Universität Wien

040115 UE UE Introductory Econometrics (MA) (2024W)

2.00 ECTS (1.00 SWS), SPL 4 - Wirtschaftswissenschaften
Continuous assessment of course work

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 information is available for each group.

Groups

Group 1

max. 50 participants
Language: English
LMS: Moodle

Lecturers

Classes (iCal) - next class is marked with N

  • Friday 11.10. 11:30 - 13:00 Hörsaal 12 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 15.11. 11:30 - 13:00 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Friday 29.11. 11:30 - 13:00 Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
  • Friday 13.12. 11:30 - 13:00 Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
  • Friday 17.01. 11:30 - 13:00 Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
  • Friday 24.01. 11:30 - 13:00 Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock

Aims, contents and method of the course

In this course unit, we will apply and practice the concepts taught in the 040111 KU Introductory Econometrics (MA). Our primary focus will be on practical application through empirical exercises using the R software (if you are not familiar with the software, please make sure to visit the R tutorial). Additionally, we will review key derivations and proofs on the board to improve your understanding of the material. The course will be held on-site, there is no online option.

Assessment and permitted materials

The course assessment will involve group problem sets, where you will collaboratively solve analytical exercises and implement empirical solutions in R. In addition, there will be short quizzes to be solved individually during class. Attendance and active participation will also contribute to your final grade.

Minimum requirements and assessment criteria

To successfully complete the course, students must earn at least 50% of the total available points. The grading components are as follows:
- Problem Sets: 45 points
- Quizzes: 45 points
- Attendance and Participation: 10 points

There will be several opportunities to collect bonus points through the problem sets.

-----

The final grade will be calculated based on the total points (P) earned:

Sehr Gut (1): P > 90
Gut (2): 75 < P ≤ 90
Befriedigend (3): 62.5 < P ≤ 75
Genügend (4): 50 < P ≤ 62.5
Nicht Genügend (5): P < 50

Examination topics

All material covered in this course is relevant for the assessments. Course materials, including solutions to problem sets after submission, will be available on Moodle. The content closely follows the material from the parallel lecture (040111 KU Introductory Econometrics).

Reading list

The following literature was used to prepare the course materials:
Angrist, J. D. (2014). Mastering'metrics: The path from cause to effect. Princeton University Press.
Hanck, C., Arnold, M., Gerber, A., & Schmelzer, M. (2021). Introduction to Econometrics with R. Universität Duisburg-Essen.
Stock, J. H., & Watson, M. W. (2020). Introduction to econometrics. Pearson.
Verbeek, M. (2017). A guide to modern econometrics. John Wiley & Sons.
Wooldridge, J. M. (1996). Introductory Econometrics: A Modern Approach 3rd ed.

Group 2

max. 50 participants
Language: English
LMS: Moodle

Lecturers

Classes (iCal) - next class is marked with N

  • Friday 11.10. 09:45 - 11:15 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Friday 15.11. 09:45 - 11:15 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Friday 29.11. 09:45 - 11:15 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Friday 13.12. 09:45 - 11:15 Hörsaal 16 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 17.01. 09:45 - 11:15 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 24.01. 09:45 - 11:15 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock

Aims, contents and method of the course

In this course unit, we will apply and practice the concepts taught in the 040111 KU Introductory Econometrics (MA). Our primary focus will be on practical application through empirical exercises using the R software (if you are not familiar with the software, please make sure to visit the R tutorial). Additionally, we will review key derivations and proofs on the board to improve your understanding of the material. The course will be held on-site, there is no online option.

Assessment and permitted materials

The course assessment will involve group problem sets, where you will collaboratively solve analytical exercises and implement empirical solutions in R. In addition, there will be short quizzes to be solved individually during class. Attendance and active participation will also contribute to your final grade.

Minimum requirements and assessment criteria

To successfully complete the course, students must earn at least 50% of the total available points. The grading components are as follows:
- Problem Sets: 45 points
- Quizzes: 45 points
- Attendance and Participation: 10 points

There will be several opportunities to collect bonus points through the problem sets.

-----

The final grade will be calculated based on the total points (P) earned:

Sehr Gut (1): P > 90
Gut (2): 75 < P ≤ 90
Befriedigend (3): 62.5 < P ≤ 75
Genügend (4): 50 < P ≤ 62.5
Nicht Genügend (5): P < 50

Examination topics

All material covered in this course is relevant for the assessments. Course materials, including solutions to problem sets after submission, will be available on Moodle. The content closely follows the material from the parallel lecture (040111 KU Introductory Econometrics).

Reading list

The following literature was used to prepare the course materials:
Angrist, J. D. (2014). Mastering'metrics: The path from cause to effect. Princeton University Press.
Hanck, C., Arnold, M., Gerber, A., & Schmelzer, M. (2021). Introduction to Econometrics with R. Universität Duisburg-Essen.
Stock, J. H., & Watson, M. W. (2020). Introduction to econometrics. Pearson.
Verbeek, M. (2017). A guide to modern econometrics. John Wiley & Sons.
Wooldridge, J. M. (1996). Introductory Econometrics: A Modern Approach 3rd ed.

Group 3

max. 50 participants
Language: English
LMS: Moodle

Lecturers

Classes (iCal) - next class is marked with N

  • Monday 07.10. 15:00 - 15:45 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 14.10. 15:00 - 15:45 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 28.10. 15:00 - 15:45 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 04.11. 15:00 - 15:45 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 11.11. 15:00 - 15:45 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 18.11. 15:00 - 15:45 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 25.11. 15:00 - 15:45 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 02.12. 15:00 - 15:45 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 09.12. 15:00 - 15:45 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 16.12. 15:00 - 15:45 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 13.01. 15:00 - 15:45 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 20.01. 15:00 - 15:45 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 27.01. 15:00 - 15:45 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock

Aims, contents and method of the course

Application and practice of the contents of the parallel lecture (040111 KU Introductory Econometrics by Professor Zulehner) through recap sessions, quizzes and applied projects.

The first lectures (on October 3 and 6) will serve as introduction to the course and explanation of course requirements. From the second week onward, there will be weekly sessions providing summaries and intuition of the concepts taught in the main lecture. This will include working through applied exercises, but also revising theory. A few sessions will be dedicated to the introduction of the open source programming language R.

The course will be held in class only. There is no online option!

Assessment and permitted materials

The assessment of this course consists of two 30 min quizzes covering material from the recap sessions. Additionally, there will be two empirical take home exams in the form of applied projects. This will provide students with hands-on experience in working with R as well as the concepts learned in the main lecture. The third part of the assessment will be drawn from attendance and active participation in the recap sessions.

Minimum requirements and assessment criteria

To successfully complete the course, students must receive at least 50% of the available points. Points are divided as follows: max 45 points for the quizzes (max 22.5 points each), max 45 points for the applied projects (max 22.5 points each) and max 10 points for attendance.

The final grade is calculated as follows depending on obtained points P:
Sehr Gut (1) P ? 87.5,
Gut (2) 75 ? P < 87.5,
Befriedigend (3) 62.5 ? P < 75,
Genügend (4) 50 ? P < 62.5,
Nicht Genügend (5) P < 50.

Examination topics

The slides as well as exercises will be uploaded on Moodle. The content of these are heavily based on the material of the parallel lecture (040111 KU Introductory Econometrics by Professor Zulehner).

Reading list

-

Group 4

max. 50 participants
Language: English
LMS: Moodle

Lecturers

Classes (iCal) - next class is marked with N

  • Monday 07.10. 15:45 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 14.10. 15:45 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 28.10. 15:45 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 04.11. 15:45 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 11.11. 15:45 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 18.11. 15:45 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 25.11. 15:45 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 02.12. 15:45 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 09.12. 15:45 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 16.12. 15:45 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 13.01. 15:45 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 20.01. 15:45 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 27.01. 15:45 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock

Aims, contents and method of the course

Application and practice of the contents of the parallel lecture (040111 KU Introductory Econometrics by Professor Zulehner) through recap sessions, quizzes and applied projects.

The first lectures (on October 3 and 6) will serve as introduction to the course and explanation of course requirements. From the second week onward, there will be weekly sessions providing summaries and intuition of the concepts taught in the main lecture. This will include working through applied exercises, but also revising theory. A few sessions will be dedicated to the introduction of the open source programming language R.

The course will be held in class only. There is no online option!

Assessment and permitted materials

The assessment of this course consists of two 30 min quizzes covering material from the recap sessions. Additionally, there will be two empirical take home exams in the form of applied projects. This will provide students with hands-on experience in working with R as well as the concepts learned in the main lecture. The third part of the assessment will be drawn from attendance and active participation in the recap sessions.

Minimum requirements and assessment criteria

To successfully complete the course, students must receive at least 50% of the available points. Points are divided as follows: max 45 points for the quizzes (max 22.5 points each), max 45 points for the applied projects (max 22.5 points each) and max 10 points for attendance.

The final grade is calculated as follows depending on obtained points P:
Sehr Gut (1) P ? 87.5,
Gut (2) 75 ? P < 87.5,
Befriedigend (3) 62.5 ? P < 75,
Genügend (4) 50 ? P < 62.5,
Nicht Genügend (5) P < 50.

Examination topics

The slides as well as exercises will be uploaded on Moodle. The content of these are heavily based on the material of the parallel lecture (040111 KU Introductory Econometrics by Professor Zulehner).

Reading list

-

Association in the course directory

Last modified: Th 03.10.2024 16:45