标题： 通过估计条件分位数函数来估计条件不平等曲线和度量 显示英文标题

标题： Estimation of conditional inequality curves and measures via estimating the conditional quantile function

摘要： 经典的不平等曲线和度量概念被扩展到条件不平等曲线和度量，并引入了条件不平等度量曲线。这种扩展提供了对与协变量相关的不平等更细致的分析。特别是，这使得能够在协变量的某些值条件下比较不同子总体之间的不平等。为了估计这些曲线和度量，提出了一种新的估计条件分位数函数的方法。该方法结合了一个修改的分位数回归框架，采用等距回归以确保没有分位数交叉。证明了所提出估计量的一致性，通过模拟研究评估了它们的小样本性能，并与现有的分位数回归方法进行了比较。最后，通过分析不同员工年龄组之间的工资不平等，展示了条件不平等度量在实证研究中的潜力。本文中呈现结果所使用的代码可在专用的GitHub仓库中获得。 显示英文摘要

摘要： The classical concept of inequality curves and measures is extended to conditional inequality curves and measures and a curve of conditional inequality measures is introduced. This extension provides a more nuanced analysis of inequality in relation to covariates. In particular, this enables comparison of inequalities between subpopulations, conditioned on certain values of covariates. To estimate the curves and measures, a novel method for estimating the conditional quantile function is proposed. The method incorporates a modified quantile regression framework that employs isotonic regression to ensure that there is no quantile crossing. The consistency of the proposed estimators is proved while their finite sample performance is evaluated through simulation studies and compared with existing quantile regression approaches. Finally, practical application is demonstrated by analysing salary inequality across different employee age groups, highlighting the potential of conditional inequality measures in empirical research. The code used to prepare the results presented in this article is available in a dedicated GitHub repository.