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基于混合动态模型的居民收入分布的演变研究

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自改革开放后随着时间的推移,居民收入分布的位置及形状随之呈现多元化发展趋势,收入分布格局经历了深刻曲折的变迁过程.对收入分布的收敛情况和演变历程的研究多数基于静态的分析视角,或用非参数核密度探究某时间段内分布形式的动态趋势.本文选用1989-2015年CHNS中居民收入数据从动态视角拟合混合收入分布及其演变趋势,认识到收入分布不断右移且离散程度在持续恶化及其客观存在的事实性,目的是探究两分量混合分布函数随着时间变化的动态演变路径及估算衡量收入差距的基尼系数,研究发现收入分布呈现两阶段的发展趋势,即1989-2006年,2009-2015年.结果表明,随着时间的推移,居民收入水平和收入差距呈逐年递增且存在显著地阶段性发展态势,从动态视角更详细的反映出收入分布的演变过程.
Research on the Evolution of Residents' Income Distribution Based on Hybrid Dynamic Model
With the passage of time since the reform and opening up,the position and shape of the income distribution of residents has shown a diversified development trend,and the income distribution pattern has undergone a profoundly tortuous process of change.Most studies on the convergence and evolution of income distribution are based on static analysis perspectives,or use non-parametric kernel density to explore the dynamic trend of the distribution form over a period of time.This paper uses the income data of residents in CHNS from 1989 to 2015 to fit the mixed income distribution and its evolution trend from a dynamic perspective.It is recognized that the income distribution continues to shift to the right and the degree of dispersion continues to deteriorate and the factual existence of the objective,the research purpose is to explore the two-component mixed distribution function with time change of the dynamic evolution path and estimate to measure the Gini coefficient of income gap,the study found that the income distribution showed a two-stage development trend,that is,1989-2006 and 2009-2015.The results show that with the passage of time,the income level and income gap of residents are increasing year by year and there is a significant period of development,which reflects the evolution of income distribution in more detail from a dynamic perspective.

hybrid dynamic modelincome distributionevolution processGini coefficient

周雪娇、张宝学、李群

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山东财经大学统计与数学学院,山东济南 250014

首都经济贸易大学统计学院,北京 100070

混合动态模型 收入分布 演变过程 基尼系数

国家自然科学基金面上项目山东省人文社会科学课题

122713702021-YYGL-12

2024

数理统计与管理
中国现场统计研究会

数理统计与管理

CSTPCDCSSCICHSSCD北大核心
影响因子:1.114
ISSN:1002-1566
年,卷(期):2024.43(4)
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