Course teacher(s)
Philip VERWIMP (Coordinator)ECTS credits
5
Language(s) of instruction
english
Course content
Theory of change, M&E and impact evaluation
Randomisation: all we need to know
Confounders in evaluation design
Alternatives to randomization
Ethical issues in evaluation
Guest lecture: from theory to practice
Objectives (and/or specific learning outcomes)
The lead question in the course is: how should we design an intervention (be it in public policy, in an organisation, …) to be able to attribute potential changes in outcome indicators to the intervention. It is the application of rigorous scientific practice (originating in epidemiology and medical science) to problems of a social, economic or political nature. In essence it means to work with a control group who does not benefit from the intervention and randomly allocate units of analysis (persons, schools,….) to the treatment and the control group. Students also learn that this ‘ideal’ method is not always achievable and under which conditions this is the case. They are given the tools to design evaluations that do not meet the ideal standards. It is a course on THINKING how good data can be collected to be able to measure potential changes, rather than analyzing existing data. The course is not a pure econometric course, meaning I do not teach how to analyse data. The course is all about the steps we take before we start with data analysis.
Teaching methods and learning activities
lecture
video documentary
guest lectures
student presentation of group assignment
Contribution to the teaching profile
From le Profile d'Enseignement de MA-ECON:
in particular:
Main Competency: ‘Résoudre des problème complexes de nature économique, financière et de politique publique en s’appuyant sur une démarche scientifique de transposition des savoirs afin d’opérationnaliser les solutions’;
Sub Competency : ‘Faire preuve d’abstraction théorique dans l’analyse d’une situation économique afin de transférer ses connaissances au context’;
and also, to a lesser degree
Main Competency :’ Analyser une situation, en s'appuyant sur des techniques de gestion de données et de modélisation, en vue de développer des outils d'aide à la décision, de prospective et d'évaluation’,
Sub Competency : ‘Pratiquer une veille scientifique, politique et d’actualité dans le domaine des sciences économiques afin d’actualiser ses pratiques professionnelles
Sub Competency:’ Concevoir et exploiter de grandes bases de données afin d’en extraire les informations pertinentes au travers d’outils quantitatifs”.
References, bibliography, and recommended reading
Are listed each class on the PowerPoint slides
Other information
Contacts
email: philip.verwimp@ulb.ac.be
personal website: https://sites.google.com/site/philipverwimp1/
Evaluation
Method(s) of evaluation
- Other
Other
individiual assignment: short but detailed technical assignment
group assignment: designing an impact evaluation from scratch. Large assignment, resulting in 20p report.
and oral exam
Mark calculation method (including weighting of intermediary marks)
20% of the grade on the individual assignment
30% on the group assignment
and 50% o the oral exam
Language(s) of evaluation
- english