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ØKA2005 Introductory Econometrics

    • Number of credits
      7,5
    • Teaching semester
      2023 Autumn, 2024 Autumn, 2025 Autumn
    • Language of instruction
      English
    • Campus
      Lillehammer
    • Required prerequisite knowledge

      An introductory course in social science research methods; an introductory course in calculus/mathematics and statistics (advisable). 

Course content

The course is a continuation of the course Introduction to social science research methods. The objective is to give students a comprehensive introduction to some of the main the statistical techniques that fall under the heading of econometrics. In particular, the emphasis is on linear regression analysis and its extensions. 

Application is a key word for the course. The instructor will explain and demonstrate the various statistical analyses in class and the students will replicate these in a “computer laboratory” after class under supervision. As the first part of a mandatory hand-in, students will in groups (up to 5) gather their own data for an econometrics project. The second part of this hand-in, carried out in pairs, consist of demonstrating the various “tricks of the trade” covered during the course. The evaluation of the hand-in emphasizes clarity and reasonability in the presentation of results.

Learning Outcome

Upon passing the course, students have achieved the following learning outcomes:

Knowledge

The student

  • can describe the general research process in an econometrics project
  • can explain how linear regression analyses works in general
  • can describe the assumptions of linear regression, and how to test the “testable” ones
  • can discuss the meaning of a correctly specified model and different functional forms
  • can articulate how logistic regression analysis works and how to interpret its findings (roughly) 
  • can articulate how times-series regression analysis works (roughly)
Skills

The student

  • can design an econometrics project (e.g. a bachelor project) based on regression analysis as the main methodological tool
  • can perform basic data management tasks (e.g. construction of polynomials, logarithms, interactions etc.)
  • can carry out, interpret and present results from regression analyses in a satisfactory manner with respect to clarity and reasonability
  • understand the various assumptions that regression analysis rests upon as well as how to test certain of these assumptions
  • can grasp and articulate the notion of a “correctly specified model” and understand the ideas behind the use of various functional forms
  • can carry out basic logistic regression analysis
  • can carry out basic time-series regression analysis
General competence

The student

  • can ascertain whether a research question could be stated in terms of an econometrics project
  • can define, redefine and confine a research question into an econometrics project 
Teaching and working methods

Traditional lectures, lectures with demonstrations of regression analysis and econometric problem solving in a “computer laboratory.” How to use a particular statistical software will be demonstrated in class and in the computer laboratory. Presently, the statistical software is Stata.

Required coursework

A two-part mandatory hand-in (the first part prepared group wise; the second part prepared pair wise). To be allowed to take the final exam, the mandatory hand-in must be passed.

Assessments
Form of assessmentGrading scaleGroupingDuration of assessmentSupport materialsProportionComment
Written examination with invigilation
ECTS - A-F
Individual
3 Hour(s)
  • Approved calculator
100
About permitted aids: calculator that meets the requirements for the use of calculator at the business education at INN. Updated guidelines are available and will be distributed at start-up each year.
Faculty
Inland School of Business and Social Sciences
Department
Department of Business Administration