MA Applied Economics of Education

Applied Economics of Education

Syllabus Sommersemester 2020(414.8 KB, 2 Seiten)

This course introduces into the empirical methods that are typically applied in order to identify causal effects rather than correlation only. Identifying causal effects is of great interest and importance (e.g. in terms of policy evaluation), but also challenging. Against this background, this course deals with the methods approaching these challenges; covering:


• Panel data techniques
• Instrumental-Variable (IV) approach
• Regression-Discontinuity (RD) approach
• Differences-In-Differences (DID) approach


A further purpose of the course is to make students familiar with the literature that has applied these methods to questions in the field of education economics.

In accompanying tutorials students will work with the statistic software Stata. Tutorials are not mandatory, but highly recommended to attend, and will focus on the following: i) how to read and critically reflect an empirical paper, ii) how to implement the mentioned methods using Stata and iii) how to replicate published articles. Pre-experience with is Stata desirable, but not mandatory and the tutorials will start with a brief introduction. This “Crash Course” may not be sufficient. Therefore, students are encouraged and asked to take own initiative in filling potential gaps. However, support material will be announced during class, “free classes” are offered in order to solve problems in smaller groups and students are always welcome to make appointments during office hours. See Syllabus “Stata – Advanced Course” for details.

Basic Reading list:

Verbeek, Marno (2012): A Guide to Modern Econometrics. 4th edition. Chichester: John Wiley.
Cameron, Colin A. und Pravin K. Trivedi (2005): Microeconometrics. Methods and Applications. Cambridge: Cambridge University Press [selected chap-ters]
Angrist, J.D., and J.S. Pischke (2009), Mostly Harmless Econometrics, Princeton University Press.
Further literature will be announced in class.