Econ Papers Daily / 期刊论文
有序选择模型在低报情况下的变化中的变化方法
Changes-in-Changes for Ordered Choice Models with Underreporting
摘要
We develop a Difference-in-Differences framework for discrete, ordered outcomes subject to underreporting. Such outcomes commonly arise in self-reported surveys on socially undesirable or stigmatized behaviors, where respondents may conceal their true behavior. For a discrete Changes-in-Changes model that is shown to admit an equivalent threshold-crossing representation, we derive nonparametric bounds for the counterfactual and factual outcome distributions as well as for the associated quantile treatment effects when outcomes are underreported. These bounds are shown to be sharp uniformly across outcome levels under additional support conditions, and we propose suitable estimation and bootstrap inference procedures. In an extension, we also consider a semiparametric underreporting model that allows to point identify and estimate distributional treatment effects. As an application, we investigate the impact of recreational marijuana legalization on the consumption behavior of 8th-grade students in several U.S. states.
中文摘要
我们构建了一个针对离散、有序且受低报影响结果的差分中的差分框架。此类结果常见于关于社会不期望或污名化行为的自报调查中，受访者可能隐瞒其真实行为。对于一个离散的变化中的变化模型，我们证明其可等价地表示为阈值跨越形式，并在结果存在低报时，推导出反事实与实际结果分布以及相关分位数处理效应的非参数界。在附加支撑条件下，这些界被证明在所有结果水平上一致地是紧的，我们提出了合适的估计与自助推断程序。在一项扩展中，我们还考虑了一个半参数低报模型，该模型允许点识别并估计分布处理效应。作为一个应用，我们考察了娱乐性大麻合法化对美国若干州八年级学生消费行为的影响。