Abstract

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.

中文翻译：

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基于股票市场的规则制定模型

摘要

我们考虑了政府监管机构可以通过观察受影响公司的股票价格变动来利用有关拟议规则的信息的程度——监管机构可以反过来使用这些信息来考虑是否采用该规则。该规则带有一个不知情的事前（预期）值，可以是正值也可以是负值。我们发现，如果规则的事前价值是正的，并且监管者完全依赖总体市场反应来指导其决策，那么市场中有许多公司，价格将表现出最大的信息量。当事前价值为负，然而，监管机构对市场的依赖将抑制投机者收集信息的动机，价格将变得完全没有信息。但是，如果监管机构只是部分依赖，则可以减轻后一种影响。我们还考虑了可能有动机操纵市场以引导监管机构实现私人利益的利益相关者的存在。我们发现，随着市场上有许多公司，这些利益相关者操纵的动机将会消散。本文的理论发现表明，在缺乏其他形式的可靠经验证据的情况下，基于股票市场的规则制定机制的潜在好处。