We consider the extent to which a government regulator can harness information about a proposed rule from observing the stock price movements of the affected firms – information the regulator may in turn use to deliberate whether to adopt the rule. The rule comes with an uninformed ex ante (expected) value, which can be positive or negative. We find that if the rule’s ex ante value is positive and the regulator fully relies on the aggregate market reaction to guide its decision, then with many firms in the market, prices will exhibit maximal informativeness. When the ex ante value is negative, however, the regulator’s reliance on the market will dampen speculators’ incentives to gather information, and prices will become completely uninformative. This latter effect, however, can be mitigated if the regulator’s reliance is only partial. We also consider the presence of stakeholders who may be motivated to manipulate the market to steer the regulator toward privately beneficial outcomes. We find that with many firms in the market, such stakeholders’ incentives to manipulate will dissipate. The theoretical findings of this article suggest the potential benefits of a stock-market-based rulemaking mechanism in the absence of other forms of reliable empirical evidence.
Yoon-Ho Alex Lee, A Model of Stock-Market-Based Rulemaking, American Law and Economics Review, https://doi.org/10.1093/aler/ahaa011. Published: 12 May 2021.