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Open Access Publications from the University of California

Testing Attrition Bias in Field Experiments

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We approach attrition in field experiments with baseline data as an identification problem in a panel model. A systematic review of the literature indicates that there is no consensus on how to test for attrition bias. We establish identifying assumptions for treatment effects for both the respondent subpopulation and the study population, and propose procedures to test their sharp implications. We then relate our proposed tests to current empirical practice, and demonstrate that the most commonly used test in the literature is not a test of internal validity in general. We illustrate the relevance of our analysis using several empirical applications.

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