Economic Forecasting

Module code: EC3010

This module introduces the theories and techniques used to forecast economic and financial variables, equipping you with the analytical tools required to understand, predict and evaluate developments in complex economic environments. You will examine how economists and policymakers generate forecasts, assess uncertainty, and use quantitative evidence to support decision-making.

The module covers a range of forecasting methods, progressing from simple univariate time-series models to more advanced forecasting systems. You will study autoregressive and moving average models, Box–Jenkins analysis, vector autoregressive (VAR) models, dynamic factor models, and modern approaches to analysing volatility and uncertainty, including ARCH and GARCH models. The course also explores density forecasting, forecast combination techniques, and the use of Monte Carlo methods to evaluate risk and uncertainty.

Alongside the theoretical foundations, the module places a strong emphasis on practical application. Through hands-on computer classes, you will gain experience using econometric software to construct forecasts, analyse economic and financial data, evaluate forecasting performance, and apply advanced quantitative techniques to real-world problems.

By the end of the module, you will be able to produce and evaluate forecasts using a range of econometric methods, understand the strengths and limitations of different forecasting frameworks, and critically assess alternative approaches to modelling uncertainty and economic dynamics. These skills are highly valued by employers in economics, finance, consulting, government and data analytics, where forecasting and evidence-based decision-making play a central role.