A Unified Approach to Estimating and Testing Income Distributions With Grouped Data

Yi-Ting Chen

Journal of Business & Economic Statistics, 2018, vol. 36, issue 3, 438-455

Abstract: 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.

Date: 2018
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DOI: 10.1080/07350015.2016.1194762

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