Testing for Attrition Bias in Field Experiments

Dalia Ghanem (dghanem@ucdavis.edu), Sarojini Hirshleifer and Karen Ortiz-Becerra
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Dalia Ghanem: UC Davis

No 202010, Working Papers from University of California at Riverside, Department of Economics

Abstract: We approach attrition in field experiments with baseline outcome 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. We then derive their sharp testable implications on the baseline outcome distribution and propose randomization procedures to test them. We demonstrate that the most commonly used test does not control size in general when internal validity holds. Simulations and applications illustrate the empirical relevance of our analysis.

Keywords: attrition; non-response; treatment effects; field experiment; randomized experiment; randomized control trial; internal validity; identifying assumptions; randomization test; panel data (search for similar items in EconPapers)
JEL-codes: C12 C21 C23 C93 (search for similar items in EconPapers)
Date: 2019-08, Revised 2020-03
New Economics Papers: this item is included in nep-exp and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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https://economics.ucr.edu/repec/ucr/wpaper/202010.pdf First version, 2019 (application/pdf)
https://economics.ucr.edu/repec/ucr/wpaper/202010R.pdf Revised version, 2020 (application/pdf)

Related works:
Working Paper: Testing Attrition Bias in Field Experiments (2019)
Working Paper: Testing for Attrition Bias in Field Experiments (2019)
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Persistent link: https://EconPapers.repec.org/RePEc:ucr:wpaper:202010

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