居民收入的分位数回归与反事实因素分解
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摘要
本文基于CHNS调查数据,首先以城镇人均住户收入为例,对我国居民收入的分布形态、分位数的变化与收入差距进行了简单描述,认为我国居民收入分布存在明显的右偏“厚尾”现象,传统的关于收入正态分布假定或对数正态分布假定的方法受到质疑,而非参数核密度估计则被认为是一个比较适合的研究方法。实证研究表明,最近20年在不同的收入分位点呈现“分位点越高,增长趋势越快”的态势,反映出我国收入分配领域已经存在“穷者愈穷,富者愈富”的“马太效应”,居民收入差距在不断扩大。
进一步,本文将非参数、半参数理论与分位数回归分析技术结合起来,应用到我国居民个人收入分布的研究中,顺次构建了均值线性回归模型、线性分位数回归模型、非参数分位数回归模型与半参数分位数回归模型,对比研究了适合我国居民收入分布数据的最佳模型,最终论证了性别、教育、城乡户籍对收入的参数影响和年龄、地区经济对收入的非参数影响,同时讨论了同一影响因素在收入不同分位点处影响作用及显著性呈现巨大差异的原因,全方位展示了性别、年龄、教育、地区经济和城乡户籍等因素对收入的影响结构及变化规律。
本文最后在实证分析的另一方面,将反事实分析方法与传统的指数理论结合起来,分别在时间与截面两个维度上,运用分位数回归模型对居民收入的变化进行了因素分解研究,将居民收入的时间变化、性别差异与城乡差异分解为要素报酬效应、变量效应与残差效应,既分析了绝对收入效应的影响,又反映了各效应引起的相对收入变化,使居民收入在时间与截面两个维度的变化得到了较为透彻的分解,并得出了合理的分析结论。尤其是针对性别与城乡两个截面维度对收入进行分解时,成功地将代表女性因性别带来收入劣势和农民因户籍带来收入劣势的要素报酬效应从收入的性别差距与城乡差距中剥离出来,并分析了各种效应在不同的收入分位点对居民收入影响作用的差异。
本文对我国居民收入差距的深度研究与收入分配政策导向具有一定的借鉴意义,同时对税收、社会保障以及各种民生制度的完善也能够提供一定的参考。
In this paper, based on the CHNS survey data, we describe the urban household per capita income distribution in China, and find that the income obeys a right-tailed distribution. It is difficult to choose a good parametric method to fit the distribution. Naturally, nonparametric kernel density estimation is a more appropriate one. Meanwhile, we give a description about the income quantile changes and income gap in brief, and consider that the gap is expanding ceaselessly due to the Matthew effect.
Then, we combine the nonparametric and semi-parametric theory and quantile regression analysis to study on the individual income distribution, construct the least-square linear regression, the linear quantile regression, the nonparametric quantile regression, and the semi-parametric quantile regression one by one, disscuss the best model to fit the data in this paper, and conclude that the gender, education and the urban-rural household registration have a parametric influence on the income, while the age and the region economy give a nonparametric one. In terms of every single factor, the effects on the different income quantiles show a large divergence. The semi-parametric quantile regression analysis provides an all-round display of the income structure and its change rules caused by the factors mentioned above.
Finally, in the empirical analysis based on the quantile regression, we employ the counterfactual analysis method with the traditional index theory together, to decompose the gap of the income distribution into several factors, not only on the time dimension, but on the cross-sectional one. We separate three effects from the income change, which are aroused by the coefficients, the covariates, and the residuals respectively. We get a relatively thorough decomposition of the income change and draw a rational conclusion. Especially, the decomposition conclusions on the two cross-sectional dimensions deserve to be mentioned. We successfully separate the gender discrimination and the rural discrimination from the income gender difference and urban-rural difference respectively, and take deep account about the different effects on the different income quantiles.
These conclusions have certain significance in deep study on the income gap and the income allocation policy in China. Meanwhile, they also can provide certain reference to make decisions about the tax, social security and the people's livelihood system.
进一步,本文将非参数、半参数理论与分位数回归分析技术结合起来,应用到我国居民个人收入分布的研究中,顺次构建了均值线性回归模型、线性分位数回归模型、非参数分位数回归模型与半参数分位数回归模型,对比研究了适合我国居民收入分布数据的最佳模型,最终论证了性别、教育、城乡户籍对收入的参数影响和年龄、地区经济对收入的非参数影响,同时讨论了同一影响因素在收入不同分位点处影响作用及显著性呈现巨大差异的原因,全方位展示了性别、年龄、教育、地区经济和城乡户籍等因素对收入的影响结构及变化规律。
本文最后在实证分析的另一方面,将反事实分析方法与传统的指数理论结合起来,分别在时间与截面两个维度上,运用分位数回归模型对居民收入的变化进行了因素分解研究,将居民收入的时间变化、性别差异与城乡差异分解为要素报酬效应、变量效应与残差效应,既分析了绝对收入效应的影响,又反映了各效应引起的相对收入变化,使居民收入在时间与截面两个维度的变化得到了较为透彻的分解,并得出了合理的分析结论。尤其是针对性别与城乡两个截面维度对收入进行分解时,成功地将代表女性因性别带来收入劣势和农民因户籍带来收入劣势的要素报酬效应从收入的性别差距与城乡差距中剥离出来,并分析了各种效应在不同的收入分位点对居民收入影响作用的差异。
本文对我国居民收入差距的深度研究与收入分配政策导向具有一定的借鉴意义,同时对税收、社会保障以及各种民生制度的完善也能够提供一定的参考。
In this paper, based on the CHNS survey data, we describe the urban household per capita income distribution in China, and find that the income obeys a right-tailed distribution. It is difficult to choose a good parametric method to fit the distribution. Naturally, nonparametric kernel density estimation is a more appropriate one. Meanwhile, we give a description about the income quantile changes and income gap in brief, and consider that the gap is expanding ceaselessly due to the Matthew effect.
Then, we combine the nonparametric and semi-parametric theory and quantile regression analysis to study on the individual income distribution, construct the least-square linear regression, the linear quantile regression, the nonparametric quantile regression, and the semi-parametric quantile regression one by one, disscuss the best model to fit the data in this paper, and conclude that the gender, education and the urban-rural household registration have a parametric influence on the income, while the age and the region economy give a nonparametric one. In terms of every single factor, the effects on the different income quantiles show a large divergence. The semi-parametric quantile regression analysis provides an all-round display of the income structure and its change rules caused by the factors mentioned above.
Finally, in the empirical analysis based on the quantile regression, we employ the counterfactual analysis method with the traditional index theory together, to decompose the gap of the income distribution into several factors, not only on the time dimension, but on the cross-sectional one. We separate three effects from the income change, which are aroused by the coefficients, the covariates, and the residuals respectively. We get a relatively thorough decomposition of the income change and draw a rational conclusion. Especially, the decomposition conclusions on the two cross-sectional dimensions deserve to be mentioned. We successfully separate the gender discrimination and the rural discrimination from the income gender difference and urban-rural difference respectively, and take deep account about the different effects on the different income quantiles.
These conclusions have certain significance in deep study on the income gap and the income allocation policy in China. Meanwhile, they also can provide certain reference to make decisions about the tax, social security and the people's livelihood system.
引文
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