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Impact analysis

academic year

Course teacher(s)

Philip VERWIMP (Coordinator)

ECTS credits


Language(s) of instruction


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.


Courses requiring this course

Teaching methods and learning activities


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


Method(s) of evaluation

  • 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