Identification and estimation in a linear correlated random coefficients model with censoring

Zhengyu Zhang and Zequn Jin

Econometric Reviews, 2019, vol. 39, issue 2, 196-213

Abstract: In this paper, we study the identification and estimation of a linear correlated random coefficients model with censoring, namely, Y=max{B0+X′B,C}, where C is a known constant or an unknown function of regressors. Here, random coefficients (B0,B) can be correlated with one or more components of X. Under a generalized conditional median restriction similar to that in Hoderlein and Sherman, we show that both the average partial effect and the average partial effect on the treated are identified. We develop estimators for the identified parameters and analyze their large sample properties. A Monte Carlo simulation indicates that our estimators perform reasonably well with small samples. We then present an application.

Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.1080/07474938.2019.1580949 (text/html)
Access to full text is restricted to subscribers.

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:taf:emetrv:v:39:y:2019:i:2:p:196-213

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/LECR20

DOI: 10.1080/07474938.2019.1580949

Access Statistics for this article

Econometric Reviews is currently edited by Dr. Essie Maasoumi

More articles in Econometric Reviews from Taylor & Francis Journals
Bibliographic data for series maintained by ().