A Note on Adapting Propensity Score Matching and Selection Models to Choice Based Samples
James J. Heckman and
Petra Todd
No 15179, NBER Working Papers from National Bureau of Economic Research, Inc
Abstract:
The probability of selection into treatment plays an important role in matching and selection models. However, this probability can often not be consistently estimated, because of choice-based sampling designs with unknown sampling weights. This note establishes that the selection and matching procedures can be implemented using propensity scores fit on choice-based samples with misspecified weights, because the odds ratio of the propensity score fit on the choice-based sample is monotonically related to the odds ratio of the true propensity scores.
JEL-codes: C13 C51 (search for similar items in EconPapers)
Date: 2009-07
New Economics Papers: this item is included in nep-ecm
Note: TWP
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (55)
Published as James J. Heckman & Petra E. Todd, 2009. "A note on adapting propensity score matching and selection models to choice based samples," Econometrics Journal, Royal Economic Society, vol. 12(s1), pages S230-S234, 01.
Downloads: (external link)
http://www.nber.org/papers/w15179.pdf (application/pdf)
Related works:
Journal Article: A note on adapting propensity score matching and selection models to choice based samples (2009)
Working Paper: A Note on Adapting Propensity Score Matching and Selection Models to Choice Based Samples (2009) 
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:nbr:nberwo:15179
Ordering information: This working paper can be ordered from
http://www.nber.org/papers/w15179
Access Statistics for this paper
More papers in NBER Working Papers from National Bureau of Economic Research, Inc National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.. Contact information at EDIRC.
Bibliographic data for series maintained by ().