Time series and forecasting**

A great variety of physical and economic data are in the form of time series. Typical objectives include: · Identify the effect of past shocks on the current state of the world: were the shocks transitory or permanent? How much of a past shock is still relevant today? · Forecasting future values For multivariate time series, we are also interested in· Modelling the dynamic interaction between different series.

By the end of the module you will be able to: Understand the difference between a time series and an independent random sample. Apply non-parametric and parametric techniques to model time series. Choose and estimate parametric models for time series. Compute the impulse response function. Forecast future values.