In this course parts of the book
Badi H. Baltagi: Econometric Analysis of Panel Data, John Wiley, 3rd edition, 2005
will be read jointly.
The book is a classic in the area of panel data modeling. Panel data appear widely in all areas of economics as well as in psychology, sociology and many other sciences. Panels are constituted by different waves of data collection where in each wave a number of invidividuals (potentially the same in all waves) are observed.
The session are set up in the following way:
1. Discussion of "left overs" from the last session (remaining questions, follow up etc.): D. Bauer.
2. Presentation of a summary of the current material (typically a part of a chapter): students.
3. Discussion of the material: all.
Talks and discussions will be in English.
More details on the modalities of the course will be discussed in the first meeting.
The course is open for students from the master "Statistische Wissenschaften" and BigSem. The upper limit for participants is 20.
Badi H. Baltagi: Econometric Analysis of Panel Data, John Wiley, 3rd edition, 2005.
The book is available in the library in small numbers. Electronic copies can be found on the web.
Frequency | Weekday | Time | Format / Place | Period |
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Module | Course | Requirements | |
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31-SW-StaFo Forschung in der Statistik | Reading Course | Graded examination
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Student information |
The binding module descriptions contain further information, including specifications on the "types of assignments" students need to complete. In cases where a module description mentions more than one kind of assignment, the respective member of the teaching staff will decide which task(s) they assign the students.
Degree programme/academic programme | Validity | Variant | Subdivision | Status | Semester | LP | |
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Economics and Management (BiGSEM) / Promotion | 4 | ||||||
Statistische Wissenschaften / Master | (Enrollment until SoSe 2014) | SW8 | 3. | 2 |
Prerequisites for the attendance in this course is the profound mastering of linear regression models and its accompanying inference framework (t-tests, F-tests). Matrix notation will be used within the course, but is not a mandatory prerequisite. The necessary foundations will be reviewed in the first session.