Details

Faculty	Faculty of Management, Economics and Social Sciences
Domain	Economics
Code	UE-EEP.00143
Languages	English
Type of lesson	Lecture
Level	Master
Semester	SS-2024

Schedules and rooms

Summary schedule	Thursday 11:15 - 14:00, Hebdomadaire (Spring semester)
Hours per week	3

Teaching

Teachers	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.
Training objectives	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.
Condition of access	introductory econometrics
Softskills	Yes
Softskills seats	10
Off field	Yes
BeNeFri	Yes
Mobility	Yes
UniPop	No
Auditor	Yes

Documents

Bibliography

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

Written exam - SS-2024, Session d'été 2024

Date	12.06.2024 17:00 - 18:30
Assessments methods	By rating
Descriptions of Exams	Examination time: 90 Min. and participation in PC sessions

Written exam - SS-2024, Session de rattrapage 2024

Date	30.08.2024 14:00 - 15:30
Assessments methods	By rating
Descriptions of Exams	Examination time: 90 Min. and participation in PC sessions

Written exam - AS-2024, Session d'hiver 2025

Date	07.01.2025 11:00 - 12:30
Assessments methods	By rating
Descriptions of Exams	Examination time: 90 Min. and participation in PC sessions