TrainingsDE 2ème/3ème cycleDESU Magistère Ingénieur EconomisteCoursesTime series

DESU Magistère Ingénieur EconomisteUE Time series


You will understand the theory behind models for time series data. These exhibit often rich dynamic structures, so data are dependent. Their analysis therefore requires techniques that are often different from cross-sectional settings. Theory is fully supported by extensive exercises and practical illustrations using the software R.

Course overview :

The course will focus on the analysis of a univariate time series.

The dynamics will be analysed by considering the autocorrelations of the series.

  1. We start with concepts of statistical regularities (weak and strong stationarity, asymptotic independence), then consider in detail the class of ARIMA models.
  2. Model estimation and model selection.
  3. Non-stationary models (deterministic and stochastic trends, structural breaks) ; unit roots.

Language used

Main language used by this course: Anglais et Français.


There is no textbook for this course, but the lecture handouts are fairly self-contained.

The material is also covered in some classic textbooks, such as :

  • Hamilton, J. “Time Series Analysis”, Princeton University Press (1994)
  • Brockwell, P, and R. Davis., “Time series : Theory and methods”, second edition Springer Verlag New York (1991).
  • Stock, J.H. and M.W. Watson, “Introduction to econometrics”, Pearson Addison Wesley (chap 14-15).

Recommended prerequisites

Competences in Econometrics appropriate for the M1 level.

Structure and organisation

This module consists of 24 hours, which will be organized as lectures and sessions devoted to exercise sets.

Some teaching time will be set aside for practical illustrations on a computer using the software package R, freely available from A good editor, which will simplify interaction with R considerably is Rstudio, freely available from