一个新的基尼系数子群分解公式——兼论中国总体基尼系数的城乡分解

基尼系数的子群分解公式有多种形式,不同分解公式的实证结论有较大差异。本文分析了群内基尼系数的权数以及群间不平等指标所应具备的基尼系数内涵,提出了一个新的群间不平等指标,从而给出了一个新的基尼系数子群分解公式。利用这个新的基尼系数子群分解公式,本文实证分析了近年来中国总体基尼系数的城乡分解。实证结果表明,农村群间不平等对总体基尼系数的贡献率最大,城镇群内不平等的贡献率不断上升,这是促使中国总体基尼系数不断上升的两个重要因素。     

基尼系数组群分解新方法研究:从城乡二亚组到多亚组

本文尝试在程永宏(2006)的基尼系数城乡分解方法基础上,论证一种适合多亚组的基尼系数组群分解新方法。主要内容是:第一,分析了现有分解方法不完善的原因;第二,推导出不含交叠项的多亚组情形下的分解方法,摆脱了交叠项的困扰;第三,提出一个组间不平等新指标并论证其理论依据;第四,明确解释了分解式和组间不平等新指标的社会福利含义。     

教育基尼系数的计算及其分解

除了入力资本水平外，人力资本分布均等程度也是影响经济增长的重要因素。对于从事人力资本分布均等程度与经济增长等相关问题研究的学者来说，科学合理地测量人力资本分布不均等程度至关重要，教育基尼系数是一个稳定的、有效的测度人力资本（教育）分布的指标。计算教育基尼系数的方法也有两种，即直接方法和间接方法；教育基尼系数还可以进行分解，对其进行分解是发现总的教育不均等的来源，即群间贡献和群内贡献的关键。     

简论对不同人群的收入差距分解分析

对不同人群的收入差距分解分析一直存在争议。本文提出了一个更简洁的基尼系数分解公式,并在此基础上对群体间基尼系数的应用和群体内基尼系数的进一步分解问题进行了讨论。文章说明,由于交叉项的存在,基尼系数只能对不同收入群体进行有限的分解,对群体内基尼系数的进一步分解是极为勉强的。只有当各群体收入重叠程度较低时,方可对交叉项进行忽略,此时对群体内基尼系数的进一步分解才具有较清晰的经济含义。     

二元经济中城乡混合基尼系数的计算与分解

关于基尼系数计算方法的文献已经十分丰富,但专门计算城乡混合基尼系数的理论方法,却一直没有得到很好的解决,这导致全国收入分配长期变化方面的某些研究难以深入。本文建立了城乡混合基尼系数的新算法,并给出新的分解形式,同时还提出并论证了度量城乡差距的新指标。该分解形式具有明确的经济含义和理论意义,并且不依赖于“城乡收入分布不重叠”的假定。利用这一分解形式的经济含义,我们分析了几个重要理论问题。最后,应用新算法计算并分解了中国个别年份的城乡混合基尼系数,以检验新算法的有效性。     

中国省际碳排放公平性的测度与分解

本文基于中国1995-2011年碳排放的经验数据,运用基尼系数子群分解方法对中国省际碳排放公平性进行了测度与分解。研究结果表明,我国总体碳排放基尼系数为0.2933,这说明我国各省碳排放尚处在较为公平的区间范围之内。进一步对我国总体碳排放公平性的子群分解研究表明,我国东、中、西三大子群内部的碳排放非均衡性对总体不公平性的贡献额较大,而各子群间的碳排放非均衡性水平对总体不公平性的贡献程度则相对较低;各子群碳排放水平交叠程度高,但分层程度却较低,这说明在进行碳排放分配权划分过程中,必须摈弃简单按照传统东、中、西部三大区域进行划分的方式,将自然资源富集程度、人口比重大小、产业聚集程度以及产业自东向西转移等因素纳入考察范围之内。     

中国农村地区间居民收入差距及构成变化:1995—2008年——基于基尼系数的分解

本文采用分省的面板数据对农村地区间基尼系数分解结果表明,1995—2008年,中国农村地区间收入差距总体上仍然呈现上升趋势,基尼系数上升了0.0639,但增幅出现明显减弱趋势。基尼系数变化及农村居民工资性收入对基尼系数的贡献变化显示出与经济发展阶段变化一致的含义;结构性效应已不再是农村地区间收入差异的唯一构成来源,收入集中效应对基尼系数起了明显的增加作用,工资性收入的集中效应超过了其他收入来源。这些构成来源的变化蕴含着中国面临调节地区间农村收入差距的政策机遇。     

评厉以宁教授的新基尼系数

中国的基尼系数已经超过了国际上规定的警戒线,这是一个不争的事实。我们不能改变基尼系数的算法来解释中国现阶段城乡二元经济的情况,厉以宁教授发明的新基尼系数算法是先分别算出城市和农村的基尼系数,然后,再用加权平均方法算出中国的基尼系数。由于分类计算降低了总体的方差,这种分类算出的基尼系数比不分类算出的基尼系数要小。实际上,新基尼系数是一个加权平均基尼系数,这是用平均指标代替结构相对指标,使两个性质完全不同的指标混为一谈。得出与直观判断完全相反的结论。     

不平等的度量与分解

本文从实证研究需要的角度,较为完整地叙述了收入分配的度量及其分解,包括常用不平等指数的构建和计算,随机占优分析,以及基尼系数、泰尔指数和基于回归方程的分解。虽然没有对应用性文献进行综述,但简要讨论了研究我国不平等时应该注意的主要问题。     

不平等的度量与分解

本文从实证研究需要的角度,较为完整地叙述了收入分配的度量及其分解,包括常用不平等指数的构建和计算,随机占优分析,以及基尼系数、泰尔指数和基于回归方程的分解。虽然没有对应用性文献进行综述,但简要讨论了研究我国不平等时应该注意的主要问题。     

A matrix approach to the Gini index decomposition by subgroup and by income source

The literature offers two main ways of decomposing the Gini index: decomposition by population subgroup and by income source. This article proposes merging the two decomposition dimensions by suggesting a matrix formula for the Gini index which permits the simultaneous decomposition by subgroup and by income source. Using this multi‐decomposition, one can investigate the role of the interaction between the subgroup and the source components in determining the overall inequality. We apply the methodology to sample data on Italian household incomes collected in 2008.     

Decomposition of the Gini Index by Sources of Income

The Gini concentration coefficient is considered to be the best synthetic inequality measure and is widely used in economic research. In this paper, we present its decomposition by factor components with an application to income distributions in Poland. Income inequality measures proposed by Gini, Zenga and Bonferroni are calculated for different socio-economic groups based on their exclusive or primary source of maintenance. For theoretical income distribution, the Dagum type-I model was used. The basis for the calculations was the individual data coming from the Household Budgets Survey conducted quarterly by the Polish Central Statistical Office. Using the decomposition of inequality by source, we were able to examine how changes in particular income components affected overall inequality.      

影响我国农村居民收入差距的主要因素:从收入构成角度的分解分析

This paper attempts to explore the causes behind the change of the inequality in China rural areas at the very beginning of this century by decomposing the inequality of the total per capita income into the contributions from different income components. Furthermore, we develop the decomposition method of Gini coefficients from the income components and use it not only in the static analysis but also in comparative static analysis. Namely it can be used to explore the change of the overall inequality by decomposing the change of Gini Coefficient from income components. The empirical results show that the wage from local employment, the income from agricultural household business and the incomes from non-agricultural household business are the three income components that made the largest contributions to the inequality of the total per capita income. The total contribution to the overall inequality of non-agricultural incomes was much more than that of agricultural incomes. The incomes from agricultural household business, the incomes from non-agricultural household business and the wages from migration made the positive impact on the increase of the overall inequality. The incomes donated by relatives and friends made the most important negative impact on the increase of the overall inequality.     

Income inequality between overlapping and stratification: a longitudinal analysis of personal earnings in France and Italy

The aim of this paper is to gain new insights into the generation process of personal income in France and Italy, two countries that are in close geographical proximity but have a large disparity in terms of income growth and distribution. In the first step, the potential of EU-SILC balanced panel (2004–2007) is exploited by random effects models, which also make it possible to explore the primary factors that are likely to explain differences in generating personal labour earnings. In the second step, the ANOGI (Analysis of Gini) decomposition enables one to assess the contribution of each sub-population to overall income inequality and the degree to which each subgroup is stratified. A joint evaluation of income determinants gives evidence of the high complexity of inequality process and throws light on the role of gender, skill levels and job characteristics in determining different degrees of income stratification. Indeed, although the high heterogeneity among members of a same subgroup (within-group inequality) explains a large share of overall income inequality, the between-group inequality becomes significant in explaining the income differentials between employment status and occupation types.     

Empirical likelihood confidence intervals for the Gini measure of income inequality

Gini coefficient is among the most popular and widely used measures of income inequality in economic studies, with various extensions and applications in finance and other related areas. This paper studies confidence intervals on the Gini coefficient for simple random samples, using normal approximation, bootstrap percentile, bootstrap-t and the empirical likelihood method. Through both theory and simulation studies it is shown that the intervals based on normal or bootstrap approximation are less satisfactory for samples of small or moderate size than the bootstrap-calibrated empirical likelihood ratio confidence intervals which perform well for all sample sizes. Results for stratified random sampling are also presented.     

Some Ethnic Dimensions of Income Distribution from Pre- to Post-reform New Zealand, 1984–1998*

Based on unit record data from four household surveys conducted by Statistics New Zealand for the years 1983/1984, 1991/1992, 1995/1996 and 1997/1998, this paper addresses some ethnic dimensions of income inequality among New Zealanders over the period of the surveys. It applies alternative techniques of decomposition of the Gini coefficient of inequality by subgroups of population. It then analyses how changes in the incomes of specific population subgroups affect the overall inequality. The results help quantify the economic distances among the different ethnic populations of New Zealand, and indicate how and why these distances have been changing over time.     

A Gini decomposition analysis of inequality in the Czech and Slovak Republics during the transition1

Disposable income inequality, as measured by the Gini coefficient and using the Family Budget Survey data, increased very little, and by a similar amount, from 1989 to 1993 in the Czech Republic and Slovakia. This surprising result is examined with an analysis of changes in the channels of redistribution and Gini decomposition. We find that the sizeable increase in overall inequality due to changes in the wage earnings component is mitigated by changes in the tax and transfer components in both republics. As for the relative effects of government policies, changes in the transfer component contributed more than changes in the tax component to lowering the growth of inequality in the Czech Republic, while the reverse was true for Slovakia.     

Income Distribution and Aggregate Saving: A Non‐Monotonic Relationship

Drawing on a panel of advanced economies, this paper documents a concave and non‐monotonic link between inequality and the aggregate household saving rate. We find that, at a low level of inequality, more inequality is associated with higher saving; but we also show that a negative relationship between inequality and saving prevails where inequality is high. Using different empirical approaches, we locate the turning point, where the marginal effect of inequality turns from positive to negative, at a net income Gini coefficient of around 30. Moreover, we show that the relationship between inequality and saving also depends on financial market conditions. While inequality increases saving, when credit is scarce it tends to reduce saving at high levels of credit. This paper primarily focuses on household saving, yet we also find some evidence for a non‐monotonic effect of inequality on private saving, national saving, and the current account balance.     

THE DISAGGREGATION OF THE GIN1 COEFFICIENT BY FACTOR COMPONENTS AND ITS APPLICATIONS TO AUSTRALIA

This paper demonstrates the proper use of the disaggregation of the Gini coefficient by factor components by deriving a formula of the elasticity of the Gini coefficient with respect to specific income components. The method is then applied to Australian household expenditure survey data to find the effects of various components of income on overall income inequality. The results are important in examining the effects of growth in specific components on the overall inequality and hence in policy decisions with respect to redistribution of income.