Prof. Dr. Fabian Woebbeking
Assistant Professor of Financial Economics
IWH - Leibniz Institute for Economic Research
MLU - Martin Luther University Halle-Wittenberg
fabian.woebbeking@iwh-halle.de
Birte Winter
PhD Candidate, Teaching Assistant (TA)
IWH - Leibniz Institute for Economic Research
This seminar is designed to immerse students in the practical aspects of econometric analysis, with an emphasis on empowering them with the data and tools necessary to select and apply the appropriate empirical methods to various research questions. Procuring data consumes significant time and resources; hence, in this seminar, datasets are provided for each topic, enabling students to immediately dive into hands-on analysis. This approach allows for practical experience in handling data, choosing the right models, and interpreting results. The methods covered range from simple linear regression to advanced models for causal inference.
The deadline for submitting the seminar paper is the first day of presentations: 2024-06-27!
Dates and rooms can be found on Stud.IP: https://studip.uni-halle.de/dispatch.php/course/details?sem_id=5a9defd4ce9b514471199574c12ee710&again=yes
After you have had time to do some research on your topic, you should contact the TA to schedule a first meeting where we can discuss your plan and structure.
Please send an email to Birte Winter (birte.winter@iwh-halle.de) with a ranking of your topic preferences. You will receive a notice with your assigned topic by 2024-04-21.
If you do not submit your preferences, you will receive a topic assigned at random. Please note that signing the registration form is required to participate in the seminar. You can withdraw from the seminar by contacting the examination office within 14 days of receiving the topic.
The grading policy is discussed in detail during the first meeting.
- Seminar project and paper: 70%
- Presentation and discussion: 30%
- Own presentation: 20%
- Questions and discussion: 10%
- Linear regression, least squares and statistical significance
- Research Question: Explain square meter prices with the property age
- Multivariate regression, goodness of fit and information criteria
- Research Question: Explain square meter prices with property age, acquisition date, distance to the nearest metro station, number of supermarkets in the neighborhood, and accessibility amenities factor (which is the number of supermarkets divided by the distance to the next metro)
- Principal component analysis (PCA)
- Research Question: Use a PCA to model the yield curve of spot rates. Is there an economic interpretation for the components?
- Non-linear regression
- Research Question: Explain square meter prices with property age, acquisition date, distance to the nearest metro, number of supermarkets in the neighborhood, and property age squared
- Linear probability, Logit-/ and Probit models
- Research Question: Predict the likelihood of a prospective client's contentment with the provided service and discern the key elements articulated by clients that predominantly impact airline satisfaction.
- Tobit regression
- Consider a scenario where we aim to analyze academic aptitude scores (ranging from 200 to 800) by incorporating reading and math test results, alongside the type of program the student is enrolled in (academic, general, or vocational). Students who answer every question correctly on the academic aptitude test are awarded a perfect score of 800, regardless of potential differences in their actual aptitude levels. Similarly, those who answer all questions incorrectly receive the minimum score of 200, despite potential variations in their true aptitude levels.
- Research Question: Investigate the relationship between academic aptitude and reading proficiency, math proficiency, and program type, while considering the potential truncation at both upper and lower limits of the aptitude scale
- Panel data, H-Test, random and fixed effect models*
- Research Question: How does the total cost of airline operations vary with factors such as revenue passenger miles, fuel price, and load factor?
- Regression discontinuity*
- Research Question: Investigate the relationship between the outcome variable and the running variable. Specifically, does the outcome variable change significantly as the running variable crosses a certain threshold while considering other relevant factors such as age, income, education level, health status, and work experience?
- Difference in difference*
- Research Question: explain the effect of the treatment (did) on GPD per Capital (gdppc). Account for group-specific and time-specific effects. Check the parallel trend assumption.
- Instrumental variable regression*
- Research Question: Wage should be explained by ability. However, this is unobservable. Use an individual’s mother’s education as an instrumental variable.
(*) Advanced topics
Please find general writing guidelines as well as a template at: https://github.com/cafawo/WritingGuidelines
Each seminar paper and presentation should cover:
- Introduction: A brief description of your research question and, specifically, your methodology. Why is this method suitable for your research question?
- Literature: High quality references that link your analysis to the current state of academic research. In contrast to typical research papers, particular focus should be on showcasing the method, not to give an extensive literature review on your research question. This means that you are encouraged to add references that use your method and explain the research objectives and findings therein, even if these papers are not related to your own research question.
- Methodology: Explain the methodology, when and why to use it and potential limitations.
- Data structure and visualization: You have been given a test dataset. Show the data (e.g. a tabular snapshot) and why it lends itself to your methodology.
- Summary statistics: Show a table with summary statistics of your data.
- Model specifications: Specify the corresponding empirical model (mathematical notation) and explain.
- Results and interpretation: Fit the model and show your results. Provide a brief interpretation (Which coefficient(s) are significant? What does that mean?).
- Conclusion: A very brief summary of your findings.
While your seminar paper should cover the aforementioned points, you are free to adjust the structure and content to whatever yields a well structured and readable seminar paper.
You will need a software toolbox that is capable of statistical analysis. Use what you are most familiar with, for example:
- https://www.r-project.org/ (open source)
- https://www.python.org/ (open source)
- https://www.stata.com/
- https://www.ibm.com/spss
- https://gretl.sourceforge.net/ (open source)
Despite the vast amount of high-quality online and open-source resources available, if you are looking for a textbook, I recommend "Mastering metrics : the path from cause to effect" or the more comprehensive (Master/PhD level) "Mostly Harmless Econometrics: An Empiricist's Companion" both by Joshua D. Angrist and Jörn-Steffen Pischke. Both books are available at the Library.