields of mathematical economics, statistics, and applied
econometrics. His studies have explored a variety of subjects from covariate dependent
censoring and non-stationary panel data, to causal effects of education on wage inequality
and the variables affecting infant mortality rates in Brazil. He was awarded funding
by National Science Foundation grants for his projects ent

Articles written by Duke faculty are made available through the campus open access policy. For more information see: Duke Open Access Policy
Rights for Collection: Scholarly Articles
Works are deposited here by their authors, and represent their research and opinions, not that of Duke University. Some materials and descriptions may include offensive content. More info