DRE 7025 Regime Switching in VAR and DSGE Models: Theory and Applications
DRE 7025 Regime Switching in VAR and DSGE Models: Theory and Applications
Regime switches are ubiquitous in economic data and can no longer be ignored in policy discussions. In a world with sometimes abrupt changes in uncertainty, breakdowns of economic structures and policy shifs (e.g unconventional policies), agents have to take into account the possibility of such events reoccurring.
This course will provide you with the necessary tools to analyse regime switches in economics.
Course participants will master a range of tools for solving and estimating Bayesian Vector Autoregressive (BVAR) and Dynamic Stochastic General Equilibrium (DSGE) models in which parameters (or more general regimes) change subject to a switching process that is potentially endogenous. The course will be based on the Rationality In Switching Environments (RISE) Toolbox.
The problems tackled by the tools used in this course are for the most part nonstandard, computationally challenging and massively difficult to solve. Solving those, however, will equip you with the necessary tools to address important economic and policy-relevant issues.
The good news for students following this course is that recent advances in solution methods make it easy for anybody with a basic knowledge of VAR and DSGE modeling to solve an estimate regime-switching models without being a programmer.
I) Constant parameter BVAR (brief introduction)
- Identification and normalization
- Linear restrictions and Gibbs sampling
- Classical/Bayesian
- Priors
- Forecasting (unconditional and conditional)
- Zero and sign restrictions
- Application/Computer session
II) Switching BVAR
- Exogenous swtiching VAR
- Endogeous swtiching VAR
- Simulation: Artificial data, irfs, variance decomposition, shock decomposition
- Application/Computer session
III) DSGE introduction
- Solution methods
- Perturbation
- Taylor projections
- Simulation: Artificial data, forecasting, variance decomposition
- Filtering (linear and non-linear)
- Estimation
- Application/Computer session using RISE
IV) Time varying parameters in DSGE models
- Exogenous switching
- Simulation
- Time varying parameters in DSGE models
- Endogenous switching
- Application/Computer session
V) Occasionally binding constraints
- Optimal Simple rules
- Optimal policy
- Application/Computer session
Students are required to participate actively in class, as well as solve and hand in solutions to exercises and problems
Applicants must have their own laptops with the following programs installed :
MATLAB
- optimization toolbox
- statistics toolboks
RISE toolbox : free
Oxedit (optional): A free version exists
Reading list will be provided in class
Enrollment in a PhD programme is a general requirement for participation in PhD courses at BI Norwegian Business School.
External candidates are kindly asked to attach confirmation of enrollment in a PhD programme when signing up for a course. Other candidates may be allowed to sit in on courses by approval of the course leader. Sitting in on a course does not permit registration for the course, handing in exams or gaining credits for the course. Course certificates or confirmation letters will not be issued for sitting in on courses.
Good knowledge of VAR/DSGE and basic programming skills using MATLAB
Exam category | Weight | Invigilation | Duration | Grouping | Comment exam |
---|---|---|---|---|---|
Exam category: Submission Form of assessment: Written submission Exam code: DRE 70251 Grading scale: Pass/fail Grading rules: Internal and external examiner Resit: Examination when next scheduled course | 100 | No | 4 Week(s) | Individual |
A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 6 ECTS credits corresponds to a workload of at least 160 hours.