Prologue

Abstract

In making choices between alternative courses of action, decision makers at all structural levels often need predictions of aggregated variables. For example, in the process of planning a government budget, forecasts of annual tax revenues may be required. If quarterly or monthly figures of previous revenues are available then a time series model may be constructed for the generation process of the quarterly or monthly data. This model can then be used to obtain predictions for the next quarters or months and these forecasts can be aggregated to obtain annual forecasts of the tax revenues. Alternatively, the available monthly or quarterly data may be aggregated to obtain an annual series of tax revenues. Based on this series a model may be constructed to generate annual forecasts.