IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/25408.html
   My bibliography  Save this paper

Dynamic Treatment Effects of Job Training

Author

Listed:
  • Jorge Rodríguez
  • Fernando Saltiel
  • Sergio S. Urzúa

Abstract

This paper estimates the dynamic returns to job training. We posit a dynamic-discrete choice model of sequential training participation, where choices and earnings depend on observed and unobserved characteristics.We define treatment effects, including policy relevant parameters, and link them to continuation values. The empirical analysis is carried out using data combining job training records, matched employee-employer information, and pre-labor market ability measures from Chile. We document small positive average returns, large unobserved heterogeneity in responses, and dynamic substitutability of training investments. Our policy relevant treatment effects vary across dynamic response types, highlighting the relevance of our framework.

Suggested Citation

  • Jorge Rodríguez & Fernando Saltiel & Sergio S. Urzúa, 2018. "Dynamic Treatment Effects of Job Training," NBER Working Papers 25408, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:25408
    Note: LS
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w25408.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Jeremy Lise & Fabien Postel-Vinay, 2020. "Multidimensional Skills, Sorting, and Human Capital Accumulation," American Economic Review, American Economic Association, vol. 110(8), pages 2328-2376, August.
    2. Orazio Attanasio & Arlen Guar�n & Carlos Medina & Costas Meghir, 2015. "Long Term Impacts of Vouchers for Vocational Training: Experimental Evidence for Colombia," Borradores de Economia 13326, Banco de la Republica.
    3. James J. Heckman & Stefano Mosso, 2014. "The Economics of Human Development and Social Mobility," Annual Review of Economics, Annual Reviews, vol. 6(1), pages 689-733, August.
    4. David Card & Jochen Kluve & Andrea Weber, 2010. "Active Labour Market Policy Evaluations: A Meta-Analysis," Economic Journal, Royal Economic Society, vol. 120(548), pages 452-477, November.
    5. Bocar A. Ba & John C. Ham & Robert J. LaLonde & Xianghong Li, 2017. "Estimating (Easily Interpreted) Dynamic Training Effects from Experimental Data," Journal of Labor Economics, University of Chicago Press, vol. 35(S1), pages 149-200.
    6. Pedro Carneiro & James J. Heckman & Edward Vytlacil, 2010. "Evaluating Marginal Policy Changes and the Average Effect of Treatment for Individuals at the Margin," Econometrica, Econometric Society, vol. 78(1), pages 377-394, January.
    7. A. Smith, Jeffrey & E. Todd, Petra, 2005. "Does matching overcome LaLonde's critique of nonexperimental estimators?," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 305-353.
    8. Orazio Attanasio & Sarah Cattan & Emla Fitzsimons & Costas Meghir & Marta Rubio-Codina, 2015. "Estimating the Production Function for Human Capital: Results from a Randomized Control Trial in Colombia," Cowles Foundation Discussion Papers 1987, Cowles Foundation for Research in Economics, Yale University.
    9. Hansen, Karsten T. & Heckman, James J. & Mullen, K.J.Kathleen J., 2004. "The effect of schooling and ability on achievement test scores," Journal of Econometrics, Elsevier, vol. 121(1-2), pages 39-98.
    10. Clément de Chaisemartin & Xavier D'Haultfœuille, 2020. "Two-Way Fixed Effects Estimators with Heterogeneous Treatment Effects," American Economic Review, American Economic Association, vol. 110(9), pages 2964-2996, September.
    11. James J. Heckman & Hidehiko Ichimura & Petra E. Todd, 1997. "Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 605-654.
    12. Thomas Cornelissen & Christian Dustmann & Anna Raute & Uta Schönberg, 2018. "Who Benefits from Universal Child Care? Estimating Marginal Returns to Early Child Care Attendance," Journal of Political Economy, University of Chicago Press, vol. 126(6), pages 2356-2409.
    13. Pedro Carneiro & Karsten T. Hansen & James J. Heckman, 2003. "Estimating Distributions of Treatment Effects with an Application to the Returns to Schooling and Measurement of the Effects of Uncertainty on College," NBER Working Papers 9546, National Bureau of Economic Research, Inc.
    14. Jack Mountjoy, 2022. "Community Colleges and Upward Mobility," American Economic Review, American Economic Association, vol. 112(8), pages 2580-2630, August.
    15. James J. Heckman & Edward Vytlacil, 2005. "Structural Equations, Treatment Effects, and Econometric Policy Evaluation," Econometrica, Econometric Society, vol. 73(3), pages 669-738, May.
    16. Orazio Attanasio & Sarah Cattan & Emla Fitzsimons & Costas Meghir & Marta Rubio-Codina, 2020. "Estimating the Production Function for Human Capital: Results from a Randomized Controlled Trial in Colombia," American Economic Review, American Economic Association, vol. 110(1), pages 48-85, January.
    17. Jane Cooley Fruehwirth & Salvador Navarro & Yuya Takahashi, 2016. "How the Timing of Grade Retention Affects Outcomes: Identification and Estimation of Time-Varying Treatment Effects," Journal of Labor Economics, University of Chicago Press, vol. 34(4), pages 979-1021.
    18. Sergio Urzúa, 2008. "Racial Labor Market Gaps: The Role of Abilities and Schooling Choices," Journal of Human Resources, University of Wisconsin Press, vol. 43(4).
    19. Cattaneo, Matias D., 2010. "Efficient semiparametric estimation of multi-valued treatment effects under ignorability," Journal of Econometrics, Elsevier, vol. 155(2), pages 138-154, April.
    20. Bernd Fitzenberger & Aderonke Osikominu & Robert Völter, 2008. "Get Training or Wait? Long-Run Employment Effects of Training Programs for the Unemployed in West Germany," Annals of Economics and Statistics, GENES, issue 91-92, pages 321-355.
    21. Michael Lechner, 2000. "An Evaluation of Public-Sector-Sponsored Continuous Vocational Training Programs in East Germany," Journal of Human Resources, University of Wisconsin Press, vol. 35(2), pages 347-375.
    22. Ashenfelter, Orley C, 1978. "Estimating the Effect of Training Programs on Earnings," The Review of Economics and Statistics, MIT Press, vol. 60(1), pages 47-57, February.
    23. Frazis, Harley & Loewenstein, Mark A., 2007. "On-the-Job-Training," Foundations and Trends(R) in Microeconomics, now publishers, vol. 2(5), pages 363-440, February.
    24. Rucker C. Johnson & C. Kirabo Jackson, 2019. "Reducing Inequality through Dynamic Complementarity: Evidence from Head Start and Public School Spending," American Economic Journal: Economic Policy, American Economic Association, vol. 11(4), pages 310-349, November.
    25. Heckman, James J. & Navarro, Salvador, 2007. "Dynamic discrete choice and dynamic treatment effects," Journal of Econometrics, Elsevier, vol. 136(2), pages 341-396, February.
    26. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The skill content of recent technological change: an empirical exploration," Proceedings, Federal Reserve Bank of San Francisco, issue Nov.
    27. James J. Heckman & John Eric Humphries & Gregory Veramendi, 2018. "Returns to Education: The Causal Effects of Education on Earnings, Health, and Smoking," Journal of Political Economy, University of Chicago Press, vol. 126(S1), pages 197-246.
    28. Arellano, Manuel & Honore, Bo, 2001. "Panel data models: some recent developments," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 53, pages 3229-3296, Elsevier.
    29. Patrick Kline & Christopher R. Walters, 2016. "Evaluating Public Programs with Close Substitutes: The Case of HeadStart," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1795-1848.
    30. Carneiro, Pedro & Hansen, Karsten T. & Heckman, James J., 2003. "Estimating Distributions of Treatment Effects with an Application to the Returns to Schooling and Measurement of the Effects of Uncertainty on College Choice," IZA Discussion Papers 767, Institute of Labor Economics (IZA).
    31. Michael Lechner & Conny Wunsch, 2009. "Are Training Programs More Effective When Unemployment Is High?," Journal of Labor Economics, University of Chicago Press, vol. 27(4), pages 653-692, October.
    32. Peter R. Mueser & Kenneth R. Troske & Alexey Gorislavsky, 2007. "Using State Administrative Data to Measure Program Performance," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 761-783, November.
    33. Acemoglu, Daron & Pischke, Jorn-Steffen, 1999. "Beyond Becker: Training in Imperfect Labour Markets," Economic Journal, Royal Economic Society, vol. 109(453), pages 112-142, February.
    34. Pedro Carneiro & Karsten T. Hansen & James J. Heckman, 2003. "2001 Lawrence R. Klein Lecture Estimating Distributions of Treatment Effects with an Application to the Returns to Schooling and Measurement of the Effects of Uncertainty on College Choice," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(2), pages 361-422, May.
    35. Heckman, James J. & Urzúa, Sergio, 2010. "Comparing IV with structural models: What simple IV can and cannot identify," Journal of Econometrics, Elsevier, vol. 156(1), pages 27-37, May.
    36. Fitzenberger, Bernd & Furdas, Marina & Sajons, Christoph, 2016. "End-of-year spending and the long-run employment effects of training programs for the unemployed," ZEW Discussion Papers 16-084, ZEW - Leibniz Centre for European Economic Research.
    37. Andrew Goodman-Bacon, 2018. "Difference-in-Differences with Variation in Treatment Timing," NBER Working Papers 25018, National Bureau of Economic Research, Inc.
    38. Fredriksson, Peter & Johansson, Per, 2008. "Dynamic Treatment Assignment," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 435-445.
    39. Fernando Saltiel & Miguel Sarzosa & Sergio Urzúa, 2017. "Cognitive and socio-emotional abilities," Chapters, in: Geraint Johnes & Jill Johnes & Tommaso Agasisti & Laura López-Torres (ed.), Handbook of Contemporary Education Economics, chapter 2, pages 21-42, Edward Elgar Publishing.
    40. Fatih Guvenen & Burhan Kuruscu & Satoshi Tanaka & David Wiczer, 2020. "Multidimensional Skill Mismatch," American Economic Journal: Macroeconomics, American Economic Association, vol. 12(1), pages 210-244, January.
    41. Magne Mogstad & Andres Santos & Alexander Torgovitsky, 2018. "Using Instrumental Variables for Inference About Policy Relevant Treatment Parameters," Econometrica, Econometric Society, vol. 86(5), pages 1589-1619, September.
    42. Erik Hanushek & F. Welch (ed.), 2006. "Handbook of the Economics of Education," Handbook of the Economics of Education, Elsevier, edition 1, volume 1, number 1, June.
    43. James J. Heckman & Jora Stixrud & Sergio Urzua, 2006. "The Effects of Cognitive and Noncognitive Abilities on Labor Market Outcomes and Social Behavior," Journal of Labor Economics, University of Chicago Press, vol. 24(3), pages 411-482, July.
    44. Edward Vytlacil & James J. Heckman, 2001. "Policy-Relevant Treatment Effects," American Economic Review, American Economic Association, vol. 91(2), pages 107-111, May.
    45. Jacklyn Buhrmann, 2017. "Good Enough Jobs: Skill Mismatch and Two-Sided Heterogeneity in Frictional Labor Markets," Purdue University Economics Working Papers 1287, Purdue University, Department of Economics.
    46. Carl Sanders & Christopher Taber, 2012. "Life-Cycle Wage Growth and Heterogeneous Human Capital," Annual Review of Economics, Annual Reviews, vol. 4(1), pages 399-425, July.
    47. Jacob A. Mincer, 1974. "Schooling, Experience, and Earnings," NBER Books, National Bureau of Economic Research, Inc, number minc74-1, July.
    48. repec:eme:rlepps:v:18:y:1999:i:1999:p:439-461 is not listed on IDEAS
    49. James Heckman & Rodrigo Pinto & Peter Savelyev, 2013. "Understanding the Mechanisms through Which an Influential Early Childhood Program Boosted Adult Outcomes," American Economic Review, American Economic Association, vol. 103(6), pages 2052-2086, October.
    50. Ibarrarán, Pablo & Kluve, Jochen & Ripani, Laura & Shady, David Rosas, 2015. "Experimental evidence on the long term impacts of a youth training program," Ruhr Economic Papers 562, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    51. David Card & Pablo Ibarrarán & Ferdinando Regalia & David Rosas-Shady & Yuri Soares, 2011. "The Labor Market Impacts of Youth Training in the Dominican Republic," Journal of Labor Economics, University of Chicago Press, vol. 29(2), pages 267-300.
    52. Fredrik Andersson & Harry J. Holzer & Julia I. Lane & David Rosenblum & Jeffrey Smith, 2024. "Does Federally Funded Job Training Work? Nonexperimental Estimates of WIA Training Impacts Using Longitudinal Data on Workers and Firms," Journal of Human Resources, University of Wisconsin Press, vol. 59(4), pages 1244-1283.
    53. Andrew Dyke & Carolyn J. Heinrich & Peter R. Mueser & Kenneth R. Troske & Kyung-Seong Jeon, 2006. "The Effects of Welfare-to-Work Program Activities on Labor Market Outcomes," Journal of Labor Economics, University of Chicago Press, vol. 24(3), pages 567-608, July.
    54. Jared Ashworth & V. Joseph Hotz & Arnaud Maurel & Tyler Ransom, 2021. "Changes across Cohorts in Wage Returns to Schooling and Early Work Experiences," Journal of Labor Economics, University of Chicago Press, vol. 39(4), pages 931-964.
    55. Ashenfelter, Orley & Card, David, 1985. "Using the Longitudinal Structure of Earnings to Estimate the Effect of Training Programs," The Review of Economics and Statistics, MIT Press, vol. 67(4), pages 648-660, November.
    56. Matias D. Cattaneo, 2010. "multi-valued treatment effects," The New Palgrave Dictionary of Economics,, Palgrave Macmillan.
    57. Orazio Attanasio & Adriana Kugler & Costas Meghir, 2011. "Subsidizing Vocational Training for Disadvantaged Youth in Colombia: Evidence from a Randomized Trial," American Economic Journal: Applied Economics, American Economic Association, vol. 3(3), pages 188-220, July.
    58. Heckman, J.J. & Hotz, V.J., 1988. "Choosing Among Alternative Nonexperimental Methods For Estimating The Impact Of Social Programs: The Case Of Manpower Training," University of Chicago - Economics Research Center 88-12, Chicago - Economics Research Center.
    59. Fitzenberger, Bernd & Volter, Robert, 2007. "Long-run effects of training programs for the unemployed in East Germany," Labour Economics, Elsevier, vol. 14(4), pages 730-755, August.
    60. Cunha, Flavio & Heckman, James J. & Lochner, Lance, 2006. "Interpreting the Evidence on Life Cycle Skill Formation," Handbook of the Economics of Education, in: Erik Hanushek & F. Welch (ed.), Handbook of the Economics of Education, edition 1, volume 1, chapter 12, pages 697-812, Elsevier.
    61. Jorge Rodríguez & Sergio Urzúa & Loreto Reyes, 2016. "Heterogeneous Economic Returns to Post-Secondary Degrees: Evidence from Chile," Journal of Human Resources, University of Wisconsin Press, vol. 51(2), pages 416-460.
    62. Abbring, Jaap H. & Heckman, James J., 2007. "Econometric Evaluation of Social Programs, Part III: Distributional Treatment Effects, Dynamic Treatment Effects, Dynamic Discrete Choice, and General Equilibrium Policy Evaluation," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 72, Elsevier.
    63. Heckman, James J. & Humphries, John Eric & Veramendi, Gregory, 2016. "Dynamic treatment effects," Journal of Econometrics, Elsevier, vol. 191(2), pages 276-292.
    64. Brantly Callaway & Pedro H. C. Sant'Anna, 2018. "Difference-in-Differences with Multiple Time Periods and an Application on the Minimum Wage and Employment," DETU Working Papers 1804, Department of Economics, Temple University.
    65. Ingram, Beth F. & Neumann, George R., 2006. "The returns to skill," Labour Economics, Elsevier, vol. 13(1), pages 35-59, February.
    66. Lynch, Lisa M, 1992. "Private-Sector Training and the Earnings of Young Workers," American Economic Review, American Economic Association, vol. 82(1), pages 299-312, March.
    67. Ibarrarán, Pablo & Kluve, Jochen & Ripani, Laura & Rosas Shady, David, 2015. "Experimental Evidence on the Long-Term Impacts of a Youth Training Program," IZA Discussion Papers 9136, Institute of Labor Economics (IZA).
    68. Yoram Ben-Porath, 1967. "The Production of Human Capital and the Life Cycle of Earnings," Journal of Political Economy, University of Chicago Press, vol. 75(4), pages 352-352.
    69. James Heckman & Hidehiko Ichimura & Jeffrey Smith & Petra Todd, 1998. "Characterizing Selection Bias Using Experimental Data," Econometrica, Econometric Society, vol. 66(5), pages 1017-1098, September.
    70. Lechner, Michael, 2009. "Sequential Causal Models for the Evaluation of Labor Market Programs," Journal of Business & Economic Statistics, American Statistical Association, vol. 27, pages 71-83.
    71. Callaway, Brantly & Sant’Anna, Pedro H.C., 2021. "Difference-in-Differences with multiple time periods," Journal of Econometrics, Elsevier, vol. 225(2), pages 200-230.
    72. Jonathan R. Veum, 1997. "Training and job mobility among young workers in the United States," Journal of Population Economics, Springer;European Society for Population Economics, vol. 10(2), pages 219-233.
    73. Moffitt, Robert A. (ed.), 2016. "Economics of Means-Tested Transfer Programs in the United States, Volume II," National Bureau of Economic Research Books, University of Chicago Press, number 9780226392493, March.
    74. Aakvik, Arild & Heckman, James J. & Vytlacil, Edward J., 2005. "Estimating treatment effects for discrete outcomes when responses to treatment vary: an application to Norwegian vocational rehabilitation programs," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 15-51.
    75. Francesco Agostinelli & Matthew Wiswall, 2016. "Identification of Dynamic Latent Factor Models: The Implications of Re-Normalization in a Model of Child Development," NBER Working Papers 22441, National Bureau of Economic Research, Inc.
    76. Erik Hanushek & F. Welch (ed.), 2006. "Handbook of the Economics of Education," Handbook of the Economics of Education, Elsevier, edition 1, volume 2, number 2, June.
    77. Jacob A. Mincer, 1974. "Schooling and Earnings," NBER Chapters, in: Schooling, Experience, and Earnings, pages 41-63, National Bureau of Economic Research, Inc.
    78. Jaap H. Abbring & Gerard J. van den Berg, 2003. "The Nonparametric Identification of Treatment Effects in Duration Models," Econometrica, Econometric Society, vol. 71(5), pages 1491-1517, September.
    79. Moffitt, Robert A. (ed.), 2016. "Economics of Means-Tested Transfer Programs in the United States, Volume I," National Bureau of Economic Research Books, University of Chicago Press, number 9780226370477, March.
    80. Laura Larsson, 2003. "Evaluation of Swedish Youth Labor Market Programs," Journal of Human Resources, University of Wisconsin Press, vol. 38(4).
    81. Francesco Agostinelli & Matthew Wiswall, 2016. "Estimating the Technology of Children's Skill Formation," NBER Working Papers 22442, National Bureau of Economic Research, Inc.
    82. Booth, Alison L, 1993. "Private Sector Training and Graduate Earnings," The Review of Economics and Statistics, MIT Press, vol. 75(1), pages 164-170, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Oliver Cassagneau-Francis & Robert Gary-Bobo & Julie Pernaudet & Jean-Marc Robin, 2022. "A Nonparametric Finite Mixture Approach to Difference-in-Difference Estimation, with an Application to On-the-job Training and Wages," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-03869547, HAL.
    2. Shosei Sakaguchi, 2024. "Policy Learning for Optimal Dynamic Treatment Regimes with Observational Data," Papers 2404.00221, arXiv.org, revised May 2025.
    3. Shosei Sakaguchi, 2021. "Estimation of Optimal Dynamic Treatment Assignment Rules under Policy Constraints," Papers 2106.05031, arXiv.org, revised Aug 2024.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jorge Rodriguez, 2017. "Understanding the Effects of Income and Child Care Subsidies on Children's Academic Achievement," 2017 Papers pro1077, Job Market Papers.
    2. Fernando Saltiel, 2019. "What's Math Got to Do With It? Multidimensional Ability and the Gender Gap in STEM," 2019 Meeting Papers 1201, Society for Economic Dynamics.
    3. Jaap Abbring & James Heckman, 2008. "Dynamic policy analysis," CeMMAP working papers CWP05/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Heckman, James J. & Humphries, John Eric & Veramendi, Gregory, 2016. "Dynamic treatment effects," Journal of Econometrics, Elsevier, vol. 191(2), pages 276-292.
    5. Biewen, Martin & (neé Tapalaga), Madalina Thiele, 2020. "Early tracking, academic vs. vocational training, and the value of ‘second-chance’ options," Labour Economics, Elsevier, vol. 66(C).
    6. Heckman, James J. & Urzúa, Sergio, 2010. "Comparing IV with structural models: What simple IV can and cannot identify," Journal of Econometrics, Elsevier, vol. 156(1), pages 27-37, May.
    7. Heckman, James J. & Humphries, John Eric & Veramendi, Gregory & Urzua, Sergio, 2014. "Education, Health and Wages," IZA Discussion Papers 8027, Institute of Labor Economics (IZA).
    8. Martin Biewen & Bernd Fitzenberger & Aderonke Osikominu & Marie Paul, 2014. "The Effectiveness of Public-Sponsored Training Revisited: The Importance of Data and Methodological Choices," Journal of Labor Economics, University of Chicago Press, vol. 32(4), pages 837-897.
    9. James J. Heckman & John Eric Humphries & Gregory Veramendi, 2018. "Returns to Education: The Causal Effects of Education on Earnings, Health, and Smoking," Journal of Political Economy, University of Chicago Press, vol. 126(S1), pages 197-246.
    10. Mogstad, Magne & Torgovitsky, Alexander, 2024. "Instrumental variables with unobserved heterogeneity in treatment effects," Handbook of Labor Economics,, Elsevier.
    11. Lechner, Michael & Wunsch, Conny, 2013. "Sensitivity of matching-based program evaluations to the availability of control variables," Labour Economics, Elsevier, vol. 21(C), pages 111-121.
    12. Heckman, James J. & Navarro, Salvador, 2007. "Dynamic discrete choice and dynamic treatment effects," Journal of Econometrics, Elsevier, vol. 136(2), pages 341-396, February.
    13. James J. Heckman, 2008. "The Principles Underlying Evaluation Estimators with an Application to Matching," Annals of Economics and Statistics, GENES, issue 91-92, pages 9-73.
    14. Hugo Reis & Emilio Borghesan, 2022. "Learning Through Repetition? A Dynamic Evaluation of Grade Retention in Portugal," Working Papers w202220, Banco de Portugal, Economics and Research Department.
    15. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    16. Rahul Singh & Liyuan Xu & Arthur Gretton, 2020. "Kernel Methods for Causal Functions: Dose, Heterogeneous, and Incremental Response Curves," Papers 2010.04855, arXiv.org, revised Oct 2022.
    17. Jorge Luis García & James J. Heckman & Duncan Ermini Leaf & María José Prados, 2017. "Quantifying the Life-cycle Benefits of a Prototypical Early Childhood Program," NBER Working Papers 23479, National Bureau of Economic Research, Inc.
    18. Elizabeth M. Caucutt & Lance Lochner, 2020. "Early and Late Human Capital Investments, Borrowing Constraints, and the Family," Journal of Political Economy, University of Chicago Press, vol. 128(3), pages 1065-1147.
    19. Oliver Cassagneau-Francis & Robert Gary-Bobo & Julie Pernaudet & Jean-Marc Robin, 2022. "A Nonparametric Finite Mixture Approach to Difference-in-Difference Estimation, with an Application to On-the-job Training and Wages," Working Papers hal-03869547, HAL.
    20. Grit Muehler & Michael Beckmann & Bernd Schauenberg, 2007. "The returns to continuous training in Germany: new evidence from propensity score matching estimators," Review of Managerial Science, Springer, vol. 1(3), pages 209-235, November.

    More about this item

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nbr:nberwo:25408. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.