MET 1333 Econometrics

MET 1333 Econometrics

Course code: 
MET 1333
Department: 
Economics
Credits: 
7.5
Course coordinator: 
Christian Brinch
Course name in Norwegian: 
Økonometri
Product category: 
Bachelor
Portfolio: 
Bachelor of Science in Business and Economics - Programme Courses
Semester: 
2018 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.

Learning outcomes - Knowledge

After having completed this course you should be able to explain how regression analysis is used to quantify economic relationships. You should be able to explain under what circumstances empirical analysis may be given a causal interpretation. You should be able to interpret empirical analysis critically.

Learning outcomes - Skills

You should acquire the relevant skills to be able to use regression analysis to quantify causal relationships. You should be able to discuss different modelling strategies useful for prediction and policy analysis. In addition to linear regression methods, you should also understand non-linear regression functions (such as log specifications), regression with panel data (combined cross sectional and time series data), non-linear probability methods (probit and logit), and methods for isolation variation in explanatory variables that are independent from the error term.

Learning Outcome - Reflection

The course provides you with critical thinking skills relevant for discussing assumptions that least square techniques build on. You should be able to use models and methods relevant for the data you have available and be able to discuss critically whether the assumptions imposed hold 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
Learning process and requirements to students

The course consists of 36 hours of lectures and 9 hours of problem-solving.

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.

Required prerequisite knowledge

MET 1180 Mathematics, MET 1190 Statistcs or equivalent.

Mandatory courseworkCourseworks givenCourseworks requiredComment coursework
Mandatory75I løpet av kurset bil det bli gitt syv (7) oppgaver via læringsplattformen It’s learning. Det er et krav at studentene skal ha fått godkjent fem (5) av disse for å kunne gå opp til eksamen. Tilbakemelding på oppgavene vil både skje elektronisk og gjennom oppgavegjennomgang i plenum. Ved kursstart vil det bli opplyst om tidsfristene for arbeidskravene. Arbeidskravene krever bruk av STATA.
Mandatory coursework:
Mandatory coursework:Mandatory
Courseworks given:7
Courseworks required:5
Comment coursework:I løpet av kurset bil det bli gitt syv (7) oppgaver via læringsplattformen It’s learning. Det er et krav at studentene skal ha fått godkjent fem (5) av disse for å kunne gå opp til eksamen. Tilbakemelding på oppgavene vil både skje elektronisk og gjennom oppgavegjennomgang i plenum. Ved kursstart vil det bli opplyst om tidsfristene for arbeidskravene. Arbeidskravene krever bruk av STATA.
Exam categoryWeightInvigilationDurationSupport materialsGroupingComment exam
Exam category:
Submission
Form of assessment:
Written submission
Exam code:
MET13331
Grading scale:
ECTS
Grading rules:
Internal and external 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
Exam organisation: 
Ordinary examination
Total weight: 
100
Student workload
ActivityDurationComment
Teaching
36 Hour(s)
Feedback activities and counselling
9 Hour(s)
Prepare for teaching
100 Hour(s)
Group work / Assignments
52 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.