Trade Secrets, Proprietary Information, and Managerial Learning


I study changes in managerial learning from stock prices after an increase in the protection of trade secrets allows managers to withhold proprietary information and substitute it with increased disclosure of nonproprietary information. Using the staggered U.S. state-level adoption of the Uniform Trade Secrets Act, I show that this trade-off leads to a decline in the sensitivity of firm investment to Tobin's Q. Consistent with the managerial learning hypothesis, further analysis shows that this decline is concentrated in firms with low financing constraints and more sophisticated investors. Using theoretical motivation from literature and machine learning techniques, I identify industries with a positive “treatment” effect, but a different relative value of proprietary and nonproprietary information to provide novel evidence that the type of disclosure plays an additional role beyond its level. Disclosure of information that acts as a substitute (complement) to the information aggregation activities leads to reduced (increased) managerial learning.

Additional Information

Draft available upon request.

Hassan Ilyas
Hassan Ilyas
PhD Student at Cornell University