KAFP 4290 - Quantitative methods and evaluation of public policy - graduate level

The course is an introduction to experimental and non-experimental statistical evaluation methods. The presentation is not very technical. The course will be completed by exercises to be done using the ​​Stata software (the version 17.0 of the Stata software is downloadable for Master Students at Sciences Po). The first part of the course will be devoted to (reminders of) elementary notions of statistics (such as descriptive statistics, tests, correlation, linear regression) which will facilitate the understanding and the implementation of evaluation methods which are most often used, and which will be presented in the second part of the course.
Fatimetou EL BAH,Denis FOUGERE
Cours magistral seul
English
Before each session of the course, it is advisable to read textbook chapters dealing with the topics covered in the session. In addition, the instructor will indicate during each session academic articles or working papers in which the methods discussed during the session are implemented. Reading these articles or working papers is strongly recommended. It will complete and facilitate the understanding of the course.
In theory, there is no need for any prerequisite in probability and statistics. However, it would be useful to have a very basic knowledge in statistics (descriptive statistics, variables, and distributions, etc.). But it is not necessary. Indeed, a first part of the course will be devoted to reminders of elementary useful concepts. However, it is recommended (but not mandatory) to have taken one of the following courses in the first semester of the Master: “Policy analysis and evaluation - beginner level”, “Policy Analysis and evaluation - intermediate level”, “Policy analysis and evaluation for social policy”. Please note that this course is not intended for EPP students, insofar as they are enrolled in a quantitative class as part of their Policy Stream's curriculum.
Spring 2022-2023
40% of the final mark will come from two exercises which will be distributed to students at the end of two sessions. These exercises will be done using the Stata software. Their solution must be sent by email to the instructor before the next session of the course. The remaining 60% will be awarded to a two-hour final exam which will take place during the twelfth and final session of the course.
Lessons and computer exercises during and after class.
Angrist (Joshua), Pischke (Jörn-Steffen), Mostly Harmless Econometrics: An Empiricist's Companion, Princeton University Press, 2009
Gertler (Paul), Martinez (Sebastian), Premand (Patrick), Rawlings (Laura), Vermeersch (Christel), Impact Evaluation in Practice, Second Edition. Washington, DC: Inter-American Development Bank and World Bank, 2016. https://openknowledge.worldbank.org/han
Imbens (Guido), Rubin (Donald), Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction. Cambridge University Press, 2015
Cunningham (Scott), Causal Inference: The Mixtape. Yale University Press: New Haven and London, 2021.
Glennerster (Rachel), Takavarasha (Kudzai), Running Randomized Experiments – A Practical Guide, Princeton University Press, 2013.
Holmes (William), Using Propensity Scores in Quasi-Experimental Designs, Sage Publications, 2013
Lee (Myoung-Jae), Matching, Regression Discontinuity, Difference in Differences, and Beyond, Oxford University Press, 2016
Huntington-Klein Nick, The Effect: An Introduction to Research Design and Causality, Chapman and Hall/CRC Press: Boca Raton, Florida, 2022.