Economics, Economics Research and Communication, Advanced Course, 7.5 credits

Learning outcomes

Knowledge and understanding

On successful completion of the course, students are expected to demonstrate

• an understanding of how theories in economics can be used to analyze economic questions
• an understanding of what is meant by having a scientific approach in empirical investigations
• broad knowledge of and the ability to interpret regression models using different types of data, as well as understanding central problems in empirical investigations, such as endogeneity, selection and causality.

Competence and skills

On successful completion of the course, students are expected to demonstrate

• ability to analyse and critically discuss economic questions based on relevant theoretical and empirical models
• ability to communicate in writing
• ability to summarise, present and discuss own and other students’ reports.

Judgment and approach

On successful completion of the course, students are expected to

• be able to assess the societal relevance and usefulness of own work and previous research in economics
• demonstrate an understanding of the merits and drawbacks of theory and methods in economics
• demonstrate ability to assess the reliability of different sources of knowledge.

Content

• Scientific approach
• Regression analysis with cross-sectional data
• Regression analysis with panel data
• Regression analysis with time series data

Examinations and grades

Economics Research and Communication, Computer Lab Sessions (Code: A001)
Grades used are Participated (DT).

Economics Research and Communication, Individual Task, 3.5 credits (Code: A004)
Grades used are Fail (F), Sufficient (E), Satisfactory (D), Good (C), Very Good (B) or Excellent (A).

Economics Research and Communication, Written Examination, 4 credits (Code: A005)
Grades used are Fail (F), Sufficient (E), Satisfactory (D), Good (C), Very Good (B) or Excellent (A).

According to the Higher Education Ordinance, Chapter 6, Section 18, a grade is to be awarded on the completion of a course, unless otherwise prescribed by the university. The university may determine which grading system is to be used. The grade must be determined by a teacher specifically nominated by the university (the examiner).

In accordance with university regulations on grading systems for first and second-cycle courses and study programmes (Vice-Chancellor’s decision ORU 2018/00929), one of the following grades is to be used: fail (U), pass (G) or pass with distinction (VG). For courses included in an international master’s programme (60 or 120 credits) or offered to the university’s incoming exchange students, the A to F grading scale is to be used. The vice-chancellor, or a person appointed by them, may decide on exceptions from this provision for a specific course, if there are special grounds for doing so.

The grades used on this course are Fail (F), Sufficient (E), Satisfactory (D), Good (C), Very Good (B) or Excellent (A).

Comments on grades

To obtain a passing grade for the course as a whole, a minimum of grade E is required for all examination components on the course and the grade Participated for mandatory components. To arrive at a course grade, the grades awarded for each examination assignment, grades A–E, are first converted to the numerical values 5–1. An average value is then calculated, also taking into account the number of credits for each examination assignment in relation to the total number of credits for the course. The course grade is thus awarded by means of a weighted average of the examination assignments included on the course.

Modes of assessment

Computer Lab Sessions (Code: A001)
Written Individual Task, 3.5 credits (Code: A004)
Written Examination, 4 credits (Code: A005)

A prerequisite to participate in the examination Individual Report is participation in the first two computer lab sessions. These sessions contains learning components necessary to complete the individual report. A student who for special reasons couldn't attend the first two sessions are offered a new opportunity at any of the other computer lab sessions during the course. A student who couldn't attend two of the sessions is referred to the next time the course is given.

For students with a documented disability, the university may approve applications for adapted or other modes of assessment.

For further information, see the university's local examination regulations.

Specific entry requirements

Economics, basic course, 30 credits and successful completion of 15 credits from Economics, intermediate course, 30 credits. In addition, successful completion of 18 credits in statistics at basic level including 6 credits on the course Data Mining and Business Analytics, Basic Course, 15 credits alternatively Successful completion of 22 credits in statistics at basic level including Regression Analysis, basic course, 7.5 credits.

For further information, see the university's admission regulations.

Other provisions

Students who have been admitted to and registered on a course have the right to receive tuition and/or supervision for the duration of the time period specified for the particular course to which they were accepted (see, the university's admission regulations (in Swedish)). After that, the right to receive tuition and/or supervision expires.

Reading list and other learning resources

Required Reading

Hansson, Sven Ove
The Art of Doing Science
KTH, Stockholm, Compendium, about 100 pages

Wooldridge, Jeffrey M. (most recent edition)
Introductory Econometrics: A Modern Approach
Michigan State University

Additions and Comments
Articles and other materials.