Fachbereich 02: Wirtschaftswissenschaften - Master-Studiengang Betriebs- und Volkswirtschaftslehre (M.Sc.) - BWL/VWL-Module

Struktur: Vorlesung + Übung / Lecture and Exercise Class
Turnus: Sommersemester / Summer term
Credits: 6 CP
Sprache: Englisch
Prüfungsform: Klausur und Projektarbeit / Written exam and project
The course takes place in person

The course Time Series Econometrics and Computer-based Methods complements the course Advanced Econometrics taught in the winter term. Methods of estimation and inference are used for advanced methods for the analysis of time series data (e.g. financial market or macroeconomic data). Besides traditional econometric methods, specific emphasis is given to computer-based methods (e.g. Monte Carlo simulations, Bootstrap, non-parametric estimators). The students will learn about the properties of the methods, how to implement them, difficulties and limits of applications.
Besides the lecture and the exercise class, students will apply the econometric methods introduced in this course on a small-scale research project. The projects may be proposed by the students or be based on suggestions by the lecturers.
In order to reproduce examples from lecture and exercise class as well as for conducting your own project, you will need access to a suitable econometric software package. The lecture will use examples both based on the commercial software EViews and the free package R. For own projects, we recommend using the free software package R. As platform for R, we recommend RStudio (https://rstudio.com/).
Please note that the number of participants for this course is limited – the selection of students will be based on your background in statistics and econometrics. To allow for a swift admission, please send a Email with your enrollment number and information about your background in statistics and econometrics (modules attended at JLU or elsewhere) to Jana Röder (jana.roeder@uni-giessen.de). If you finished the module “Advanced Econometrics” successfully or participated in the retake exam, please let us know as well.
The first lecture will take place on April, 22nd 2025.

Link zu JLU-Maps:
https://www.uni-giessen.de/JLUmaps/?id=167813&lang=de

Struktur: Vorlesung + Übung / Lecture and Exercise Class
Turnus: Sommersemester / Summer term
Credits: 6 CP
Sprache: Englisch
Prüfungsform: Klausur und Projektarbeit / Written exam and project
The course takes place in person

The course Time Series Econometrics and Computer-based Methods complements the course Advanced Econometrics taught in the winter term. Methods of estimation and inference are used for advanced methods for the analysis of time series data (e.g. financial market or macroeconomic data). Besides traditional econometric methods, specific emphasis is given to computer-based methods (e.g. Monte Carlo simulations, Bootstrap, non-parametric estimators). The students will learn about the properties of the methods, how to implement them, difficulties and limits of applications.
Besides the lecture and the exercise class, students will apply the econometric methods introduced in this course on a small-scale research project. The projects may be proposed by the students or be based on suggestions by the lecturers.
In order to reproduce examples from lecture and exercise class as well as for conducting your own project, you will need access to a suitable econometric software package. The lecture will use examples both based on the commercial software EViews and the free package R. For own projects, we recommend using the free software package R. As platform for R, we recommend RStudio (https://rstudio.com/).
Please note that the number of participants for this course is limited – the selection of students will be based on your background in statistics and econometrics. To allow for a swift admission, please send a Email with your enrollment number and information about your background in statistics and econometrics (modules attended at JLU or elsewhere) to Jana Röder (jana.roeder@uni-giessen.de). If you finished the module “Advanced Econometrics” successfully or participated in the retake exam, please let us know as well.
The first lecture will take place on April, 22nd 2025.

Link zu JLU-Maps:
https://www.uni-giessen.de/JLUmaps/?id=167813&lang=de

Struktur: Vorlesung + Übung
Turnus: Unregelmäßig
Credits: 6 CP
Sprache: Englisch (Regelfall) bzw. Deutsch (Ausnahmefall)
Prüfungsform: Klausur und Hausarbeit mit Präsentation

Qualifikationsziele:
• Beschreibung und Verständnis der Digitalisierung und ihrer Auswirkungen auf wirtschaftliche
Prozesse
• Kenntnis von theoretischen Konzepten und empirischen Methoden zur Messung der Digitalisierung
und zur Analyse ihrer Auswirkungen
• Beschreibung, Interpretation und Bewertung empirischer Ergebnisse
• Kritische Diskussion der ökonomischen und sozialen Auswirkungen der Digitalisierung
•
Inhalte:
• Informations- Kommunikationstechnologien als Querschnittstechnologie
• Auswirkungen der Digitalisierung auf Unternehmen
• Auswirkungen der Digitalisierung auf Beschäftigte
• Digitale Märkte und Plattformen


Für die Teilnahme an der Veranstaltung ist der erfolgreiche Abschluss von Kursen in Industrieökonomik und Ökonometrie sehr empfehlenswert. Weitere Informationen dazu finden Sie auch auf der Homepage.

Die Veranstaltung findet in Präsenz statt.

Link zu JLU-Maps:
https://www.uni-giessen.de/JLUmaps/?id=167813&lang=de

Struktur: Vorlesung + Übung
Turnus: Unregelmäßig
Credits: 6 CP
Sprache: Englisch (Regelfall) bzw. Deutsch (Ausnahmefall)
Prüfungsform: Klausur und Hausarbeit mit Präsentation

Qualifikationsziele:
• Beschreibung und Verständnis der Digitalisierung und ihrer Auswirkungen auf wirtschaftliche
Prozesse
• Kenntnis von theoretischen Konzepten und empirischen Methoden zur Messung der Digitalisierung
und zur Analyse ihrer Auswirkungen
• Beschreibung, Interpretation und Bewertung empirischer Ergebnisse
• Kritische Diskussion der ökonomischen und sozialen Auswirkungen der Digitalisierung
•
Inhalte:
• Informations- Kommunikationstechnologien als Querschnittstechnologie
• Auswirkungen der Digitalisierung auf Unternehmen
• Auswirkungen der Digitalisierung auf Beschäftigte
• Digitale Märkte und Plattformen


Für die Teilnahme an der Veranstaltung ist der erfolgreiche Abschluss von Kursen in Industrieökonomik und Ökonometrie sehr empfehlenswert. Weitere Informationen dazu finden Sie auch auf der Homepage.

Die Veranstaltung findet in Präsenz statt.

Link zu JLU-Maps:
https://www.uni-giessen.de/JLUmaps/?id=167813&lang=de

Struktur: Vorlesung + Übung
Turnus: Sommersemester
Credits: 6 CP
Sprache: Englisch
Prüfungsform: Klausur
Die Veranstaltung findet in Präsenz statt.

Die Veranstaltung ist für alle Studierende im Master VWL, EGR, BWL und AFS geöffnet und besteht aus einer wöchentlichen Vorlesung und Übung.

Der Kurs basiert auf dem Buch Causal Inference von Scott Cunningham, sowie den Büchern Mostly Harmless Econometrics und Mastering Metrics von Joshua Angrist und Jörn-Steffen Pischke.

Many of the big questions in the social sciences (and economics) deal with cause and effect. How does immigration affect pay and employment levels? How does a longer education affect someone's future income? These questions are difficult to answer because we have nothing to use as a comparison. We do not know what would have happened if there had been less immigration or if that person had not continued studying.

However, last years Laureates of the Nobel Prize in Economics - David Card, Joshua Angrist, and Guido Imbens - have shown that it is possible to answer these and similar questions using natural experiments. The key is to use situations in which chance events or policy changes result in groups of people being treated differently, in a way that resembles clinical trials in medicine.

If you are curious about how economists can draw plausible conclusions about cause and effect I invite you to join this course. The course covers core methods and seminal applications (discussed in the lecture and replicated in the exercise) dealing with causal inference.

Preliminary schedule:
- Randomized Controlled Trials
- Linear Regression and Matching
- Difference-in-Differences
- Regression Discontinuity Designs
- Instrumental Variables

Struktur: Vorlesung + Übung
Turnus: Sommersemester
Credits: 6 CP
Sprache: Englisch
Prüfungsform: Klausur
Die Veranstaltung findet in Präsenz statt.

Die Veranstaltung ist für alle Studierende im Master VWL, EGR, BWL und AFS geöffnet und besteht aus einer wöchentlichen Vorlesung und Übung.

Der Kurs basiert auf dem Buch Causal Inference von Scott Cunningham, sowie den Büchern Mostly Harmless Econometrics und Mastering Metrics von Joshua Angrist und Jörn-Steffen Pischke.

Many of the big questions in the social sciences (and economics) deal with cause and effect. How does immigration affect pay and employment levels? How does a longer education affect someone's future income? These questions are difficult to answer because we have nothing to use as a comparison. We do not know what would have happened if there had been less immigration or if that person had not continued studying.

However, last years Laureates of the Nobel Prize in Economics - David Card, Joshua Angrist, and Guido Imbens - have shown that it is possible to answer these and similar questions using natural experiments. The key is to use situations in which chance events or policy changes result in groups of people being treated differently, in a way that resembles clinical trials in medicine.

If you are curious about how economists can draw plausible conclusions about cause and effect I invite you to join this course. The course covers core methods and seminal applications (discussed in the lecture and replicated in the exercise) dealing with causal inference.

Preliminary schedule:
- Randomized Controlled Trials
- Linear Regression and Matching
- Difference-in-Differences
- Regression Discontinuity Designs
- Instrumental Variables