Facts about the course

ECTS Credits:
Responsible department:
Faculty of Business Administration and Social Sciences
Course Leader:
Alexander Krumer
Lecture Semester:
Spring, Autumn
Teaching language:
½ year

BØK730 Econometrics (Autumn 2020)

About the course

  • Review of probability distributions, random variables, and statistical inference

  • Linear regresssion models

  • Challenges in using classical linear regression models with data and questions from economics

  • Time Series Models

  • Simple Panel Data Methods

  • Simultaneous Equations Models

  • Limited dependent variable methods

The course is connected to the following study programs

Recommended requirements

Bachelor i økonomi og administrasjon eller tilsvarende samt emnet LOG 708 Applied Statistics eller tilsvarende. 

The student's learning outcomes after completing the course

After completion of the course, students should:

  • Have a good knowledge of basic econometrics and statistical methods as a scientific tool in the analysis of practical economic problems

  • Be familiar with the basic methods of regression analysis as well as the main challenges in applying such to economic questions

  • Be able to specify and estimate appropriate econometric models to test their research questions

  • Be able to interpret and understand estimation results

  • Detect and correct common statistical problems in economic data and models


Forms of teaching and learning

3 timer forelesning per uke samt 2 timer øvinger

Coursework requirements - conditions for taking the exam

  • Obligatorisk arbeidskrav: Oppgave(r)

  • Antall arbeidskrav:

  • Påkrevde arbeidskrav:

  • Fremmøte: Ikke påkrevd

  • Kommentar: Obligatoriske innleveringer i kurset kan være påkrevd.


  • Vurderingsform: Annen vurderingsform, definer i kommentarfelt

  • Andel: 100%

  • Varighet: Timer

  • Gruppering: Individuell

  • Karakterskala: Bokstavkarakter

  • Hjelpemidler: -


Click here for reading list

Last updated from FS (Common Student System) Dec. 8, 2022 4:31:07 AM