For this lecture participation is obligatory. Students are allowed to miss a maximum of 20% (no matter if excused or not excused).
Registration via LPIS
|Tuesday||10/01/19||02:30 PM - 04:30 PM||TC.4.14|
|Tuesday||10/08/19||02:30 PM - 04:30 PM||TC.5.04|
|Tuesday||10/15/19||02:30 PM - 04:30 PM||D2.0.342 Teacher Training Raum|
|Tuesday||10/22/19||02:30 PM - 04:30 PM||TC.5.04|
|Tuesday||10/29/19||02:30 PM - 04:30 PM||TC.5.04|
|Tuesday||11/05/19||12:30 PM - 02:30 PM||TC.2.02|
|Tuesday||11/12/19||02:30 PM - 04:30 PM||D3.0.222|
|Tuesday||11/19/19||02:30 PM - 04:30 PM||D3.0.222|
|Tuesday||11/26/19||02:30 PM - 04:30 PM||TC.4.14|
|Tuesday||12/03/19||02:30 PM - 04:30 PM||TC.4.14|
|Tuesday||12/10/19||02:30 PM - 04:30 PM||TC.4.14|
|Tuesday||12/17/19||12:00 PM - 02:00 PM||TC.2.02|
The course covers basic concepts of econometrics. After an introduction into the characteristics of economic data, concepts such as causality and correlation are discussed. The classical regression model and the assumptions underlying the model are discussed in detail. The method of OLS estimation as well as asymptotic tests are explained in detail. Other topics include model selection such as choice of functional form, misspecification, dummy variables and heteroscedasticity.
The course provides an introduction to the analysis of economic data using econometric methods based on multiple regression. After the course, students will be able to understand and discuss empirical studies using the methods covered in this course. Moreover, students will learn how to independent conduct their own analyses of economic data.
4 case studies (in groups), 8 points each
2 written exams (individually), 24 points each
1: 72 – ∞
2: 64 – 71.99
3: 56 – 63.99
4: 48 – 55.99
5: 00 – 47.99
Class attendance is compulsory.