Stochastic Processes and Their Applications in Economics and the Social Sciences


The aim of this module is to give an introduction into the statistical methods of the social and economic sciences, with special emphasis on the analysis of time series data..

By the end of this module, a student should understand

  • which methods are used to collect and analyse time series data.

Syllabus of the lecture course

  1. Time series: Overview
  2. Time series: Component Methods (Local and Global)
  3. Stochastic Processes: Overview
  4. Stochastic Processes: White Noise, Random Walk, General Linear Processes
  5. The Concept of Stationarity
  6. Time and Frequency
  7. The ARIMA Model
  8. Transformation of Time Series and Stochastic Processes, Filters
  9. Prediction
  10. Summary

Course material

All slides for this course can be found here.

Basic Reading

  • Reiner Schlittgen, Bernd H.J. Streitberg (2001): Zeitreihenanalyse, München: Oldenbourg 9. Aufl. 2001
  • Peter J. Brockwell, Richard A. Davis (1991): Time Series: Theory and Methods, New York: Springer, 2nd edition
  • Peter J. Brockwell, Richard A. Davis (2002): Introduction to Time Series and Forecasting, New York: Springer, 2nd edition