A Unified Approach to Estimating and Testing Income Distributions With Grouped Data
提出一种灵活适用于多种分组数据的参数收入分布估计与检验的统一方法，提供参数自助法并证明其渐近有效性，通过蒙特卡洛模拟评估性能，并应用于中国和美国收入分布恢复。
We propose a unified approach that is flexibly applicable to various types of grouped data for estimating and testing parametric income distributions. To simplify the use of our approach, we also provide a parametric bootstrap method and show its asymptotic validity. We also compare this approach with existing methods for grouped income data, and assess their finite-sample performance by a Monte Carlo simulation. For empirical demonstrations, we apply our approach to recovering China's income/consumption distributions from a sequence of income/consumption share tables and the U.S. income distributions from a combination of income shares and sample quantiles. Supplementary materials for this article are available online.