Accounting for Dropouts in Evaluations of Social Experiments
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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|Date of creation:||1994|
|Date of revision:|
|Contact details of provider:|| Postal: UNIVERSITY OF CHICAGO, ECONOMICS RESEARCH CENTER, NORC, CHICAGO ILLINOIS 60637 U.S.A.|
Web page: http://economics.uchicago.edu/research.shtml
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- 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.
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- James J. Heckman, 1991. "Randomization and Social Policy Evaluation," NBER Technical Working Papers 0107, National Bureau of Economic Research, Inc.
- Heckman, James J, 1990. "Varieties of Selection Bias," American Economic Review, American Economic Association, vol. 80(2), pages 313-18, May.
- 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.
- 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.
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