Economics, Causal Inference for Economics - An Introduction, Second Cycle, 7.5 credits

Learning outcomes

Knowledge and understanding

Upon completion of the course, the students should be able to:

• Demonstrate understanding of when a relationship can be interpreted as causal and discuss different ways to calculate/estimate and interpret causal relationships.
• Demonstrate understanding of how problems such as endogeneity, selection and/or reverse causality could influence the estimated relationship.

Competence and skills

Upon completion of the course, the students should be able to:

• Use different types of data to estimate causal relationships using a statistical software.
• Use contrafactual models, i.e models that tries to handle endogeneity, selection and/or reverse causality.

Judgement and approach

Upon completion of the course, the students should be able to:

• Critically evaluate estimated effects.
• Discuss how economic conclusions can be influenced by how the economic and econometric analysis of the available data is done.

Content

The main framework for causal inference
Different methods for causal inference such as:

• Randomised controlled trials
• Instrumental variables
• Regression discontinuity design
• Difference-in-differences.

Examinations and grades

Examination, 7.5 credits (Code: A001)
Grades used are Fail (F), Sufficient (E), Satisfactory (D), Good (C), Very Good (B) or Excellent (A).

Computer Lab Sessions (Code: A002)
Grades used are Participated (DT).

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 moments on the course. To arrive at a course grade, the grades awarded for each examination moment, grades A-E, are first converted to the numerical values 5-1. An average value is then calculated. The course grade is thus awarded by means of a weighted average of the examination moments included on the course.

Modes of assessment

Examination, 7.5 credits (Code: A001)
Written assignments.

Computer Lab Sessions (Code: A002)

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

First-cycle courses of 75 credits in Economics including an independent project of 15 credits.

Statistics, Basic Course, 15 credits and Data Mining and Business Analytics, Basic Course, 15 credits, alternatively Statistics, Basic Course, 15 credits and 7.5 credits in regression analysis/econometrics/scientific method within economic or statistics. The applicant must also have qualifications corresponding to the course "English 6" or "English B" from the Swedish Upper Secondary School.

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

Other provisions

The course will be given in English.

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

Angrist, J. D. and Pischke J (2015)
Mastering Metrics. The path from cause to effect
Princeton: Princeton University Press

Cunningham, Scott (2021)
Causal inference: the mixtape
Yale University Press