K2SP 3905 - Advanced Analysis and Evaluation of Public Policy II

K2SP 3905 · Spring semester 2025-2026

Language of tuition
English
Course type
Cours magistral
Number of hours
36
Credits
6

Information

Description

This advanced course will provide an in-depth coverage of quantitative policy evaluation. The course is the continuation of the Policy Analysis and Policy Evaluation class delivered in the Fall and will build on the notions and skills acquired in the first semester. The course will cover a wide variety of evaluation designs, and their applications to concrete policy questions. Students will learn the whole toolbox of evaluation methods, including consolidating their knowledge of regressions, randomized control trials, difference-in-differences, instrumental variables, and regression discontinuity designs. Importantly, students will learn these methods not only through theory and examples during the lectures, but also through practice in bi-weekly seminars, which will teach them how to use the statistical software R for data description and analysis. Students will also learn how to rigorously read and interpret quantitative evidence, under the form of academic publications or policy reports. Finally, students will pursue their policy evaluation group project, to which they will add a data analysis component and work towards the production of a technical evaluation report.

Prerequisites

Advanced Analysis and Evaluation of Public Policy

Teaching format

Moodle

Assessment

Mid-term exam: multiple choice questions with justification. 40% of the final mark

Group Policy Evaluation Project: 60% of final mark.

  • One-Pager to be prepared at home and submitted mid-term 15%
  • In class presentation at the end of the term 15%
  • Final technical report to be handed over at the end of the term 30%

Workload

12 x 2h lectures + 6 x 2h seminars, 2 groups + 3 x 20 min IT project clinics between mid-March and late-April

Readings

Main readings 5

  1. Angrist, J. D. and J.-S. Pischke (2014). Mastering'metrics: The path from cause to effect Princeton university press

  2. Duflo, E., R. Glennerster, and M. Kremer (2006, December). Using Randomization in Development Economics Research: A Toolkit. NBER Technical Working Papers 0333, National Bureau of Economic Research

  3. Gertler, P. J., S. Martinez, P. Premand, L. B. Rawlings, and C. M. Vermeersch (2016). Impact evaluation in practice. World Bank Publications https://openknowledge.worldbank.org/handle/10986/25030

  4. Glennerster, Rachel and Kudzai Takavarasha Running Randomized Evaluations: A Practical Guide. Princeton University Press. 2013

    Read online

  5. Hansen (2022) Econometrics Princeton university press

Further readings 5

  1. J-PAL Online Research Resources: https://www.povertyactionlab.org/research-resources?view=toc

  2. LIEPP (2023) Methods Briefs https://sciencespo.hal.science/LIEPP-METHOD

  3. Wooldridge, J. M. (2015). Introductory econometrics: A modern approach. Cengage learning.

  4. World Bank Development Research in Practice The DIME Analytics Data Handbook: https://worldbank.github.io/dime-data-handbook/

  5. World Bank DIME Analytics Online Resources: https://dimewiki.worldbank.org/Main_Page

Teaching units

Unit no.Unit type Teaching unitsTeachers Number of hoursCredits
58777Cours magistral Advanced Analysis and Evaluation of Public Policy II Justine KNEBELMANN246
58989Tutorat Groupe Advanced Analysis and Evaluation of Public Policy II Alexandre GRELLET120
58990Tutorat Groupe Advanced Analysis and Evaluation of Public Policy II Alexandre GRELLET120
59547Teaching assistant Project clinic Leïla COSTIL120

Teachers

  • Justine KNEBELMANN
  • Alexandre GRELLET
  • Leïla COSTIL

In the curricula

Contacts and resources

Contact
DEBARD Laura