The RFBerlin Applied Economics Seminar series brings leading researchers to Berlin to share their latest work and engage with our community. We are pleased to welcome Lawrence F. Katz (Harvard University) for this session, where he will share his work.

Lawrence F. Katz is the Elisabeth Allison Professor of Economics at Harvard University and a Research Associate of the National Bureau of Economic Research.  His research focuses on issues in labor economics and the economics of social problems. He is the author (with Claudia Goldin) of The Race between Education and Technology (Harvard University Press, 2008), a history of U.S. economic inequality and the roles of technological change and the pace of educational advance in affecting the wage structure. 

Event Topic:

Matching Estimators in the Age of Big Data: New Evidence on the Impacts of Workforce Training Programs

We re-examine the bias (effectiveness at replicating experimental estimates) of observational matching estimators for program effects using big administrative data. We find that both sample size and model complexity matter.  Observational matching can work in big data because it permits estimation of high-dimensional non-parametric models that better capture selection. We apply our matching estimators in big data to assess the determinants of the effectiveness of U.S. workforce training programs.

Event Details:

Date: 3 November 2025
Time: 16:30–17:45

Participation: the seminar is open to the public and targeted to an academic audience.

If you have any questions or need further information, feel free to contact us using the form or email us at [email protected]