Methods for modeling and testing economic relationships using data are rapidly evolving. They become on the one hand more relevant, as the demand for evidence-based decision making increases in business as well as in the public sector. On the other hand it is more feasible as data becomes more abundant. Our research contributes to this development in a number of ways. One focus is on the development of methods for estimating causal relationships based both on structural and experimentalist approaches. The other focus is on non-linear and dynamic models. Our research comprises Bayesian and frequentist methods and it ranges from purely methodological projects to strongly applied ones.
Exemplary project: Fatal Attraction? Access to Early Retirement and Mortality (A. Kuhn, J.-P. Wuellrich, J. Zweimüller)
While the retirement age in most developed countries rises, we wonder what a fall would imply. We take advantage of the change in unemployment insurance rules in Austria that allowed workers in eligible regions to withdraw permanently from employment up to 3.5 years earlier than workers in non-eligible regions. Using instrumental variable techniques to examine the causal impact of early retirement on mortality, we find that a reduction in the retirement age causes a significant increase in the risk of premature death – for males but not for females. Thus people should be careful about what they long for.
Selected research projects
- The Causal Effect of Early Retirement on Health (J. Zweimüller)
- Estimating Large-Dimensional Covariance Matrices (M. Wolf)
- A Dynamic Hurdle Model of Health Demand (R. Winkelmann)
- Structural Econometric Models of the Television Market (G. Crawford)
- Technology Shocks and Aggregate Fluctuation (U. Woitek)
- Models for Discrete Choice and Count Data (R. Winkelmann)
- Multivariate Times Series Prediction (M. Paolella)
- The Causal Effect of Motivational Skill Training on Children's Abilities (E. Fehr)
Connections to courses
Some basic familiarity with empirical research methods is required for those particularly interested in our topic. Students focusing on this field by taking more advanced topic-related courses are well prepared to work in any position where they have to undertake, or at least understand, quantitative analyses. This includes banking, the public sector, as well as many other businesses. The following list provides examples of courses related to Empirical Methods in Economic Research and Policy Analysis.
List of courses
More detailed information on each module can be found by copying the 8-digit code into the search field of the University’s course catalogue.
|Applied Statistics - Regression Analysis||BOEC0076|
|Analysis of Microdata||MOEC0049|
|Time Series Analysis||MOEC0028|
|Introduction to Financial Time Series||MFOEC161|
|Fundamental Probability for Finance||MOEC0294|
|Quantitative Economic History||MOEC0051
|Program Evaluation and Causal Inference||MOEC0338|
|Empirical Models in Monetary Policy||MOEC0272|
|Structural Estimation in Applied Microeconomics||DOEC0468|
|Empirical Industrial Organization||DOEC0134|
Faculty members involved
The following Faculty members research and/or teach in Empirical Methods in Economic Research and Policy Analysis.