Syllabus
Registration at the institute
Day | Date | Time | Room |
---|---|---|---|
Wednesday | 03/02/22 | 09:00 AM - 12:30 PM | D1.1.074 |
Monday | 03/07/22 | 03:00 PM - 04:00 PM | D2.0.038 |
Wednesday | 03/09/22 | 09:00 AM - 12:30 PM | D2.0.392 |
Monday | 03/14/22 | 03:00 PM - 04:00 PM | D2.0.038 |
Wednesday | 03/16/22 | 09:00 AM - 12:30 PM | D2.0.374 |
Monday | 03/21/22 | 03:00 PM - 04:00 PM | D2.0.038 |
Wednesday | 03/23/22 | 09:00 AM - 12:30 PM | D2.0.038 |
Monday | 03/28/22 | 03:00 PM - 04:00 PM | D2.0.392 |
Wednesday | 03/30/22 | 09:00 AM - 12:30 PM | D4.0.019 |
Monday | 04/04/22 | 03:00 PM - 04:00 PM | D2.0.038 |
Wednesday | 04/06/22 | 09:00 AM - 12:30 PM | D2.0.392 |
Wednesday | 04/27/22 | 09:00 AM - 12:30 PM | TC.4.14 |
Friday | 04/29/22 | 03:00 PM - 04:00 PM | D2.0.392 |
Monday | 05/02/22 | 09:00 AM - 12:30 PM | D5.0.002 |
After completing this class the student will have the ability to:
- understand fundamental concepts, techniques and tools in Bayesian data analysis
- know about various computational approaches towards Bayesian econometrics
- use hierarchical models to answer economic questions
- apply univariate and multivariate models for capturing heteroskedasticity in (financial) time series
- independently and competently perform Bayesian analysis of economic time series
- compare different approaches to point- and density-prediction
- evaluate various forecasting techniques
- connect to state-of-the art literature in Bayesian modeling of economic and financial data
For this lecture, participation is obligatory. Students are allowed to miss a maximum of 20% (no matter if excused or not excused).
The course consists of a mix between lectures and tutorials, reading assignments, case studies and students' presentations. Participants are required to independently apply the models to actual data problems, both in-class as well as between classes.
The grade is composed as follows:
- 5 points: active classroom participation
- 15 points: students' presentations
- 60 points: case studies / homework
- 20 points: final exam
Overall, 100 points can be achieved. The final grade is computed according to
- 1: at least 90
- 2: at least 80
- 3: at least 70
- 4: at least 60
Please log in with your WU account to use all functionalities of read!t. For off-campus access to our licensed electronic resources, remember to activate your VPN connection connection. In case you encounter any technical problems or have questions regarding read!t, please feel free to contact the library at readinglists@wu.ac.at.
Email: darjus.hosszejni@wu.ac.at
Office hours: the Monday entries and the Friday entry in the calendar. No need to register; I will be there.
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