Identifying changes in the distribution of income from higher-order moments with an application to Australia

Pub Date : 2024-01-17 DOI:10.1111/anzs.12405
Vance L. Martin, Jialu Shi, Yang Song, Wenying Yao
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Abstract

Changes in the distribution of income over time are identified based on an adjusted two-sample version of the Neyman smooth test by using subsampling methods to approximate the sampling distribution of the test statistic when samples are not independent of each other. A range of Monte Carlo experiments show that the approach corrects for size distortions arising from dependent samples as well as generating monotonic power functions. Applying the approach to studying the distribution of income in Australia over the business cycle and the Global Financial Crisis, the empirical results highlight the importance of higher-order moments and demonstrate that business cycles are not all alike as the relative strengths of higher-order moments vary over phases of the cycle.

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从高阶矩确定收入分配的变化并应用于澳大利亚
在样本互不独立的情况下,使用子抽样方法近似检验统计量的抽样分布,根据调整后的奈曼平滑检验的双样本版本,确定收入分布随时间的变化。一系列蒙特卡罗实验表明,该方法可以纠正因依赖样本而产生的大小失真,并生成单调的幂函数。应用该方法研究澳大利亚在商业周期和全球金融危机期间的收入分配情况,实证结果突出了高阶矩的重要性,并表明商业周期并不都是一样的,因为高阶矩的相对强度随周期的不同阶段而变化。
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