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Jeffrey A. Smith

University of Wisconsin, and NBER, USA, and IZA, Germany

I think IZA World of Labor is a truly valuable innovation in the thoughtful translation of academic research into forms readily used by policymakers and journalists. I have also used some of the entries myself as a quick and easy way to introduce students (or even myself) to a literature

IZA World of Labor role

Author

Current position

Professor of Economics, University of Wisconsin, USA

Research interest

Experimental and non-experimental methods for the evaluation of interventions, with particular application to social and educational programs

Website

https://ssc.wisc.edu/~econjeff/

Positions/functions as a policy advisor

Consultant to governments in the US, Canada, the UK, and Australia on evaluation issues for labor market and educational interventions

Past positions

Faculty at University of Western Ontario (1994–2001); faculty at University of Maryland (2001–2005); faculty at University of Michigan (2005–2017)

Qualifications

PhD Economics, University of Chicago, 1996

Selected publications

  • "Is the threat of reemployment services more effective than the services themselves?" American Economic Review 93:4 (2003): 1313–1327 (with D. Black, M. Berger, and B. Noel).

  • "The economics and econometrics of active labor market programmes." In: Ashenfelter, O. C., and D. Card (eds.). Handbook of Labor Economics, Volume 3A. Amsterdam: Elsevier, 1999: 1865–2097 (with J. Heckman and R. LaLonde).

  • "Does matching overcome LaLonde's critique of nonexperimental methods?" Journal of Econometrics 125:1–2 (2005): 305–353 (with P. Todd).

  • "Heterogeneous program impacts: Experimental evidence from the PROGRESA Program." Journal of Econometrics 64 (2008): 487–535 (with H. Djebbari).

  • "Government-sponsored vocational education." In: Hanushek, E. A., S. Machin, and L. Woessmann (eds). Handbook of the Economics of Education, Volume 5. Amsterdam: Elsevier, 2016; 479–652 (with B. McCall and C. Wunsch).

article(s)

  • The usefulness of experiments

    Are experiments the gold standard or just over-hyped?

    Jeffrey A. Smith, May 2018
    Non-experimental evaluations of programs compare individuals who choose to participate in a program to individuals who do not. Such comparisons run the risk of conflating non-random selection into the program with its causal effects. By randomly assigning individuals to participate in the program or not, experimental evaluations remove the potential for non-random selection to bias comparisons of participants and non-participants. In so doing, they provide compelling causal evidence of program effects. At the same time, experiments are not a panacea, and require careful design and interpretation.
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