Time Series Econometrics and Forecasting

The purpose of this core course is to provide students with an in-depth understanding of the fundamental concepts of time series econometrics and forecasting and with the practical skills to use econometric software to model and forecast economic time series and identify models with the best forecasting abilities. The module would build on the foundation of econometrics core course and prepare students for MSc and PhD research.

This module can be taken as part of a PG Certificate, PG Diploma or Full Masters Program. 

Key Skills

By the end of this course, participants should have knowledge and ability to: 

Understand how to model a univariate or multivariate time series process.

Understand the Maximum Likelihood estimation method, and understand how to forecast a univariate or a multivariate time series process

Distinguish between stationary and nonstationary series and understand the implications of using nonstationary series.

Build, estimate and forecast from univariate and multivariate time series models using econometric software.

Desired Skills

By the end of this course, students should be able to: 

Engage in abstract thinking by extracting the essential features of complex systems to facilitate problem solving and decision-making.

Communicate and present complex arguments in oral and written form with clarity and succinctness.

Use statistical and other packages effectively, presenting, interpreting and analysing information in numerical form.

Apply econometrics techniques to aid understanding of the financial and macroeconomic environment.



Time Series Econometrics and Forecasting is a core 20 credit course and therefore students are expected to input approximately 200 hours of study into the course.


The total number of contact hours is 25 hours. This leaves 185  hours for private study.


This module consists of 4 - hour lectures per day for 5 days, plus a 1 - hour tutorial per day. 

 There will be optional clinics on the last day of the course.   

The dates of each lecture are confirmed closer to the start of each term. If you have any questions about dates, please contact