How do income and education affect health inequality: evidence from four developing countries

Using household survey data from four countries ? Albania, Nepal, Tajikistan and Tanzania ? this article calculates income-related inequality in health care utilization. We measure health disparity separately for generally and chronically ill individuals by constructing two models: one for the probability of a visit to a physician and another for the number of visits. Following model-based measurements, we decompose inequality into two major parts: one accounted for by identity-related factors and another by socioeconomic and other factors such as education, geography and distance to a clinic. We propose a new method to quantify the effect of changes in income and education on health disparity. One of our important findings suggests that health disparity is pro-rich in all our sample countries. The pro-rich disparity is prevalent among generally ill as well as chronically ill patients, in both visit probability and visit frequency models. Health inequality seems primarily driven by income differences followed by nonidentity factors. Further, the principle of equal treatment for equal need is not fulfilled in any of our countries. Among policy implications, increasing average income and education in a way that also reduces disparity in income and education, respectively, will substantially shrink inequality in health care utilization.     

我国居民收入不平等的主要原因：市场还是政府政策？

市场因素和政府收入再分配政策是决定一国居民收入不平等程度的两个重要因素。本文采用中国家庭收入调查（China Household Income Project ,CHIP）住户数据,计算出我国居民市场收入基尼系数与可支配收入基尼系数,并同发达国家进行比较,借此探讨目前我国居民收入不平等是由市场力量造成的,还是政府收入再分配政策力度不足的结果。研究发现,从市场收入基尼系数来看,我国与发达国家之间的差距并不大。由此认为,政府收入再分配政策效果不明显是导致我国居民收入分配不平等状况较发达国家严重的主要原因。加大转移支付等再分配政策力度是缓解和改善目前我国居民收入不平等的主要途径。     

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.     

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.     

Unemployment Shocks and Income Distribution: How did the Nordic Countries Fare during their Crises?

We study the inequality of disposable income in Denmark, Finland, Norway and Sweden during the late 1980s and early 1990s when unemployment rose dramatically in all four countries. A standard measure of inequality — the Gini coefficient – was surprisingly stable in all countries during this period. By decomposing the Gini into income components, we test hypotheses about the reasons for this stable income distribution. Our most straightforward hypothesis, that rising unemployment benefits counteracted the impact of more unequally distributed earnings, receives only limited support. More complex mechanisms seem to have been at work.
JEL classification: D 30; D 31; J 60     

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。     

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.     

A tale of two Ginis in the US, 1921–2012

Following a methodology by Jantzen and Volpert (2012), we use IRS Adjusted Gross Income data for the US (1921–2012) to estimate two Gini indices representing inequality at the bottom and the top of the income distribution, and to calculate the overall Gini as a function of the parameters underlying the two indices. A steady increase in the overall Gini since the Second World War actually hides two different periods of distributional changes. First, the increase in inequality from the mid 1940s to the late 1970s is driven by rising inequality at the bottom of the income distribution that more than offsets a decrease in inequality at the top. The implication is that middle-income earners gained relative to high-incomes, and especially relative to low-income earners. Second, the rise in the Gini after 1981 is driven by rising inequality at the top. Third, top-driven inequality follows a U-shaped trajectory consistent with Piketty and Saez (2003, 2006). Fourth, the welfare effects of the different distributional changes behind increasing inequality can be evaluated in light of the Lorenz-dominance criterion by Atkinson (1970): we argue that the rise in inequality since 1981 is much more likely to be associated with a social welfare loss net of compensating growth.     

GROWTH, POVERTY, AND INEQUALITY IN LATIN AMERICA: A CAUSAL ANALYSIS, 1970–94

Taking advantage of consistent poverty and income inequality data for 12 Latin American countries between 1970 and 1994, we analyze the determinants of changes in the incidence of urban and rural poverty and in Gini coefficients over spells of years, stressing in particular the role of aggregate income growth. We find that income growth reduces urban and rural poverty but not inequality. We also find that income growth is more effective in reducing urban poverty if the levels of inequality and poverty are lower, and the levels of secondary education higher. We show that there is an asymmetry in the impact of growth on poverty and inequality, with recession having strong negative effects on both poverty and inequality. Since growth does not reduce inequality, economic cycles create ratchet effects on the level of inequality. However, post-structural adjustment growth is quite effective at reducing poverty, particularly if inequality is low.     

BETWEEN GROUP INEQUALITY AND TARGETED TRANSFERS

This paper provides two extensions to the group decomposition of the Gini index by Yitzhaki and Lerman. First, within group, stratification, and between group inequality are analyzed along several dimensions at once. This provides for a better understanding of the determinants of inequality. Second, the impact on the Gini of marginal changes in income or consumption by group is derived. This can be used to evaluate targeted redistributive policies or assess the impact of exogenous shocks by group. The analysis is applied to data from Bangladesh with a focus on the impact of land ownership, education, and occupation on inequality.     

代际流动约束下生育率与收入不平等关系的国际检验

收入不平等问题和人口生育率过低问题是当下中国面临的两大难题,但目前理论界关于人口因素与收入不平等关系的研究,很少从生育率视角来考察以及考虑代际收入流动在其中的作用.文章从理论与经验两个方面来考察生育率对收入不平等的影响,理论模型表明:在关于代际收入流动的假设下,一个经济体中生育率的提高会使穷人比重提高,进而拉大收入不平等.进一步地,文章利用1970-2011年76个国家(地区)面板数据的经验研究发现:(1)总和生育率的提高会拉大收入不平等,如果每个妇女平均多生育一个孩子,将会使基尼系数增加0.025;(2)以出生率作为总和生育率替代指标的实证结果与基准结果基本一致,这说明不同生育率测算指标高度相关且可相互替代;(3)对于代际收入流动弹性越高、收入水平越低或生育率越高的国家(地区),其生育率提高对收入不平等的拉大作用越大.文章关于生育率对收入不平等影响的作用机制和异质性特征的考察,对于我国如何在实施"全面二孩"政策下寻求应对严峻的收入分配问题之策提供了国际经验和启示.     

Income Inequality and Macroeconomic Volatility: An Empirical Investigation

We explore the impact of macroeconomic volatility on the distribution of income. Using a cross‐section of developed and developing countries, we find that greater output volatility, defined as the standard deviation of the rate of output growth, is associated with a higher Gini coefficient and income share of the top quintile. The coefficients suggest that a strong effect on inequality resulting from a reduction in volatility: the Gini coefficient of a country like Chile would fall by 6 points if it were to reduce its volatility to the same level as Sweden or Norway. Our results seem not to be driven by the high‐inequality/high‐volatility Latin American countries.     

Inequality in Japan*

This paper analyzes income inequality, based on government income statistics and an attitude survey. First, the paper describes the present income inequality in Japan by using Gini coefficients, the income share of the top and bottom income classes, and mobilities among income classes. Second, by using the Japan–USA international survey, this paper analyzes the cause of the increasing awareness that Japan's income gap is widening. In these two countries, their distinct value judgments about the causes for the gap influence how they perceive it. The Japanese have negative perceptions about the income gap because they perceive it to be influenced by talent, academic background, or luck, and this perception seems relatively uncommon in the USA. A large percentage of Japanese also think one's income is decided by talent, academic background, or luck, although it should not be. Such disagreements between the desired and perceived determinants of income are thought to raise their negative perception of the gap.     

Not by growth alone: The role of the distribution of income in regional diversity in poverty reduction

This study examines the role of the distribution of income in determining the responsiveness of poverty to income growth and changes in income inequality using panel data of 58 developing countries for the period 1980-1998. We show that the large cross-regional variation in the capacity of income growth to reduce poverty, i.e. the income elasticity, is largely explained by differences in the initial distribution of income and present region and time specific estimates of the income and Gini elasticities of poverty. We find that the income elasticity of poverty in the mid-1990s equals −1.31 on average and ranges from −0.71 for Sub-Saharan Africa to −2.27 for the Middle East and North Africa, and that the Gini elasticity of poverty equals 0.80 on average and ranges from 0.01 in South Asia to 1.73 in Latin America. Furthermore we show that while differing income growth rates account for most of the regional diversity in poverty trends, the additional impact of differences across regions in rates of inequality change and income and inequality elasticities of poverty is almost always significant and far too large to be ignored, most notably so in Eastern Europe and Central Asia.     

Inflation and income distribution in Central America,Mexico, Panama,and the Dominican Republic

Analyses of the impact of inflation on income distribution typically only consider the general inflation rate. However, when the consumption structure of households is shaped by its income level and inflation varies across goods and services, they are affected differently by inflation. The aim of this study is to contribute to the analysis of this effect in Central American countries (Guatemala, El Salvador, Honduras, Nicaragua, and Costa Rica), Panama, Mexico, and the Dominican Republic (CAPMDR) for the period 2007–2018. According to our findings, there have been significant differences in the inflation rates faced by different income groups. By employing these percentile‐specific inflation rates, we have computed an “inflation‐corrected Gini index.” This adjustment is important because although inequality has been decreasing during past years in the countries in our sample, on average, about half of the gains observed using the standard Gini index are lost once the Gini indices are corrected for inflation, a clearly nonnegligible magnitude.     

Income inequality and FDI: evidence with Turkish data

This article explores how foreign direct investment (FDI) and other determinants impact income inequality in Turkey in the short- and long-run. We apply the nonlinear auto-regressive distributed lag (ARDL) modelling approach, which is suitable for small samples. The data for the study cover the years from 1970 to 2008. The empirical results indicate the existence of a co-integration relationship among the variables with asymmetric adjustment of the income distribution in the short- and long-run. The negative impact of FDI on the Gini coefficient, decreasing income inequality, is statistically significant in the short- and long-run, though with a quantitatively small impact in both cases. In the short run, GDP growth increases inequality initially, an effect that is reversed in the next period, increases in domestic gross capital formation decreases inequality, and increases in the literacy rate have very minor adverse effects on income equality. However, in the long run these variables have no statistically significant effects on the Gini coefficient. A reduction in the population growth rate reduces inequality in the short run but has no effect in the long run, whereas an increase in the rate reduces inequality in the long run but has no effect in the short run.     

本地非农就业、外出务工与中国农村收入不平等*

随着巨大的经济和社会变革,中国的收入不平等程度发生了巨大变化。依据CHIP家庭微观调查1988-2007年的数据,使用基尼系数分解以及非参数分解等多种方法,本文试图对本地非农就业、外出务工等不同类型的家庭从业模式与农村收入不平等的关系进行较为全面的探讨。研究得出了一些有价值的结论：首先,从整体的收入分布来看,早期的农村地区的发展更多伴随着不平等程度提高,而后期经济增长则带来更多福利改善;其次,家庭主要非农收入来源是本地非农就业,外出务工所得具有缩小收入差距的作用,而本地非农就业则具有扩大作用,随着时间推移其作用程度也有所改变;最后,经济增长成果惠及不同群体,但并非平均分配,不同群体获益情况不同,增长和不平等通过作用于不同类型家庭影响到最终的收入分布。     

Why has Income Inequality in Germany Increased From 2002 to 2011? A Behavioral Microsimulation Decomposition

This paper proposes a method to decompose changes in income inequality into the contributions of policy changes, wage rate changes, and population changes while considering labor supply reactions. Using data from the Socio‐Economic Panel (SOEP), this method is applied to decompose the increase in income inequality in Germany from 2002 to 2011, a period that saw tax reductions and a controversial overhaul of the transfer system. The simulations show that tax and transfer reforms have had an inequality‐reducing effect as measured by the mean log deviation and the Gini coefficient. For the Gini, these effects are offset by labor supply reactions. In contrast, policy changes explain part of the increase in the ratio between the 90th and the 50th income percentiles. Changes in wage rates have led to a decrease in income inequality. Thus, the increase in inequality was due to changes in the population.     

On the impact of innovation and inequality in economic growth

We present robust results on the empirical relationship among income inequality, innovation, and economic growth for a panel dataset of 74 countries over the period 1996–2014. We estimate pairwise causality tests to show that there is bidirectional causality between GDP per capita and R&D, while R&D causes the Gini index of income inequality, and it causes human capital. Allowing coefficients to be different across cross-sections of countries, we get in any case a pairwise bi-directionality. By dynamic panel data estimations, when regressing R&D on GDP per capita, we obtain a threshold value of 0.16% of R&D such that for values above it there is economic growth. While regressing R&D on the Gini index, we get a threshold of 0.10% of R&D above which, the income distribution begins to improve. Finally, we estimate a growth equation that depends on R&D, income inequality, and physical capital. We obtain two thresholds, one of 38.79 for the Gini (above which the economic growth decreases), and one of 0.06% for R&D such that above it, economic growth is rising.     

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.