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040121 UK Applied Econometrics 1 (BA) (2026S)
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 09.02.2026 09:00 to Tu 17.02.2026 12:00
- Deregistration possible until Sa 14.03.2026 23:59
Details
max. 120 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
- Tuesday 03.03. 18:30 - 20:00 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Thursday 05.03. 13:15 - 14:45 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
- Tuesday 10.03. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Tuesday 17.03. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Thursday 19.03. 13:15 - 14:45 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
- Tuesday 24.03. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Thursday 26.03. 13:15 - 14:45 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
- Tuesday 14.04. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Thursday 16.04. 13:15 - 14:45 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
- Tuesday 21.04. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Thursday 23.04. 13:15 - 14:45 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
- Tuesday 28.04. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Thursday 30.04. 13:15 - 14:45 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Information
Aims, contents and method of the course
The aim of the course is to provide students a thorough understanding of theoretical foundations and proper applications of basic econometric techniques of least squares estimation and related topics. 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. The tutorial will be offered by Yavor Iliev.
Assessment and permitted materials
AssessmentThree closed-book exams, a 45 min:
Part I, April 14, 2026 (HS 1, 16:45-17:30), on the correspond. topics covered in the course.
Part II, May 5, 2026 (HS 1, 16:45-17:30); on the corresponding topics covered in the course.
Part III, May 5, 2026 (HS 1, 17:30-18:15); on R.Questions can consist of multiple-choice questions, analytical derivations and interpretations of empirical results.
For each exam the Moodle system will be used. Hence, it is necessary to have your laptops with you!
Part I, April 14, 2026 (HS 1, 16:45-17:30), on the correspond. topics covered in the course.
Part II, May 5, 2026 (HS 1, 16:45-17:30); on the corresponding topics covered in the course.
Part III, May 5, 2026 (HS 1, 17:30-18:15); on R.Questions can consist of multiple-choice questions, analytical derivations and interpretations of empirical results.
For each exam the Moodle system will be used. Hence, it is necessary to have your laptops with you!
Minimum requirements and assessment criteria
Grading:
For the final grade the individual assignments count as follows:
i) Three exams: 100%, 30% for exam 1 and 2, 40% for the R exam
ii) 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, the attendance in the first session is mandatory and a minimum level of 50% of the total points.Grading scheme:[86%; 100%]: 1.0
[74%; 86%): 2.0
[62%;74%): 3.0
[50%; 62%): 4.0
[0; 50%): 5.0Examination language: English.
For the final grade the individual assignments count as follows:
i) Three exams: 100%, 30% for exam 1 and 2, 40% for the R exam
ii) 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, the attendance in the first session is mandatory and a minimum level of 50% of the total points.Grading scheme:[86%; 100%]: 1.0
[74%; 86%): 2.0
[62%;74%): 3.0
[50%; 62%): 4.0
[0; 50%): 5.0Examination language: English.
Examination topics
The linear regression model
Applications of the linear model and using R
Applications of the linear model and using R
Reading list
Slides are provided in MoodleDougherty, 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, 2011Online Literatur basierend auf R, see also Moodle and the tutoral
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, 2011Online Literatur basierend auf R, see also Moodle and the tutoral
Association in the course directory
Last modified: Mo 27.07.2026 09:26