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

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  • David S. Lee

Abstract

This paper empirically assesses the wage effects of the Job Corps program, one of the largest federally-funded job training programs in the United States. 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 micro-econometric 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 non-random sample selection/attrition.

Suggested Citation

  • David S. Lee, 2005. "Training, Wages, and Sample Selection: Estimating Sharp Bounds on Treatment Effects," NBER Working Papers 11721, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:11721
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    3. Brunello, Giorgio & Comi, Simona Lorena & Sonedda, Daniela, 2010. "Training Subsidies and the Wage Returns to Continuing Vocational Training: Evidence from Italian Regions," IZA Discussion Papers 4861, Institute of Labor Economics (IZA).
    4. Robert W. Fairlie & Florian Hoffmann & Philip Oreopoulos, 2014. "A Community College Instructor Like Me: Race and Ethnicity Interactions in the Classroom," American Economic Review, American Economic Association, vol. 104(8), pages 2567-2591, August.
    5. Andrea Cegolon, 2015. "Determinants and Learning Effects of Adult Education-Training: a Cross-National Comparison Using PIAAC Data," DoQSS Working Papers 15-11, Quantitative Social Science - UCL Social Research Institute, University College London.
    6. KAWAGUCHI Daiji & NAITO Hisahiro, 2006. "The Bound Estimate of the Gender Wage Convergence under Employment Compositional Change," ESRI Discussion paper series 161, Economic and Social Research Institute (ESRI).
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    9. Quintini, Glenda & Martin, John P. & Martin, Sébastien, 2007. "The Changing Nature of the School-to-Work Transition Process in OECD Countries," IZA Discussion Papers 2582, Institute of Labor Economics (IZA).
    10. Suresh de Mel & David McKenzie & Christopher Woodruff, 2009. "Returns to Capital in Microenterprises: Evidence from a Field Experiment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 124(1), pages 423-423.
    11. Florian Hoffmann & Philip Oreopoulos, 2009. "A Professor Like Me: The Influence of Instructor Gender on College Achievement," Journal of Human Resources, University of Wisconsin Press, vol. 44(2).
    12. Pablo Cotler & Christopher Woodruff, 2008. "The Impact of Short-Term Credit on Microenterprises: Evidence from the Fincomun-Bimbo Program in Mexico," Economic Development and Cultural Change, University of Chicago Press, vol. 56(4), pages 829-849, July.
    13. Gustavo J. Bobonis & Edward Miguel & Charu Puri-Sharma, 2006. "Anemia and School Participation," Journal of Human Resources, University of Wisconsin Press, vol. 41(4).
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    15. Clint Harris & Jon Eckhardt & Brent Goldfarb, 2024. "A Survey Selection Correction using Nonrandom Followup with an Application to the Gender Entrepreneurship Gap," Papers 2404.17693, arXiv.org.
    16. Helen Connolly & Peter Gottschalk, 2009. "Do earnings subsidies affect job choice? The impact of SSP subsidies on job turnover and wage growth," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 42(4), pages 1276-1304, November.
    17. Melissa A. Clark & Philip Gleason & Christina Clark Tuttle & Marsha K. Silverberg, 2011. "Do Charter Schools Improve Student Achievement? Evidence from a National Randomized Study," Mathematica Policy Research Reports af41392138504f369930e6f2b, Mathematica Policy Research.
    18. Sheena McConnell & Elizabeth A. Stuart & Barbara Devaney, 2008. "The Truncation-by-Death Problem," Evaluation Review, , vol. 32(2), pages 157-186, April.
    19. Christopher Blattman & Jeannie Annan, 2010. "The Consequences of Child Soldiering," The Review of Economics and Statistics, MIT Press, vol. 92(4), pages 882-898, November.
    20. Michael Lechner & Blaise Melly, 2007. "Earnings Effects of Training Programs," University of St. Gallen Department of Economics working paper series 2007 2007-28, Department of Economics, University of St. Gallen.
    21. repec:mpr:mprres:7138 is not listed on IDEAS
    22. Philip Gleason & Melissa Clark & Christina Clark Tuttle & Emily Dwoyer, "undated". "The Evaluation of Charter School Impacts," Mathematica Policy Research Reports 3066da11915a4b04a77b38848, Mathematica Policy Research.
    23. World Demographic and Ageing Forum & David Bell & Alison Bowes & Axel Heitmueller, 2007. "Did the Introduction of Free Personal Care in Scotland in a Reduction of Informal Care?," Journal Article y:2007:i:1, World Demographic and Ageing Forum.
    24. Florence Kondylis & Valerie Mueller, 2014. "Economic consequences of conflict and environmental displacement," Chapters, in: Robert E.B. Lucas (ed.), International Handbook on Migration and Economic Development, chapter 14, pages 388-424, Edward Elgar Publishing.

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    More about this item

    JEL classification:

    • J0 - Labor and Demographic Economics - - General
    • J3 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling

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