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Accounting for Dropouts in Evaluations of Social Experiments

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Author Info
James Heckman
Jeffrey Smith
Christopher Taber

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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.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Technical Working Papers with number 0166.

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Date of creation: Sep 1994
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Handle: RePEc:nbr:nberte:0166

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Find related papers by JEL classification:
C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Microeconomic Data
C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

  1. Heckman, James J, 1990. "Varieties of Selection Bias," American Economic Review, American Economic Association, vol. 80(2), pages 313-18, May.
  2. Joshua D. Angrist & Guido W. Imbens, 1991. "Sources of Identifying Information in Evaluation Models," NBER Technical Working Papers 0117, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  3. James J. Heckman, 1991. "Randomization and Social Policy Evaluation," NBER Technical Working Papers 0107, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  4. Gary Burtless, 1985. "Are targeted wage subsidies harmful? Evidence from a wage voucher experiment," Industrial and Labor Relations Review, ILR Review, ILR School, Cornell University, vol. 39(1), pages 105-114, October.
  5. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-75, March. [Downloadable!] (restricted)
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  6. Dubin, Jeffrey A. & Rivers, Douglas, 1993. "Experimental estimates of the impact of wage subsidies," Journal of Econometrics, Elsevier, vol. 56(1-2), pages 219-242, March. [Downloadable!] (restricted)
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. James J. Heckman, 1995. "Randomization as an Instrumental Variable," NBER Technical Working Papers 0184, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  2. Arulampalam, Wiji & Booth, Alison L & Bryan, Mark L, 2004. "Are There Asymmetries in the Effects of Training on the Conditional Male Wage Distribution?," CEPR Discussion Papers 4289, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
    Other versions:
  3. repec:ese:iserwp: is not listed on IDEAS
  4. James J. Heckman & Jeffrey A. Smith, 1997. "The Sensitivity of Experimental Impact Estimates: Evidence from the National JTPA Study," NBER Working Papers 6105, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  5. Erich Battistin & Enrico Rettore, 2003. "Another look at the regression discontinuity design," CeMMAP working papers CWP01/03, Centre for Microdata Methods and Practice, Institute for Fiscal Studies. [Downloadable!]
    Other versions:
  6. Steven Lehrer & Weili Ding, 2004. "Estimating Dynamic Treatment Effects from Project STAR," Econometric Society 2004 North American Summer Meetings 252, Econometric Society. [Downloadable!]
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