040033 KU Econometrics II (MA) (2023S)
Continuous assessment of course work
Labels
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 13.02.2023 09:00 to We 22.02.2023 12:00
- Registration is open from Mo 27.02.2023 09:00 to Tu 28.02.2023 12:00
- Deregistration possible until Fr 17.03.2023 23:59
Details
max. 50 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
Thursday
02.03.
13:15 - 14:45
Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
Thursday
02.03.
15:00 - 16:30
Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
Tuesday
07.03.
15:00 - 16:30
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Thursday
09.03.
13:15 - 14:45
Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
Thursday
09.03.
15:00 - 16:30
Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
Tuesday
14.03.
15:00 - 16:30
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Thursday
16.03.
13:15 - 14:45
Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
Thursday
16.03.
15:00 - 16:30
Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
Tuesday
21.03.
15:00 - 16:30
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Thursday
23.03.
13:15 - 14:45
Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
Thursday
23.03.
15:00 - 16:30
Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
Tuesday
28.03.
15:00 - 16:30
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Thursday
30.03.
13:15 - 14:45
Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
Thursday
30.03.
15:00 - 16:30
Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
Tuesday
18.04.
15:00 - 16:30
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Thursday
20.04.
13:15 - 14:45
Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
Thursday
20.04.
15:00 - 16:30
Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
Tuesday
25.04.
15:00 - 16:30
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Thursday
27.04.
13:15 - 14:45
Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
Thursday
27.04.
15:00 - 16:30
Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
Tuesday
02.05.
15:00 - 16:30
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Thursday
04.05.
13:15 - 14:45
Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
Thursday
04.05.
15:00 - 16:30
Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
Tuesday
09.05.
15:00 - 16:30
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Thursday
11.05.
13:15 - 14:45
Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
Thursday
11.05.
15:00 - 16:30
Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
Tuesday
16.05.
15:00 - 16:30
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Tuesday
23.05.
15:00 - 16:30
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Thursday
25.05.
13:15 - 14:45
Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
Thursday
25.05.
15:00 - 16:30
Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
Thursday
01.06.
13:15 - 14:45
Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
Thursday
01.06.
15:00 - 16:30
Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
Tuesday
06.06.
15:00 - 16:30
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Monday
12.06.
15:00 - 16:30
Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
Thursday
15.06.
13:15 - 14:45
Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
Thursday
15.06.
15:00 - 16:30
Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
Tuesday
20.06.
15:00 - 16:30
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Thursday
22.06.
13:15 - 14:45
Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
Thursday
22.06.
15:00 - 16:30
Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
Tuesday
27.06.
15:00 - 16:30
Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
Thursday
29.06.
13:15 - 14:45
Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
Thursday
29.06.
15:00 - 16:30
Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
Information
Aims, contents and method of the course
Assessment and permitted materials
The assessment consists of the following parts:i) One midterm test, ca. 60 min. Can consist of multiple-choice questions, analytical derivations and interpretations of empirical results. Depending on the pandemic situation, the tests might be done via Moodle.ii) Exam, 60 min, on all topics covered in the course. Can consist of multiple-choice questions, analytical derivations and interpretations of empirical results. Depending on the pandemic situation, the exam might be carried out via Moodle. Depending on the number of course participants, the exams might be done in oral formiii) Take-home assignments. Students have to solve and have to hand in weekly or bi-weekly written assignments. They can consist of multiple-choice questions, analytical derivations and interpretations of empirical results. The solutions may also have to be presented in the tutorials.Permitted material: No additional material except a calculator.
Minimum requirements and assessment criteria
Grading:
For the final grade the individual assignments count as follows:
i) Test: 20%
ii) Exam: 45%
iii) Assignments: 35%Important: Aside from the three assignments, there will be no additional examination possibilities afterwards.To pass the course, a minimum level of 45% has to be reached.Rating:
[85%; 100%]: 1.0
[70%; 85%): 2.0
[55%;70%): 3.0
[45%; 55%): 4.0
[0; 45%): 5.0Examination language: English
For the final grade the individual assignments count as follows:
i) Test: 20%
ii) Exam: 45%
iii) Assignments: 35%Important: Aside from the three assignments, there will be no additional examination possibilities afterwards.To pass the course, a minimum level of 45% has to be reached.Rating:
[85%; 100%]: 1.0
[70%; 85%): 2.0
[55%;70%): 3.0
[45%; 55%): 4.0
[0; 45%): 5.0Examination language: English
Examination topics
All topics covered in the course
Reading list
Adda, J. and R. W. Cooper (2003): Dynamic Economics – Quantitative Methods and Applications. MIT Press.Davidson, R. and J. MacKinnon (2004): Econometric Theory and Methods, Oxford University PressGouriéroux, C. and A. Monfort (1995): Statistics and Econometric Models, Cambridge University Press.Gouriéroux, C. and A. Monfort (1996): Simulation-Based Econometric Methods, Oxford University Press.Greenberg, E. (2008): Introduction to Bayesian Econometrics, Cambridge University
Press.Hansen, Bruce E. (2019): Econometrics. Freely available at: http://www.ssc.wisc.edu/~bhansen/econometrics/Hayashi, F. (2000): Econometrics, Princeton University Press.Newey, W. K. (1993). “Efficient Estimation of Models with Conditional Moment Restrictions, “ Handbook of Statistics, 11, 419-453.Newey, W. K. and D. McFadden (1994): “Large Sample Estimation and Hypothesis Testing”, in Handbook of Economtrics, e.d by R. F. Engle and D. L. McFadden, Elsevier, Chap. 36, 2111-2245.
Press.Hansen, Bruce E. (2019): Econometrics. Freely available at: http://www.ssc.wisc.edu/~bhansen/econometrics/Hayashi, F. (2000): Econometrics, Princeton University Press.Newey, W. K. (1993). “Efficient Estimation of Models with Conditional Moment Restrictions, “ Handbook of Statistics, 11, 419-453.Newey, W. K. and D. McFadden (1994): “Large Sample Estimation and Hypothesis Testing”, in Handbook of Economtrics, e.d by R. F. Engle and D. L. McFadden, Elsevier, Chap. 36, 2111-2245.
Association in the course directory
Last modified: We 20.12.2023 12:05
After following this course, students will have a good working knowledge of statistical inference as applied in various areas in modern econometrics, including time series econometrics, micro econometrics, panel econometrics as well as financial econometrics. In the tutorials, students will deepen the material based on exercises, examples and applications using the open-source software R.The course will be taught in class. If required due to Covid regulations, the course will be done remotely via Zoom. All necessary information and possible short-term announcements will be provided through the Moodle site of the course.Prerequisites
Students need to have basic econometric knowledge as taught in the course “Introductory Econometrics” or a similar course. Moreover, basic knowledge in R is required.Sign-In
Students have to sign in during the first week of the semester. Signing off is only possible until at latest March 15, 2023. Students who are still signed in after March 15, 2023 will be graded!