MET 1333 Econometrics

APPLIES TO ACADEMIC YEAR 2016/2017
Norwegian version

MET 1333 Econometrics


Responsible for the course
Jon H. Fiva

Department
Department of Economics

Term
According to study plan

ECTS Credits
7,5

Language of instruction
Norwegian

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 outcome
Acquired 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.

Acquired 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.


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.


Prerequisites
MET 1180 Mathematics, MET 1190 Statistcs or equivalent.

Compulsory reading
Books:
Stock, James H., Mark W. Watson. 2014. Introduction to Econometrics. 3rd ed. Pearson. kapittel 1, 4 - 13. Vedleggene er ikke pensum

Recommended reading
Books:
Midtbø, Tor. 2012. Stata : en entusiastisk innføring. Universitetsforlaget

Course outline

  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

Computer-based tools
STATA

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

Coursework requirements
During the course seven (7) assignments will be set through It’s Learning. Students need to pass five (5) of these to be able to sit for the exam. Feedback on the assignments will be provided electronically and in class. More information, concerning deadlines etc. will be provided at the beginning of the semester.

Recommended use of time
Activity
Hours
Lectures
36
Assignment-solving in classroom
9
Reading literature and preparation for lectures
100
Assignment-solving
52
Examination
3
Total recommended use of hours, about
200

    Coursework requirements
    At the beginning of the semester, 7 coursework requirements will be given. At least 5 of these must be approved before the students can take the examination at the end of the course.

    Examination
    3-hours individually written examination concludes the course.
    Examination code(s)
    MET 13331 - Written examination, counts 100% towards the final grade in MET 1333 Econometrics, 7.5 ects.

    Examination support materials
    BI approved exam calculator. Examination support materials at written examinations are explained under examination information in the student portal @bi. Please note use of calculator and dictionary in the section on support materials (https://at.bi.no/EN/Pages/Exa_Hjelpemidler-til-eksamen.aspx).

    Re-sit examination
    A re-sit examination is every term.
    Students that have not had their coursework requirements approved will not be able to take the examination. This means that they have to re-take the whole course, and not only the examination.


    Additional information