Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/27008 
Year of Publication: 
2008
Series/Report no.: 
Center Discussion Paper No. 969
Publisher: 
Yale University, Economic Growth Center, New Haven, CT
Abstract: 
Many social experiments are run in multiple waves, or are replications of earlier social experiments. In principle, the sampling design can be modified in later stages or replications to allow for more efficient estimation of causal effects. We consider the design of a two-stage experiment for estimating an average treatment effect, when covariate information is available for experimental subjects. We use data from the first stage to choose a conditional treatment assignment rule for units in the second stage of the experiment. This amounts to choosing the propensity score, the conditional probability of treatment given covariates. We propose to select the propensity score to minimize the asymptotic variance bound for estimating the average treatment effect. Our procedure can be implemented simply using standard statistical software and has attractive large-sample properties.
Subjects: 
experimental design
propensity score
efficiency bound
JEL: 
C1
C9
C13
C14
C93
Document Type: 
Working Paper

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