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 October 15, 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.

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

• Time Series Analysis
• Financial Econometrics
• Microeconometrics
• Panel Data Analysis

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 for the written thesis are provided in the seminar folder on Ilias.
• Orthography, grammar and style of the thesis will be taken into account for grading.
• We suggest to use Latex to prepare the thesis and the presentation. The zip-file contains a document "vorlage.tex" which illustrates the use of Latex and provides installation information. "vorlage.pdf" is the result when compiling the tex-file.
• The presentation of the final thesis has to be in Powerpoint, Latex or similar. There is no need for handouts.
• Presence at the entire final presentation session is obligatory.

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.