Abstract

Consideration set models generalize discrete-choice models by relaxing the assumption that consumers consider all available options. Determining which options were considered has previously required either survey data or restrictions on how attributes affect consideration or utility. We provide an alternative route. In full-consideration models, choice probabilities satisfy a symmetry property analogous to Slutsky symmetry in continuous-choice models. This symmetry breaks down in consideration set models when changes in characteristics perturb consideration. We show that consideration probabilities are constructively identified from the resulting asymmetries. We validate our approach in a lab experiment where consideration sets are known and then apply our framework to study a “smart default” policy in Medicare Part D, wherein consumers are automatically reassigned to lower-cost prescription drug plans with the option of opting out. Full-consideration models imply that such a policy will be ineffective because consumers will opt out to avoid switching costs. Allowing for inattention, we find that defaulting all consumers to lower-cost options produces negligible welfare benefits on average, but defaulting only consumers who would save at least $300 produces large benefits.

中文翻译：

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消费者在选择之前会考虑什么？从非对称需求响应中识别*

摘要

考虑集模型通过放宽消费者考虑所有可用选项的假设来概括离散选择模型。确定考虑哪些选项之前需要调查数据或限制属性如何影响考虑或效用。我们提供替代路线。在全考虑模型中，选择概率满足类似于连续选择模型中的 Slutsky 对称性的对称特性。当特征的变化扰乱考虑时，这种对称性在考虑集模型中失效。我们表明，考虑概率是从由此产生的不对称性中建设性地确定的。我们在实验室实验中验证了我们的方法，其中考虑集是已知的，然后应用我们的框架来研究医疗保险 D 部分中的“智能默认”政策，其中消费者可以自动重新分配到低成本的处方药计划，并可以选择退出。全面考虑模型意味着这样的政策将是无效的，因为消费者会选择退出以避免转换成本。考虑到疏忽，我们发现将所有消费者默认为较低成本的选择所产生的平均福利收益可忽略不计，但仅将至少会节省 300 美元的消费者默认会产生很大的收益。