Time series data is nowadays collected for several phenomena in social and empirical sciences. The aim of this course is to show participants how to use Stata to perform analysis, modelling and forecasting of time series. The course provides an overview of methods for analysing, modelling and forecasting the dynamic behaviour of economic time series and offers several practical examples of empirical modelling using real-world data. The course does not require any previous knowledge of Stata, since Module 1 provides an introduction to Stata’s basic commands before moving to the analysis of time series features and to univariate time series models. Module 2 covers multivariate time series models for stationary and non-stationary series.
In common with TStat’s training philosophy, throughout the course theory and methods are illustrated in an intuitive way and are complemented by practical exercises with Stata. In this manner, the course leader is able to bridge the “often difficult” gap between theory and practice of time series modelling and forecasting. At the end of the course, participants are expected to be able to autonomously implement the methods discussed in the course.