Selected Quantitative Methods / Bachelorarbeitsseminar (englisch)
Information
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
Presentations
Literature
• 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: dwied@uni-koeln.de / 0221-470 4514