Predicting Earnings: Entity versus Subentity Data

Abstract

The reporting of subentity earnings by large diversified corporations has been the subject of much discussion and research. Attention has centered on the need for the information by investors and the theoretical and practical problems to be encountered in furnishing the information.' Those who have supported the reporting of subentity earnings data have argued that rates of growth and profitability and degrees of risk differ among the segments of a company operating in substantially different industries. This makes the prediction of consolidated earnings of the diversified company unnecessarily difficult. Since little information on subentity earnings has been made public in the past, research in this area has been confined to calling attention to possible uses of the data by investors. The purpose of this study is to test the relative predictive power of subentity earnings data for a sample of companies which have voluntarily reported sales and earnings data by subentity. Consolidated earnings for these firms will be predicted for 1968 and 1969 using subentity and entity sales and earnings data in conjunction with other investment and economic data available in early 1968 and early 1969, respectively. Specifically the question examined is: Will the disaggregation of consolidated earnings permit better predictions of next year's earnings using certain objective prediction models? Relatively simple prediction models are employed as objectively as possible in order to isolate a measure of the value of certain investment in-