DE / EN

Empirical Tax Research

TAX 913 for Doctoral Students

Lecturers Prof. Dr. Johannes Voget
Prof. Dr. Philipp Dörrenberg
Frequency Spring Semester
Courses Lecture
ECTS 10
Language English
Form of Assessment Essay and/or presentation

Course Details

Class sessions are mostly organized along the methods in the standard tool kit of empirical research. We start off each topic with a brief and easy overview of the method. Afterwards, a student will summarize a paper using the respective method and we will discuss in class. For each method, we identify a set of core papers which use the respective method, present examples of a state-of-the art application and are relevant topic wise. These core papers are summarized and discussed in class. We expect all students to read the core papers that we cover in class.

In addition, students learn basic knowledge of the statistical software package “R” and we will talk about “How to survive in academia”. Toward the end of the term, students present their summer project. Summer projects are conducted over the summer and presented during the beginning of the subsequent fall term.


    Course Structure

  • Goals

    • 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.
  • Table of Contents

    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

    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). 

Schedule

Type From To Weekday From To Room
Lecture 10.02.20
14.02.20
25.05.20
29.05.20
Monday
Friday
13:45
15:30
17:00
17:00
SO 133
SO 133

Registration

You can register for the course via the course catalog on the CDSB website.