–
- Code:
- ECOM-412/DPE-9412
- Field:
- Econometrics
- Targets:
- Master’s students Research Master's students PhD students
- Organiser:
- University of Helsinki - Economics
- Instructor:
- Jani Luoto
- Period:
- Period 1
- Format:
- Lecture
- Method:
- Contact teaching
- Venue:
- Economicum
- Enrollment:
In case of conflicting information consider the Sisu/Course/Moodle pages the primary source of information.
Aalto and Hanken economics students can enroll in their home university’s SISU! Further instructions can be found on the How to enroll page, also for other students.
Before taking and completing the course make sure that the credits can be counted towards your degree at your home university by checking which courses are included in your curriculum or by contacting your home university’s student/learning services.
Please note that there is a different code for UH PhD students: DPE-9412
Content
The course provides an introduction to the empirical implementation of DSGE models and deepens the knowledge of structural VAR models. In addition, the relationship between these two main approaches to empirical research in macroeconomics are discussed, including the validation of DSGE models by vector autoregressions. Finally, identification of the structural VAR model by sign restrictions, often derived from DSGE models, is covered. The emphasis is on the practical application of the methods discussed in modelling macroeconomic data.
Learning outcomes
After the course, the student should
- Be familiar with the solution methods of dynamic stochastic general equilibrium (DSGE) models to the extent needed for their empirical implementation
- Be able to estimate DSGE models, and use them for forecasting and dynamic analysis
- Be aware of the relationship between vector autoregressive (VAR) and DSGE models
- Understand how DSGE models can be validated by means of vector autoregressions, and be familiar with DSGE-VAR models
- Know how structural VAR models can be identified by sign restrictions
- Be able to apply methods of classical and Bayesian statistical inference in DSGE and structural VAR models
- Be able to report empirical research results obtained using the methods covered