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Selected Quantitative Methods / Bachelorarbeitsseminar (englisch)


This course is used both for the module “Schwerpunktmodul Quantitative Methoden” (SQM, 6 CP) and the “Bachelorarbeitsseminar” (6 CP). It is recommended to take both modules.

The course is aimed at bachelor students close to the end of their studies, students from the “Profilgruppe quantitative Methoden der Wirtschafts- und Sozialwissenschaften” and exchange students with interest in quantitative methods. The students are expected to have a good knowledge in Statistics and interact during the classes. A prior course in Econometrics is strongly recommended (either Introductory Econometrics in Cologne or a comparable course somewhere else).

Assignments, projects and grades

You will have to complete three assignments for the first 6 CP treating:

1. OLS (deadline: beginning of May)

2. Cross-sectional data, instrument variables (deadline: beginning of June)

3. Time-series data (deadline: beginning of July)

Programming (data analysis and Monte Carlo simulations), writing down the results nicely in a report and maybe giving a small presentation about the results is expected. Towards the end of the course you will independently work on a project (either theoretical/method oriented or empirical). A short paper of about 20 pages and a somewhat longer presentation make up the second 6 CP.

The projects will be completed in small groups of 2-3 students, but individual reports are required. For getting a grade, you will have to formally register for the exam in the middle of May at the latest. The course is taught in English. Assignments and the final project can be handed in English or German, also presentations can be given in both languages. 

The aim of the course

In general: advanced econometrics for bachelor level

Review some things you have learned in statistics and econometrics courses

Increase your understanding of known concepts

Learn about more advanced topics in econometrics

Learn how to deal with practical/implementation issues (e.g. where do I find software, data, etc.)

Obtain basic programming skills using R

Good preparation for bachelor thesis in econometrics/statistics

Good preparation for a master program

Course content 

Review linear regression models and OLS 

Review of parametric statistical models, distributions, estimation principles, hypothesis tests and introduction to Monte Carlo Simulations

Heteroscedasticity: Tests, White robust standard errors, generalized least squares

Omitted variables bias and instrumental variables

Time series, ARMA models and related issues

Unit root testing and spurious regression, introduction to cointegration

Treatment effects

Introduction to panel data and/or introduction to structural break analysis

Start with projects

Lecture on scientific writing and presentations



Primary textbook: Jeffrey Wooldridge, Introductory Econometrics - A modern approach

Other standard textbooks may be useful for some topics, for example William Greene, Econometric Analysis, or Francis Diebold, Elements of Forecasting

Lecture frames, exercises and additional material is available on ILIAS

Further Information

Prof. Dr. Dominik Wied: / 0221-470 4514