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IAB Colloquium

The discussion series "Labour Market and Occupational Research (IAB-Colloquium zur Arbeitsmarkt- und Berufsforschung)" is a forum where primarily external researchers present the results of their work and discuss these with experts from IAB. Practitioners from the political, administrative and business fields are naturally also welcome.

Recent developments in Economics of Education

IAB-Colloquium with Prof. Eric Hanushek, PhD, Stanford University, Prof. Jeffrey Smith, PhD, University of Wisconsin-Madison

Prof. Eric Hanushek, PhD
Titel: Developing a Market for Teacher Quality
Abstract: tba

Prof. Jeffrey Smith, PhD
Titel: How Many Children Left Behind? A Meta-Analysis of Treatment Effect Heterogeneity in Developing-Country Education Programs
Extensive research on the effects of education programs in developing countries has left a key question unanswered: how many students benefit from these programs?

We answer this question by re-analyzing the microdata from the universe of published education RCTs from developing countries. Despite the current enthusiasm for replication, we were able to obtain data for just 45% of the studies in our sampling frame. Our analytic sample includes more than half a million observations covering 123 different interventions run in 24 countries. Using this data, we construct non-parametric lower bounds on the across-student variance of treatment effects for each intervention. Our meta-analytic estimate of the standard deviation of treatment effects is 0.12 SDs of control-group test scores, which is nearly twice as large as the average treatment effect for the studies in our sample. The across-student variation in the effects of the same intervention is more than half as large as the variation in impacts across studies.

Moreover, the standard deviation of impacts varies widely, from nearly zero for 20% of programs to almost half an SD of test scores for the top handful of interventions. The variance of treatment effects is strongly correlated with the average effect. However, we can explain almost none of the variance in treatment effects with the observed covariates from the studies, even if we use machine learning methods to estimate and partial out CATEs. Our results suggest that education interventions in developing countries leave over a quarter of children behind.

Joint: Hanna Han, Jason Kerwin, Juan S. Munoz-Morales, Jeffrey Smith, and Rebecca Thornton

Date

21.11.2025

, 9.30 a.m. until noon

Venue

Institute for Employment Research
Regensburger Straße 104
90478 Nuremberg
Room 164

or online via MS Teams

Programme

09:30                  Welcome by Prof. Bernd Fitzenberger, PhD
09:40 – 10:40    Prof. Jeffrey Smith, PhD
10:40 – 11:00    Break
11:00 – 12:00    Prof. Eric Hanushek, PhD

Registration

Researchers who like to participate, please send a e-mail to IAB.Colloquium@iab.de