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Training, Wages, and Sample Selection: Estimating Sharp Bounds on Treatment Effects

LEE, DAVID S.·2009·Review of Economic Studies
DOI 10.1111/j.1467-937x.2009.00536.x
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Abstract

This paper empirically assesses the wage effects of the Job Corps program, one of the largest federally funded job training programs in the U.S. Even with the aid of a randomized experiment, the impact of a training program on wages is difficult to study because of sample selection, a pervasive problem in applied microeconometric research. Wage rates are only observed for those who are employed, and employment status itself may be affected by the training program. This paper develops an intuitive trimming procedure for bounding average treatment effects in the presence of sample selection. In contrast to existing methods, the procedure requires neither exclusion restrictions nor a bounded support for the outcome of interest. Identification results, estimators, and their asymptotic distribution are presented. The bounds suggest that the program raised wages, consistent with the notion that the Job Corps raises earnings by increasing human capital, rather than solely through encouraging work. The estimator is generally applicable to typical treatment evaluation problems in which there is nonrandom sample selection/attrition. Copyright Copyright © 2009 The Review of Economic Studies Limited.

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Research works printed but not linked: 36

  1. AHN, 1993, “Semiparametric Estimation of Censored Selection Models with a Nonparametric Selection Mechanism”, Journal of Econometrics, 58, 3, 10.1016/0304-4076(93)90111-H · DOI · Paper page
  2. ANDREWS, D. W. K. (1994), “Empirical Process Methods in Econometrics”, in R. F.Engle and D. L.McFadden (eds.) Handbook of Eonometrics, Vol. 4 (Amsterdam: North Holland) 2248-2296.
  3. ANDREWS, 2007, “Performance of Conditional Wald Tests in IV Regression with Weak Instruments”, Journal of Econometrics, 139, 116, 10.1016/j.jeconom.2006.06.007 · DOI
  4. ANDREWS, 1998, “Semiparametric Estimation of the Intercept of a Sample Selection Model”, Review of Economic Studies, 65, 497, 10.1111/1467-937X.00055 · DOI
  5. ANGRIST, 1997, “Conditional Independence in Sample Selection Models”, Economics Letters, 54, 103, 10.1016/S0165-1765(97)00022-0 · DOI
  6. BALKE, 1997, “Bounds on Treatment Effects from Studies with Imperfect Compliance”, Journal of the American Statistical Association, 92, 1171, 10.1080/01621459.1997.10474074 · DOI · Paper page
  7. BARNOW, 1987, “The Impact of CETA on the Post-Program Earnings of Participants”, Journal of Human Resources, 22, 157, 10.2307/145901 · DOI · Paper page
  8. BLUNDELL, 2007, “Changes in the Distribution of Male and Female Wages Accounting for Employment Composition Using Bounds”, Econometrica, 75, 323, 10.1111/j.1468-0262.2006.00750.x · DOI · Paper page
  9. BURGHARDT, 2001, Does Job Corps Work? Summary of the National Job Corps Study
  10. CARD, 1999, Handbook of Labor Economics, 1801
  11. CHAMBERLAIN, G. (1994), “Quantile Regression, Censoring, and the Structure of Wages”, in C. A.Sims (ed.) Advances in Econometrics, Sixth World Congress, Vol. 1 (Cambridge: Cambridge University Press) 171-220. · DOI · Paper page
  12. DAS, 2003, “Nonparametric Estimation of Sample Selection Models”, Review of Economic Studies, 70, 33, 10.1111/1467-937X.00236 · DOI · Paper page
  13. HECKMAN, 1990, “Varieties of Selection Bias”, American Economic Review, 80, 313
  14. HECKMAN, J. J. , LALONDE, R. J. and SMITH, J. A. (1999), “The Economics and Econometrics of Active Labor Market Programs”, in O.Ashenfelter and D.Card (eds.) Handbook of Labor Economics, Vol. 3A (Amsterdam: North Holland) 1865-2097. · DOI · Paper page
  15. HECKMAN, 1986, Drawing Inferences from Self-selected Samples, 63, 10.1007/978-1-4612-4976-4_7 · DOI · Paper page
  16. HECKMAN, 1999, “Local Instrumental Variables and Semiparametric Estimation and Latent Variable Models for Identifying and Bounding Treatment Effects”, Proceedings of the National Academy of Sciences, 96, 4730, 10.1073/pnas.96.8.4730 · DOI · Paper page
  17. HECKMAN, J. J. and VYTLACIL, E. (2000a), “Instrumental Variables, Selection Models, and Tight Bounds on the Average Treatment Effect” (Technical Working Paper No. 259, National Bureau of Economic Research). · doi:10.3386/t0259
  18. HECKMAN, J. J. and VYTLACIL, E. (2000b), “Local Instrumental Variables” (Technical Working Paper No. 252, National Bureau of Economic Research). · DOI · Paper page
  19. HOLLISTER, 1984, The National Supported Work Demonstration
  20. HOROWITZ, 1995, “Identification and Robustness with Contaminated and Corrupted Data”, Econometrica, 63, 281, 10.2307/2951627 · DOI · Paper page
  21. HOROWITZ, 2000, “Nonparametric Analysis of Randomized Experiments with Missing Covariate and Outcome Data”, Journal of the American Statistical Association, 95, 77, 10.1080/01621459.2000.10473902 · DOI · Paper page
  22. HOROWITZ, 2000, “Rejoinder: Nonparametric Analysis of Randomized Experiments with Missing Covariate and Outcome Data”, Journal of the American Statistical Association, 95, 87
  23. IMBENS, 2004, “Confidence Intervals for Partially Identified Parameters”, Econometrica, 72, 1845, 10.1111/j.1468-0262.2004.00555.x · DOI · Paper page
  24. KIEFER, 1979, The Economic Benefits of Four Employment and Training Programs
  25. KRUEGER, 2001, “The Effect of Attending a Small Class in the Early Grades on College-Test Taking and Middle School Test Results: Evidence from Project STAR”, Economic Journal, 111, 1, 10.1111/1468-0297.00586 · DOI · Paper page
  26. LEE, D. S. (2002), “Trimming for Bounds on Treatment Effects with Missing Outcomes” (Center for Labor Economics Working Paper No. 38, University of California, Berkeley). · DOI
  27. LEE, D. S. (2005), “Training, Wages, and Sample Selection: Estimating Sharp Bounds on Treatment Effects” (NBER Working Paper No. 11721, National Bureau of Economic Research). · DOI · Paper page
  28. MARTIN, 2000, “What Works among Active Labour Market Policies: Evidence from OECD Countries' Experiences”, OECD Economic Studies, 30, 79
  29. NEWEY, W. K. and MCFADDEN, D. (1994), “Large Sample Estimation and Hypothesis Testing”, in R. F.Engle and D. L.McFadden (eds.) Handbook of Eonometrics, Vol. 4 (Amsterdam: North Holland) 2113-2245.
  30. ROBINS, J. (1989), “The Analysis of Randomized and Non-Randomized AIDS Treatment Trials Using a New Approach to Causal Inference in Longitudinal Studies”, in L.Sechrest, H.Freeman and A.Mulley (eds.) Health Service Research Methodology: A Focus on AIDS (Washington, DC: U.S. Public Health Service) 113-159.
  31. RUBIN, 1976, “Inference and Missing Data”, Biometrika, 63, 581, 10.1093/biomet/63.3.581 · DOI · Paper page
  32. SMITH, 1986, Closing the Gap: Forty Years of Economic Progress for Blacks
  33. STIGLER, 1973, “The Asymptotic Distribution of the Trimmed Mean”, Annals of Statistics, 1, 472, 10.1214/aos/1176342412 · doi:10.1214/aos/1176342412
  34. VYTLACIL, 2002, “Independence, Monotonicity, and Latent Index Models: An Equivalence Result”, Econometrica, 70, 331, 10.1111/1468-0262.00277 · DOI · Paper page
  35. ZHANG, 2003, “Estimation of Causal Effects via Principal Stratification When Some Outcomes Are Truncated by ‘Death’”, Journal of Educational and Behavioral Statistics, 28, 353, 10.3102/10769986028004353 · DOI · Paper page
  36. ZHANG, 2008, “Evaluating the Effects of Job Training Programs on Wages through Principal Stratification”, Modelling and Evaluating Treatment Effects in Econometrics, 119

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Metadata

Authors
LEE, D. S.
Venue
Review of Economic Studies
Publisher
Oxford University Press (OUP)
Published
2009-07
Volume
76
Issue
3
Pages
1071-1102
ISSN
  • 0034-6527 (ISSN-L)
  • 1467-937X
DOI
10.1111/j.1467-937x.2009.00536.x
OpenAlex
W2890543633
Cited by
1,399
References
6
FWCI
21.86
Type
journal article
Language
en
Open access
closed

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LEE, D. S. (2009). Training, Wages, and Sample Selection: Estimating Sharp Bounds on Treatment Effects. Review of Economic Studies. https://doi.org/10.1111/j.1467-937x.2009.00536.x

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