KAFP 4355 - Policy Analysis and Policy Evaluation - Intermediate level

The aim of the course is to enable students to develop a critical view on public policy evaluation results and methods. After a brief overview of the different methods (qualitative, quantitative, mixed), this course will focus on econometric methods allowing to measure the "pure" effect of a given public policy (“causal inference”). The course will include both theoretical content and practical work, through the use of statistical software and the study of recent evaluation papers in various fields of public policy (environment, social protection, labour market, development and poverty alleviation, etc.).
Juliette DUCOULOMBIER,Jules CORNETET
Cours magistral seul
English
This course will be accompanied by short (home) data assignments. Step by step, over the 12 classes, we will learn how to use R to answer a public policy question (expected workload: < 1h per week). Additionally, there will be one mandatory reading per student during the semester. These will be empirical papers on applications of the methods seen in class.
Pre-requisites are the following: (1) knowledge of basic statistical measures (mean, variance) and concepts (sampling). (2) Notions, experience or learning ability in data analysis, statistical tools and software (R) (3) Basic knowledge in Economics, including labour economics, public policies and political economy.
Autumn 2023-2024
(i) Intermediate exam (session 8, 30%): MCQ. (ii) Final exam (home assignment, by group, 60%): students will have the choice between two options (1) a summary paper on a public policy issue, based on a corpus of impact evaluations or (2) a data assignment, consisting in reconstructing and criticizing impact indicators. (iii) Participation grade (10%).
Each session (excluding introductory sessions) will be divided into three parts: first, we will quickly correct and discuss the short data assignment. The core of the session will consist in presenting an evaluation method. The last part of the session will be dedicated to presenting public policy applications, based on the economic literature.
1 Huntington-Klein N. (2022), The Effect: An Introduction to Research Design and Causality, ‎ Chapman and Hall/CRC, 1st Edition
2 Barone, C. (2023). Randomised Controlled Trials. LIEPP Methods Brief n°1.
3 Fougere, D. & Jacquemet, N. (2023). Difference-in-differences. LIEPP Methods Brief n°10.
4 Fougere, D. & Jacquemet, N. (2023). The regression discontinuity design. LIEPP Methods Brief n°14.
5 Givord, P. (2023) Matching methods. LIEPP Methods Brief n°18.
6 Grolemund, G., & Wickham, H. (2017). R for Data Science. O'Reilly Media.
7 Wooldridge, J. M. (2012). Introductory econometrics : a modern approach. Mason, Ohio :South-Western Cengage Learning.
8 Angrist, J. D., & Pischke, J.-S. (2008). Mostly harmless econometrics. Princeton University Press.
9 Cunningham S. (2021). Causal Inference: The Mixtape, Yale University Press
10 Bozio, A. & Grenet, J. (2017). Economie des politiques publiques, La Découverte