Anatomy of the Selection Problem

Charles Manski

Journal of Human Resources, 1989, vol. 24, issue 3, 343-360

Abstract: This article considers anew the problem of estimating a regression E(y|x) when realizations of (y, x) are sampled randomly but y is observed selectively. The central issue is the failure of the sampling process to identify E(y|x). The problem faced by the researcher is to find correct prior restrictions which, when combined with the data, identify the regression. Two kinds of restrictions are examined here. One, which has not been studied before, is a bound on the support of y. Such a bound implies a simple, useful bound on E(y|x). The other, which has received much attention, is a separability restriction derived from a latent variable model.

Date: 1989
References: Add references at CitEc
Citations: View citations in EconPapers (297)

Downloads: (external link)
http://www.jstor.org/stable/pdfplus/145818
A subscription is required to access pdf files. Pay per article is available.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:uwp:jhriss:v:24:y:1989:i:3:p:343-360

Access Statistics for this article

More articles in Journal of Human Resources from University of Wisconsin Press
Bibliographic data for series maintained by ().