The Effects of Employment and Training Programs for Populations with Low Incomes: Evidence from the Pathways Clearinghouse

Leah Shiferaw (), Sarah Dolfin () and Andrei Streke ()
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Leah Shiferaw: Mathematica Inc
Sarah Dolfin: Mathematica Inc
Andrei Streke: Mathematica Inc

Journal of Labor Research, 2024, vol. 45, issue 3, No 3, 385-402

Abstract: Abstract A large body of research has studied the impacts of employment and training programs, yet there is no clear consensus regarding whether these programs are effective in improving outcomes for people with low incomes. This article uses meta-analytic approaches to synthesize the causal evidence on the impacts of employment and training programs for populations in the U.S. and Canada with low incomes. Using data on over 1,800 estimates from 191 evaluations of 144 programs with outcomes observed over a range of follow-up periods, we find modest-sized average effects equivalent to an improvement of about $1,000 in annual earnings. However, we find substantial heterogeneity depending on the services offered and other characteristics of the interventions. Interventions offering work- and work-based learning were the most effective in improving labor market outcomes, particularly when offered in conjunction with employment services such as work readiness training or employment coaching. Our research makes several important contributions to the literature. First, we developed a comprehensive review protocol and rigorous standards guide to transparently and consistently identify both published and unpublished causal research. Second, we estimated average impacts of interventions for labor market outcomes overall and separately for specific outcomes (employment, earnings, public benefit receipt, and educational attainment). Third, we coded a large number of types of services offered by each intervention, as well as study and sample characteristics, to assess which services, combinations of services, and other characteristics are associated with intervention effectiveness. Fourth, our findings are corroborated using both frequentist and Bayesian meta-analytical methods.

Keywords: Employment and training; Meta-analysis; Meta-regression; Bayesian methods (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s12122-024-09364-x

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