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| Semester | spring semester 2018 |
| Course frequency | Every spring sem. |
| Lecturers | Christian Kleiber (christian.kleiber@unibas.ch, Assessor) |
| Content | Introductory econometrics courses mainly cover the linear regression model, which is suitable for modelling response variables that may be considered as continuous. However, there are many practical situations where data are naturally discrete, e.g. binary, multinomial, or count data. The course will cover the classical nonlinear regression models for such data. It will use the framework of generalized linear models (GLMs), which provides a unified approach to models such as logit, probit and Poisson regression. Inference will be likelihood based. Empirical illustrations may include data from labor economics, health economics, or marketing, among further sources. The course will make use of the R language for statistical computing and graphics, hence basic knowledge of this software (including data import, running regressions) is expected. |
| Bibliography | Literature: R. Winkelmann und S. Boes: Analysis of Microdata, 2. Aufl. Springer 2009. Cameron AC, Trivedi PK (2005): Microeconometrics, Cambridge Univ. Press. Fahrmeir, L, Kneib T, Lang S, Marx B (2013): Regression -- Models, Methods and Applications, Springer. [available in electronic form via the university library!] |
| Weblink | Weblink |
| Admission requirements | Prerequisites: completed Master in Business and Economics or equivalent |
| Course application | Course Registration: Register in MOnA; |
| Language of instruction | English |
| Use of digital media | No specific media used |
| Interval | Weekday | Time | Room |
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No dates available. Please contact the lecturer.
| Modules |
Modul Advanced Field Courses (Doctoral Studies - Faculty of Business and Economics) Modul Fachlich-methodische Weiterbildung (Doctoral Studies - Faculty of Business and Economics) |
| Assessment format | end-of-semester examination |
| Assessment details | PhD students will be given individual tasks, which may include (some of) the following: replication of an empirical paper, more advanced aspects of models covered in class, paper on models not covered in class, etc. |
| Assessment registration/deregistration | Registration: course registration |
| Repeat examination | no repeat examination |
| Scale | 1-6 0,1 |
| Repeated registration | as often as necessary |
| Responsible faculty | Faculty of Business and Economics , studiendekanat-wwz@unibas.ch |
| Offered by | Faculty of Business and Economics |