Syllabus
Registration via LPIS
Day | Date | Time | Room |
---|---|---|---|
Monday | 03/06/23 | 10:00 AM - 12:00 PM | TC.5.18 |
Monday | 03/13/23 | 10:00 AM - 12:00 PM | TC.5.18 |
Monday | 03/20/23 | 10:00 AM - 12:00 PM | TC.5.18 |
Monday | 03/27/23 | 10:00 AM - 12:00 PM | EA.5.040 |
Monday | 04/17/23 | 10:00 AM - 12:00 PM | TC.5.18 |
Monday | 04/24/23 | 10:00 AM - 12:00 PM | TC.5.18 |
Monday | 05/08/23 | 10:00 AM - 12:00 PM | TC.5.18 |
Monday | 05/15/23 | 10:00 AM - 12:00 PM | TC.5.18 |
Monday | 05/22/23 | 10:00 AM - 12:00 PM | TC.5.18 |
Monday | 06/05/23 | 10:00 AM - 12:00 PM | TC.5.18 |
Monday | 06/12/23 | 10:00 AM - 12:00 PM | TC.5.18 |
Monday | 06/19/23 | 10:00 AM - 12:00 PM | TC.5.18 |
Monday | 06/26/23 | 10:00 AM - 12:00 PM | TC.5.18 |
The econometrics teaching program is offered in a cycle over 3 terms. In Econometrics I, the foundations of the subject are dealt with: causality, correlation, assumptions of the linear regression model, OLS estimation, asymptotic tests, misspecification, outliers, heteroskedasticity and an introduction to R. In Econometrics II, advanced subjects are covered: Time series analysis, endogeneity, instrumental variable estimation, panel data and limited dependent variable models. In Applied Econometrics, a deeper analysis of selected topics is offered and students are required to write an empirical, applied-econometric essay.
'Econometrics I' comprises chapters 1-8 of Wooldridge's “Introductory Econometrics. A Modern Approach”, in particular:
- Univariate regression model and the ordinary least squares estimator (OLS)
- Multivariate regression model (application, interpretation)
- Properties of the OLS estimator (classical assumptions, finite sample properties, asymptotic behaviour, Gauss-Markov theorem)
- Regression model inference (hypothesis testing, confidence intervals, model selection)
- Assumption failures (heteroskedasticity, serial correlation, multicollinearity)
- Functional forms (log-transformations, dummy variables, interaction terms)
This course provides an introduction to the analysis of economic data using econometric methods. After having taken the course, students should be able to understand empirical studies published in scientific journals and carry out econometric work by themselves.
The lectures are based on a slideset and are complemented by 4 empirical homework assignments.
Midterm exam (40%), final exam (40%), assignments (20%). A positive combined exam mark (average of midterm and final) is required to be positive in the course.
The grading scheme is:
- [90, 100]
- [78, 90)
- [65, 78)
- [50, 65)
- [0, 50)
If you have a valid registration for the lecture, but will not participate, please deregister during the registration period of LPIS. Your place will be available for other students.
During the registration period, free places are filled according to the “first-come, first-served” principle. After the end of the registration period, the number of places is increased and students on the waiting list will be registered for the lecture. Students in the BBE-program will be added first, should places remain, they will be filled by BaWiSo-students based on their progress in their studies.
Attendance in the first session is necessary, any absence will lead to deregistration! Any remaining places in the classes will be allocated to students attending the first session according to the waiting list. No places will be allocated by email or by phone.
Registration for the lecture cannot be guaranteed. Any student dropping out of the course who has already submitted a gradable task will receive a negative grade.
Please log in with your WU account to use all functionalities of read!t. For off-campus access to our licensed electronic resources, remember to activate your VPN connection connection. In case you encounter any technical problems or have questions regarding read!t, please feel free to contact the library at readinglists@wu.ac.at.
Supplementary Literature:
Baltagi, B. (2008). Econometrics, New York: Springer.
Greene, W. (2003). Econometric analysis, 5. ed., U.S.River, N.J.: Prentice Hall.
Gujarati, D.N., Porter, D.C. (2009). Basic Econometrics, New York: McGraw Hill.
Hackl, P. (2005). Einführung in die Ökonometrie. München: Pearson Studium.
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