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Teaching - Current Courses

    Autumn semester 2020

  • E823 Advanced Time Series Analysis

    Type

    Lecture

    Title

    E823 Advanced Time Series Analysis

    Lecturer

    Prof. Dr. Carsten Trenkler

    Semester

    Autumn semester 2020

    Target Audience

    PhD

    Start/EndStart: 07.09., End: 10.12.

    Time & Location

    Monday, 15:30 to 17:00 and Thursday, 10:15 to 11:45 in TBA

    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 issues on stationary univariate time series models discussed in Advanced Econometrics III, we will first deal with stable VAR models and their use for forecasting, Granger causality, and impulse response analysis. To this end, we will also discuss important issues on asymptotic- and bootstrap-based inference. Afterwards, we briefly discuss stable VARMA processes and infinite-order VARs. In part 5, we deal with univariate unit root processes and introduce the relevant asymptotic approach for this set-up. Then, we turn to a treatment of multivariate unit root processes which are assumed to be integrated of order one, I(1). Finally, 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.

    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. We may cover e.g.~Bayesian VARs, structural VARs, factor-augmented VARs, VARMA models, etc..

    Our course is complementary to the course offered by Matthias Meier. While the latter course focus on structural modelling approaches from an applied macro perspective, we take an econometric approach and deal with multivariate I(1) approaches, VECM, and VARMA models in more detail.

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  • E508 Multiple Time Series Analysis (Master)

    Notes:

    Type

    Lecture and Tutorial

    Title

    E508 Advanced Econometrics III

    Lecturer

    Prof. Dr. Carsten Trenkler

    Semester

    Autumn Semester 2020

    Target AudienceMaster
    Start/End

    Start: 28.09., End: 09.12.

    Time & Location

    Mon: 5.15 - 6.45pm (Online)

    Wed: 10.15-11.45pm (Online)

    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

    The lecture gives an introduction to multiple time series techniques and will cover vector autoregressive (VAR) processes, VAR estimation, VAR order selection and model checking. We will also introduce the concept of cointegration and summarize how to do inference in VAR models for nonstationary variables. The use of VAR models in forecasting, causality, and impulse response analysis will be explained and illustrated using empirical examples and by discussing a selected set of research papers.

    Downloads

     

    • Course Outline with extended information
    • Further material can be found in the course's Ilias group.
     

    Spring semester 2020

  • Vorlesung: Grundlagen der Ökonometrie

    Hinweise:

    • Beachten Sie bitte, dass die Übungen in der ERSTEN Vorlesungswoche beginnen!

    Art der Veranstaltung

    Vorlesung/Lecture und Übung

    Titel der Veranstaltung

    Grundlagen der Ökonometrie

    Dozent

    Prof. Dr. Carsten Trenkler

    Semester

    Frühjahrsemester 2019

    Zeit & Ort Vorlesung

    Di 13.45 - 15.15 in B6, 23-25, Bauteil A - A001

    Zeit & Ort Übung

    10 Übungsgruppen, Termine und Räume folgen

    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 Erwartungswerte und lineare Projektionen, KQ-Schätzer und ihre Eigenschaften, die Grundzüge asymptotischer Theorie, Verzerrung durch ausgelassene Variablen, Restriktionstests, Modellspezifikation, Modelldiagnose, perfekte und imperfekte Multikollinearität, Kausalitätsanalyse, 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 und die Übungstermine.

    Weitere Details (inklusive Vorlesungsfolien) finden Sie auf der Ilias Seite zum Kurs.

  • E508 Multiple Time Series Analysis (Master)

    Notes:

    • Note: The session on February 21 (Thursday) is canceled.

    Type

    Lecture and Tutorial

    Title

    E508 Advanced Econometrics III

    Lecturer

    Prof. Dr. Carsten Trenkler

    Semester

    Spring Semester 2019

    Target AudienceMaster
    Start/End

    Start: 11.02., End: 27.05.

    Time & Location

    Mon: 5.15 - 6.45 p.m. in S031 (L7, 3-5)

    Thu: 8.30-10am in P044 (L7, 3-5)

    Course language

    English

    Prerequisites

    E601 - E603 or E700 - E703 or equivalent courses for exchange students

    Grading

    Two assignments (25%) and final exam (75%).

    ECTS

    9.5

    Course description

    The lecture gives an introduction to multiple time series techniques and will cover vector autoregressive (VAR) processes, VAR estimation, VAR order selection and model checking. If time permits, we will also cover Structural VAR models, VEC as well as VARMA models. The use of VAR models in forecasting, causality and impulse response analysis will be explained and illustrated using empirical examples and by discussing a selected set of research papers.

    Downloads

    Further details and course Material will be provided via the Ilias group. You can also download the outline here.

  • E806 Advanced Econometrics III (PhD)

    Notes:

    Type

    Lecture (and Tutorial)

    Title

    E806 Advanced Econometrics III (PhD)

    Lecturer

    Prof. Dr. Carsten Trenkler

    Semester

    Frühjahrs-/Sommersemester 2020

    Target AudiencePhD
    Start/End

    Start: 30.03., End: 28.05.

    Time & Location Lecture

    Mon 1:45 p.m. - 3.15 p.m. & Thur 10:15 a.m. - 11:45 a.m. in L7, 3-5, P043

    Time & Location Tutorial

    Mon 3:30 p.m. - 5 p.m. in L7, 3-5, P043

    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 contains some empirical questions or coding exercises. You may use any of the following (matrix) programming languages: STATA, R, Matla or Gauss to address the latter types of questions. You will have a week to complete the assignments. The assignments and programming code must be sent by email. Answers will be (partly) discussed in the tutorial sessions.

    ECTS

    5

    Course description

    In 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. After a general introduction, we fist consider stable ARMA model, then discuss the bootstrap for time series settings, and, finally turn to unit root econometrics.

    Downloads

    Further details and course Material will be provided via the Ilias group.
    You can also download the syllabus here.

  • Applied Econometrics (Bachelor, Block-Seminar)

    Type

    Block-Seminar

    Title

    Applied Econometrics

    Lecturer

    Prof. Dr. Carsten Trenkler

    Semester

    Spring semester 2020

    Target Audience

    Bachelor

    Introductory Meeting:

    Mon, 10.02.18, 1.45 p.m.-3.15 p.m. in room N.N.

    Presentations:

    Tba

    Course language

    English/German

    Prerequisites

    Grundlagen der Ökonometrie (Basic Econometrics); Statistik I+II (Statistics I + II)

    Examination

    seminar paper and presentations

    ECTS

    6

    Course description

    Each participant conducts an own empirical study in order 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 in order to solve empirical problems. The seminar topics will refer to the multiple regression model for cross-section data including IV estimation setups as well as to microeconometric, panel data and time series models. Thereby, you should gain a broad overview on the various model classes through your own and your fellow students’ projects.

    Registration

    You can register for the seminar during the regular registration week. Once you are enrolled for teh seminar I will ask you to send me an email with your three most preferred topics. The maximum number of participants in the seminar is limited to 14.

    Downloads

     

    Further information will be made available in the Ilias group of the seminar in due time.