Achtung! Das Lehrangebot ist noch nicht vollständig und wird bis Semesterbeginn laufend ergänzt.
040122 UK Applied Econometrics 2 (2025S)
Prüfungsimmanente Lehrveranstaltung
Labels
Details
max. 60 Teilnehmer*innen
Sprache: Englisch
Lehrende
Termine (iCal) - nächster Termin ist mit N markiert
- N Dienstag 13.05. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Mittwoch 14.05. 15:00 - 16:30 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Donnerstag 15.05. 13:15 - 14:45 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
- Dienstag 20.05. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Mittwoch 21.05. 15:00 - 16:30 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Donnerstag 22.05. 13:15 - 14:45 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
- Dienstag 27.05. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Mittwoch 28.05. 15:00 - 16:30 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Dienstag 03.06. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Mittwoch 04.06. 15:00 - 16:30 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Donnerstag 05.06. 13:15 - 14:45 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
- Dienstag 10.06. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Mittwoch 11.06. 15:00 - 16:30 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Donnerstag 12.06. 13:15 - 14:45 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
- Dienstag 17.06. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Mittwoch 18.06. 15:00 - 16:30 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Dienstag 24.06. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Mittwoch 25.06. 15:00 - 16:30 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Donnerstag 26.06. 13:15 - 14:45 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Information
Ziele, Inhalte und Methode der Lehrveranstaltung
Art der Leistungskontrolle und erlaubte Hilfsmittel
Assessment
The assessment consists of the following parts:(i) Three Exams, a 45 min:
Part I, June 4, 2024, (HS 1, 13:15-14:00), on the correspond. topics covered in the course.
Part II, June 25, 2024 (HS 1 13:15-14:00); on the corresponding topics covered in the course.
Part III, June 27, 2024 (HS 4, 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 Tuesday, no matter whether you choose to attend the exercise part Tuesday 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%): 5.0Examination language: Students can do the examinations in English.
The assessment consists of the following parts:(i) Three Exams, a 45 min:
Part I, June 4, 2024, (HS 1, 13:15-14:00), on the correspond. topics covered in the course.
Part II, June 25, 2024 (HS 1 13:15-14:00); on the corresponding topics covered in the course.
Part III, June 27, 2024 (HS 4, 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 Tuesday, no matter whether you choose to attend the exercise part Tuesday 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%): 5.0Examination language: Students can do the examinations in English.
Mindestanforderungen und Beurteilungsmaßstab
Assessment
The assessment consists of the following parts:(i) Three Exams, a 45 min:
Part I, June 4, 2024, (HS 1, 13:15-14:00), on the correspond. topics covered in the course.
Part II, June 25, 2024 (HS 1 13:15-14:00); on the corresponding topics covered in the course.
Part III, June 27, 2024 (HS 4, 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 Tuesday, no matter whether you choose to attend the exercise part Tuesday 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%): 5.0Examination language: Students can do the examinations in English.
The assessment consists of the following parts:(i) Three Exams, a 45 min:
Part I, June 4, 2024, (HS 1, 13:15-14:00), on the correspond. topics covered in the course.
Part II, June 25, 2024 (HS 1 13:15-14:00); on the corresponding topics covered in the course.
Part III, June 27, 2024 (HS 4, 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 Tuesday, no matter whether you choose to attend the exercise part Tuesday 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%): 5.0Examination language: Students can do the examinations in English.
Prüfungsstoff
1. Instrumentvariablen
2. Paneldatenmodelle
3. Modelle für qualitative und beschränkte abhängige Variablen
2. Paneldatenmodelle
3. Modelle für qualitative und beschränkte abhängige Variablen
Literatur
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, 2011Online 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.htmlR Studio Cloud Projekt Link: https://rstudio.cloud/project/950163
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:
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.htmlR Studio Cloud Projekt Link: https://rstudio.cloud/project/950163
Zuordnung im Vorlesungsverzeichnis
Letzte Änderung: Mi 15.01.2025 14:05
Ziel des Kurses ist es, den Studierenden ein Verständnis der theoretischen Grundlagen und der richtigen Anwendung der instrumentellen Variablenschätzung und ökonometrischer Techniken für Paneldaten und mikroökonometrische Daten zu vermitteln. Der Kurs behandelt die Methode der Zweistufige kleinsten Quadrate, spurious Regression, Fixed-Effects- und Random-Effects-Panel-Schätzung sowie ökonometrische Modelle für kategoriale Daten und für begrenzte abhängige Variablen.
Beispiele und Anwendungen werden anhand der Open-Source-Software R veranschaulicht. In einem begleitenden Tutorium vertiefen die Studierenden den Stoff anhand von Übungen und Anwendungen mit R.
Alle notwendigen Informationen und mögliche kurzfristige Ankündigungen werden über die Moodle-Seite des Kurses bereitgestellt.