ETC2450 - Applied forecasting for business and economics - 2017

Reliable forecasts of business and economic variables must often be obtained against a backdrop of structural change in markets and the economy. This unit provides a practical introduction to methods suitable for forecasting in these circumstances including the classical decomposition of time series, exponential smoothing, Box-Jenkins ARIMA modelling, and regression with auto-correlated disturbances. It also provides an introduction to applied multiple regression analysis. Students can expect to enhance their computer skills with exercises using advanced features of Microsoft Excel and an econometrics package.

The learning goals associated with this unit are to:

1. provide an understanding of common statistical methods used in business and economic forecasting
2. develop computer skills for forecasting from business and economics time series data
3. provide insights into the problems of implementing and operating large scale forecasting systems for use in production and services management.

Within semester assessment: 40% + Examination: 60%

Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of scheduled learning activities and independent study. Independent study may include associated readings, assessment and preparation for scheduled activities. The unit requires on average three/four hours of scheduled activities per week. Scheduled activities may include a combination of teacher directed learning, peer directed learning and online engagement.

See also Unit timetable information

Professor Rob Hyndman

ETC1000