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Accounting for Dropouts in Evaluations of Social Experiments

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Author Info

  • 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.

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Bibliographic Info

Paper provided by Chicago - Economics Research Center in its series University of Chicago - Economics Research Center with number 94-3.

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Length: 23 pages
Date of creation: 1994
Date of revision:
Handle: RePEc:fth:chicer:94-3

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Postal: UNIVERSITY OF CHICAGO, ECONOMICS RESEARCH CENTER, NORC, CHICAGO ILLINOIS 60637 U.S.A.
Phone: (773)834-0761
Web page: http://economics.uchicago.edu/research.shtml
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Keywords: evaluation;

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References

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  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.
  3. 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.
  4. Joshua D. Angrist & Guido W. Imbens, 1995. "Identification and Estimation of Local Average Treatment Effects," NBER Technical Working Papers 0118, National Bureau of Economic Research, Inc.
  5. Gary Burtless, 1985. "Are targeted wage subsidies harmful? Evidence from a wage voucher experiment," Industrial and Labor Relations Review, ILR Review, Cornell University, ILR School, vol. 39(1), pages 105-114, October.
  6. James J. Heckman, 1991. "Randomization and Social Policy Evaluation," NBER Technical Working Papers 0107, National Bureau of Economic Research, Inc.
  7. Arulampalam, W. & Robin A. Naylor & Jeremy P. Smith, 2002. "University of Warwick," Royal Economic Society Annual Conference 2002 9, Royal Economic Society.
  8. V. Joseph Hotz & Seth Sanders, . "Bounding Treatment Effects in Controlled and Natural Experiments Subject to Post-Randomization Treatment Choice," University of Chicago - Population Research Center 94-2, Chicago - Population Research Center.
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Cited by:
  1. 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.
  2. 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.
  3. repec:ese:iserwp:2004-01 is not listed on IDEAS
  4. Steven Lehrer & Weili Ding, 2004. "Estimating Dynamic Treatment Effects from Project STAR," Econometric Society 2004 North American Summer Meetings 252, Econometric Society.
  5. Battistin, Erich & Enrico Rettore, 2003. "Another look at the Regression Discontinuity Design," Royal Economic Society Annual Conference 2003 18, Royal Economic Society.
  6. James J. Heckman, 1995. "Randomization as an Instrumental Variable," NBER Technical Working Papers 0184, National Bureau of Economic Research, Inc.
  7. 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.
  8. 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.

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