A Model of Stock-Market-Based Rulemaking

Yoon-Ho Alex Lee
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引用次数: 2

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.
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基于股市的规则制定模型
我们考虑政府监管机构在多大程度上可以通过观察受影响公司的股价变动来利用有关拟议规则的信息——监管机构可能反过来使用这些信息来考虑是否采用该规则。该规则带有一个未知的事前(预期)值,可以是正的,也可以是负的。我们发现,如果规则的先验值为正,且监管者完全依赖市场的总体反应来指导其决策,那么当市场上有许多公司时,价格将表现出最大的信息性。然而,当事前价值为负时,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。然而,如果监管者只是部分依赖,后一种影响是可以减轻的。我们还考虑了利益相关者的存在,他们可能有动机操纵市场,引导监管机构走向对私人有利的结果。我们发现,当市场上有许多公司时,这些利益相关者的操纵动机将消散。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,以股票为基础的规则制定机制的潜在好处。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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