Understanding Program Complementarities: Estimating the Dynamic Effects of a Training Program with Multiple Alternatives

In this paper we estimate the causal effect of a training program for disadvantaged youths on their long-run labor market outcomes. Individuals receive lottery offers to participate in the program, but are allowed to choose when to leave the program and to participate in alternative programs. We consider a multistage decision setting, where individuals sequentially select which program to participate in at every stage. The standard IV estimator using initial random assignment as instrumental variable identifies a weighted average of the effects of the treatment for subgroups of individuals differing in terms of potential duration of participation and choice of alternative programs. We estimate a sequential choice model that allows us to estimate the effect of the treatment for these different subgroups separately. We use the estimated model to investigate the dynamic complementarity between different training programs and explore program targeting to improve the cost-effectiveness relative to the existing program.

[1]  John C. Ham,et al.  Estimating (Easily Interpreted) Dynamic Training Effects from Experimental Data , 2017, Journal of Labor Economics.

[2]  M. Lechner,et al.  Identification of the effects of dynamic treatments by sequential conditional independence assumptions , 2005 .

[3]  Joseph G. Altonji,et al.  Do Wages Rise with Job Seniority? A Reassessment , 1997 .

[4]  J. Heckman,et al.  Returns to Education: The Causal Effects of Education on Earnings, Health, and Smoking , 2016, Journal of Political Economy.

[5]  Peter Z. Schochet,et al.  Does Job Corps Work? Impact Findings from the National Job Corps Study , 2008 .

[6]  S. Urzua,et al.  Dynamic Treatment Effects of Job Training , 2018, Journal of Applied Econometrics.

[7]  Robert J. LaLonde,et al.  THE EFFECT OF SAMPLE SELECTION AND INITIAL CONDITIONS IN DURATION MODELS: EVIDENCE FROM EXPERIMENTAL DATA ON TRAINING , 1996 .

[8]  Jeffrey A. Smith,et al.  The Women of the National Supported Work Demonstration , 2017, Journal of Labor Economics.

[9]  James J. Heckman,et al.  Substitution and Dropout Bias in Social Experiments: A Study of an Influential Social Experiment , 2000 .

[10]  David Card,et al.  Estimating the Effects of a Time Limited Earnings Subsidy for Welfare Leavers , 2004 .

[11]  Christopher R. Taber Semiparametric identification and heterogeneity in discrete choice dynamic programming models , 2000 .

[12]  Winston T. Lin,et al.  The Benefits and Costs of JTPA Title II-A Programs: Key Findings from the National Job Training Partnership Act Study , 1997 .

[13]  Sheena McConnell,et al.  National Job Corps Study: The Benefits and Costs of Job Corps. Washington, DC: Mathematica Policy Research , 2001 .

[14]  M. Gentzkow Valuing New Goods in a Model with Complementarity: Online Newspapers , 2007 .

[15]  Robert J. LaLonde,et al.  The Impact of Being Offered and Receiving Classroom Training on the Employment Histories of Disadvantaged Women: Evidence from Experimental Data , 1997 .

[16]  Bronwyn H Hall,et al.  Estimation and Inference in Nonlinear Structural Models , 1974 .

[17]  Yuya Takahashi,et al.  How the Timing of Grade Retention Affects Outcomes: Identification and Estimation of Time-Varying Treatment Effects , 2016, Journal of Labor Economics.

[18]  M. Lechner Program Heterogeneity and Propensity Score Matching: An Application to the Evaluation of Active Labor Market Policies , 2002, Review of Economics and Statistics.

[19]  Alfonso Flores-Lagunes,et al.  Bounds on Average and Quantile Treatment Effects of Job Corps Training on Wages , 2013, The Journal of Human Resources.

[20]  James G. Mulligan,et al.  The Review of Economics and Statistics , 1998 .

[21]  Donald B. Rubin,et al.  Evaluating the Effect of Training on Wages in the Presence of Noncompliance, Nonemployment, and Missing Outcome Data , 2012 .

[22]  Gerard J. van den Berg,et al.  The nonparametric identification of treatment effects in duration models , 2003 .

[23]  Nathaniel Hendren,et al.  The Policy Elasticity , 2013, Tax Policy and the Economy.

[24]  Magne Mogstad,et al.  Field of Study, Earnings, and Self-Selection , 2014 .

[25]  R. Lalonde Evaluating the Econometric Evaluations of Training Programs with Experimental Data , 1984 .

[26]  Bernd Fitzenberger,et al.  Get Training or Wait? Long-Run Employment Effects of Training Programs for the Unemployed in West Germany , 2006, SSRN Electronic Journal.

[27]  James J Heckman,et al.  Understanding Instrumental Variables in Models with Essential Heterogeneity , 2006, The Review of Economics and Statistics.

[28]  R. Lalonde Employment and Training Programs , 2003 .

[29]  Alfonso Flores-Lagunes,et al.  Estimating the Effects of Length of Exposure to Instruction in a Training Program: The Case of Job Corps , 2012, Review of Economics and Statistics.

[30]  Myoung‐jae Lee,et al.  On Nonparametric Identification of Treatment Effects in Duration Models , 2016, SSRN Electronic Journal.

[31]  David S. Lee Training, Wages, and Sample Selection: Estimating Sharp Bounds on Treatment Effects , 2005 .

[32]  James J Heckman,et al.  Comparing IV with Structural Models: What Simple IV Can and Cannot Identify , 2009, Journal of econometrics.

[33]  Patrick M. Kline,et al.  Evaluating Public Programs with Close Substitutes: The Case of Head Start , 2015 .