DE / EN

Autumn Semester 2024

Type	Lecture
Title	E823 Advanced Time Series Analysis
Lecturer	Prof. Dr. Carsten Trenkler
Semester	Autumn Semester 2024
Target Audience	PhD
Start/End	Start: 02.09., End: 05.12.
Time & Location	Monday, 3:30 to 5:00pm (L7, 3–5, P043) and Thursday, 10:15 to 11:45am (L7, 3–5, 410)
Course language	English
Prerequisites	E703, E803, E806 Advanced Econometrics I – III
Examination	Assignments (30%), presentation (30%), paper (40%)
ECTS	9
Course description	The course 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. 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 Further material can be found in the course's Ilias group once set up.

Notes:

Type	Lecture and Tutorial
Title	E508 Multiple Time Series Analysis
Lecturer	Prof. Dr. Carsten Trenkler
Semester	Autumn Semester 2024
Target Audience	Master
Start/End	Start: 02.09., End: 04.12.
Time & Location	Mon: 5.15 – 6.45pm (L9, 1–2, room 003) Wed: 10.15–11.45am (L9, 1–2, room 003)
Course language	English
Prerequisites	E601 – E603 or E700 – E703 or equivalent courses for exchange students, (Basic knowledge of Matlab)
Grading	Two assignments (25%) and final exam (75%).
ECTS	9.5
Course description	This course is intended to give an introduction to multiple time series analysis with a strong emphasis on vector autoregressive (VAR) processes. We focus on the mechanics of the various procedures and their application. Asymptotic properties of estimators and test statistics will only be mentioned but not derived. We start with introducing some important univariate time series concepts. If time permits, we may also cover factor models and factor-augmented VAR models at the end of the course. During the course we will discuss a related empirical research paper and a monthly report of the Bundesbank
Downloads	Course Outline with extended information Further material can be found in the course's Ilias group.

Type	Seminar
Title	Applied Econometrics
Lecturer	Prof. Dr. Carsten Trenkler
Semester	Autumn Semester 2024
Target Audience	Bachelor
Start/End:	Start: 04.09., End: 04.12.
Time & Location:	Wednesday 8.30–10.00am in room L7, 3–5, P044
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 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	Seminar description Further information will be made available in the Ilias group of the seminar.

Teaching – Current Courses

Spring Semester 2024

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	Prof. Dr. Carsten Trenkler
Semester	Frühjahrsemester 2024
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 Erwartungswertfunktionen, KQ-Schätzer und ihre Eigenschaften, Restriktionstests, Kausalanalyse (potentielle Ergebnisse, BMU-Annahme, OV-Bias), Modellspezifikation, 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.

Type	Lecture and Tutorials
Title	Introduction to Multiple Time Series Analysis
Lecturer	Prof. Dr. Carsten Trenkler
Semester	Spring Semester 2024
Target Audience	Bachelor
Time & Location Lecture	Mon 5:15pm-6:45pm, room 357, L7, 3–5
Time & Location Tutorials	Tue 8:30am-10am, room 003 in L9, 1–2 (bi-weekly, schedule will be announced later)
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 very short recap 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 impulse response analysis. 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 here. Further information will be made available in the Ilias group as soon as possible.

Notes:

Type	Lecture and Tutorial
Title	E806 Advanced Econometrics III (PhD)
Lecturer	Prof. Dr. Carsten Trenkler
Semester	Spring Semester 2024
Target Audience	PhD
Start/End	Start: 17.4., End: 30.5.
Time & Location Lecture	Wed 10:15 a.m. – 11.45 a.m., Thur 8:30 a.m. – 10:00 a.m. P044 (L7, 3–5) Alternative dates for holidays: May 10, 8:30–11:45am (L7, 157), May 31, 8:30–11:45am (L7, P043)
Time & Location Tutorial	Thur 10:15 a.m. – 11:45 a.m. P044 (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, Matlab, or Gauss 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.