On completion of the course the students will be able to:

Students shall:
1. Apply modern microeconometric study designs and techniques in order to assess and analyze economic empirical issues involving causal relationships.

Students shall be able to:
2. Set up study designs and apply adequate microeconometric techniques to economic problems
3. Replicate empirical estimations
4. Use statistical softwares appropriate for econometric analysis

Students shall be able to:
5. Critically discern and judge upon the adequacy of the application of microeconometric techniques, and their interpretation as presented in e.g. published articles

This course covers modern econometric models and empirical strategies for the analysis of register-based or experimental cross-sectional and panel micro-data. We go through the econometric theory behind these models and the course also requires reading, analysis and (replications using real as well as simulated data sets), of articles published in top economic journals.

Methods covered includes (1) the randomized experiment and social experiments, (2) instrumental variables estimation, (3) Fixed effects and difference-in-differences techniques applied to panel data, and to other data structures such as family-level and twin data, (4) regression discontinuity designs and (5) matching estimators, such as propensity scores and kernel-matching.

Connection to Research and Practice

This course covers modern econometric models and empirical strategies for the analysis of register-based or experimental cross-sectional and panel micro-data. It links econometric techniques to practical empirical problems and research. The main course literature is a set of recent articles published in top economic journals and covers a wide array of methods and problems. In the examination the students have to critically discern these articles. They also have to come up with a practical research problem of their own, and argue how it could be analysed via different econometric techniques and present software coding (STATA) on how to conduct such an analysis. In this way top notch research is used to enhance the student’s learning, enabling them to assess practical problems both in theory and practice.

The course consist of lectures and seminars.

The teaching is conducted in English.

Bachelor’s Degree in Business or Economics equal to 180 credits including 15 credits in Statistics/ Econometrics; and Mathematical Methods for Economic and Financial Analysis, 7.5 credits (or the equivalent).

The course is graded A, B, C, D, E, FX or F.

Individual written report (ILOs: 1, 2, 3, 4), representing 4 credits.
Individual written assignments (ILOs: 1, 5), representing 3.5 credits.

Name of the Test	Value	Grading
Individual written report1	4 credits	A/B/C/D/E/FX/F
Individual written assignments1	3.5 credits	A/B/C/D/E/FX/F

¹ All parts of compulsory examination in the course must be passed with a passing grade (A-E) before a final grade can be set. The final grade of the course is determined by the sum total of points for all parts of examination in the course (0-100 points). Grade is set in accordance to JIBS grading policy.

At the outset of the course the course coordinator ensures that course evaluators are elected (or exist) among the students. The course evaluation is carried out continuously and at the end of the course. At the completion of the course the course evaluators and course coordinator discuss the course evaluation and possible improvements. The result is reported among others to the Associate Dean for Education, the Council of Undergraduate and Master Education and the Board of Directors of JIBS. The course coordinator shall at the outset of the following course report results and measures from the previous course evaluation.

JIBS students are expected to maintain a strong academic integrity. This implies to behave within the boundaries of academic rules and expectations relating to all types of teaching and examination.
Copying someone else’s work is a particularly serious offence and can lead to disciplinary action. When you copy someone else’s work, you are plagiarizing. You must not copy sections of work (such as paragraphs, diagrams, tables and words) from any other person, including another student or any other author. Cutting and pasting is a clear example of plagiarism. There is a workshop and online resources to assist you in not plagiarizing called the Interactive Anti-Plagiarism Guide.
Other forms of breaking academic integrity include (but are not limited to) adding your name to a project you did not work on (or allowing someone to add their name), cheating on an examination, helping other students to cheat and submitting other students work as your own, and using non-allowed electronic equipment during an examination. All of these make you liable to disciplinary action.

Compulsory literature:

Causal Inference: The Mixtape.
Scott Cunningham
Yale University Press
ISBN-13: 978-0300251685
ISBN-10: 0300251688
Available also online as:
https://mixtape.scunning.com

Selection of academic journal articles

Joshua D. Angrist and Jörn-Steffen Pischke. Mostly Harmless Econometrics: An Empiricist's Companion, Princeton University Press

Additional literature:
Colin Cameron and Pravin K. Trivedi. Microeconometrics Using Stata, Stata Press