A new approach to the decomposition of the Gini income inequality ratio

The purpose of this research is to introduce a new approach to the decomposition of the Gini ratio into three components, supporting them with economic and statistical rigorous interpretations. The three components are: (i) the Gini inequalitywithin subpopulations; (ii) thenet contribution of the extended Gini inequalitybetween subpopulations; and (iii) the contribution of theintensity of transvariation between subpopulations. These components are weighted by the product of the population shares times the income shares of the corresponding subpopulations where the weights add to one.The decomposition introduced in this research is applied to the 1990 U.S. family income distribution. The population of families is disaggregated by types into the following subpopulations: (a) married-couple families; (b) male householder, no wife present; and (c) female householder, no husband present.     

A Note on α‐Gini Measures

This note provides a characterization of α‐Gini inequality measures. These measures generalize the standard Gini index by including one sensitivity parameter α, which captures different value judgments. The α‐Gini measures are shown to be weakly decomposable and unit consistent. Weak decomposition provides within‐group and between‐group inequalities. Unit consistency keeps unchanged the ranking of two income distributions when the income units vary. It is shown that the α‐Gini measures are relevant with either “leftist” or“rightist” views.     

Inequality of Happiness in the U.S.: 1972–2010

It is well accepted that a country's GDP may not fully reflect its level of well‐being. In recent years, happiness has emerged as an alternative indicator of well‐being, and research has mainly focused on determining the level of happiness. While it is important to look at the level, the distribution of happiness is also a salient aspect in any evaluation of inequality. There has been a growing interest in the distribution of happiness, although the ordinal nature of the data makes the use of standard inequality measures problematic. Our paper contributes to the literature by exploring the distributions for the U.S. from 1972 to 2010. Based on new methods developed for ordinal data, we are able to overcome the problems associated with ordinality and obtain unambiguous rankings of happiness distributions. We also compute the level of happiness inequality using existing measures based on median centred approaches. Further, we decompose the median based inequality measures of happiness by gender, race, and region.     

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.     

Foreign bank ownership and income inequality: empirical evidence

ABSTRACT

Using country-level panel data over 1995–2013 on within-country income inequality and foreign bank presence, this paper establishes a positive relation between the two, running from higher foreign bank presence to income inequality. Given that foreign bank participation increased by 62% over the period 1995 to 2013, our baseline results imply a 5.8% increase in the Gini coefficient on average over this period, ceteris paribus. These results are robust to the inclusion of country and year fixed effects and to the use of restrictions on foreign bank entry in the host countries as an instrumental variable. We show that this positive effect is channelled through the lack of greenfield entry and the associated lower levels of competition.     

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.      

International Inequality and Convergence in Educational Attainment, 1960–1990

The paper examines the international inequality and convergence of educational attainment from 1960 to 1990. Despite the increasing trend in educational attainment, the gap in educational attainment between the developing countries and developed countries and that between males and females increased in the period. However, the relative dispersion of educational attainment—as measured by the coefficient of variation, the Gini coefficient, or the standard deviation of log average years of schooling—declined consistently during the period by either development or gender status. Decompositions of the Gini coefficient indicate that the development gap and the gender gap were the main components for world inequality in educational attainment in both 1960 and 1990. Educational attainment exhibited b - and s -convergence over the period.     

Decomposing World Income Distribution: Does The World Have A Middle Class?

Using the national income/expenditure distribution data from 111 countries, we decompose total inequality between the individuals in the world, by continents and regions. We use Yitzhaki's Gini decomposition which allows for an exact breakdown of the Gini. We find that Asia is the most heterogeneous continent; between-country inequality is much more important than inequality in incomes within countries. At the other extreme is Latin America where differences between the countries are small, but inequalities within the countries are large. Western Europe/North America is fairly homogeneous both in terms of countries' mean incomes and income differences between individuals. If we divide the world population into three groups: the rich (those with incomes greater than Italy's mean income), the poor (those with incomes less than Western countries' poverty line), and the middle class, we find that there are only 11 percent of people who are "world middle class"; 78 percent are poor, and 11 percent are rich.     

ECONOMIC FREEDOM & HAPPINESS INEQUALITY: FRIENDS OR FOES?

This article examines the relationship between economic freedom and happiness inequality for a large sample of countries. We find that economic freedom is negatively associated with happiness inequality and robust to several alternative measures of happiness inequality, including the standard deviation, mean absolute difference, coefficient of variation, and Gini coefficient. Among the economic freedom areas, legal system and sound money are negatively correlated with happiness inequality. Drawing on the Engerman‐Sokoloff hypothesis, we use a measure of factor endowments as an instrument for economic freedom to provide a further robustness test, finding a negative association between economic freedom and happiness inequality. (JEL D63, I31, P16)     

How large is income inequality in China: assessment on different estimates of Gini coefficient

The rising income inequality in China has attracted social attentions, especially since SWUFE published the unbelievably high Gini coefficient in December 2012. In order to answer the question how large income inequality in current China is, this paper compares existing different Gini coefficients estimated from four different household surveys, which are the NBS household survey, the CHIP survey, the CHFS of SWUFE, and the CFPS of Peking University, and then assesses these household surveys themselves. The relevant evidences indicate that the national Gini coefficient in current China is between 0.47~0.52. The sampling defects of the CHFS are significantly major and that the national Gini coefficient of 0.61 published by SWUFE is seriously overestimated.     

INEQUALITY OF OPPORTUNITIES VS. INEQUALITY OF OUTCOMES: ARE WESTERN SOCIETIES ALL ALIKE?

This paper analyzes the relationship between income inequality and inequality of opportunities for income acquisition in nine developed countries during the 1990s. Equality of opportunity is defined as the situation where income distributions conditional on social origin cannot be ranked according to stochastic dominance criteria. We measure social origin by parental education and occupation and use the database built by Roemer et al. (2003 ). Stochastic dominance is assessed using nonparametric statistical tests. Our results indicate strong disparities in the degree of equality of opportunity across countries and a strong correlation between inequality of outcomes and inequality of opportunity. The U.S. and Italy show up as the most unequal countries in terms of both outcome and opportunity. At the opposite extreme, income distributions conditional on social origin are almost the same in Scandinavian countries even before any redistributive policy. We complement the ordinal comparison by resorting to an original scalar “Gini” index of opportunities, which can be decomposed into a risk and a return component. In our sample, inequality of opportunity is mostly driven by differences in mean income conditional on social origin, and differences in risk compensate the return element in most countries.     

Inequality and economic growth: the role of initial income

We estimate a panel model where the relationship between inequality and GDP per capita growth depends on countries’ initial incomes. Estimates of the model show that the relationship between inequality and GDP per capita growth is significantly decreasing in countries’ initial incomes. Results from instrumental variables regressions show that in Low Income Countries transitional growth is boosted by greater income inequality. In High Income Countries inequality has a significant negative effect on transitional growth. For the median country in the world, that in the year 2015 had a PPP GDP per capita of around 10000USD, IV estimates predict that a 1 percentage point increase in the Gini coefficient decreases GDP per capita growth over a 5-year period by over 1 percentage point; the long-run effect on the level of GDP per capita is around ??5%.     

Estimation of Concentration Measures and Their Standard Errors for Income Distributions in Poland

Measures of concentration (inequality) are often used in the analysis of income and wage size distributions. Among, them the Gini and Zenga coefficients are of greatest importance. It is well known that income inequality in Poland increased significantly in the period of transformation from a centrally planned economy to a market economy. High income inequality can be a source of serious problems, such as increasing poverty, social stratification, and polarization. Therefore, it seems especially important to present reliable estimates of income inequality measures for a population of households in Poland in different divisions. In this paper, some estimation methods for Gini and Zenga concentration measures are presented together with their application to the analysis of income distributions in Poland by socio-economic groups. The basis for the calculations was individual data coming from the Polish Household Budget Survey conducted by the Central Statistical Office. The standard errors of Gini and Zenga coefficients were estimated by means of the bootstrap and the parametric approach based on the Dagum model.     

Distributional national accounts for the Netherlands and a comparison with 12 other countries

Most inequality studies rely on micro data that do not capture a substantial share of income identified in the national accounts. In the Netherlands, almost one fifth of household disposable income is missed by current inequality statistics. In this paper, we present inequality statistics for the Netherlands that capture all of household income, so-called distributional national accounts. Compared to the current inequality statistics, the Gini coefficient for disposable income increases substantially from 0.289 to 0.337. Cross-country comparisons show that such a change between Gini coefficients based on micro-data versus Gini coefficients based on distributional national accounts does not apply to all countries. The difference between both Gini coefficients varies not only between countries in the size, but also in the sign of the difference.     

Calculation and decomposition of income inequality in low- and middle-income countries: a survey data analysis

This article estimates income inequality in a sample of four low- and middle-income (LMI) countries namely; Albania, Nepal, Tajikistan and Tanzania using the household survey data – Nepal Living Standard Measurement Survey Second. First, we estimate the income generation function for each country and calculate the income inequality using Gini index (GI). Second, we decompose the income Gini into the determinants of income generation functions. Based on the decomposition result, socio-economic factors are the most important determinants of income inequality followed by geographic factors. Demographic factors have the least effect on income inequality in all four countries. Third, we propose a new method to quantify the effect of change in each covariate of income generation function on income Gini. That allows us to quantify the effects of change in specific policy such as increase in investment in schooling or public health to specific group of the population in society on income inequality. A carefully chosen, integrated policy can significantly reduce inequality in all four countries under study.     

Income stratification and between-group inequality

The paper shows explicitly how the overlapping of groups impacts between-group inequality by generalizing a result on the group-wise decomposition of the Gini index to more than two groups. It is demonstrated that the ratio of Yitzhaki’s measure of between-group inequality to the conventional measure is in general equal to one minus twice the weighted average probability that a random member of a richer (on average) group is poorer than a random member of a poorer (on average) group, and may therefore be interpreted as an overall index of income stratification in the population. The results are used to tabulate the contribution of each pair of regions in the world to the overall level of global income stratification.     

Do dictatorships redistribute more?

This paper examines the effect of political institutions on fiscal redistribution for a country-level panel from 1960–2010. Using data on Gini coefficients before and after government intervention, we apply a measure of effective fiscal redistribution that reflects the effect of taxes and transfers on income inequality. Our findings clearly indicate that non-democratic regimes demonstrate significantly greater direct fiscal redistribution. Subsequently, we employ fiscal data in an attempt to enlighten this puzzling empirical finding. We find that dictatorial regimes rely more heavily on cash transfers that exhibit a direct impact on net inequality and consequently on the difference between market and net inequality (i.e., effective fiscal redistribution), whereas democratic regimes devote a larger amount of resources to public inputs (health and education) that may influence market inequality but not the difference between market and net inequality per se. We argue that the driving force behind the observed differences within the pattern on government spending and effective fiscal redistribution is that democratic institutions lead survival-oriented leaders to care more for the private market, and thus to follow policies that enhance the productivity of the whole economy.     

Ethically flexible gini indices for income distributions in the continuum

A single-parameter generalization of the Gini coefficient (S-Gini) is presented for income distributions defined in the continuum. Special cases are Dorfman's formula for the Gini, and the authors' S-Ginis for finite populations. We exploit the duality between indices of relative inequality and homothetic social-evaluation functions to construct these new indices.     

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。     

The trend of welfare disparity among subgroups of population in Australia 1983-1984 - 1993-1994

The aim of this paper is to estimate the trend of social welfare for Australia using 1983–1984, 1988–1989 and 1993–1994 Household Expenditure Survey data. The functional form of the Social Welfare Function (SWF) was derived by Sen, Degum, Yitzhaki and Shesinski (all independently). Since the function contains the Gini coefficient as the inequality parameter, it could not be formally disaggregated by subgroups of population. This paper, using a method of subgroup decomposition of the Gini coefficient developed by Podder, attempts to disaggregate the SWF. With this method it is now possible to identify disadvantaged groups by their relative shares in total welfare. In addition the method is used to determine effect of economic growth on specific subgroups, and in turn, on total social welfare. This study is based on the Australian economy. Distribution of relative shares of total social welfare among various regional groups are identified, groups determined by occupational status and groups determined by country of birth. The effect on society's welfare for a percentage change in income of a group and the trend of relative welfare of a specific group are also computed. This information can be used in a variety of social decision making situations, including cost benefit analysis.