数字技术与经济金融前沿论坛（第52期）

摘要：

    We conduct analyses of non-GAAP earnings at a macroeconomic level. Our results suggest that aggregate non-GAAP earnings better predict future GDP growth than GAAPearnings However, macroeconomic forecasters do not appear to fully incorporate the information from aggregate non-GAAP earnings. Further, when examining GDP growth components separately, we document that aggregate non-GAP earnings both directly predict leading corporate profits and indirectly predict future economic activities (taxes and wages). Additional analyses reveal that the superior performance of aggregate non-GAAP earnings is due to non-GAAP earnings better reflecting firms’ core profitability and capturing managers’ private information regarding future business activities. Finally, we use a time-series decomposition to clarify why non-GAAP earnings outperform GAAP and uncover that non-GAAP earnings contain richer business cycle information while GAAP is more susceptible to short-term disturbances. Our evidence contributes to the growing literature on aggregate earnings and the macro-economy and extends prior research on firm-level non-GAAP earnings to the aggregate level.

主讲人介绍：

      周青博士是澳大利亚麦考瑞大学商学院金融学副教授， 博士生导师。她的研究领域涵盖公司金融、银行学和气候金融，主要探讨市场与监管如何影响企业的融资与投资决策。她的研究成果发表于Journal of Corporate Finance，Journal of Banking and Finance，Journal of Empirical Finance和Journal of Business Ethics等国际学术期刊。周博士现任麦考瑞大学商学院应用金融系研究生主任，同时担任《Pacific-Basin Finance Journal》及《Accounting and Finance》副主编，《British Accounting Review》和《Global Finance Journal》特刊主编。