Abstract Since the finance industry is transforming into a data industry, measuring the quantity of data investors have about various assets is important. Informed by a structural model, we develop such a cross-sectional measure. We show how our measure differs from price informativeness and use it to document a new fact: data about large high-growth firms is becoming increasingly abundant, relative to data about other firms. Our structural model offers an explanation for this data divergence: large high-growth firms’ data became more valuable, as big firms got bigger and growth magnified the effect of these changes in size.

Firms significantly reduce their investment in response to nonfundamental drops in the stock price of their product-market peers. We argue that this results stems from managers’ limited ability to filter out the noise in the stock prices when using them as signals about their investment opportunities. Ensuing losses of capital investment and shareholders’ wealth are economically large and even affect firms not facing severe financing constraints or agency problems. Our findings offer a novel perspective on how stock market inefficiencies can affect the real economy, even in the absence of financing or agency frictions.Received December 14, 2016; editorial decision July 30, 2018 by Editor Itay Goldstein. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.