Published online by Cambridge University Press: 20 February 2023
This article proposes a new method for examining the impact on a firm’s investment of uncertainty reflected in its stock-return volatility. We simultaneously address the endogeneity of uncertainty and mismeasurement in Tobin’s Q, but earlier empirical work often neglects one of the two issues. Our nonparametric estimates further suggest that the relation between investment and uncertainty is significantly decreasing and strongly concave. This result contrasts with the existing literature that widely adopts linear regressions. Ignoring nonlinearity or measurement error in Q can lead to a substantial estimation bias. However, the bias due to the endogeneity of uncertainty is small.
We appreciate comments from seminar participants at the Econometric Society Asian meeting, China meeting, and North American summer meeting in 2019, Northern Finance Association 2019 conference (especially our discussant, Georgios Skoulakis), Bank of Finland, Shanghai University of Finance and Economics, and Wilfrid Laurier University. We give special thanks to Paul Malatesta (the editor) and Iulian Obreja (the referee) for detailed comments and helpful suggestions, and to the Social Sciences and Humanities Research Council of Canada (grant ID 430-2022-00119) for financial supports. In addition, Li coauthored this article before joining Cornerstone Research. The views expressed herein are solely those of the authors who are responsible for the content, and do not necessarily represent the views of Cornerstone Research.