The Information Basis of Matching with Propensity Score

Esfandiar Maasoumi and Ozkan Eren

No 606, Departmental Working Papers from Southern Methodist University, Department of Economics

Abstract: This paper examines the foundations for comparing individuals and treatment subjects in experimental and other program evaluation contexts. We raise the question of multiattribute "characterization" of individuals both theoretically and statistically. The paper examines the information basis of characterizing individuals and offers alternatives motivated by welfare and decision theories. The proposed method helps place propensity scores and other "matching" proposals in context and reveals their advantages and disadvantages. We do not find the implied theoretical assumptions underlying propensity scores to be attractive or robust. Our proposal does not "solve" the matching problem, but provides bounds on inferences and makes clear the arbitrariness of specific solutions.

Keywords: treatment effect; information theory; multivariate scaling; propensity scores; utility functions; fundamentalism; Kullback-Leibler; entropy; aggregation. (search for similar items in EconPapers)
JEL-codes: F18 Q4 (search for similar items in EconPapers)
Date: 2006-12
New Economics Papers: this item is included in nep-exp and nep-upt
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://ftp1.economics.smu.edu/WorkingPapers/2006/maasoumi/paper6.pdf (application/pdf)

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:smu:ecowpa:0606

Access Statistics for this paper

More papers in Departmental Working Papers from Southern Methodist University, Department of Economics Department of Economics, P.O. Box 750496, Southern Methodist University, Dallas, TX 75275-0496.
Bibliographic data for series maintained by Ömer Özak ().