Informations about the modules


Module (6 Credits)

Causality and Programme Evaluation

Name in diploma supplement
Causality and Programme Evaluation
Admission criteria
See exam regulations.
180 hours of student workload, in detail:
  • Attendance: 60 hours
  • Preparation, follow up: 60 hours
  • Exam preparation: 60 hours
The module takes 1 semester(s).
Qualification Targets

Students taking the course will

  • Acquire a sound understanding of identification strategies in microeconometrics
  • Gain knowledge of the advantages and limitations of experimental research
  • Get familiar with the most important non-experimental techniques and their underlying assumptions
  • Learn how to critically assess empirical microeconometric work

For decision makers, e.g. in public policy, it is important to identify causal effects of distinct policy programmes in order to use available resources efficiently. For this purpose there exists a broad variety of methods. This course enables students to critically assess existing empirical evidence and pursue own empirical evaluations.

Module Exam

In order to pass the course students need to solve and hand in problem sets (20% of the final grade), and to write a term paper (usually 20-30 pages, 80% of the final grade) in which they pursue an own empirical evaluation.

Usage in different degree programs
  • BWL EaFWahlpflichtbereich1st-3rd Sem, Elective
  • ECMXWahlpflichtbereichME7 Econometric Methods1st-3rd Sem, Elective
  • GOEMIKWahlpflichtbereich Bereich Volkswirtschaftslehre1st-3rd Sem, Elective
  • VWLWahlpflichtbereich I1st-3rd Sem, Elective
Name in diploma supplement
Causality and Programme Evaluation
Organisational Unit
summer semester
Participants at most
no limit
Preliminary knowledge

Good knowledge of econometrics required.


This is a Master/Ph.D.-level course in causal inference and program evaluation methodology. We will focus on using the potential outcomes approach as a general organizing principle, and examine identification and estimation of treatment effects under various types of assumptions. The course will not go into great depth in regard to any particular applied econometric method, but will instead aim to provide you with enough knowledge about each one to know when, and when not, to use it in empirical work.

  • Theories of Causation
  • Conducting Experiments in Economics
  • Randomisation
  • Differences-in-Differences
  • Instrumental Variables
  • Fuzzy DiD / Multiple Testing
  • Regression Discontinuity Design
  • Methods based on Unconfoundedness
  • Quantile Regression
  • Evaluating Evaluation Techniques
  • Angrist & Pischke (2009), Mostly Harmless Econometrics
  • Imbens & Wooldridge (2009), "Recent developments in the econometrics of program evaluation". Journal of Economic Literature.
Teaching concept

Die Veranstaltung entspricht einem Vorlesungsanteil von 2 SWS und einem Übungsanteil von 2 SWS.

Lecture with integrated exercise: Causality and Programme Evaluation (WIWI‑C0635)
Module: Causality and Programme Evaluation (WIWI‑M0473)