FIN544 Stata Programming and Applications in Finance
The course focuses on programming in Stata. Programming techniques in Stata will be introduced and applications to real datasets will be covered with the goal of identifying causal relations in empirical corporate finance. The course first covers basic aspects of Stata (for example, data management and importing of data). Subsequently, we will cover bootstrapping, panel data, diff-in-diff estimators, as well as machine learning among other things.
After completing the course, students will be able to:
- use Stata to implement modern technics to identify causal relations in empirical corporate finance
- identify causal relations in empirical corporate finance
The course takes place over seven weeks and is taught via Zoom. Each week consists of a 30 minute pre-recorded video lecture and a 60-minute synchronous lecture.
Successful completion of PhD-level empirical corporate finance course.
Requirements for course approval
Students are required to deliver four written individual assignments during the course.
Christopher F. Baum, An Introduction to Stata Programming, Second Ed., Stata Press
- ECTS Credits
- Teaching language
Spring 2020. Postponed to fall 2020 due to Covid.
Eric de Bodt, Professor of Finance