Empirical Tax Research

• Overview of the most important topics and methods for causal identification in empirical tax research. Familiarize with state-of-the-art literature. We selected papers to be studied in class which (hopefully) cover the most important topics and methods.
• Insights on “How to survive in academia”: career paths, how to publish, how to write a referee report, how to be a good “academic citizen”, conferences, role of networking, etc..
• Introduction to statistical software package “R”.
• Developing of a research project and carrying out all phases of the projects, i.e., from identifying a research question to writing up a first draft. The class will guide you through all phases of the project. If this project turns out to be feasible and promising, it could well be a first dissertation paper. The projects are conducted over the summer.

1. Statistical Software package “R”
2. Randomized Experiments
3. Difference in Difference (including event studies)
4. Instrumental Variables
5. Regression Discontinuity Design
6. Bunching
7. “How to survive in academia”
8. Presentation of idea for summer project
9. Presentation of the results of summer project.

Grading will be based on:

1. Summary and lead discussion of three papers in class.
   This includes for each paper: short summary of i) RQ, ii) data, iii) intuition behind causal identification, iv) empirical design, v) main results, vi) shortcomings, vii) guiding the discussion about the paper in class. Slides can be helpful, but are not necessary. Paper summary can be substituted by guidance through one of the “R” sessions.
2. Development of a research project.
   This includes: i) presentation of a research question, contribution and idea of empirical design (end of May), ii) writing up a first draft for the project (due Mid August), iii) presenting this draft (time slots for presentations towards the end of the summer break, taking into account our availabilities).