Teaching – Current Courses
Spring Semester 2023
Grundlagen der Ökonometrie (Bachelor)
Hinweise:
- Beachten Sie bitte, dass die Übungen in der ERSTEN Vorlesungswoche beginnen!
Art der Veranstaltung
Vorlesung und Übung
Titel der Veranstaltung
Grundlagen der Ökonometrie
Dozent
Semester
Frühjahrsemester 2023
Zeit & Ort Vorlesung
Di 13.45 – 15.15, A001 (B6, 23–25, Bauteil A)
Zeit & Ort Übung
10 Übungsgruppen, Termine und Räume finden Sie im Portal2
Methode (Stunden pro Woche):
Vorlesung und Übung (2+2)
Kurssprache
Deutsch
Voraussetzungen
Statistik I+II
Prüfung
schriftlich (90 Minuten)
ECTS
6
Kursbeschreibung
Der Kurs gibt eine Einführung in die wichtigsten Methoden der Ökonometrie. Besprochen werden das multiple Regressionsmodell, bedingte Erwartungswertfunktion, Kausalanalyse, KQ-Schätzer und ihre Eigenschaften, die Grundzüge asymptotischer Theorie, Verzerrung durch ausgelassene Variablen, Restriktionstests, Modellspezifikation, Modelldiagnose, perfekte und imperfekte Multikollinearität, nichtlineare Modellierungen, IV-Schätzung sowie Zeitreihenanalyse. Neben einer einführenden Betrachtung der theoretischen Aspekte der Methoden, wird vor allem deren Anwendung demonstriert und die empirisch relevanten Aspekte diskutiert. Die Vorlesung wird durch methodische und empirische Übungen im PC-Pool begleitet.
Downloads
Hier finden Sie den Vorlesungsplan.
Weitere Details (inklusive Vorlesungsfolien) finden Sie auf der Ilias Seite zum Kurs.
Autumn Semester 2022
E823 Advanced Time Series Analysis (PhD)
Type
Lecture
Title
E823 Advanced Time Series Analysis Lecturer
Semester
Autumn semester 2022
Target Audience PhD
Start/ End Start: 05.09., End: 07.12. Time & Location
Monday, 15:30 to 17:00 (L9, 1–2, 002) and Wednesday, 17:15 to 18:45 (L9, 1–2, 002)
Course language
English
Prerequisites
E703, E803, E806 Advanced Econometrics I – III
Examination
Assignments (30%), presentation (30%), paper (40%)
ECTS
9
Course description
The lecture will focus on multivariate time series models. After reviewing a few general concepts from probability theory and time series analysis, we will first deal with stable VAR models and their use for Granger causality, impulse response analysis, historical decompositions, and forecast error variance decompositions. To this end, we will also discuss important issues on asymptotic- and bootstrap-based inference. Depending on time, we very briefly discuss stable infinite-order VARs and VARMA processes.
Then, we deal with univariate unit root processes and introduce the relevant asymptotic approach for this set-up. In a next step, we turn to a treatment of multivariate unit root processes which are assumed to be integrated of order one, I(1). Afterwards, we briefly introduce the concept of cointegration and learn how cointegration can be integrated into VAR framework leading to a so-called vector error correction model (VECM). As cointegration is not that popular anymore in empirical work, we will only summarize how to do appropriate inference in potentially cointegrated VARs with I(1) variables.
If time permits, I would like to give an overview on estimating high-dimensional VARs and factor models in the last part of the course.
The course both addresses asymptotic analyses as well as implementation issues. Accordingly, tutorial sessions are also devoted to coding and empirical problems besides addressing theoretical problems.
In the last part of the course, participants introduce or discuss in more details (further) model classes by giving presentations and writing a paper. This year, I will provide a set of recent papers on network analysis using multiple time series approaches. This shall give an impression and overview on a recent strand in the literature.
Our course is complementary to the course offered by Matthias Meier. While the latter course focus on structural modeling approaches from an applied macro perspective, we take an econometric approach on multiple time series frameworks.
Downloads
- Preliminary Syllabus
- Some comments on adjustments for this year's course
- Further material can be found in the course's Ilias group.
Applied Econometrics (Bachelor, Seminar)
Type
Seminar
Title
Applied Econometrics
Lecturer
Semester
Autumn semester 2022
Target Audience Bachelor
Start/
End: Start: 05.09., End: 07.12.
Time & Location:
Wednesday 10.15–11.45 in room L7, 3–5, P043
Course language
English
Prerequisites
Grundlagen der Ökonometrie (Basic Econometrics); Statistik I+II (Statistics I + II)
Examination
seminar paper and presentations
ECTS
6
Course description
You conduct an own empirical study to become familiar with applied research, what includes the ability to interpret empirical results in a meaningful way. Based on the material covered in the course Grundlagen der Ökonometrie, you will extend your knowledge on econometric models, estimation methods, and test procedures to solve empirical problems. The seminar topics will refer to the multiple regression model for cross-section data including IV estimation set-ups as well as to microeconometric, panel data and time series models. Moreover, some projects will specifically deal with heteroskedasticity, experimental data, and so-called shrinkage estimators. Thereby, you should gain a broad overview on the various model classes and methods through your own and your fellow students’ projects. Registration Closed Downloads
Further information will be made available in the Ilias group of the seminar.