The role of propensity score in the efficient estimation of the average treatment effects is examined. If the treatment is ignorable given some observed characteristics, it is shown that the propensity score is ancillary for estimation of the average treatment effects but not for estimation of average treatment effects on the treated. Efficient semiparametric estimators take the form of relevant sample averages of the data completed by the nonparametric imputation method. Projection on the propensity score is not necessary for efficient semiparametric estimation of the average treatment effects on the treated even if the propensity score is known.
Download Info
To our knowledge, this item is not available for
download. To find whether it is available, there are three
options:
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page
whether it is in fact available.
3. Perform a search for a similarly titled item that would be
available.
Publisher Info
Article provided by Econometric Society in its journal Econometrica.
Volume (Year): 66 (1998) Issue (Month): 2 (March) Pages: 315-332 Download reference. The following formats are available: HTML
(with abstract),
plain text
(with abstract),
BibTeX,
RIS (EndNote, RefMan, ProCite),
ReDIF
For technical questions regarding this item, or to correct its listing, contact: (Christopher F. Baum).
Related research
Keywords:
Other versions of this item:
Cited by: (explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.) This item has more than 25 citations. To prevent cluttering this page, these citations are listed on a separate page.
Did you know? All full texts are decentralized with the publishers, none reside on this server, thus making it possible to offer this service for free to all parties.