Syllabus

Title
1532 Advanced Macroeconometrics: Applications
Instructors
Prof. Dr. Gernot Doppelhofer, Ph.D.
Contact details
Gernot.Doppelhofer@nhh.no
Type
FS
Weekly hours
2
Language of instruction
Englisch
Registration
11/19/18 to 11/30/18
Registration via LPIS
Notes to the course
Subject(s) Doctoral/PhD Programs
Research Seminar in Main Subject I - Economics
Research Seminar in Main Subject I - Empirical Business Research
Research Seminar in Main Subject II - Economics
Research Seminar in Main Subject II - Empirical Business Research
Research Seminar in Main Subject III - Economics
Research Seminar in Main Subject III - Empirical Business Research
Research Seminar in Main Subject IV - Economics
Research Seminar in Main Subject IV - Empirical Business Research
Dissertation-relevant theories - Economics
Dissertation-relevant theories - Empirical Business Research
Research Seminar - Economics
Research Seminar - Empirical Business Research
Research Seminar - Economics
Research Seminar - Empirical Business Research
Research Seminar - Participating in scientific discourse I
Research Seminar - Participating in scientific discourse II
Dates
Day Date Time Room
Tuesday 12/04/18 10:00 AM - 02:00 PM D4.0.047
Wednesday 12/05/18 09:00 AM - 01:00 PM D4.0.047
Monday 12/10/18 09:00 AM - 01:00 PM D4.0.047
Tuesday 12/11/18 09:00 AM - 01:00 PM TC.4.28
Wednesday 12/12/18 09:00 AM - 01:00 PM D4.0.047
Thursday 12/13/18 09:00 AM - 01:00 PM TC.5.12
Friday 12/14/18 09:00 AM - 01:00 PM TC.3.09

On this page:

to top
Contents

The course gives an introduction to methods in Macroeconometrics with special emphasis on Bayesian techniques.

We will discuss the following topics:

- Vector Auto Regressions (VARs): estimation, identification, impulse response functions

- Dynamic Stochastic General Equilibrium (DSGE) models 

- Likelihood methods: Kalman filter, ML estimation of DSGE models

- Introduction to Bayesian estimation and simulation

- Bayesian VARs (BVARs): priors for VARs, Bayesian estimation, structural BVARs

- Bayesian time series: Factor models, time-varying parameter models, Bayesian DSGE estimation and evaluation

- Model uncertainty and model misspecification 

Form of evaluation:  

- practical exercises

- short research paper

to top
Learning outcomes
Upon completion of the course, students will be familiar with methods employed in macroeconometrics. Students will have the opportunity to apply macroeconometric methods in practical exercises. Students will also submit a short research paper using macroeconometric methods. The research paper can be based on their own research project or outline a novel research question.
to top
Teaching/learning method(s)
Combination of lectures and practical exercises. Students can also give a short presentation of their research proposal.
to top
Assessment

The course grade will be determined by a combination of the practical exercises and the submitted research paper or proposal.

- Practical exercises (30%)

- Presentation (30%)

- Term paper (40%)

to top
Prerequisites for participation and waiting lists

Students are presumed to have knowledge of econometrics at the intermediate undergraduate level. No prior knowledge of Bayesian estimation is required. Some basic knowledge of programming using Matlab or R is expected for the practical exercises.


to top
Availability of lecturer(s)

Gernot.Doppelhofer@nhh.no

Last edited: 2018-09-04



Back