When meteorologists predict the weather for a month, they often use one of the so-called naïve forecasts. What the average spend during June for the last five years – the counterpart of the climate of the region and the basis for the naïve forecast – stands as a first-cut forecast.
A second type of naïve forecast is persistence, which would predict spending based on the average of the preceding months. All else being equal, it assumes the pattern will continue. A model developed to predict something needs to perform better than both of the naïve forecasts.
A third method, which is not described in David Orrell, Apollo’s Arrow: the Science of Prediction and the Future of Everything (Harper 2007) at 150, looks at the trend line of preceding months. The (persistence) average smoothes out and hides change; a trend line suggests the direction of change and therefore gives more information.