3.40314 FORECASTING

This course is designed to give a thorough, applied, and simple to comprehend presentation of most of the procedures useful in modelling and forecasting time series economic data. The course aims to equip students with the various forecasting methods, both qualitative and quantitative, however, the emphasis is more on the quantitative methods. The methods include: the Naïve model, Simple Moving Average, Trend model using regression analysis, Exponential Smoothing, Decomposition method, Exponential Smoothing - seasonal models, Box-Jenkins non-seasonal and seasonal models, and the Causal model using multiple regression analysis. Students are taught how to use Excel spreadsheet, MINITAB (statistical software) and SHAZAM (Econometrics software) to implement these forecasting methods.

Prerequisite: 3.30303; 3.30304

Text:

Gaynor, P. E & Kirkpatrick, R. C., 1994, Time-Series Modelling and Forecasting in Business and Economics, McGraw-Hill Inc, New York