Multiple Time Series Analysis SS2016

Participating students are expected to be familiar with basic time series analysis and methods of econometrics. The course covers advanced methods of modelling and analysing multiple time series. Students are introduced to the models, parameter estimation and specification of the relevant models. They will learn to use them for economic analysis and forecasting.

Course Syllabus

Contents

  • Review of univariate time series analysis
  • Vector autoregressive (VAR) models
  • Specification and estimation of VAR models
  • Cointegration
  • Vector error correction models (VECMs)
  • Estimation of VECMs
  • Cointegration tests and specifications of VECMs
  • Structural vector autoregressive analysis

Literature

  • Hamilton, J., Time Series Analysis, Princeton University Press, Princeton, NJ, 1994.
  • Johansen, S., Likelihood-based Inference in Cointegrated Vector Autoregressive Models, Oxford University Press, Oxford, 1995.
  • Lütkepohl, H., New Introduction to Multiple Time Series Analysis, Springer, Berlin, 2005.

 

This course will be offered in Summer Semester 2016, Thursdays from 10 to 12 am and 2 to 4 pm in Hs105. The first lecture will take place on April 21.


Please check this page again for any updates on the time schedule.

Forschungsschwerpunkt Statistik und Ökonometrie
Graduate Center of DIW Berlin