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2020/2021  KAN-COECO1058U  Econometrics

English Title

Course information

Language English
Course ECTS 7.5 ECTS
Type Mandatory offered as elective
Level Full Degree Master
Duration One Semester
Start time of the course Autumn
Timetable Course schedule will be posted at calendar.cbs.dk
Max. participants 50
Study board
Study Board for MSc in Advanced Economics and Finance
Course coordinator
  • Ralf Andreas Wilke - Department of Economics (ECON)
Main academic disciplines
  • Statistics and quantitative methods
  • Economics
Teaching methods
  • Blended learning
Last updated on 15-06-2020

Relevant links

Learning objectives
  • Understand econometric methods of estimation and inference for cross section, time series and panel data, and models with limited dependent variables.
  • State and prove properties of least squares and maximum likelihood estimators.
  • Choose an econometric model, form those introduced in the course, and explain why it is the suitable model for the specific situation.
  • Interpret estimation results in STATA output correctly and comment on appropriateness of their presentation.
  • Relate STATA code and STATA output to the econometric models introduced in the course.
  • Estimate the model and be able to interpret the estimation results, using appropriate software (STATA).
Course prerequisites
This is a mandatory course for the MSc in Advanced Economics and Finance. It is assumed that students have knowledge similar to the entry requirements for this programme. The course has 60 contact hours and there is a high level of interaction betw. lecturer and students, and in general a high work load.

The course has a high technical level and is intended for OECON students. Students are required to have the knowledge of the content of an introductory econometrics course. This includes that the basic tools and fundamentals of mathematics and statistics are already known to students (Compare Appendices A-D in Wooldridge, 2020, Introductory Econometrics, 7th Edition, Cengage ).

To sign up send a 1-page motivational letter and a grade transcript to ily.stu@cbs.dk before the registration deadline for elective courses. You may find the registration deadlines on my.cbs.dk ( https:/​/​studentcbs.sharepoint.com/​graduate/​pages/​registration-for-electives.aspx )

Please also remember to sign up through the online registration.
The exam in the subject consists of two parts:
Sub exam weight50%
Examination formWritten sit-in exam on CBS' computers
Individual or group examIndividual exam
Assignment typeWritten assignment
Duration2 hours
Grading scale7-point grading scale
Examiner(s)One internal examiner
Exam periodAutumn
AidsLimited aids, see the list below:
The student is allowed to bring
  • Non-programmable, financial calculators: HP10bll+ or Texas BA II Plus
  • Language dictionaries in paper format
The student will have access to
  • Advanced IT application package
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.
NOTE: The retake exam will be a written sit-in exam irrespective of the number of students signed up.
Description of the exam procedure

The midterm exam covers the first part of the course (multiple linear regression model, OLS,(F)GLS, MLE).


Sub exam weight50%
Examination formHome assignment - written product
Individual or group examIndividual exam
Size of written productPlease see text below
There is no max., but you have 2 hours to work on your answer.
Assignment typeWritten assignment
DurationWritten product to be submitted on specified date and time.
Grading scale7-point grading scale
Examiner(s)One internal examiner
Exam periodWinter
Make-up exam/re-exam
Same examination form as the ordinary exam
Description of the exam procedure

The final exam mainly covers the content of the second part of the course (topics in Micro- and Panel Econometrics). It bases on the content of the first part of the course.


Course content, structure and pedagogical approach

The aim of the course is to provide the students with an understanding of models, estimation methods within the field of econometrics. Cross sectional, and panel data sets will be used to analyze various economic models. The course provides both a theoretical and an applied (hands on) angle on the topic. The course consists of two parts, the first of which is a (high level) presentation of estimation and inference methods for the multiple linear regression model. Here practical aspects are covered and statistical properties are proved. In the second part the course covers several topics from Micro- and Panel Econometrics. In particular, it elaborates the use of single equation regression models with an emphasis on endogeneity problems and instrumental variable estimation based on cross sectional data set. It focuses on the analysis of panel data sets – their merits, special problems, estimation methods etc. Finally, it covers binary dependent variable models. The course builds on a standard introductory course in econometrics. Knowledge of fundamental concepts of mathematics and statistics is required. Students need to be familiar with matrix notation.


Description of the teaching methods
Lectures and computer based exercise classes.
Feedback during the teaching period
During exercise classes when students present their solutions

After mid-term exam during lectures

Office hours
Student workload
Classes 60 hours
Preparation 95 hours
Preparation for written exam 51 hours
Further Information

Part of this course may also be taken as a PhD course for a limited number of PhD students.

Expected literature




  • Lecture notes
  • Selected scientific articles to be specified during the course
  • Further recommended readings, revision material and articles wil be posted in Canvas



  • Wooldridge, J. (2020), "Introductory Econometrics", 7th edition, Cengage,

    ISBN10: 1-337-55886-9

  • Jeffrey Wooldridge (2010), "Econometric Analysis of Cross Section and Panel Data", 2nd ed, MIT Press
Last updated on 15-06-2020