Détails

Faculté	Faculté des sciences économiques et sociales et du management
Domaine	Economie politique
Code	UE-EEP.00143
Langues	Anglais
Type d'enseignement	Cours
Cursus	Master
Semestre(s)	SP-2024

Horaires et salles

Horaire résumé	Jeudi 11:15 - 14:00, Hebdomadaire (Semestre de printemps)
Heures par semaine	3

Enseignement

Enseignants	Huber Martin
Assistants	Stoller Andreas
Description	This course discusses econometric tools for assessing the causal impact of some policy intervention (also referred to as “treatment”) on an outcome of interest. This may, for instance, concern the effectiveness of public policies (e.g. training programs for unemployed, income support for poor families, public childcare,…), corporate policies (marketing campaigns, educational programs for employees,…), health interventions (new medical treatments…), among many other examples. The following topics are covered: - The definition of causal effects (using the “potential outcome” notation) - Methods for policy and impact evaluation under exogeneity: estimation based on regression, matching, and weighting - Methods for policy and impact evaluation under endogeneity: estimation based on instruments, regression discontinuities and kinks, differences in differences, and changes in changes - Methods for assessing causal mechanisms underlying a particular causal effect (mediation analysis) The lecture is accompanied by 4 PC sessions based on the software package "R", in which the methods are applied to empirical data.
Objectifs de formation	Students should comprehend the intuition behind the econometric methods discussed and recognize the scenarios where these methods can or cannot be utilized to evaluate the causal impact of a specific policy. Additionally, students should develop practical skills in applying these methods to real-world data for conducting causal analyses.
Conditions d'accès	introductory econometrics
Softskills	Oui
Places softskills	10
Hors domaine	Oui
BeNeFri	Oui
Mobilité	Oui
UniPop	Non
Auditeur	Oui

Documents

Bibliographie

Huber, M. (2023). Causal Analysis: Impact Evaluation and Causal Machine Learning with Applications in R. The MIT Press.

Examen écrit - SP-2024, Session d'été 2024

Date	12.06.2024 17:00 - 18:30
Mode d'évaluation	Par note
Description	Examination time: 90 Min. and participation in PC sessions

Examen écrit - SP-2024, Session de rattrapage 2024

Date	30.08.2024 14:00 - 15:30
Mode d'évaluation	Par note
Description	Examination time: 90 Min. and participation in PC sessions