Econometrics, Statistics and Empirical Economics

S510/S520 Topics in Economics and Finance

This seminar is jointly offered by the departments of Prof. Dr. Martin Biewen (Statistics, Econometrics, and Quantitative Methods) and Prof. Dr. Joachim Grammig (Econometrics, Statistics, and Empirical Economics).

Please register by joining the ILIAS folder, where you will have to upload a current transcript of records and fill out a survey regarding your topic preferences by April 16, 11:55pm. Your supervising chair will be assigned to you based on your indicated preferences, and you will be contacted once the decision has been made.

Lecturer

Prof. Dr. Martin Biewen

Prof. Dr. Joachim Grammig

Dr. Julie Schnaitmann

Dr. Jantje Sönksen

Constantin Hanenberg

Alexander Reining

Marian Rümmele

Miriam Sturm

Level Master
Prerequisites

At least one successfully completed master course offered by the departments of Prof. Biewen or Prof. Grammig

Language English
Credit Points 9
Exam

1. Term paper

2. Paper presentation

3. Discussion of another paper

Timeline

until 16.04.2023, 11:55pm Upload transcript of records to the Ilias folder and fill out survey  
until 21.04.2023 Assignment to supervising chair via email
until 27.04.2023 Discussion of the chosen topic with supervisor  
28.04.2023 Start of working time  
07.07.2023, noon (12:00) Deadline for submitting seminar thesis  

14.07.2023

Presentation of final thesis time and place tba

Seminar outline

The seminar will be held jointly by the departments of Prof. Biewen and Prof. Grammig. Topics of the seminar will include:

Each participant will be assigned a specific topic. We expect all participants to prepare a professional presentation and a term-paper on his/her topic, which may include a small empirical application using data such as German Socio-Economic Panel Study or a data set from the field of finance.

Formal guidelines

Plagiarism and academic fraud

It is strictly forbidden to: i) copy/paste text from existing publications outside a regular quote, ii) copy essential thoughts or structures from existing work without acknowledging their sources, iii) use substantial external help in carrying out research or writing without acknowledging this, iv) produce fake research results. Any violations of these rules may lead to exmatriculation. Academic fraud may also destroy your career if discovered later in your life. We will use software to detect potential academic misconduct.