Generic Inference on Quantile and Quantile Effect Functions for Discrete Outcomes
离散结果的分位数与分位数效应函数通用推断AI 解读 ↓
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离散结果的分位数与分位数效应函数通用推断
- 研究问题
- 对于离散或可能离散的结果变量，如何构造分位数与分位数效应函数的同时置信带，以支持描述性和因果分布分析？
- 方法与思路
- 作者将分布函数的同时置信带变换为分位数及其差异的置信带，允许结合不同建模方法处理观测与反事实分布。
- 材料陈述的贡献
- 摘要称，该构造适用于多类模型和抽样方案，并用于保险覆盖的医疗利用分布效应及种族测试成绩差距的分布分解。
- 阅读关注点
- 应核对分布置信带变换、离散点与分位数差异的处理，以及反事实分布的识别条件如何影响两项应用的解释。
- 阅读边界
- 所据为 arXiv 预印本，不能据此认定已同行评审或期刊接收；通用变换仍依赖有效的输入置信带，摘要未说明应用识别细节。
原文摘要
Quantile and quantile effect functions are important tools for descriptive and causal analyses due to their natural and intuitive interpretation. Existing inference methods for these functions do not apply to discrete random variables. This paper offers a simple, practical construction of simultaneous confidence bands for quantile and quantile effect functions of possibly discrete random variables. It is based on a natural transformation of simultaneous confidence bands for distribution functions, which are readily available for many problems. The construction is generic and does not depend on the nature of the underlying problem. It works in conjunction with parametric, semiparametric, and nonparametric modeling methods for observed and counterfactual distributions, and does not depend on the sampling scheme. We apply our method to characterize the distributional impact of insurance coverage on health care utilization and obtain the distributional decomposition of the racial test score gap. We find that universal insurance coverage increases the number of doctor visits across the entire distribution, and that the racial test score gap is small at early ages but grows with age due to socio economic factors affecting child development especially at the top of the distribution. These are new, interesting empirical findings that complement previous analyses that focused on mean effects only. In both applications, the outcomes of interest are discrete rendering existing inference methods invalid for obtaining uniform confidence bands for observed and counterfactual quantile functions and for their difference -- the quantile effects functions.