Assessing the performance of matching algorithms when selection into treatment is strong
Jochen Kluve () and
Boris Augurzky ()
Journal of Applied Econometrics, 2007, vol. 22, issue 3, 533-557
This paper investigates the method of matching regarding two crucial implementation choices: the distance measure and the type of algorithm. We implement optimal full matching-a fully efficient algorithm-and present a framework for statistical inference. The implementation uses data from the NLSY79 to study the effect of college education on earnings. We find that decisions regarding the matching algorithm depend on the structure of the data: In the case of strong selection into treatment and treatment effect heterogeneity a full matching seems preferable. If heterogeneity is weak, pair matching suffices. Copyright © 2007 John Wiley & Sons, Ltd.
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (15) Track citations by RSS feed
Downloads: (external link)
http://hdl.handle.net/10.1002/jae.919 Link to full text; subscription required (text/html)
http://qed.econ.queensu.ca:80/jae/2007-v22.3/ Supporting data files and programs (text/html)
Working Paper: Assessing the Performance of Matching Algorithms When Selection into Treatment Is Strong (2004)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:jae:japmet:v:22:y:2007:i:3:p:533-557
Ordering information: This journal article can be ordered from
http://www3.intersci ... e.jsp?issn=0883-7252
Access Statistics for this article
Journal of Applied Econometrics is currently edited by M. Hashem Pesaran
More articles in Journal of Applied Econometrics from John Wiley & Sons, Ltd.
Bibliographic data for series maintained by Wiley-Blackwell Digital Licensing () and Christopher F. Baum ().