中文摘要
我们研究选择集规模变化对健康保险市场中选择质量的影响。利用俄勒冈州学区雇员参保情况和医疗理赔的新数据，我们发现，普通雇员通过转投成本更低的保险计划平均可节省600美元。结构模型揭示出巨大的“选择不一致”，例如未能使花费在保费与自付费用上的每一美元实现均等化；还揭示出一种新的“近似惯性”形式：参保人转投其他保险计划的可能性过高，而这些计划在保险计划设计表上与当前计划相近。利用各学区之间以及不同时间保险计划选择数量的差异，我们发现，当选择集较小时，参保人会作出成本更低的选择。我们表明，经过精心筛选而缩小选择集，比现有最佳信息干预更能改善选择，部分原因是近似惯性降低了新信息带来的收益。我们明确检验并拒绝了这样一种假设，即这一结果是因为个人在更大的选择集中作出更差的选择，也就是“选择过载”。相反，我们表明，这一特征源于更大的选择集平均而言包含更差的选项，而这种劣势并未被个人的重新优化所抵消。
Abstract
Abstract We study the impact of changing choice set size on the quality of choices in health insurance markets. Using novel data on enrolment and medical claims for school district employees in the state of Oregon, we document that the average employee could save $600 by switching to a lower cost plan. Structural modelling reveals large “choice inconsistencies” such as non-equalization of the dollar spent on premiums and out of pocket, and a novel form of “approximate inertia” where enrolees are excessively likely to switch to other plans that are close to the current plan on the plan design spreadsheet. Variation in the number of plan choices across districts and over time shows that enrolees make lower-cost choices when the choice set is smaller. We show that a curated restriction of choice set size improves choices more than the best available information intervention, partly because approximate inertia lowers gains from new information. We explicitly test and reject the assumption that this is because individuals choose worse from larger choice sets, or “choice overload”. Rather, we show that this feature arises from the fact that larger choice sets feature worse choices on average that are not offset by individual re-optimization.