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Accounting for Dropouts in Evaluations of Social Experiments

Author

Listed:
  • Heckman, J.
  • Smith, J.
  • Taber, C.

Abstract

This paper considers the statistical and economic justification for one widely-used method of adjusting data from social experiments to account for dropping-out behavior due to Bloom (1984). We generalize the method to apply to distributions not just means, and present tests of the key identifying assumption in this context. A reanalysis of the National JTPA experiment base vindicates application of Bloom's method in this context.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Heckman, J. & Smith, J. & Taber, C., 1994. "Accounting for Dropouts in Evaluations of Social Experiments," University of Chicago - Economics Research Center 94-3, Chicago - Economics Research Center.
    • Handle: RePEc:fth:chicer:94-3
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    Cited by:

    1. Peter Z. Schochet, "undated". "Statistical Theory for the RCT-YES Software: Design-Based Causal Inference for RCTs," Mathematica Policy Research Reports a0c005c003c242308a92c02dc, Mathematica Policy Research.
    2. Wiji Arulampalam & Alison Booth & Mark Bryan, 2010. "Are there asymmetries in the effects of training on the conditional male wage distribution?," Journal of Population Economics, Springer;European Society for Population Economics, vol. 23(1), pages 251-272, January.
    3. James J. Heckman, 1995. "Randomization as an Instrumental Variable," NBER Technical Working Papers 0184, National Bureau of Economic Research, Inc.
    4. Steven Lehrer & Weili Ding, 2004. "Estimating Dynamic Treatment Effects from Project STAR," Econometric Society 2004 North American Summer Meetings 252, Econometric Society.
    5. James J. Heckman & Jeffrey Smith, 2000. "The Sensitivity of Experimental Impact Estimates (Evidence from the National JTPA Study)," NBER Chapters, in: Youth Employment and Joblessness in Advanced Countries, pages 331-356, National Bureau of Economic Research, Inc.
    6. Erich Battistin & Enrico Rettore, 2003. "Another look at the regression discontinuity design," CeMMAP working papers 01/03, Institute for Fiscal Studies.
    7. Weili Ding & Steven F. Lehrer, 2010. "Estimating Treatment Effects from Contaminated Multiperiod Education Experiments: The Dynamic Impacts of Class Size Reductions," The Review of Economics and Statistics, MIT Press, vol. 92(1), pages 31-42, February.
    8. Richter, André & Robling, Per Olof, 2013. "Multigenerational e ffects of the 1918-19 influenza pandemic in Sweden," Working Paper Series 5/2013, Stockholm University, Swedish Institute for Social Research.
    9. James J. Heckman & Jeffrey A. Smith, 1995. "Assessing the Case for Social Experiments," Journal of Economic Perspectives, American Economic Association, vol. 9(2), pages 85-110, Spring.

    More about this item

    Keywords

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    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models

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