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Sample Attrition Bias in Randomized Experiments : A Table of Two Surveys




  • Bruno CREPON


  • Marc GURGAND





The randomized trial literature has helped to renew the field of microeconometric policy evaluation byemphasizing identification issues raised by endogenous program participation. Measurement andattrition issues have perhaps received less attention. This paper analyzes the dramatic impact of sampleattrition in a large job search experiment. We take advantage of two independent surveys on the sameinitial sample of 8,000 persons. The first one is a long telephone survey that had a strikingly low andunbalanced response rate of about 50%. The second one is a combination of administrative data and ashort telephone survey targeted at those leaving the unemployment registers; this enriched data sourcehas a balanced and much higher response rate (about 80%). With naive estimates that neglect nonresponses, these two sources yield puzzlingly different results.Using the enriched administrative data as benchmark, we find evidence that estimates from the longtelephone survey lack external and internal validity. We turn to existing methods to bound the effectsin the presence of sample selection; we extend them to the context of randomization with imperfectcompliance. The bounds obtained from the two surveys are compatible but those from the longtelephone survey are somewhat uninformative. We conclude on the consequences for data collectionstrategies.

Suggested Citation

  • Luc BEHAGHEL & Bruno CREPON & Marc GURGAND & Thomas LE BARBANCHON, 2009. "Sample Attrition Bias in Randomized Experiments : A Table of Two Surveys," Working Papers 2009-05, Center for Research in Economics and Statistics.
  • Handle: RePEc:crs:wpaper:2009-05

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    References listed on IDEAS

    1. David Card & Raj Chetty & Andrea Weber, 2007. "The Spike at Benefit Exhaustion: Leaving the Unemployment System or Starting a New Job?," American Economic Review, American Economic Association, vol. 97(2), pages 113-118, May.
    2. Duflo, Esther & Glennerster, Rachel & Kremer, Michael, 2008. "Using Randomization in Development Economics Research: A Toolkit," Handbook of Development Economics, Elsevier.
    3. Ashenfelter, Orley & Ashmore, David & Deschenes, Olivier, 2005. "Do unemployment insurance recipients actively seek work? Evidence from randomized trials in four U.S. States," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 53-75.
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    Cited by:

    1. Damon Jones & Aprajit Mahajan, 2015. "Time-Inconsistency and Saving: Experimental Evidence from Low-Income Tax Filers," NBER Working Papers 21272, National Bureau of Economic Research, Inc.

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    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • J68 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Public Policy


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