DE / EN

Teaching - Previous Courses

  • Spring semester 2019

    • Grundlagen der Ökonometrie (Bachelor)
      Kussprache: Deutsch
      Voraussetzungen: Statistik I + II
      Prüfung: schriftlich (90 Minuten)
      ECTS-Credits: 6
      Course description: 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, 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.  
      Lehrbuch: Stock, J. H. and Watson, M.W. (2012), Introduction to Econometrics, 3rd ed., Pearson, Boston.
    • E 508 Multiple Time Series Analysis (Master)
      Course language: English
      Prerequisites: E601 - E603 or E700 - E703 or equivalent courses for exchange students
      Examination: written (90 minutes, 75% weight) + 2 Assignments (25% weight)
      ECTS-Credits: 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. The methods will be applied in computer tutorials.
    • E806 Advanced Econometrics III (PhD)
      Course language: English
      Prerequisites: Advanced Econometrics I+II
      ECTS-Credits: 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. 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.
  • Fall semester 2018

    • E585 Topics in Multiple Time Series Analysis
      Course language: English
      Prerequisites: E603 Advanced Econometrics
      Examination: paper (75%) and presentations (25%)
      ECTS-Credits: 5
      Course description: In this seminar students work on applied or methodological projects related to multiple time series analysis. Thereby, they can extend and broaden their background acquired during the lectures on multiple time series analysis and empirical macroeconomics. The potential topics refer e.g. to VARMA models, structural VARs, Bayesian VARs and factor models. It is expected that students independently acquire the necessary knowledge regarding the relevant model classes, methods and/or implementations. The maximum number of participants in the seminar is limited to 14.
    • Applied Econometrics (Bachelor, Seminar)
      Course language: German/English
      Prerequisites: Grundlagen der Ökonometrie (Basic Econometrics); Statistik I+II (Statistics I + II)
      Examination: paper (75%) and presentations (25%)
      ECTS-Credits: 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.  
    • E823 Advanced Time Series Analysis (PhD, Lecture + exercise)

      Course language: English
      Prerequisites: E700, E703, E803, E 806 or equivalent courses for exchange students
      Examination: 3 Assignments (30%), Presentation (30%) & Paper (40%)
      ECTS-Credits: 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. Finally, we consider integrated multivariate processes after a short re-cap of unit root econometrics. To this end, we will also deal with cointegration, including VEC modelling. 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.. This course is complementary to the course Structural Vector Autoregessive Analysis 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.

  • Spring semester 2018

    • Grundlagen der Ökonometrie (Bachelor)
      Kussprache: Deutsch
      Voraussetzungen: Statistik I + II
      Prüfung: schriftlich (90 Minuten)
      ECTS-Credits: 6
      Course description: Der Kurs gibt eine Einführung in die wichtigsten Methoden der Ökonometrie. Besprochen werden das multiple Regressionsmodell, 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.  
      Lehrbuch: Stock, J. H. and Watson, M.W. (2012), Introduction to Econometrics, 3rd ed., Pearson, Boston.
    • Applied Econometrics (Bachelor, Block-Seminar)
      Course language: German/English
      Prerequisites: Grundlagen der Ökonometrie (Basic Econometrics); Statistik I+II (Statistics I + II)
      Examination: paper and presentation
      ECTS-Credits: 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.  
    • E806 Advanced Econometrics III (PhD)
      Course language: English
      Prerequisites: Advanced Econometrics I+II
      ECTS-Credits: 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. 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.
      Contact person:Prof. Dr. Carsten Trenkler
  • Spring semester 2017

    • E 508 Multiple Time Series Analysis (Master)
      Course language: English
      Prerequisites: E601 - E603 or E700 - E703 or equivalent courses for exchange students
      Examination: written (90 minutes, 75% weight) + 2 Assignments (25% weight)
      ECTS-Credits: 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. The methods will be applied in computer tutorials. 
      Textbook: Lütkepohl, H. (2005), New Introduction to Multiple Time Series Analysis, Springer, Berlin, Chapters 1 - 4, 6 - 9, and 11 - 13, Appendices A - D. The list of covered research papers and additional literature will be provided at the beginning of the course.
    • E803 Advanced Econometrics II (PhD)
      Course language: English
      Prerequisites: Advanced Econometrics I
      ECTS-Credits: 5
      Course description: The goal of the module is to offer advanced treatment to econometric theory and to serve as the gate way to further advanced theoretical and applied econometric modules offered in the economics graduate program. In Part I, we deal with single-equation linear models. Some of the material is probably already familiar to some of you. We then turn to system approaches also dealing with the GLS and GMM estimators. Finally, Part III considers (nonlinear) extremum estimators, with a focus on M-estimation, and then discuss the three main testing principles (LR, LM, WALD).
  • Fall semester 2016

    E823 Advanced Time Series Analysis (PhD, Lecture + exercise)

    Course language: English
    Prerequisites: E700, E703, E803, E 806 or equivalent courses for exchange students
    Examination: written (1/3 weight) + 3 Assignments (1/3 weight) + presentation & short paper (1/3 weight)
    ECTS-Credits: 9

    Course description: The lecture will cover the asymptotics for univariate and multivariate time series models. After reviewing a few issues on stationary univariate time series models discussed in Adv. Econometrics III, we will deal with stable multivariate VAR models and their use for impulse response analysis. To this end, we will also deal with bootstrap confidence intervals. Afterwards, we discuss integrated univariate and multivariate processes. Tutorial sessions will cover both theoretical and empirical issues. In the last part of the course participants will introduce further model classes by giving presentations. We may cover e.g. VARMA models, Bayesian VARs, structural VARs etc.

    Literature: Hayashi, F. (2000), Econometrics, Princeton University Press; Lütkepohl, H. (2005), New Introduction to Multiple Time Series Analysis, Springer; Hamilton, J.D. (1994), Time Series Analysis, Princeton University Press; Lütkepohl, H. and Krätzig, M. (2004), Applied Time Series Econometrics, CUP; Horowitz, J. L. (2001). The Bootstrap, in J. J. Heckmann & E. E. Leamer (eds), Handbook of Econometrics, Vol. 5, North-Holland, Amsterdam; Davidson, R. & MacKinnon, J. G. (2004). Econometric Theory and Methods, Chapters 4-5, Oxford University Press.

    Contact persons: Prof. Dr. Carsten Trenkler

  • Spring semester 2016

    • E806 Advanced Econometrics III (PhD)
      Course language: English
      Prerequisites: Advanced Econometrics I+II
      ECTS-Credits: 5
      Course description: In Part I we will first reconsider extremum estimators, with a focus on M-estimation, then discuss the three main testing principles (LR, LM, WALD) and, finally, introduce the bootstrap in relation to testing. Wile Part II is devoted to basic analysis of panel data (models), Part III deals with time series analysis. Part III is somewhat more detailed but we will just focus on stationary time series set-ups.
      Contact person:Prof. Dr. Carsten Trenkler
    • Applied Econometrics (Bachelor, Block-Seminar)
      Language: German/English
      Prerequistes: Grundlagen der Ökonometrie (Basic Econometrics); Statistik I+II (Statistics I + II)
      Examination: seminar paper and presentations
      ECTS-Credits: 6
      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.
      Contact person: Prof. Dr. Carsten Trenkler
  • Fall semester 2015

    • Applied Econometrics (Bachelor, Seminar)
      Language: German/English
      Prerequistes: Grundlagen der Ökonometrie (Basic Econometrics); Statistik I+II (Statistics I + II)
      Examination: Seminar paper and presentation
      ECTS-Credits: 6
      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.
      Contact person: Prof. Dr. Carsten Trenkler
    • E585 Topics in Multiple Time Series Analysis (Master, Seminar)
      Language: English
      Prerequisites: Lecture on Multiple Time Series Analysis
      Examination: Seminar paper and presentation
      ECTS-Credits: 5
      Description: In this seminar students work on applied or methodological projects related to multiple time series analysis. Thereby, they can extend and broaden their background acquired during the lecture on multiple time series analysis. The potential topics refer e.g. to VARMA models, structural VARs, Bayesian VARs and factor models. It is expected that students independently acquire the necessary knowledge regarding the relevant model classes, methods and/or implementations. 
      The maximum number of participants in the seminar is limited to 14. The enrolment takes place between 27 and 31 July. Note that a successful exam in Basic Econometrics is a pre-requirement for participating in the seminar.
      Contact person: Prof. Dr. Carsten Trenkler
  • Spring semester 2015

    • E 508 Multiple Time Series Analysis (Master)
      Course language: English
      Prerequisites: E601 - E603 or E700 - E703 or equivalent courses for exchange students
      Examination: written (90 minutes, 75% weight) + 2 Assignments (25% weight)
      ECTS-Credits: 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. The methods will be applied in computer tutorials. 
      Textbook: Lütkepohl, H. (2005), New Introduction to Multiple Time Series Analysis, Springer, Berlin, Chapters 1 - 4, 6 - 9, and 11 - 13, Appendices A - D. The list of covered research papers and additional literature will be provided at the beginning of the course.
    • E806 Advanced Econometrics III (PhD)
      Course language: English
      Prerequisites: Advanced Econometrics I+II
      ECTS-Credits: 5
      Course description: In Part I we will first reconsider extremum estimators, with a focus on M-estimation, then we discuss the three main testing principles (LR, LM, WALD) and, finally, introduce the bootstrap in relation to testing. Part II is devoted to time series analysis and Part III deals with the basic analysis of panel data (models). The former part is somewhat more detailed but we will just focus on stationary time series set-ups.
  • Fall semester 2014

    • Applied Econometrics (Bachelor, Seminar)
      Language: German/English
      Prerequistes: Grundlagen der Ökonometrie (Basic Econometrics); Statistik I+II (Statistics I + II)
      Examination: Seminar paper and presentation
      ECTS-Credits: 6
      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.
      Contact person: Prof. Dr. Carsten Trenkler
    • E585 Topics in Multiple Time Series Analysis (Master, Seminar)
      Language: English
      Prerequisites: Lecture on Multiple Time Series Analysis
      Examination: Seminar paper and presentation
      ECTS-Credits: 6
      Description: In this seminar students work on applied or methodological projects related to multiple time series analysis. Thereby, they can extend and broaden their background acquired during the lecture on multiple time series analysis. The potential topics refer e.g. to VARMA models, structural VARs, Bayesian VARs and factor models. It is expected that students independently acquire the necessary knowledge regarding the relevant model classes, methods and/or implementations. 
      The maximum number of participants in the seminar is limited to 14. The enrolment takes place between 28 and 31 July. Note that a successful exam in Basic Econometrics is a pre-requirement for participating in the seminar.
      Contact person: Prof. Dr. Carsten Trenkler
    • E823 Advanced Time Series Analysis (PhD, Lecture + exercise)
      Language: English
      Prerequisites: PhD program in economics: E700-E703 and E801-E806; other programs: E700, E703, E803 and E806 or equivalent courses
      Examination: Exam and assignments
      ECTS-Credits: 7
      Description: The lecture will mainly cover asymptotics analysis related to time series models. Partly, empirical issues are discussed as well. We will deal with univariate time series models, unit root asymptotics, multivariate VAR models, bootstrap methods, and, depending on time, with VARMA models and cointegration.
      Contact person: Prof. Dr. Carsten Trenkler