Predicting Restatements in Macroeconomic Indicators using Accounting Information

Initial announcements of macroeconomic indicators are based on imprecise and incomplete information. Government statistical agencies routinely restate the initial estimates over the course of several subsequent years as more information becomes available. We find that simple accounting-based aggregates, such as earnings dispersion, can predict future restatements in macroeconomic estimates, including nominal and real GDP growth and unemployment. Out-of-sample tests suggest early macroeconomic estimates can be significantly improved by incorporating accounting information. Early macroeconomic releases attract intense scrutiny from policy makers, capital market investors, business planners, and other economic agents. Therefore, improving the accuracy of early macroeconomic estimates has wide-ranging implications for the efficiency of a large spectrum of economic decisions.