This paper studies the ex-ante prediction and ex-post evaluation of the effects of cooling-off policies when consumers may exhibit a projection bias. We set up a theoretical model in which a firm optimally reacts to consumers' preferences and the regulatory framework and show that neither the adoption of a mandatory cooling-off period nor a return policy is generically superior or consumer welfare improving. We then analyze how market-level data can help to evaluate the policies ex post using baseline statistics. This exploits the firm's optimal response to a policy. With a return policy, data on quantities, return frequencies, and market size are sufficient to always assess the directional change in consumer welfare, while aggregate quantities alone are sufficient with a mandatory cooling off period. We discuss robustness of the model predictions and ex-post assessment to a variety of modifications, and discuss the benefits of the approach for policy design.

本文研究了当消费者可能表现出预测偏差时冷却政策效果的事前预测和事后评估。我们建立了一个理论模型，在该模型中，公司对消费者的偏好和监管框架做出最佳反应，并表明采用强制性冷静期或退货政策通常都没有优势，消费者福利也没有改善。然后，我们分析了市场层面的数据如何使用基线统计数据帮助事后评估政策。这利用了公司对政策的最佳反应。对于退货政策，数量、退货频率和市场规模的数据足以始终评估消费者福利的方向变化，而在强制冷静期的情况下，仅凭总量就足够了。