MET 1333 Econometrics
MET 1333 Econometrics
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 fundementally international outlook, through the textbook, applications and the subject matter itself. The course teaches digital tools for analyzing data.
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.
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.
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.
- Simple linear regression
- Multiple linear regression
- Non-linear regression functions
- Internal and external validity
- Regressions using panel data
- Probit and logit regressions
- Regressions with instrumental variables
- Experiments and quasi-experiments
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 on their own. Students get access to video with suggested solutions. In addition, there are seven work requirements implemented on its learning.
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.
Higher Education Entrance Qualification
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.
MET 1180 Mathematics, MET 1190 Statistics or equivalent.
| Mandatory coursework | Courseworks given | Courseworks required | Comment coursework |
|---|---|---|---|
| Mandatory | 7 | 5 | 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. |
| Assessments |
|---|
Exam category: Submission Form of assessment: Written submission Invigilation Weight: 100 Grouping: Individual Support materials:
Duration: 3 Hour(s) Exam code: MET13331 Grading scale: ECTS Resit: Examination every semester |
| Activity | Duration | Comment |
|---|---|---|
Prepare for teaching | 71 Hour(s) | |
Teaching | 28 Hour(s) | |
Digital resources
| 14 Hour(s) | |
Group work / Assignments | 60 Hour(s) | |
Feedback activities and counselling | 24 Hour(s) | |
Examination | 3 Hour(s) |
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.