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Please Call Again: Correcting Nonresponse Bias in Treatment Effect Models

Author

Listed:
  • Luc Behaghel

    (Paris School of Economics, Inra)

  • Bruno Crépon

    (Crest)

  • Marc Gurgand

    (Paris School of Economics, CNRS)

  • Thomas Le Barbanchon

    (Bocconi University and IGIER)

Abstract

We propose a novel selectivity correction procedure to deal with survey attrition in treatment effect models, at the crossroads of the Heckit model and the bounding approach of Lee (2009). As a substitute for the instrument needed in sample selectivity correction models, we use information on the number of prior calls made to each individual before obtaining a response to the survey. We obtain sharp bounds to the average treatment effect on the common support of responding individuals. Because the number of prior calls brings information, we can obtain tighter bounds than in other nonparametric methods.

Suggested Citation

  • Luc Behaghel & Bruno Crépon & Marc Gurgand & Thomas Le Barbanchon, 2015. "Please Call Again: Correcting Nonresponse Bias in Treatment Effect Models," The Review of Economics and Statistics, MIT Press, vol. 97(5), pages 1070-1080, December.
    • Handle: RePEc:tpr:restat:v:97:y:2015:i:5:p:1070-1080
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    Keywords

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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
    • J6 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers

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