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040178 UK Applied Economics (BA) (2021W)
Continuous assessment of course work
Labels
REMOTE
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 13.09.2021 09:00 to Th 23.09.2021 12:00
- Deregistration possible until Fr 15.10.2021 23:59
Registration information is available for each group.
Groups
Group 1
Lecturer: Yan XuONLINE-Teaching
max. 30 participants
Language: English
LMS: Moodle
Lecturers
Classes (iCal) - next class is marked with N
Lectures consist of asynchronized videos and short live sessions. The above lecture dates might be different.
- Wednesday 06.10. 16:45 - 18:15 Digital
- Wednesday 13.10. 16:45 - 18:15 Digital
- Wednesday 20.10. 16:45 - 18:15 Digital
- Wednesday 27.10. 16:45 - 18:15 Digital
- Wednesday 03.11. 16:45 - 18:15 Digital
- Wednesday 10.11. 16:45 - 18:15 Digital
- Wednesday 17.11. 16:45 - 18:15 Digital
- Wednesday 24.11. 16:45 - 18:15 Digital
- Wednesday 01.12. 16:45 - 18:15 Digital
- Wednesday 15.12. 16:45 - 18:15 Digital
- Wednesday 12.01. 16:45 - 18:15 Digital
- Wednesday 19.01. 16:45 - 18:15 Digital
- Wednesday 26.01. 16:45 - 18:15 Digital
Aims, contents and method of the course
This group is for students majoring in Economics. Students majoring in Economic History, please attend Mario Holzner's Group.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 econometric software and acquire the tools to carry out empirical research projects on their own.
Reading list
The following textbooks are available in the library:1) Hill R. C., Griffiths W. E., Lim G. C. (2018). Principles of Econometrics. (Fifth edition)2) Wooldridge, J. (2015). Introductory econometrics: A modern approach (Sixth edition, student ed.).
Group 2
Lecturer: Yan XuONLINE-Teaching
max. 30 participants
Language: English
LMS: Moodle
Lecturers
Classes (iCal) - next class is marked with N
Lectures consist of asynchronized videos and short live sessions. The above lecture dates might be different.
- Thursday 07.10. 16:45 - 18:15 Digital
- Thursday 14.10. 16:45 - 18:15 Digital
- Thursday 21.10. 16:45 - 18:15 Digital
- Thursday 28.10. 16:45 - 18:15 Digital
- Thursday 04.11. 16:45 - 18:15 Digital
- Thursday 11.11. 16:45 - 18:15 Digital
- Thursday 18.11. 16:45 - 18:15 Digital
- Thursday 25.11. 16:45 - 18:15 Digital
- Thursday 02.12. 16:45 - 18:15 Digital
- Thursday 09.12. 16:45 - 18:15 Digital
- Thursday 16.12. 16:45 - 18:15 Digital
- Thursday 13.01. 16:45 - 18:15 Digital
- Thursday 20.01. 16:45 - 18:15 Digital
- Thursday 27.01. 16:45 - 18:15 Digital
Aims, contents and method of the course
This group is for students majoring in Economics. Students majoring in Economic History, please attend Mario Holzner's group.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 econometric software and acquire the tools to carry out empirical research projects on their own.
Reading list
The following textbooks are available in the library:
1) Hill R. C., Griffiths W. E., Lim G. C. (2018). Principles of Econometrics. (Fifth edition)2) Wooldridge, J. (2015). Introductory econometrics: A modern approach (Sixth edition, student ed.).
1) Hill R. C., Griffiths W. E., Lim G. C. (2018). Principles of Econometrics. (Fifth edition)2) Wooldridge, J. (2015). Introductory econometrics: A modern approach (Sixth edition, student ed.).
Information
Assessment and permitted materials
Four problem sets (total of 60%), final exam (40%).
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.
Examination topics
We will seek to cover the following topics in this course:
1. Introduction
2. Review of the Linear Regression Model and Inference
4. Multiple Linear Regression Model
5. Endogeneity
1. Introduction
2. Review of the Linear Regression Model and Inference
4. Multiple Linear Regression Model
5. Endogeneity
Association in the course directory
Last modified: Fr 12.05.2023 00:12