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040122 UK Applied Econometrics 2 (2025S)

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

Details

max. 60 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

  • Wednesday 14.05. 15:00 - 16:30 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Thursday 15.05. 13:15 - 14:45 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
  • Tuesday 20.05. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Wednesday 21.05. 15:00 - 16:30 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Thursday 22.05. 13:15 - 14:45 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
  • Tuesday 27.05. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Wednesday 28.05. 15:00 - 16:30 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Tuesday 03.06. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Wednesday 04.06. 15:00 - 16:30 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Thursday 05.06. 13:15 - 14:45 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
  • Tuesday 10.06. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Wednesday 11.06. 15:00 - 16:30 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Thursday 12.06. 13:15 - 14:45 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
  • Tuesday 17.06. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Wednesday 18.06. 15:00 - 16:30 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Tuesday 24.06. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Wednesday 25.06. 15:00 - 16:30 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Thursday 26.06. 13:15 - 14:45 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock

Information

Aims, contents and method of the course

Aims and Contents

The aim of the course is to provide students a thorough understanding of theoretical foundations and proper applications of instrumental variable estimation and econometric techniques for panel data and microeconometric data. The course will cover two-stage least squares, seemingly unrelated regression, fixed-effects and random-effects panel estimation as well as econometric models for categorical data and for limited dependent variables. Examples and applications will be illustrated using the open-source software R.
In an accompanying tutorial, students will deepen the material based on exercises and applications using R.

Form of Teaching
The course will be taught in class. All necessary information and possible short-term announcements will be provided through the Moodle site of the course.

Assessment and permitted materials

Assessment
The assessment consists of the following parts:

(i) Three Exams, a 45 min:
Part I, June 3, 2025, (HS 1, 16:45-17:30), on the correspond. topics covered in the course.
Part II, June 26, 2025 (HS 14 13:15-14:00); on the corresponding topics covered in the course.
Part III, June 26, 2025 (HS 14, 13:15-14:00); on R.
Questions can consist of multiple-choice questions, analytical derivations and interpretations of empirical results.

For the Exam the Moodle system will be used. Hence, it is necessary to have your laptops with you!

ii) Take-home assignments. Students have to solve and have to hand in written assignments. They can consist of multiple-choice questions, analytical derivations, and interpretations of empirical results. Solved exercises have to be uploaded to the Moodle system before the start of the exercise part on Wednesday, no matter whether you choose to attend the exercise part on Wednesday or on Thursday.

Necessary material for (i-iii): you need a laptop, for all exams moodle will be used.

Grading:
For the final grade the individual assignments count as follows:
i) Three exams: 75%, 25% each
ii) Assignments: 25%
iii) Extra points for class room participation in the “exercise block”, 3% per participation.

Important: Aside from the three assignments, there will be no additional examination possibilities afterwards.

To pass the course, a minimum level of 50% has to be reached.

Rating:
[86%; 100%]: 1.0
[74%; 86%): 2.0
[62%;74%): 3.0
[50%; 62%): 4.0
[0; 50%): 5.0

Examination language: English.

Minimum requirements and assessment criteria

Assessment
The assessment consists of the following parts:

(i) Three Exams, a 45 min:
Part I, June 3, 2025, (HS 1, 16:45-17:30), on the correspond. topics covered in the course.
Part II, June 26, 2025 (HS 14 13:15-14:00); on the corresponding topics covered in the course.
Part III, June 26, 2025 (HS 14, 13:15-14:00); on R.

Questions can consist of multiple-choice questions, analytical derivations and interpretations of empirical results.

For the Exam the Moodle system will be used. Hence, it is necessary to have your laptops with you!

ii) Take-home assignments. Students have to solve and have to hand in written assignments. They can consist of multiple-choice questions, analytical derivations, and interpretations of empirical results. Solved exercises have to be uploaded to the Moodle system before the start of the exercise part on Wednesday, no matter whether you choose to attend the exercise part on Wednesday or on Thursday.

Necessary material for (i-iii): you need a laptop, for all exams moodle will be used.

Grading:
For the final grade the individual assignments count as follows:
i) Three exams: 75%, 25% each
ii) Assignments: 25%
iii) Extra points for class room participation in the “exercise block”, 3% per participation.

Important: Aside from the three assignments, there will be no additional examination possibilities afterwards.

To pass the course, a minimum level of 50% has to be reached.

Rating:
[86%; 100%]: 1.0
[74%; 86%): 2.0
[62%;74%): 3.0
[50%; 62%): 4.0
[0; 50%): 5.0

Examination language: Students can do the examinations in English.

Examination topics

1. Instrumental variables
2. Panel model
3. Models with qualitative variables

Reading list

Slides - see moodle

Dougherty, C., “Introduction to Econometrics”, 3rd ed., Oxford University Press, 2007.
Franses, P. H., van Dijk, D., and Opschoor, A., “Time Series Models for Business and Economic Forecasting”, 2nd ed., Cambridge University Press, 2014.
Heij, De Boer, Franses, Kloek, and Van Dijk, ''Econometric Methods with Applications in Business and Economics'', Oxford University Press, 2004.
Stock, J.H., Watson, M.W., ''Introduction to Econometrics'', 3rd edition, Pearson, 2012.
Studenmund, A. H. “Using Econometrics”, 6th ed., Pearson, 2011

Online Literatur basierend auf R:
Heiss, F., “Using R for Introductory Econometrics”, 2016, http://www.urfie.net
Hanck, C., Arnold, M., Gerber, A., and Schmelzer, M., 2019, https://www.econometrics-with-r.org/index.html

R Studio Cloud Projekt Link: https://rstudio.cloud/project/950163, see tutorial

Association in the course directory

Last modified: Tu 28.01.2025 11:05