Economic and statistical measures of forecast accuracy

This paper argues in favour of a closer link between the decision and the f orecast evaluation problems. Although the idea of using decision theory for forecast evaluation appears early in the dynamic stochastic programming li terature, and has continued to be used with meteorological forecasts, it is hardly mentioned in standard academic texts on economic forecasting. Some of the main issues involved are illustrated in the context of a two-state, two-action decision problem as well as in a more general setting. Relations hips between statistical and economic methods of forecast evaluation are di scussed and links between the Kuipers score used as a measure of forecast a ccuracy in the meteorology literature and the market timing tests used in f inance are established. An empirical application to the problem of stock ma rket predictability is also provided, and the conditions under which such p redictability could be explained in the presence of transaction costs are d iscussed. Copyright (C) 2000 John Wiley & Sons, Ltd.