Research Areas

(A) Behavioural Decision Making
(B) Intertemporal Choice and Markets
(C) Political Decisions and Institutions
(D) Information Processing and Statistical Analysis.

Area A: Behavioural Decision Making

Doctoral students studying in Area A specialise in the fields of experimental economics or psychology. Students are expected to have obtained a solid core education in economics, in particular in behavioural economics or in cognitive or social/motivation psychology. Besides doctoral training in this area, students will also take one course and/or seminars from the other areas. Here, they can particularly benefit from quantitative economics (Area B) or from statistical and econometric methods (Area D).

Area B: Intertemporal Choice and Markets

Doctoral students studying in Area B specialise in the fields of finance, personnel economics, labour economics or macroeconomics. Students are expected to have obtained a solid core education in advanced econometrics, microeconomics, macroeconomics, and possibly, in finance. Aside from doctoral training in this area, students can benefit from training in behavioural decision making and experimental techniques (Area A), political economy (Area C) or statistical and econometric methods (Area D).

Area C: Political Decisions and Institutions

Doctoral students studying in Area C will obtain a balanced training in political economy and political science. Students are expected to have a strong background either in microeconomics and economic policy or in the rational choice school of political science. The courses offered by the Graduate School typically combine formal modelling and advanced empirical strategies. Moreover, all students will receive training in quasi-experimental research designs. These courses will particularly focus on causal inference and the multi-level nature of collective decision making. For students who have an interest in testing their models in an experimental setting special course modules will be offered.

Area D: Information Processing and Statistical Analysis

Students specialising in Area D are provided with a strong background in statistical theory and econometric modelling. Core competence has to be developed for the two crucial research stages: data generation and statistical analysis. Students majoring in the other three areas will also benefit from the training programme in Area D, which enables them to develop a consistent research design for their own independent empirical research. In addition to graduate level courses in econometrics, students need to be trained in courses dealing with sampling and survey methodology. Students who need to extend their background in mathematics and statistics can take courses of our Master’s Programme in Quantitative Methods in the Social Sciences, which complements the training aspects of the Graduate School. In particular, the Master’s Programme, offers courses in statistical inference and probability theory. A course in multivariate analysis is offered as a propaedeutic course for the Graduate School.