EconPapers    
Economics at your fingertips  
 

Estimation of Heterogeneous Individual Treatment Effects With Endogenous Treatments

Qian Feng, Quang Vuong and Haiqing Xu

Journal of the American Statistical Association, 2020, vol. 115, issue 529, 231-240

Abstract: This article estimates individual treatment effects (ITE) and its probability distribution in a triangular model with binary-valued endogenous treatments. Our estimation procedure takes two steps. First, we estimate the counterfactual outcome and hence, the ITE for every observational unit in the sample. Second, we estimate the ITE density function of the whole population. Our estimation method does not suffer from the ill-posed inverse problem associated with inverting a nonlinear functional. Asymptotic properties of the proposed method are established. We study its finite sample properties in Monte Carlo experiments. We also illustrate our approach with an empirical application assessing the effects of 401(k) retirement programs on personal savings. Our results show that there exists a small but statistically significant proportion of individuals who experience negative effects, although the majority of ITEs is positive. Supplementary materials for this article are available online.

Date: 2020
References: Add references at CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://hdl.handle.net/10.1080/01621459.2018.1543121 (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:jnlasa:v:115:y:2020:i:529:p:231-240

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/UASA20

DOI: 10.1080/01621459.2018.1543121

Access Statistics for this article

Journal of the American Statistical Association is currently edited by Xuming He, Jun Liu, Joseph Ibrahim and Alyson Wilson

More articles in Journal of the American Statistical Association from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:jnlasa:v:115:y:2020:i:529:p:231-240