Topics in Public Economics
State Capacity, Corruption, and Public Administration
Lecture and Exercise
This course familiarizes you with recent research on corruption and state capacity from a public economics perspective. You will be acquainted with empirical evidence on how much corruption there is, with the determinants of corruption, with the consequences of corruption for efficiency and economic growth as well as with different measures to fight corruption. In the course, we will cover both theoretical models and empirical evidence.
Seminar in Public Economics
Put your skills to work by participating in a seminar in Public Economics: This seminar explores the use of randomized field and survey experiments to study key questions in public economics. Conducted in real-world settings, these experiments provide rigorous empirical evidence on individual preferences and on the effectiveness of policy interventions in shaping behaviour.
Empirical and Experimental Public Economics
Lecture and Exercise
You will learn to critically assess the latest empirical papers in the area of public economics and you will be taught how to apply modern econometric methods, which are commonly used in empirical public economics, to a variety of research questions. The overall focus of the lecture is on behavioural responses to taxation, covering real, shifting and evasion responses. When discussing the relevant literature, you will become acquainted with, amongst others, the following empirical approaches: natural and randomized field experiments, difference-in-differences estimations, instrumental variables, discrete-choice analysis, and panel data analysis.
Next lecture will take place during summer term 2027.
Here you can find general information regarding writing a thesis at our chair. If you are writing your thesis at our chair, please read the following documents. Please notice that we only supervise master theses of students who have successfully completed at least one master course from our field.
Afterwards, please write us a Mail: fiwi@uni-hohenheim.de.
Information on the Consequences of Plagiarism and the Use of Generative AI Systems