Munich Personal RePEc Archive

Adaptive Experimental Design Using the Propensity Score

Hahn, Jinyong and Hirano, Keisuke and Karlan, Dean (2008): Adaptive Experimental Design Using the Propensity Score.

[img]
Preview
PDF
MPRA_paper_8315.pdf

Download (197kB) | Preview

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.

UB_LMU-Logo
MPRA is a RePEc service hosted by
the Munich University Library in Germany.