Infant mortality,relative income and public policy

Do health outcomes depend on relative income as well as on an individual's absolute level of income? We use infant mortality as a health status indicator and find a significant and positive link between infant mortality and income inequality using cross-national data for 93 countries. Holding constant the income of each of the three poorest quintiles of a country's population, we find that an increase in the income of the upper 20% of the income distribution is associated with higher, not the lower infant mortality. Our results are robust and not just caused by the concave relationship between income and health. The estimates imply a decrease in infant mortality by 1.5% for a one percentage point decrease in the income share of the richest quintile. The overall results are sensitive to public policy: public health care expenditure, educational outcomes, and access to basic sanitation and safe water can explain the inequality–health relationship. Thus, our findings support the hypothesis of public disinvestment in human capital in countries with high income inequality. However, we are not able to determine whether public policy is a confounder or mediator of the relationship between income distribution and health. Relative deprivation caused by the income distance between an individual and the individual's reference group is another possible explanation for a direct effect from income inequality to health.     

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.     

Aggregation bias-correcting approach to the health–income relationship: Life expectancy and GDP per capita in 148 countries, 1970–2010

A large amount of data consisting of 148 countries for the years 1970 to 2010 is analysed in the context of the health–income relationship. The literature suggests that the biased income–health effect obtained with macro data can be a result of the aggregation of individual concave income functions on average health. This aggregation problem is analysed in detail, and a bias-correcting method is proposed to overcome it. The results with new model alternatives show that they correct the income effects on average health in the right direction; that is, they produce smaller parameter estimates than biased models. Augmenting the results with the quantile regression approach, which is sensitive to health differences between countries, indicates that the poorest countries’ income gradient is still much larger than that of rich countries. However, the median life expectancy effect of the log of GDP per capita across the countries decreased during the sample decennials. The results for income inequality measured with the Gini coefficient indicate that the effects of inequality on health are still significant in the poorest countries but non-significant among rich countries after the year 2000. We argue that the proposed bias-correcting method retains the interest in macro health modelling and offers new model alternatives in other contexts.     

Capitalist systems and income inequality

The paper investigates the relationship between compositional inequality (how the shares of capital and labor income vary along income distribution) and inter-personal income inequality. Using a new methodology and data from 47 countries covering the period 1995–2018, we show that higher compositional inequality is associated with higher inter-personal inequality. This is clearly shown by Latin American countries and India. Nordic countries are exceptional because they combine high compositional inequality with low inter-personal inequality. Their exceptionalism is attenuated when pension income received from largely government-mandated accumulated savings is added to capital income. The analysis shows the theoretical possibility of societies where low compositional inequality may be combined with high income inequality. Currently, China and the United States come closest to that position.     

Growth, income distribution and well-being in transition countries

We apply several well-being measures that combine average income with a measure of inequality to international and intertemporal comparisons of well-being in transition countries. Our well-being measures drastically change the impression of levels and changes in well-being compared to a traditional reliance on income measures. Due to low inequality and moderate income levels, socialist countries enjoyed relatively high levels of economic well-being. In the transition process, rising inequality and falling incomes have led to a dramatic absolute decline in well-being and a considerable drop in relative well-being vis-à-vis non-transition countries. We also find a close correlation between income losses and inequality increases. While the transition has been successful in expanding political and civil rights, our indicators suggest that most transition countries are still below the level of economic well-being of the late 1980s.
JEL classification: D6, O15, P27.     

Do Piketty and Saez Misstate Income Inequality? Critiquing the Critiques

A large body of literature points to sharply growing income inequality over the past half century. The Piketty and Saez dataset that measures income distribution provides empirical support for this claim. Our article evaluates three prominent criticisms of this dataset as well as the responses of Piketty and Saez to these criticisms. One key argument against using their dataset is that Piketty and Saez do not control for income shifting by top income earners in response to the Tax Reform Act of 1986 (TRA86) and thus overstate income inequality. In evaluating this criticism we find that a segment of their dataset likely understates income inequality; this is just the opposite of what critics assert. This implies that the Piketty–Saez dataset is a valuable resource for income inequality research and that scholars can use it to build more refined, accurate and insightful measures of income inequality.     

Financial development,control of corruption and income inequality

This paper examines the effect of financial development and control of corruption on income inequality in 21 Sub-Saharan African (SSA) countries over the period 1985–2011 using the pooled mean group (PMG) estimator. The empirical results show that financial development measures have positive impact on income inequality, which suggest that financial development increases income inequality. On the other hand, the coefficients of control of corruption are negative and significantly related to income inequality which implies that corruption control reduces income inequality. Further, the interaction of the financial development and the control of corruption is found to be negatively and significantly related to income inequality. Equally the interaction of the financial development and transparency index (an alternate measure of corruptibility) is found to be negatively and significantly related to income inequality. These findings suggest that the control of corruption and transparency in governance are crucial in reducing income inequality in SSA.     

Decomposing differences in health and inequality using quasi-objective health indices

People in Canada and the United States often make claims regarding whose country has a better health system. Several researchers have attempted to address this question by analysing subjective health measures in the two countries, thus assuming a common definition of ‘good’ health. Using data from the Joint Canada/US Survey of Health, which provides rich and comparable health information for the two countries, I generate two quasi-objective health indices and show that Canadians and Americans define ‘good’ health differently. After controlling for cross-country reporting heterogeneity, health differences between Americans and Canadians are eliminated for intermediate health statuses, while health differences at the tails of the health distribution lead to slightly better average population health in Canada. With respect to health inequality, my results show that income and education gradients increase steeply with poor health in both countries. Hence, considering differences along the health distribution is crucial when assessing population health or health inequality.     

Can social spending cushion the inequality effect of globalization?

This paper examines whether social spending cushions the effect of globalization on within‐country inequality. Using information on disposable and market income inequality and data on overall social spending, and health and education spending from the ILO and the World Bank/WHO, we analyze whether social spending moderates the association between economic globalization and inequality. The results confirm that economic globalization—especially economic flows—associates with higher income inequality, an effect driven by non‐OECD countries. Health spending is strongly associated with lower inequality, but we find no robust evidence that any kind of social spending negatively moderates the association between economic globalization and inequality.     

Income mobility of individuals in China and the United States

Although much has been written about annual income inequality in China, little research has been conducted on longer‐run measures of income inequality and on income mobility. This paper compares income mobility of urban individuals in China and the United States in the 1990s. The following questions are taken up: To what extent are measures of annual income inequality misleading indicators of long‐run income inequality? How much income mobility was there in China in the first half of the 1990s and how did this compare with mobility in other countries? Have real income increases been greater for the poor or the rich? How important is the variation in permanent incomes in China and how has this changed?     

Income, income inequality, and health: Evidence from China

This paper tests using survey data from China whether individual health is associated with income and community-level income inequality. Although poor health and high inequality are key features of many developing countries, most of the earlier literature has drawn on data from developed countries in studying the association between the two. We find that self-reported health status increases with per capita income, but at a decreasing rate. Controlling for per capita income, we find an inverted-U association between self-reported health status and income inequality, which suggests that high inequality in a community poses threats to health. We also find that high inequality increases the probability of health-compromising behavior such as smoking and alcohol consumption. Most of our findings are robust to different measures of health status and income inequality. Journal of Comparative Economics 34 (4) (2006) 668–693.     

Housing and Income Inequality in Europe: Distributional Effects of Non-Cash Income From Imputed Rents

This article uses survey data to estimate non-cash income from imputed rents, using a consistent methodology for all countries to assemble comparable statistics that allow for a valid inter-country comparison. We can confirm a significant impact of non-cash income and find an inequality-decreasing effect for the unconditional income distribution which highly correlates with the proportion of owner-occupiers in the respective countries. However, aggregated inequality measures are not suited to analyze the increase in the conditional income inequality between owner-occupiers and renters, who do not obtain income from imputed rents by definition. Therefore, we apply a reweighting decomposition that controls for the heterogeneous housing characteristics among European countries and allows us to decompose the distributional changes into a part that is explained by the proportion of tenure types and household size and a remaining part that reflects the relative dispersion of imputed rents along the income distribution.     

Income inequality and education revisited: persistence,endogeneity and heterogeneity

This article presents new results on the relationship between income inequality and education expansion – that is, increasing average years of schooling and reducing inequality of schooling. When dynamic panel estimation techniques are used to address issues of persistence and endogeneity, we find a large, positive, statistically significant and stable relationship between inequality of schooling and income inequality, especially in emerging and developing economies and among older-age cohorts. The relationship between income inequality and average years of schooling is positive, consistent with constant or increasing returns to additional years of schooling. While this positive relationship is small and not always statistically significant, we find a statistically significant negative relationship with years of schooling of younger cohorts. Statistical tests indicate that our dynamic estimators are consistent and that our identifying instruments are valid. Policy simulations suggest that education expansion will continue to be inequality reducing. This role will diminish as countries develop, but it could be enhanced through a stronger focus on reducing inequality in the quality of education.     

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.     

Inequality and growth: What comes from the different inequality measures?

The objective of the paper is to verify if income inequality impedes the growth rates in OECD countries in the period of 1990–2014 and to reveal whether the choice of the income inequality measure determines the sign and the strength of the estimated relationship. We use system GMM to estimate parameters of a dynamic panel growth model. The research indicates that income inequality negatively affects economic growth. We also find evidence that various measures of inequality bring the different scale of consequences for economic growth, with measures that give more weight to the middle part of the distribution being the weakest predictor of GDP growth. Simultaneously, we present the test of weak instruments, which helps to explain these differences.     

Does microfinance affect income inequality?

This study addresses the question whether participation of the poor in microfinance contributes to reducing a country’s level of income inequality. Using data from 70 developing countries, we show that higher levels of microfinance participation are indeed associated with a reduction of the income gap between rich and poor people. We also show, however, that the effects of microfinance on reducing income inequality are relatively small. The results of this study add to the discussion on the impact of microfinance on poverty by showing that, although access to microfinance does seem to improve the relative income position of the poor, this improvement is modest, which is probably because the use of microfinance is generally small as compared to the size of the economy of the countries in our sample. Microfinance should, therefore, not be seen as a panacea for bringing down income inequality in a significant way.     

Income-related inequalities of health and health care utilization

By utilizing the China Health and Nutrition Survey (CHNS) data, this paper examines the extent of deviations in terms of horizontal equity in the field of China’s health and medical community, i.e., that those in equal demand ought to be treated equally, and computes the contribution of income in health inequality and utilization inequality of health care. The main conclusions are: There is pro-rich inequality in health and utilization of health care; income contribution to inequality of health care utilization accounts for 0.13–0.2; insurance also enlarges the inequality of health care utilization; health inequality in rural area is larger than that of in urban area; and both rural and urban health inequality are increasing. From 1991 to 2006, income changes in urban districts and rural area account for 7.08% and 13.38% respectively of raising inequality of rural and urban health.     

Does economic freedom increase income inequality? Evidence from the EU countries

This paper examines the relationship between economic liberalization and income inequality in the EU using panel data for the 2000s. The empirical evidence suggests that economic freedom is strongly related to income inequality. However, not all areas of economic freedom affect income distribution similarly. Government size is robustly associated with inequality, and also when controlling for potential endogeneity in a dynamic panel data analysis. Regulation is linked to income inequality as well, whereas legal system and sound money have no significant effects on income distribution. In the case of freedom to trade internationally, the relationship differs between old (EU-15) and new (former socialist) EU countries.     

International income inequality, 2005–2011: what a difference 6 years can make

While much attention has recently been given to the rising inequality in high-income countries, particularly the US, inequality across countries has received less attention. Based on reports of the International Comparison Program, which provide the most accurate measures of PPP income at the country level, this study computes three highly recommended measures of intercountry income inequality for the years 2005 and 2011. A dramatic, and perhaps unprecedented, fall in intercountry inequality over the relatively short period of 6 years is noted. As a correlate of the fall in intercountry inequality, aggregate PPP GDP for six major high-income countries is compared with that for three large developing countries, and the dramatic increase over the 6-year period in the ratio of the total GDP of the three developing countries to that for the six high-income countries is noted, thus extending, from the most accurate data, the theme of the ‘rise of the South’ articulated in Human Development Report 2013.     

收入、收入不均与健康:城乡差异和职业地位的影响

本文使用来自中国9个省的微观面板数据,检验了居民自评健康与家庭人均收入和社区内收入不均之间的相关关系。考虑到中国城乡分割的二元经济社会特征,本文将农村样本和城镇样本分开处理;考虑到中国的社会分层结构,计量方程中引入了代表职业地位的变量及其与收入和收入不均的交互项。在实证结果的基础上,本文讨论了收入、收入不均与健康关系的作用机制。主要结论是:收入与健康的关系、收入不均与健康的关系都存在城乡差异和职业差异,这说明在收入、收入不均与健康的关系中,社会经济地位的影响十分重要。要解决健康不平等问题,关键在于加强对社会经济地位较低者,主要是农村居民和生活在城镇的农民的医疗保障,同时要设法改善农村的基础设施和社会资本,并逐步取消各种造成城乡分割的制度。