Research Economic Seminar: The rise of intangible investments in cross-sectional earnings forecasting and implied cost of capital estimation

This paper contributes to the literature on cross-sectional earnings forecasting by showing that considering intangible investments significantly enhances the quality of the forecasts and the resulting implied cost of capital estimates. Specifically, I augment existing models by including investment main selling and general administrative expenses, research and development expenses, and advertising expenses as predictors. While the idea of intangible investments playing a role in earnings forecasting has been articulated and tested in prior research (Gerakos and Gramacy, 2013; Hou et al., 2012), this paper is the first that provides evidence that intangible investments are indeed important predictors in cross-sectional earnings forecast models. Earlier research has not been able to empirically confirm the compelling theoretical arguments for considering intangible investments because their importance has substantially increased during the past decade (2010-2019). Further analysis shows that patent count or citation data can substitute and complement research and development expenses in the extended cross-sectional earnings forecast models. Overall, my findings are consistent with a transformation towards an intangible “knowledge economy” (Haskel and Westlake, 2017), which also affects the set of useful predictors in cross-sectional earnings forecast models