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Testing Attrition Bias in Field Experiments

Author

Listed:
  • Dalia Ghanem
  • Sarojini Hirshleifer
  • Karen Ortiz-Becerra

Abstract

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 respondents 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.

Suggested Citation

  • Dalia Ghanem & Sarojini Hirshleifer & Karen Ortiz-Becerra, 2026. "Testing Attrition Bias in Field Experiments," Journal of Human Resources, University of Wisconsin Press, vol. 61(2), pages 690-731.
  • Handle: RePEc:uwp:jhriss:v:61:y:2026:i:2:p:690-731
    Note: DOI: https://doi.org/10.3368/jhr.0920-11190R2
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    More about this item

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments

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