Nonstationary Time Series and Panel Analysis

I. Syllabus:

The aim of the course is to provide you with knowledge and understanding typical inferential pitfalls that come with nonstationary data, be they time series or panel data. The rst part of the course is concerned with introducing the suitable asymptotic tools. We discuss estimation and inference in the cointegrated VAR model in the second part, and address some issues with panel unit root and cointegration tests in the nal part. While the rst part is more lecture-style, the latter two are based on discussing relevant articles, as will be the exam.

  • Stationary time series models
  • (Co-)Integrated processes
  • Invariance principles (the functional CLT)
  • Quasi-ML analysis of the cointegrated VAR (Johansen)
  • Panel unit root tests
  • Panel cointegration

 

II. Prerequisites:

 

III. Exam:

  • oral exam
  • Examina Day Date Time Room

     

    IV. Materials:

     

    V. Literature:

    • Background notes & materials for the rest part as pdf file.
    • Relevant research articles tba.
    • Some useful (yet tough) textbooks:
      • Hassler, U. (2007). Stochastische Integration und Zeitreihenmodellierung: Eine Einführung mit Anwendungen aus Finanzierung und Ökonometrie. Springer.
      • Johansen, S. (1996). Likelihood Based Inference on Cointegration in the Vector Autoregressive Model (2nd ed.). Oxford University Press.
      • Lütkepohl, H. (2004). New Introduction to Multiple Time Series Analysis. Springer.
      • White, H. (2000) Asymptotic Theory for Econometricians: Revised Edition. Academic Press.

     

    VI. Lecture:

    Tag Zeit Ort Dozent Termin UnivIS

     

    VII. Registration:

    Access to the computer lab requires a one-time registration with a Stu-Account.