Identification of Average Treatment Effects in Social Experiments Under Alternative Forms of Attrition

Martin Huber

Journal of Educational and Behavioral Statistics, 2012, vol. 37, issue 3, 443-474

Abstract: As any empirical method used for causal analysis, social experiments are prone to attrition which may flaw the validity of the results. This article considers the problem of partially missing outcomes in experiments. First, it systematically reveals under which forms of attrition—in terms of its relation to observable and/or unobservable factors—experiments do (not) yield causal parameters. Second, it shows how the various forms of attrition can be controlled for by different methods of inverse probability weighting (IPW) that are tailored to the specific missing data problem at hand. In particular, it discusses IPW methods that incorporate instrumental variables (IVs) when attrition is related to unobservables, which has been widely ignored in the experimental literature before.

Keywords: experiments; attrition; inverse probability weighting (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (21)

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Persistent link: https://EconPapers.repec.org/RePEc:sae:jedbes:v:37:y:2012:i:3:p:443-474

DOI: 10.3102/1076998611411917

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