非参数选择模型中的福利效应估计：以教育券为例
Estimating Welfare Effects in a Nonparametric Choice Model: The Case of School Vouchers
AI总结：
本文开发了非参数选择模型下的稳健离散选择工具，用于估计价格补贴的福利效应，并应用于教育券项目，发现现行及反事实教育券多有正向净收益，低学费学校是关键因素，标准logit模型会低估收益规模。
摘要：
我们开发了新的稳健离散选择工具，用于研究在价格存在外生离散变化的情况下，消费者对价格补贴的平均支付意愿及其对需求的影响。我们的研究起点是一个非参数、不可分的选择模型。我们利用了这样一个洞见：该模型中的福利参数可以表示为不同备选方案需求的函数。然而，尽管数据中的变化揭示了观测价格下的需求值，但这些参数通常还取决于这些价格之外的需求值。我们展示了如何清晰地刻画当需求被设定为完全非参数形式或灵活参数化形式时我们所能了解的信息，这两种情况都意味着参数不一定能得到点识别。我们使用这些工具分析了DC Opportunity Scholarship Program（DC机会奖学金计划）中教育券提供的价格补贴的福利效应。我们发现，现行教育券以及各种不同金额的反事实教育券都能产生正向且可能很大的净成本收益。这种正向效应可以用该计划中低学费学校的受欢迎程度来解释；将这些学校从计划中移除可能导致净收益为负。我们还发现，相比之下，各种标准logit设定仅关注对教育券需求较低的需求函数，无法捕捉到与数据可信一致的大幅收益。
英文摘要：
We develop new robust discrete choice tools to learn about the average willingness to pay for a price subsidy and its effects on demand given exogenous, discrete variation in prices. Our starting point is a nonparametric, nonseparable model of choice. We exploit the insight that our welfare parameters in this model can be expressed as functions of demand for the different alternatives. However, while the variation in the data reveals the value of demand at the observed prices, the parameters generally depend on its values beyond these prices. We show how to sharply characterize what we can learn when demand is specified to be entirely nonparametric or to be parameterized in a flexible manner, both of which imply that the parameters are not necessarily point identified. We use our tools to analyze the welfare effects of price subsidies provided by school vouchers in the DC Opportunity Scholarship Program. We find that the provision of the status quo voucher and a wide range of counterfactual vouchers of different amounts can have positive and potentially large benefits net of costs. The positive effect can be explained by the popularity of low-tuition schools in the program; removing them from the program can result in a negative net benefit. We also find that various standard logit specifications, in comparison, limit attention to demand functions with low demand for the voucher, which do not capture the large magnitudes of benefits credibly consistent with the data.
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