The role of accounting information for public policy making has received increased attention in recent years. Konchitchki and Patatoukas, 2014a, Konchitchki and Patatoukas, 2014b 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.

近年来，会计信息在公共政策制定中的作用越来越受到重视。Konchitchki 和 Patatoukas，2014a，Konchitchki 和 Patatoukas，2014b 表明，总会计收益的增长可以预测名义和实际国内生产总值 (GDP) 的未来增长。我们通过将收益分解为研发和研发前的组成部分，将微观文献扩展到宏观文献。使用 Almon (1965) 有限分布滞后模型，我们发现这两个分量都可以预测未来的真实具有不同领先滞后结构的 GDP 增长。重要的是，这种分解显着增加了使用会计信息的预测模型的解释能力。聚合会计R&D可以通过GDP的个人消费、企业投资和净出口渠道来预测实际GDP。我们的研究扩展了先前关于总体会计信息预测有用性的研究，并对宏观预测和有关上市公司创新活动的公共政策制定具有实际意义。