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Impact Evaluation Methods

General Information:

  • Master
  • Summer Term
  • Lecture and Tutorial
  • Teaching/ Working Language: English


The course introduces students to the counterfactual causality model and provides them with a unified framework for answering the questions of cause and effect. It covers the state-of-the-art methods of causal inference such as experimental designs, matching, instrumental variables, regression discontinuity, differences-in-differences and synthetic controls. The course emphasises the intuition behind the methodology rather than formal proofs. It is based on a mixture of textbooks and articulated lessons as well as practical exercises using the most popular software packages.


After completing this module, students will be able to

  • build a counterfactual model
  • explain the assumptions required to identify a causal effect in experimental and non-experimental designs
  • know when to use different causal inference methods
  • perform causal inference with existing data sets
  • Interpret the results of causal inference


Written term paper of 12 - 15 pages


Chair of Empirical Economics


Dr. Aleksandr Alekseev

Alex Alekseev

E-Mail: aleksandr.alekseev@ur.de

Phone: +49 941 943-2740
Office: RW(L) 5.18

Office hours: by arrangement