摘要翻译：
分位数和分位数效应函数因其自然直观的解释而成为描述性分析和因果分析的重要工具。这些函数的现有推理方法不适用于离散随机变量。本文给出了可能离散随机变量分位数和分位数效应函数同时置信带的一个简单实用的构造。它是基于分布函数同时置信带的自然变换，这对于许多问题都是很容易得到的。该结构是通用的，不依赖于潜在问题的性质。它与观测分布和反事实分布的参数、半参数和非参数建模方法相结合，不依赖于抽样方案。我们应用我们的方法来刻画保险复盖率对卫生保健利用的分布影响，并得到种族测试分数差距的分布分解。我们发现，全民保险覆盖增加了整个分布的医生就诊次数，种族测试分数差距在早期很小，但随着年龄的增长，由于影响儿童发展的社会经济因素，尤其是在分布的顶端。这些是新的、有趣的经验发现，补充了以前只关注均值效应的分析。在这两种应用中，感兴趣的结果都是离散的，使得现有的推理方法不能为观察到的分位数函数和反事实分位数函数以及它们的差异--分位数效应函数--获得一致的置信带。
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英文标题：
《Generic Inference on Quantile and Quantile Effect Functions for Discrete
  Outcomes》
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作者：
Victor Chernozhukov, Iv\'an Fern\'andez-Val, Blaise Melly, and Kaspar
  W\"uthrich
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最新提交年份：
2018
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分类信息：

一级分类：Statistics        统计学
二级分类：Methodology        方法论
分类描述：Design, Surveys, Model Selection, Multiple Testing, Multivariate Methods, Signal and Image Processing, Time Series, Smoothing, Spatial Statistics, Survival Analysis, Nonparametric and Semiparametric Methods
设计，调查，模型选择，多重检验，多元方法，信号和图像处理，时间序列，平滑，空间统计，生存分析，非参数和半参数方法
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一级分类：Economics        经济学
二级分类：Econometrics        计量经济学
分类描述：Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
计量经济学理论，微观计量经济学，宏观计量经济学，通过新方法发现的经济关系的实证内容，统计推论应用于经济数据的方法论方面。
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英文摘要：
  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.
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PDF链接：
https://arxiv.org/pdf/1608.05142