Economics & Finance / Economic Theory / Econometrics

Data Driven Policy Impact Evaluation: Surprising Findings from 40 Research Papers

Statistics and Information Systems for Policy Evaluation

Bruno Bertaccini, Luigi Fabbris, Alessandra Petrucci

This video explores the cutting-edge field of data-driven policy evaluation, based on the ASA 2021 conference proceedings 'Statistics and Information Systems for Policy Evaluation' edited by Bruno Bertaccini, Luigi Fabbris, and Alessandra Petrucci. We dive into 40 peer-reviewed papers that reveal counterintuitive insights across education, health, decision-making, and tourism. Discover why hiring managers prefer 'average' candidates over top performers, how immigrant students face hidden barriers in school transitions, and why age—not biomarkers—is the strongest predictor of COVID-19 mortality. Using advanced methods like Bayesian Lasso, bifactor analysis, and random forests, these studies challenge common assumptions and offer practical lessons for policymakers. Watch to learn how data can uncover the truth behind policy impacts and why ‘common sense’ often fails.