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040178 UK Applied Economics (BA) (2023W)
Continuous assessment of course work
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Summary
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 11.09.2023 09:00 to Fr 22.09.2023 12:00
- Deregistration possible until Fr 20.10.2023 23:59
Registration information is available for each group.
Groups
Group 1
max. 30 participants
Language: English
LMS: Moodle
Lecturers
Classes (iCal) - next class is marked with N
- Wednesday 04.10. 16:45 - 18:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Wednesday 11.10. 16:45 - 18:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Wednesday 18.10. 16:45 - 18:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Wednesday 08.11. 16:45 - 18:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Wednesday 15.11. 16:45 - 18:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Wednesday 22.11. 16:45 - 18:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Wednesday 29.11. 16:45 - 18:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Wednesday 06.12. 16:45 - 18:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Wednesday 13.12. 16:45 - 18:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Wednesday 10.01. 16:45 - 18:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Wednesday 17.01. 16:45 - 18:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Wednesday 24.01. 16:45 - 18:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Wednesday 31.01. 16:45 - 18:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Examination topics
We will seek to cover the following topics in this course:
1. Introduction to R
2. Review of the Multiple Linear Regression Model and Inference
3. Endogeneity
4. Panel Data Methods
5. Instrumental Variable Estimation
1. Introduction to R
2. Review of the Multiple Linear Regression Model and Inference
3. Endogeneity
4. Panel Data Methods
5. Instrumental Variable Estimation
Group 2
max. 30 participants
Language: English
LMS: Moodle
Lecturers
Classes (iCal) - next class is marked with N
- Thursday 05.10. 16:45 - 18:15 PC-Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Thursday 12.10. 16:45 - 18:15 PC-Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Thursday 19.10. 16:45 - 18:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Thursday 09.11. 16:45 - 18:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Thursday 16.11. 16:45 - 18:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Thursday 23.11. 16:45 - 18:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Thursday 30.11. 16:45 - 18:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Thursday 07.12. 16:45 - 18:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Thursday 14.12. 16:45 - 18:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Thursday 11.01. 16:45 - 18:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Thursday 18.01. 16:45 - 18:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Thursday 25.01. 16:45 - 18:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Thursday 01.02. 16:45 - 18:15 Hörsaal 13 Oskar-Morgenstern-Platz 1 2.Stock
Examination topics
We will seek to cover the following topics in this course:
1. Introduction to R
2. Review of the Multiple Linear Regression Model and Inference
3. Endogeneity
4. Panel Data Methods
5. Instrumental Variable Estimation
1. Introduction to R
2. Review of the Multiple Linear Regression Model and Inference
3. Endogeneity
4. Panel Data Methods
5. Instrumental Variable Estimation
Information
Aims, contents and method of the course
This is a course in which students will reinforce the tools learned in Introductory Econometrics (BA) by applying them to real world data sets using econometric software. Prior knowledge at the level will be assumed throughout the course. The aim of the course is for students to get hands on experience in analyzing observational data using the open source programming language R and acquire the tools to carry out empirical research projects on their own.
Assessment and permitted materials
Four problem sets (total of 60%), final exam (40%). The problem sets can be done in groups of up to three.
Minimum requirements and assessment criteria
Students should hand in all problem sets and attend the final exam. A minimum of 51% is required to pass the course.
Reading list
1) Wooldridge, J. (2015). Introductory econometrics: A modern approach (Sixth edition, student ed.)
2) Hill R. C., Griffiths W. E., Lim G. C. (2018). Principles of Econometrics. (Fifth edition)
3) Heiss, F. (2020). Using R for Introductory Econometrics (2nd edition)
2) Hill R. C., Griffiths W. E., Lim G. C. (2018). Principles of Econometrics. (Fifth edition)
3) Heiss, F. (2020). Using R for Introductory Econometrics (2nd edition)
Association in the course directory
Last modified: Fr 20.10.2023 11:26