Time series analysis

This course introduces to the time series methods and practices generally used in the analysis of economic and financial time series. We will cover both univariate and multivariate models of stationary and non-stationary time series. The aim of the course is twofold: first to develop a comprehensive set of tools and techniques for analysing various forms of univariate and multivariate time series, and second to acquire knowledge of recent changes in the methodology of econometric analysis of time series.

At the end of the course students will be able to analyse macroeconomic and financial time series and use them in econometric models. Specifically, students will be familiar with univariate statistical techniques generally used to study the dynamics of a time series, like ARMA and ARIMA models, and the dynamics of their conditional variance, like ARCH and GARCH models. They will be also able to deal with linear regression models using stationary and non-stationary time series, as in the case of cointegration. Finally, students will be familiar with recent methodologies concerning multiequational models, like VARs and Structural VARs. They will be able to specify and estimate the unknown parameters of the equations and use them to investigate about the dynamic and causal impact of macroeconomic and financial shocks on the endogenous variables of the model.