DRE XX25 Topics in Macroeconomics II
This course will focus on numerical solutions, on the implementation on RISE, and on applications to forecasting, conditional projections, and other policy exercises (see separate program)
The students should master and produce sophisticated research on dynamic general equilibrium models and models of international macroeconomics.
After taking this course the students should have a solid knowledge of numerical methods used to solve problems in macroeconomics and understand basic and advanced models of open economy and monetary policy.
The students should be able to build and estimate models so as to analyse research questions that are at the frontier in macroeconomics.
Lecture 1-6 is covered in DRE XX24 Topics in Macroeconomics I
Lecture 1: Calibration of DSGE models
Lectures 2-3: Maximum likelihood estimation of DSGE models
Lectures 4-5: Bayesian analysis and Markov chain Monte Carlo methods
Lecture 6: Bayesian estimation of DSGE models
This course covers lectures 7 - 12.
Lecture 7: Identification issues, DSGE-VARs, Choice of data for estimation.
Lecture 8: Prior and measurement errors specification problems
Lecture 9: Semi-structural DSGE; Data rich estimation
Lecture 10: Trends and non-balance growth paths; Eliciting priors from the data
Lecture 11: Prior Predictive analysis; Time varying coefficients DSGEs.
Lecture 12: Misspecification: composite likelikood and quasi-Bayesian methods.
Students are required to participate in class – both in discussions and by presenting models/material from the reading lists – as well as solve and hand in solutions to exercises and problems.
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.
To properly follow the course, participants must be familiar with DSGE models, and must have followed the basic first year time series course. Familiarity with Matlab is a prerequisite. Knowledge of Dynare and Rise a plus.
|Exam category||Weight||Invigilation||Duration||Grouping||Comment exam|
Form of assessment:
Internal and external examiner
Examination when next scheduled course
|100||No||1 Month(s)||Individual||Written assignment ( individually ) consisting of a maximum of 10 pages (plus references and appendix ).|
|Form of assessment:||Written submission|
|Comment:||Written assignment ( individually ) consisting of a maximum of 10 pages (plus references and appendix ).|
|Exam code:||DRE XXXX1|
|Resit:||Examination when next scheduled course|
Group work / Assignments
Student's own work with learning resources
Teaching on Campus
A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 3 ECTS credit corresponds to a workload of at least 80 hours.