DRE 7025 Regime Switching in VAR and DSGE Models: Theory and Applications

DRE 7025 Regime Switching in VAR and DSGE Models: Theory and Applications

Course code: 
DRE 7025
Department: 
Economics
Credits: 
6
Course coordinator: 
Hilde Christiane Bjørnland
Junior Maih
Product category: 
PhD
Portfolio: 
PhD Economics courses
Semester: 
2018 Spring
Active status: 
Active
Teaching language: 
English
Course type: 
One semester
Introduction

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. 

Learning outcomes - Knowledge

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. 

Learning outcomes - Skills

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.

Learning outcomes - Reflection

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.

Course content

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

 

Learning process and requirements to student

Students are required to participate actively in class, as well as solve and hand in solutions to exercises and problems

Software tools
Matlab
Additional information

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

Qualifications

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.

Required prerequisite knowledge

Good knowledge of VAR/DSGE and basic programming skills using MATLAB

Exam categoryWeightInvigilationDurationGroupingComment 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
100No4 Week(s)Individual
Exams:
Exam category:Submission
Form of assessment:Written submission
Weight:100
Invigilation:No
Grouping (size):Individual
Duration:4 Week(s)
Comment:
Exam code: DRE 70251
Grading scale:Pass/fail
Resit:Examination when next scheduled course
Exam organisation: 
Ordinary examination
Total weight: 
100