Course Descriptions

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Lecturer: Prof. Dr. Mathias Kifmann

In this course, we discuss variants of health care systems in Europe. We analyze how they organize the finance and delivery of health care. The health care systems of Germany and England will be presented in greater detail. Furthermore, we consider selected features of other European countries. We discuss institutional structures, indicators of health and health care systems, and findings of empirical studies.

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Lecturer: Prof. Dr. Tom Stargardt

This course lectures on how to conduct health economic evaluation of health-related technologies using cost-effectiveness (CEA) and/or cost-utility analysis (CUA). The first part includes detailed lectures on the costing of health care interventions as well as on measuring effectiveness and quality of life. In the second part, we concentrate on modelling CEAs and CUAs using decision-trees and markov models. Students are also taught on how to conduct deterministic and probabilistic sensitivity analyses. The course follows a hands-on approach that combines lectures with a practical application in exercises.

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Lecturer: Prof. Dr. Martin Spindler

This course gives an introduction into health econometrics and recent advances. The focus will be on causal inference, heterogeneity and machine learning, in particular how machine learning methods can be used for causal inference. In the health sector digitization leads to many new high-dimensional / big data sets which are available for practitioner and researchers. A key challenge is how these big data sets can be analysed, in particular how causal statements can be derived which are important for policy evaluation.

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Lecturer: Prof. Dr. Johanna Kokot

The behavioral economics approach focuses on better predicting and understanding human behavior in order to develop more effective public policies.

The course aims to introduce to participants the main principles, methods, and insights of behavioral economics. At the same time, key state-of-the-art applications to health economics are discussed. Through discussions and analyses of behavioral experiments, participants will advance their skills of understanding of human behavior, preferences, and errors in cognition. In terms of teaching formats, the course will be using a mixture of formats and approaches – from traditional lectures to interactive seminar sessions.

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Lecturer: Prof. Dr. Jan Marcus

Risky health behaviors such as smoking, alcohol consumption, poor diets, no exercising, and illicit drug use are a leading source of preventable deaths. This course provides an introduction to the economics of risky health behaviors and to methods for causal inference that are applied to (i) determine which factors influence risky health decisions and (ii) to evaluate whether a policy intervention leads to improved health behaviors. The course covers theoretical models of risky health behaviors, policies (and their rationale) to affect risky health behaviors, and causal state-of-the-art methods for situations in which randomised controlled trials are infeasible (including propensity score matching, difference-in-differences, and instrument variable regression).

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