Learning more by aggregating less

Abstract

We propose and find that aggregating a small number of earnings signals from highly macroeconomically exposed firms yields an informative leading indicator of future GDP. This challenges the convention of defining aggregate earnings using a comprehensive set of public earnings signals. Our findings suggest that aggregate earnings lead future GDP primarily through the information conveyed by this small subset of firms. We further find that this smaller aggregate relates to the wage and tax components, but not the corporate profits component, of GDP. Thus, our results question the view that there is a mechanical link between aggregate earnings and GDP. We shed light on the “black box” of how market participants form expectations by showing that forecasters across organizations fail to efficiently incorporate the news contained in top macro-exposed firms. Overall, our results highlight the importance of aggregation for forming macroeconomic expectations and clarify the mechanism underlying the relation between aggregate earnings and GDP

Keywords: aggregate earnings; Gross Domestic Product (GDP); corporate profits; forecasting

JEL Classification: E00, E01, E52, G17, G24, M41