DRE 7041 Topics in Macroeconomics II

DRE 7041 Topics in Macroeconomics II

Course code: 
DRE 7041
Department: 
Economics
Credits: 
3
Course coordinator: 
Fabio Canova
Course name in Norwegian: 
Topics in Macroeconomics II
Product category: 
PhD
Portfolio: 
PhD Economics courses
Semester: 
2021 Autumn
Active status: 
Active
Level of study: 
PhD
Teaching language: 
English
Course type: 
One semester
Introduction

The content of  this  course  will  change  over  the  years. In  the  next  year,  it  will cover global numerical solutions, solutions models  with  occasionally  binding  constraints and modeling, solution and  estimation  of  New Keynesian Heterogeneous  agents (HANK) models.

Learning outcomes - Knowledge

The students should master and produce sophisticated research on dynamic general equilibrium models and on their  implementation with computer  simulations.

Learning outcomes - Skills

After taking this course the students should have a solid knowledge of advances numerical methods used to solve problems in macroeconomics, finance and  international economics, understand how  to  deal  with  zero  lower  bounds and  with time  varying  structures, and  solve  and  analyze  heterogeneous  models  of monetary and  fiscal policy.

General Competence

The students should be able to build, solve and estimate models so as to analyze research questions that are at the frontier in macroeconomics. 

Course content

Lecture 1-2: Global solution methods  for  DSGE models.
Lecture 3: Occasionally  binding  constraints  and  time varying  structures.
Lecture 4-5: Theory  and solution of  HANK models
Lecture 6: Estimation of  Hank models.

Teaching and learning activities

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.

Software tools
Matlab
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 courseleader. 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.

Covid-19

Due to the Covid-19 pandemic, there may be deviations in teaching and learning activities as well as exams, compared with what is described in this course description.

Teaching 

Information about what is taught on campus and other digital forms will be presented with the lecture plan before the start of the course each semester.

Required prerequisite knowledge

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.

Assessments
Assessments
Exam category: 
Submission
Form of assessment: 
Written submission
Weight: 
100
Grouping: 
Individual
Duration: 
1 Month(s)
Comment: 
Written assignment ( individually ) consisting of a maximum of 10 pages (plus references and appendix ).
Exam code: 
DRE 70411
Grading scale: 
Pass/fail
Resit: 
Examination when next scheduled course
Type of Assessment: 
Ordinary examination
Total weight: 
100
Student workload
ActivityDurationComment
Group work / Assignments
30 Hour(s)
Specified learning activities (including reading).
Student's own work with learning resources
40 Hour(s)
Teaching
15 Hour(s)
Sum workload: 
85

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.