Forecasting Sales : A Model and Some Evidence from the Retail Industry

This paper presents a sales forecasting model and tests the model on a sample of firms in the retail industry. The model distinguishes between sales growth due to an increase in the number of sales-generating units (e.g. opening new stores) and growth due to an increase in the sales rate at the existing units (e.g. the comparable store growth rate). The model accommodates different trends in the sales rates, allowing new stores to earn more or less than existing stores, perhaps because new stores take either a long time to reach maturity or alternatively enjoy an early “fad” status. The model uses only a few years of firm-specific, publicly available information, yet generates in-sample forecast errors of less than two percent of sales, generates out-of-sample forecast errors that are almost as accurate as analyst revenue forecasts and, when used together with analyst forecasts, results in a modified forecast that is significantly more accurate than the analyst forecast alone