040043 UK Microeconometrics (MA) (2020W)
Continuous assessment of course work
Labels
Diese Lehrveranstaltung gilt ebenso für die Pflichtlehrveranstaltung / This course correlates with the compulsory course: "Introductory Econometrics" for the Master Programme "Banking & Finance".
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
- Registration is open from Mo 14.09.2020 09:00 to We 23.09.2020 12:00
- Registration is open from Mo 28.09.2020 09:00 to We 30.09.2020 12:00
- Deregistration possible until Sa 31.10.2020 12:00
Details
max. 92 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
Dear all,
this course in micro-econometrics will be offered fully online in the winter semester 2020/21. For this course there will be no classroom teaching. Information on the exams will follow in the next weeks.
Thursday
01.10.
20:15 - 22:00
Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Tuesday
06.10.
13:15 - 14:45
Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Thursday
08.10.
20:15 - 22:00
Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Tuesday
13.10.
13:15 - 14:45
Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Thursday
15.10.
20:15 - 22:00
Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Tuesday
20.10.
13:15 - 14:45
Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Thursday
22.10.
20:15 - 22:00
Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Tuesday
27.10.
13:15 - 14:45
Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Thursday
29.10.
20:15 - 22:00
Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Tuesday
03.11.
13:15 - 14:45
Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Thursday
05.11.
20:15 - 22:00
Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Tuesday
10.11.
13:15 - 14:45
Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Thursday
12.11.
20:15 - 22:00
Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Tuesday
24.11.
13:15 - 14:45
Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Thursday
26.11.
20:15 - 22:00
Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Tuesday
01.12.
13:15 - 14:45
Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Thursday
03.12.
20:15 - 22:00
Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Thursday
10.12.
20:15 - 22:00
Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Tuesday
15.12.
13:15 - 14:45
Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Thursday
17.12.
20:15 - 22:00
Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Thursday
07.01.
20:15 - 22:00
Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Tuesday
12.01.
13:15 - 14:45
Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Thursday
14.01.
20:15 - 22:00
Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Tuesday
19.01.
13:15 - 14:45
Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Thursday
21.01.
20:15 - 22:00
Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Information
Aims, contents and method of the course
Assessment and permitted materials
Assessment is based on a written test (50%), a small independent empirical econometric project (40%) and attendance of classes (10%), i.e. max. 2 lectures can be skipped. To pass the course, a minimum of 50% is required.Since the course will be offered online information an the exams will follow in the next weeks.
Minimum requirements and assessment criteria
Rating:
[90%; 100%]: 1.0
[75%; 90%): 2.0
[60%; 75%): 3.0
[50%; 60%): 4.0
[0; 50%): 5.0
[90%; 100%]: 1.0
[75%; 90%): 2.0
[60%; 75%): 3.0
[50%; 60%): 4.0
[0; 50%): 5.0
Examination topics
Basic knowledge in linear regression, linear algebra and probability theory.
All material covered in class and in the tutorials.
All material covered in class and in the tutorials.
Reading list
Association in the course directory
Last modified: Th 01.10.2020 10:48
i. Providing a sound background econometric models for qualitative dependent variables, models for limited dependent variables, and panel data
ii. Implementing econometric theory using real data
iii. Practicing programing in RThe following topics are targeted in particular:1. A Review of Linear Regression
2. Generalizations of the Linear Model
3. Maximum Likelihood
4. Instrumental Variable Estimation
5. Models for Qualitative Dependent Variables
6. Models for Limited Dependent Variables
7. Panel Data