Resumen de Toward an input-based perspective on categorization: : Investor reactions to chemical accidents
Luis Diestre, Nandini Rajagopalan
We build on the literature on categorization to develop and test a model of input-level spillover effects. Our model predicts that, when one firm suffers an accident with a particular input, investors will punish other users of that input by discounting their stocks, and that the magnitude of this negative spillover can be predicted by the nonresponsible firm’s level of input usage. We also hypothesize that the magnitude of the punishment will be moderated by intermediaries’ assessments of the input: Ex ante regulatory sanctions on the input will amplify negative spillovers, while the presence of input-level associations will weaken these effects. Finally, we predict that similarity between the responsible and nonresponsible firm in terms of two peripheral attributes— input portfolio and geographic location—will amplify the negative effect of input usage. We find strong support for our predictions in an event study that examines the stock market valuations of 270 nonresponsible manufacturing firms triggered by 78 industrial accidents involving a toxic chemical. We highlight our study’s theoretical and empirical contributions to the categorization and spillover literatures
