Syllabus for Economics C: Analysis of Economic Data

Nationalekonomi C: Analys av ekonomiska data


  • 7.5 credits
  • Course code: 2NE775
  • Education cycle: First cycle
  • Main field(s) of study and in-depth level: Economics G2F

    Explanation of codes

    The code indicates the education cycle and in-depth level of the course in relation to other courses within the same main field of study according to the requirements for general degrees:

    First cycle

    • G1N: has only upper-secondary level entry requirements
    • G1F: has less than 60 credits in first-cycle course/s as entry requirements
    • G1E: contains specially designed degree project for Higher Education Diploma
    • G2F: has at least 60 credits in first-cycle course/s as entry requirements
    • G2E: has at least 60 credits in first-cycle course/s as entry requirements, contains degree project for Bachelor of Arts/Bachelor of Science
    • GXX: in-depth level of the course cannot be classified

    Second cycle

    • A1N: has only first-cycle course/s as entry requirements
    • A1F: has second-cycle course/s as entry requirements
    • A1E: contains degree project for Master of Arts/Master of Science (60 credits)
    • A2E: contains degree project for Master of Arts/Master of Science (120 credits)
    • AXX: in-depth level of the course cannot be classified

  • Grading system: Fail (U), Pass (G), Pass with distinction (VG)
  • Established: 2012-03-01
  • Established by:
  • Revised: 2020-11-03
  • Revised by: The Department Board
  • Applies from: Autumn 2021
  • Entry requirements:

    At least 52.5 credits from Economics A and B and 15 credits in statistics or mathematics.

  • Responsible department: Department of Economics

Learning outcomes

After completing the course, the student is expected to be able to

- independently plan, perform, and present basic empirical work within economics,

- explain and interpret results from regression analyses,

- explain and understand the potentials and limitations of regression analysis,

- understand and explain the intuition behind the most common statistical methods used to isolate causal effects,

- identify strengths and weaknesses in empirical studies,

- perform basic data processing and estimation with the statistical software Stata.


The course will cover tools and concepts that are widely used in economic and many other social science studies as well as within a large number of professional areas such as public administration, financial analysis, and marketing. The course focuses on the analysis of cross-sectional data and the concepts, intuition and software skills needed to independently perform and interpret results from a multiple regression analysis. The statistical methods and concepts covered include multiple regression analysis with continuous, dummy, and interaction variables, t- and F-tests, and omitted variable bias. The course also introduces students to the intuition behind more advanced statistical methods commonly used in economics to isolate casual effects, such as instrumental variable methods. The discussed methods are applied to real world data with the use of the statistical software Stata.


The course consists of lectures and applied work in the computer lab


The course will be examined through independent analyses of several take-home assignments. There will be three grades: pass with distinction (VG), pass (G) and fail (U).

Syllabus Revisions

Reading list

Reading list

Applies from: Spring 2023

Some titles may be available electronically through the University library.

  • Stock, James H.; Watson, Mark W. Introduction to econometrics

    Fourth edition, global edition: Harlow: Pearson, [2020]

    Find in the library