This study evaluates how economic policy uncertainty (EPU) affects firm shareholder wealth. It further investigates the moderating roles of marketing, operations, and R&D capabilities in this relationship. Analysis of longitudinal data, collected from a large sample of firms across multiple industries in the United States, reveals a complex picture. Results show that although EPU lowers firm value (i.e., Tobin’s Q and stock returns), it also reduces firm idiosyncratic risk. In addition, high marketing capability is observed to attenuate the loss in firm value arising from EPU, whereas high operations capability is seen to amplify this loss, with R&D capability not playing a significant moderating role. On the other hand, the reduction in idiosyncratic risk of firms facing EPU is marginally strengthened by operations and R&D capabilities, but not by marketing capability. Together, the conceptual framework and findings provide novel insight into the role of marketing capability in dealing with EPU.
We recognize that stock risk has two components – idiosyncratic risk and systematic risk. We focus on idiosyncratic risk as it accounts for almost 80% of the total stock risk of firms and can be influenced by managerial actions (e.g., Luo & Bhattacharya, 2009). Moreover, we analyzed systematic risk of firms and observed no significant effect of EPU on it (see Web Appendix A; Table WA.1).
Extant research in macroeconomics and finance on other types of macroeconomic and market conditions (e.g., recessions, business cycles, and overall market risk) indicate pathways through which such conditions increase idiosyncratic risk (e.g., Bartram et al., 2017; Chen & Strebulaev, 2019; Herskovic et al., 2016). As such, in our analysis, we control for various macroeconomic and market conditions and account for firm investment levels. Overall, our findings do not support that EPU has an increasing effect on idiosyncratic risk, substantiating the uniqueness of EPU as a different and unique construct. We discuss this further in the theoretical implications.
Other conceptions provide a similar breakdown into those “architectural” capabilities focused on generating and synthesizing market knowledge to create new value offerings for targeted consumers and “specialized” capabilities involving the superior execution of functional marketing mix processes, such as marketing communications, pricing, product development, distribution, etc. (e.g., Arunachalam et al., 2018).
Note that first differencing of the independent variables in the returns model (equations in Web Appendix D), reduces the sample size (N = 28,305), while the original sample remains the same for the other two metrics (i.e., Tobin’s Q and Idiosyncratic Risk) (N = 33,055).
The 21 countries include Australia, Brazil, Canada, Chile, China, Colombia, France, Germany, Greece, India, Ireland, Italy, Japan, Mexico, the Netherlands, Russia, South Korea, Spain, Sweden, the United Kingdom, and the United States.
For abnormal returns, elasticities represent the proportional change in returns from a change in one period changes in EPU/organizational capabilities. We don’t qualify this distinction in the main text for the sake of brevity.
The elasticities are calculating by using the Stata margins procedure, with median values for the variable for which elasticity is calculated (e.g. EPU or capabilities), and defaulting to means for the other variables.