A Model of Stock-Market-Based Rulemaking
39 Pages Posted: 6 Sep 2019 Last revised: 18 Dec 2020
Date Written: December 17, 2020
We consider the extent to which a government regulator can harness information about its 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 as the number of firms approaches infinity, prices will exhibit maximal informativeness. When the ex ante value is negative, however, the regulator’s reliance on the market will dampen speculators’ incentive 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, as the number of firms approaches infinity, such stakeholders’ incentives to manipulate will dissipate. The theoretical findings of this paper suggest potential benefits of a stock-market-based rulemaking mechanism in the absence of other forms of reliable empirical evidence.
Keywords: stock market, price informativeness, Securities and Exchange Commission, agency rulemaking, feedback effects, real effects, financial markets, manipulation
JEL Classification: G18, G38, K23, K22
Suggested Citation: Suggested Citation