MET 1333 Econometrics

MET 1333 Econometrics

Course code: 
MET 1333
Department: 
Economics
Credits: 
7.5
Course coordinator: 
Jon H Fiva
Course name in Norwegian: 
Økonometri
Product category: 
Bachelor
Portfolio: 
Bachelor of Science in Business and Economics - Programme Courses
Semester: 
2023 Autumn
Active status: 
Active
Level of study: 
Bachelor
Teaching language: 
Norwegian
Course type: 
One semester
Introduction

This course offers an introduction to econometrics. Econometrics uses statistical methods to quantify economic relationships. These methods are used both in business and economics, as well as in other social sciences. The course has a fundamentally international outlook, through the textbook, applications and the subject matter itself. The course teaches digital tools for analyzing data.

Learning outcomes - Knowledge

After completing the course the students will have:

  • Acquired knowledge about the application of regression analysis to quantify causal relationships.
  • Acquired knowledge about different regression models.
  • An understanding of the depth of the assumptions that must be met in order for the results of empirical analyzes to be interpreted causally.
Learning outcomes - Skills

After completing the course, students will be able to:

  • Critically interpret the results of empirical analyzes.
  • Discuss strategies for building models that can be used for predictions and policy analysis.
  • Master simple linear regression methods, as well as non-linear regression functions (such as logarithmic functions), regression with panel data (combined cross-sectional and time-series data), non-linear probability models (probil and logit), and methods for isolating variation in explanatory variables that are independent of the residual.
  • Use regression methods to analyze data using Stata.
General Competence

Students will be trained to use critical sense of the assumptions on which simple regression analysis is based. In many specific applications, these assumptions break down and they should know what problems this can cause. Students must therefore be open to testing if critical assumptions are in practice and could consider using modified models and methods that better suit the type of data they have available. The students should also be aware that there are causal relationships that are not possible to quantify in practice.

Course content
  1. Simple linear regression
  2. Multiple linear regression
  3. Non-linear regression functions
  4. Internal and external validity
  5. Regressions using panel data
  6. Probit and logit regressions
  7. Regressions with instrumental variables
  8. Experiments and quasi-experiments
Teaching and learning activities

The teaching is carried out with traditional lectures supplemented with pre-recorded video. Each lecture is accompanied by a set of assignments that the students will work on their own. Students get access to video with suggested solutions. In addition, there are seven work requirements implemented on its learning.

Software tools
Stata
Additional information

Re-sit examination
Students that have not gotten approved the coursework requirements, must re-take the exercises during the next scheduled course.

Students that have not passed the written examination or who wish to improve their grade may re-take the examination in connection with the next scheduled examination.

Qualifications

Higher Education Entrance Qualification

Disclaimer

Deviations in teaching and exams may occur if external conditions or unforeseen events call for this.

Required prerequisite knowledge

MET 1180 Mathematics, MET 1190 Statistics or equivalent.

Mandatory courseworkCourseworks givenCourseworks requiredComment coursework
Mandatory75During the course, seven (7) assignments will be given via the learning platform Itslearning. It is a requirement that the students must have passed five (5) of these in order to sit for the exam. Feedback on the assignments will take place both electronically and through a review of assignments in plenary. At the start of the course, information will be provided about the deadlines for the work requirements. The work requirements require the use of Stata.
Mandatory coursework:
Mandatory coursework:Mandatory
Courseworks given:7
Courseworks required:5
Comment coursework:During the course, seven (7) assignments will be given via the learning platform Itslearning. It is a requirement that the students must have passed five (5) of these in order to sit for the exam. Feedback on the assignments will take place both electronically and through a review of assignments in plenary. At the start of the course, information will be provided about the deadlines for the work requirements. The work requirements require the use of Stata.
Exam categoryWeightInvigilationDurationSupport materialsGroupingComment exam
Exam category:
Submission
Form of assessment:
Written submission
Exam code:
MET13331
Grading scale:
ECTS
Grading rules:
Internal examiner
Resit:
Examination every semester
100Yes3 Hour(s)
  • BI-approved exam calculator
  • Simple calculator
Individual
Exams:
Exam category:Submission
Form of assessment:Written submission
Weight:100
Invigilation:Yes
Grouping (size):Individual
Support materials:
  • BI-approved exam calculator
  • Simple calculator
Duration:3 Hour(s)
Comment:
Exam code:MET13331
Grading scale:ECTS
Resit:Examination every semester
Type of Assessment: 
Ordinary examination
Total weight: 
100
Student workload
ActivityDurationComment
Teaching
28 Hour(s)
Digital resources
  • Test with automatic feedback
14 Hour(s)
Feedback activities and counselling
24 Hour(s)
Prepare for teaching
71 Hour(s)
Group work / Assignments
60 Hour(s)
Examination
3 Hour(s)
Sum workload: 
200

A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 7,5 ECTS credit corresponds to a workload of at least 200 hours.