DE / EN

Teaching – Current Courses

Spring Semester 2024

  • 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

    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.

  • Introduction to Multiple Time Series Analysis (Bachelor)

    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.

  • E806 Advanced Econometrics III (PhD)

    Notes:

    Type

    Lecture and Tutorial

    Title

    E806 Advanced Econometrics III (PhD)

    Lecturer

    Prof. Dr. Carsten Trenkler

    Semester

    Spring Semester 2024

    Target AudiencePhD
    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)

    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

    Once available, you can download the syllabus and overview slides here. The course material will be provided via the Ilias group.