Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/20925 
Year of Publication: 
1999
Series/Report no.: 
IZA Discussion Papers No. 91
Publisher: 
Institute for the Study of Labor (IZA), Bonn
Abstract: 
The assumption that the assignment to treatments is ignorable conditional on attributes plays an important role in the applied statistic and econometric evaluation literature. Another term for it is conditional independence assumption. This paper discusses identification when there are more than two types of mutually exclusive treatments. It turns out that low dimensional balancing scores, similar to the ones valid in the case of only two treatments, exist and be used for identification of various causal effects. Therefore, a comparable reduction of the dimension of the estimation problem is achieved and the approach retains its basic simplicity. The paper also outlines a matching estimator potentially suitable in that framework.
Subjects: 
Treatment effects
balancing score
propensity score
causal model
program evaluation
matching
JEL: 
C30
C40
Document Type: 
Working Paper

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