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Bounds on Average and Quantile Treatment Effects of Job Corps Training on Wages

Author

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  • German Blanco
  • Carlos A. Flores
  • Alfonso Flores-Lagunes
Abstract
We review and extend nonparametric partial identification results for average and quantile treatment effects in the presence of sample selection. These methods are applied to assessing the wage effects of Job Corps, United States’ largest job-training program targeting disadvantaged youth. Excluding Hispanics, our estimates suggest positive program effects on wages both at the mean and throughout the wage distribution. Across the demographic groups analyzed, the statistically significant estimated average and quantile treatment effects are bounded between 4.6 and 12 percent, and 2.7 and 14 percent, respectively. We also document that the program’s wage effects vary across quantiles and demographic groups.

Suggested Citation

  • German Blanco & Carlos A. Flores & Alfonso Flores-Lagunes, 2013. "Bounds on Average and Quantile Treatment Effects of Job Corps Training on Wages," Journal of Human Resources, University of Wisconsin Press, vol. 48(3), pages 659-701.
    • Handle: RePEc:uwp:jhriss:v:48:y:2013:iii:1:p:659-701
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    Cited by:

    1. Das, Tirthatanmoy & Polachek, Solomon, 2017. "Micro Foundations of Earnings Differences," IZA Discussion Papers 10922, Institute of Labor Economics (IZA).
    2. Bartalotti, Otávio & Kédagni, Désiré & Possebom, Vitor, 2023. "Identifying marginal treatment effects in the presence of sample selection," Journal of Econometrics, Elsevier, vol. 234(2), pages 565-584.
    3. María laura Alzúa & Guillermo Cruces & Carolina Lopez, 2016. "Long-Run Effects Of Youth Training Programs: Experimental Evidence From Argentina," Economic Inquiry, Western Economic Association International, vol. 54(4), pages 1839-1859, October.
    4. Lang, Julia & Dauth, Christine, 2017. "Should the unemployed care for the elderly? The effect of subsidized occupational and further training in geriatric care," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168130, Verein für Socialpolitik / German Economic Association.
    5. Damian Clarke & Manuel Llorca Jaña & Daniel Pailañir, 2023. "The use of quantile methods in economic history," Historical Methods: A Journal of Quantitative and Interdisciplinary History, Taylor & Francis Journals, vol. 56(2), pages 115-132, April.
    6. Amin, Vikesh & Flores, Carlos A. & Flores-Lagunes, Alfonso & Parisian, Daniel J., 2016. "The effect of degree attainment on arrests: Evidence from a randomized social experiment," Economics of Education Review, Elsevier, vol. 54(C), pages 259-273.
    7. Valente, Christine, 2019. "Primary education expansion and quality of schooling," Economics of Education Review, Elsevier, vol. 73(C).
    8. Chen, Xuan & Flores, Carlos A. & Flores-Lagunes, Alfonso, 2015. "Going Beyond LATE: Bounding Average Treatment Effects of Job Corps Training," IZA Discussion Papers 9511, Institute of Labor Economics (IZA).
    9. Xiaolin Sun & Xueyan Zhao & D. S. Poskitt, 2024. "Partially Identified Heterogeneous Treatment Effect with Selection: An Application to Gender Gaps," Papers 2410.01159, arXiv.org, revised Oct 2024.
    10. Bia, Michela & Flores-Lagunes, Alfonso & Mercatanti, Andrea, 2018. "Evaluation of Language Training Programs in Luxembourg using Principal Stratification," GLO Discussion Paper Series 289, Global Labor Organization (GLO).
    11. Krug, Gerhard & Stephan, Gesine, 2013. "Is the Contracting-Out of Intensive Placement Services More Effective than Provision by the PES? Evidence from a Randomized Field Experiment," IZA Discussion Papers 7403, Institute of Labor Economics (IZA).
    12. Possebom, Vitor, 2018. "Sharp bounds on the MTE with sample selection," MPRA Paper 89785, University Library of Munich, Germany.
    13. Huber, Martin & Meier, Jonas & Wallimann, Hannes, 2022. "Business analytics meets artificial intelligence: Assessing the demand effects of discounts on Swiss train tickets," Transportation Research Part B: Methodological, Elsevier, vol. 163(C), pages 22-39.
    14. Brigham R. Frandsen & Lars J. Lefgren, 2021. "Partial identification of the distribution of treatment effects with an application to the Knowledge is Power Program (KIPP)," Quantitative Economics, Econometric Society, vol. 12(1), pages 143-171, January.
    15. Strittmatter, Anthony, 2019. "Heterogeneous earnings effects of the job corps by gender: A translated quantile approach," Labour Economics, Elsevier, vol. 61(C).
    16. Michela Bia & German Blanco & Marie Valentova, 2021. "The Causal Impact of Taking Parental Leave on Wages: Evidence from 2005 to 2015," LISER Working Paper Series 2021-08, Luxembourg Institute of Socio-Economic Research (LISER).
    17. Dauth, Christine & Lang, Julia, 2017. "Should the unemployed care for the elderly? : The effect of subsidized occupational and further training in elderly care," IAB-Discussion Paper 201713, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    18. María Laura Alzúa & Guillermo Cruces & Carolina Lopez, 2015. "Youth Training Programs Beyond Employment. Experimental Evidence from Argentina," CEDLAS, Working Papers 0177, CEDLAS, Universidad Nacional de La Plata.

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    More about this item

    JEL classification:

    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • I38 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Government Programs; Provision and Effects of Welfare Programs
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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