Teaching – Current Courses
Autumn Semester 2025
Applied Econometrics (Bachelor, Seminar)
Type Seminar Title Applied Econometrics Lecturer Prof. Dr. Carsten Trenkler Semester Autumn Semester 2025 Target Audience Bachelor Start/ End: Start: 01.09., End: 01.12. Time & Location: Monday 5.15–6.45 p.m. 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 will conduct your own empirical study to become familiar with applied research, which includes the ability to interpret empirical results meaningfully. Building on the material covered in the course Grundlagen der Ökonometrie, you will deepen your knowledge of econometric models, estimation methods, and testing procedures to address empirical problems. The seminar topics focus on the multiple regression model for cross-sectional data, including instrumental variable (IV) estimation setups, as well as microeconometric, panel data, and time series models. Additionally, some projects will specifically address experimental data and so-called shrinkage estimators. Through your own and your fellow students’ projects, you will gain a broad overview of various model classes and methods. Registration Closed Downloads Further information will be made available in the Ilias group of the seminar.
Introduction to Multiple Time Series Analysis (Bachelor)
Type Lecture and Tutorials Title Introduction to Multiple Time Series Analysis Lecturer Prof. Dr. Carsten Trenkler Semester Autumn Semester 2025 Target Audience Bachelor Time & Location Mon 3:30–5:00 p.m. in room 003, Wed 8:30am-10am in room 0033, L9, 1–2 Course language English Prerequisites Grundlagen der Ökonometrie (Basic Econometrics); Statistik I+II (Statistics I + II) Grading Exam (90 minutes, 70%), 2 assignments with two to three problems (30%) ECTS 6 Course description This course offers an introduction to multiple time series analysis, with a particular focus on impulse response analysis using vector autoregressive (VAR) models. We begin with a brief review of key univariate time series concepts before moving on to the VAR framework and its estimation. The course then introduces structural VAR (SVAR) models, which are widely used for impulse response analysis—that is, for examining the effects of economically interpretable structural shocks. We will cover basic identification strategies used to recover the structural shocks of interest. The lectures are accompanied by tutorial sessions that address both empirical applications and relevant statistical and algebraic foundations. 'Introduction to Multiple Time Series Analysis' complements well the course 'Time Series and Forecasting' but it can also be taken independently without difficulty. Downloads You can find the syllabus here (PDF, 80 kB). Further information will be made available in the Ilias group. E5120 Topics in Econometrics (Master, Blockseminar)
Type Seminar Title E5120 Topics in Econometrics Lecturer Prof. Dr. Carsten Trenkler Semester Autumn Semester 2025 Target Audience Bachelor Start/ End: Start: 02.09., End: 05.12. Time & Location: Initial meeting: Tuesday 10.15–11.45 a.m. in room tba. Time slots for presentations: tba Course language English Prerequisites Advanced Econometrics Examination seminar paper, presentation, handout ECTS 5 Course description This seminar explores recent research developments in Econometrics, addressing both theoretical and applied aspects in microeconometrics and time series analysis. Each student is expected to present a paper – or a pair of two related papers – selected from the reading list, and to write a course paper (ranging from 15 to 20 pages) on a topic related to the subject of their presentation. The course paper may be structured as a discussion paper or an empirical application of an econometric method. Registration Open Downloads Further information will be made available in the Ilias group of the seminar.
Spring Semester 2025
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 2025
Zeit & Ort Vorlesung
Di 13.45 – 15.15, A001 (B6, 23–25, Bauteil A)
Zeit & Ort Übung
12 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, KQ-Schätzer und seine Eigenschaften, Inferenz, nichtlineare Modellierungen, Kausalanalyse: potentielle Ergebnisse, OV-Bias, BMU-Annahme, Schätzung kausaler Effekte, inklusive Instrumentalvariablenschätzung, sowie Zeitreihenanalyse. Neben der Diskussion der konzeptionellen Grundlagen und der Methoden, wird die Anwendung der Methoden 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 (PDF, 76 kB).
Weitere Details (inklusive Vorlesungsfolien) finden Sie auf der Ilias Seite zum Kurs.
Introduction to Multiple Time Series Analysis (Bachelor)
Type
Lecture and Tutorials
Title
Introduction to Multiple Time Series Analysis
Lecturer
Semester
Spring Semester 2025
Target Audience Bachelor
Time & Location
Mon 5:15pm-6:45pm in room 357; L7, 3–5, Tue 8:30am-10am in room 157, L7, 3–5
Course language
English
Prerequisites
Grundlagen der Ökonometrie (Basic Econometrics); Statistik I+II (Statistics I + II)
Grading
Exam (90 minutes, 70%), 2 assignments with two to three problems (30%) ECTS
6
Course description
The course will provide an introduction to multiple time series analysis with a focus on impulse response analysis using vector autoregressive (VAR) models. We start with a short introduction of univariate time series concepts and then turn to the VAR model framework and estimation. Then, we look into structural VAR (SVAR) models that are commonly applied for impulse response analysis, i.e., the analysis of the effects of so-called structural shocks that are (economically) interpretable. We deal with basic identification schemes to recover the structural shock(s) of interest. Finally, we discuss empirical papers using structural VAR tools. The lectures are accompanied by tutorial sessions that deal with some algebraic issues and, in particular, empirical applications. 'Introduction to Multiple Time Series Analysis' complements well the course 'Time Series and Forecasting' but it can also be taken independently without any problems. Downloads
You can find the syllabus (PDF, 81 kB) here. Further information will be made available in the Ilias group.
E806 Advanced Econometrics III (PhD)
Notes:
Type
Lecture and Tutorial
Title
E806 Advanced Econometrics III (PhD)
Lecturer
Semester
Spring Semester 2025
Target Audience PhD Start/ End Start: 2.4., End: 30.5.
Time & Location Lecture
Wed 10:15 a.m. – 11.45 a.m., Thur 8:30 a.m. – 10:00 a.m. P043 (L7, 3–5)
Alternative dates for holidays: April 30 and May 28: 8:30–10:00am (009, L9, 1–2), May 30, 8:30–10:00am (001, L7, 3–5)
Time & Location Tutorial
Thur 10:15 a.m. – 11:45 a.m. P043 (L7, 3–5) Course language
English
Prerequisites
Advanced Econometrics I+II
Homework and grading
Grading for this course will be based on the final exam (100 points). You can earn up to 10 bonus points if you submit solutions to the assignments that demonstrate a sufficient attempt to solve problems. To each of the three assignments a pre-announced number of bonus points is allocated. The assignments will mainly involve methodological questions but also contain some empirical questions or coding exercises. You may use any of the following (matrix) programming languages: STATA, R, or Matlab to address the latter types of questions. You will usually have a week to complete an assignment. Your solutions and programming code must be sent by email. Answers will be (partly) discussed in the tutorial sessions.
ECTS
5
Course description
Part I is devoted to the analysis of panel data models. Besides discussing fixed- and random effects settings we also look into GMM/
IV estimation and dynamic panel models. Part II deals with univariate time series analysis. We start with discussing theoretical foundations of time series analysis and then turn to linear models, including autoregressions. Finally, we deal with non-stationary unit root time series if time permits. Downloads
The course material will be provided via the Ilias group.