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2013/2014  KAN-OECON_OE39  Econometrics II: Advanced Topics

English Title
Econometrics II: Advanced Topics

Course information

Language English
Exam ECTS 7.5 ECTS
Type Elective
Level Full Degree Master
Duration One Semester
Course period Autumn
Changes may occur.
Monday 8.00-9.40 week 36-41 og 43-48
Time Table Please see course schedule at e-Campus
Max. participants 50
Study board
Study Board for MSc in Advanced Economics and Finance
Course coordinator
  • Moira Daly - Department of Economics (ECON)
Administration: Ida Lyngby - il.eco@cbs.dk
Main academic disciplines
  • Economics, macro economics and managerial economics
Last updated on 18-03-2013
Learning objectives
After the course the students shall be able to:
  • rigorously prove the consistency (and sometime efficiency) of estimators covered in class
  • demonstrate knowledge of the concepts, models, methods and tools of econometrics as discussed during the course (when to apply what and why)
  • read and understand international research papers that employ econometric methods
  • perform an econometric analysis including identification of the problem, formulation of the theoretical background, specification of a suitable econometric model, proper estimation of the model , and relevant hypothesis testing and inference
  • evaluate an empirical study conducted by another person/researcher.
  • Conduct statistical analysis using Stata and/or R
Course prerequisites
1. Econometrics from the cand. oecon program or similar curriculum; or acceptance to the Economics or Finance Ph.D. program

2. Send in a 1 page application arguing why you want to participate and how you would contribute to the course through discussions and presentations, a 1 page CV, and a 1 page graduate grade transcript. Send this to: oecon.eco@cbs.dk no later than14 May 2013. Please also remember to sign up for the course through the online registration.
Written sit-in exam:
Examination form Written sit-in exam
Individual or group exam Individual
Assignment type Written assignment
Duration 4 hours
Grading scale 7-step scale
Examiner(s) One internal examiner
Exam period Winter Term and December/January
Aids allowed to bring to the exam Closed Book: no aids
Make-up exam/re-exam
Same examination form as the ordinary exam
If the number of registered candidates for the make-up examination/re-take examination warrants that it may most appropriately be held as an oral examination, the programme office will inform the students that the make-up examination/re-take examination will be held as an oral examination instead.
Course content and structure

The aim of the course is to extend their knowledge within the field of Econometrics beyond that which was taught in Econometrics I. Panel and time series data sets will be used to analyze various economic models. The course will provide both a theoretical and an applied (hands on) angle on the topic.
Specifically, students will be expected to understand notions of consistency and efficiency. That is, they will be expected to be able to prove that various estimators are consistent in a rigorous way (i.e. proofs at the level presented in Wooldridge 2010). Matrix notion will often be used in the presentation of the

The course will be organized as two quarter classes. The first of these will concentrate on time series methods , specifically the following topics:
(1) Multivariate VARs and Cointegration
(2) State‐Space Methods
(3) Principal Component Analysis
(4) Markov Switching Models
Time allowing, one or several of the following topics may be covered. Spectral Analysis, Dynamic Linear models, Dynamic Factor Models, Nonparametric methods for time series, Estimation of Taylor‐Rule type models using GMM, and Non‐linear time series models.

The second part of the course will concentrate on more advanced topics in microeconometrics. Elite students and first year Econ Ph.D. students will attend classes together. Specifically, we will cover:
(1) System Estimation by IV
(2) Dynamic Panel Data
(3) Structural Maximum Likelihood Estimation & Behavioral Econometrics
(4) Estimation of Average Treatment Effects
(5) Nonparametric Techniques

Teaching methods
Lectures and in-class exercises
Expected literature


Last updated on 18-03-2013