Aggregate accounting research and development expenditures and the prediction of real gross domestic product

The role of accounting information for public policy making has received increased attention in recent years. Konchitchki and Patatoukas (2014a,b) demonstrate that growth in aggregate accounting earnings can predict future growth in nominal and real Gross Domestic Product (GDP). We extend the micro to macro literature by decomposing earnings into the R&D and pre-R&D components. Using the Almon (1965) finite distributed lag model, we find that both components can predict future real GDP growth with different lead-lag structures. Importantly, this decomposition significantly increases the explanatory power of the predictive model using accounting information. Aggregate accounting R&D can predict real GDP through the personal consumption, business investment, and net export channels of GDP. Our study extends prior research on the forecasting usefulness of accounting information at the aggregate level and has practical implications for macro forecasting and for public policy making regarding innovative activities of publicly listed firms. Published by Elsevier Inc.