This course provides an overview of modern microeconometric methods for program evaluation. The course covers experimental and quasi-experimental approaches to impact evaluation, with a focus on practical applications. The objective of this course is to provide students with a set of theoretical, econometric and reasoning skills to assess causality and impact. The course will introduce students to a variety of econometric techniques in impact evaluation. Students will learn to critically analyze evaluation research and to gauge how convincing the research is in identifying a causal impact.
By the end of the course, students will have an understanding of the main experimental and quasi-experimental approaches to impact evaluation. Students will be able to explain the econometric theory underlying each approach, including the identification assumptions required for valid causal inference. By the end of the course, students will also have a conceptual understanding of the process of implementing an impact evaluation: how to identify a viable research question, what data would be required to answer it, and what steps would be involved in collecting and analyzing the relevant data.
Prerequisiti
Knowledge of key concepts in economic theory (microeconomics) and econometric analysis would be preferable. An understanding of fundamental statistical concepts including expected values and linear regression is highly recommended.
Metodi didattici
• Face-to-face lectures • Class discussions • Readings • Group work • Data analysis
Verifica Apprendimento
• General written exam at the end of the course covering the entire course material • Class participation • Readings • Group work
Testi
1) Lecture notes
2) Suggested textbooks (only certain chapters): - Mastering Metrics: The Path From Cause To Effect by Joshua D. Angrist and Jorn-Steffen Pischke, Princeton Edition, 2015. - Mostly Harmless Econometrics. An Empiricist's Companion by Joshua D. Angrist and Jorn-Steffen Pischke, Princeton Edition, 2015. - Causal Inference: The Mixtape by Scott Cunnigham
3) Journal Articles: for some topics academic articles will be indicated to study the empirical applications.
Contenuti
Main topics covered: 1. Course information and introduction to impact evaluation 2. Causality, potential outcomes and selection bias 3. Randomized controlled trials 4. Difference-in-differences 5. Event Studies 6. Instrumental Variables 7. Regression Discontinuity 8. Matching
