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Este artículo analiza la distribución conjunta del ingreso-riqueza en Uruguay y la compara con Chile, España y Estados Unidos, por medio de encuestas financieras de hogares. Se analizan las distribuciones univariantes de ingreso y riqueza, y se encuentra que la última es más concentrada y asimétrica que la primera. Se estiman cópulas no paramétricas para la distribución conjunta que revelan que los hogares de altos ingresos se encuentran entre los de mayor riqueza y que los de menores ingresos entre los de menor riqueza. Se descubre que, en Uruguay, la educación es la principal fuente de heterogeneidad del ingreso, la riqueza y la distribución conjunta.

This study aims to reveal empirically the extent to which Islamic economics contributes to Indonesia's economic equality. This study uses zakat distribution indicators and financing of Islamic banks as an instrument of income distribution in Islamic economics; GINI coefficients are indicators for measuring income inequality and using panel data with a cross-section of 12 provinces in Indonesia the 2011-2016 period. This study found that the distribution of zakat has a negative effect on income inequality and Islamic bank financing has a positive effect on income inequality.

Determining the level of income inequality requires the adoption of a specific measurement methodology. The aim of the study was to review and discuss the methodologies used to measure income inequality. Four measures are presented, each based on different assumptions. These measures were the Gini coefficient, Theil coefficient, Kukuła coefficient and unevenness coefficient. The first three measures, and in particular the Gini coefficient, are commonly described in the literature, while the unevenness coefficient is the author’s proposal for measuring income inequality. The empirical material for the research consists of data on the distribution of disposable income by decile groups in households in Poland for the years 2005–2017. The most important issue in practice regarding the measurement of income inequality was the transfer principle. Depending on the methodology adopted, the transfer of income is treated differently. The Gini, Theil and Kukula coefficients respond to any change in the income distribution, while the unevenness coefficient only to changes above the average. In a situation where the Gini coefficient (Theil and Kukula) decreases (increases), the level of inequality decreases (increases), but it is not known which transfers led to such a result. The decreasing (growing) unevenness coefficient means that these were transfers from groups with shares in income above (below) the average for groups with shares below (above) the average.

The main goal of this work is to find ways to improve the regional system for monitoring income inequality in Russia. In our paper we compare methods of measuring income inequality that are currently used in official statistics with alternative methods. Alternative indicators include those used by international organizations and those appearing in the economic literature. The empirical basis for the analysis is formed by the microdata of the Statistical Survey of Personal Income and Participation in Social Programs, held by Rosstat in 2017. Based on the results of the study, a list of additional indicators that allow to reveal specific features of regional income inequality in Russia was proposed. We also identified the list of Russian regions for which the use of additional inequality indicators is most appropriate. We expect that using the extended set of income differentiation measures will provide policymakers with an important information to design effective responses to inequality.

This paper proposes a new framework for measuring income inequality. The framework is based on the unequally distributed (UD) incomes that are obtained by removing the equally distributed parts from incomes. We then derive the normalized norm indexes from the cumulative distribution function and the unscaled Lorenz curve of the UD incomes. The relation between the normalized norm indexes and the popular Gini coefficient and coefficient of variation (CV) shows that the Gini coefficient and CV represent only parts of income inequality. We analyze example income distributions and the Luxembourg Income Study datasets to show that the normalized norm indexes evaluate income inequality appropriately and solve the negative income problem.

This note introduces original technical results in the theoretical measurement of inequality by specifying the relationships between additive separability and homotheticity (of measures of welfare ...

Does regional income inequality affect a household’s likelihood of being indebted? This question is addressed by using survey data on Italian households. The analysis shows that inequality in the regional income distribution has a negative effect on the probability of being indebted. In addition, richer households living in regions with greater income inequality have a greater likelihood of being indebted than similarly rich households residing in regions with low income inequality (and vice versa for poorer households). The study suggests that supply factors are more important than demand factors in explaining this result. These findings are consistent with the latest survey-based evidence drawn from US data which suggests that banks may use local income inequality and a household’s position in the income distribution to make inferences about an applicant’s underlying default risk. These results hold after controlling for socio-demographic differences, different types of debt, unobserved household heterogeneity using panel data and a number of robustness checks.

This article measures inequality at the provincial level in Spain for different benchmark years between 1860 and 1930. It then empirically assesses the relationship between economic growth and inequality. The results confirm that, although growing incomes did not directly contribute to reducing inequality, at least during the early stages of modern economic growth, other processes associated with economic growth such as the rural exodus to urban and industrial centers, the demographic transition, and the spread of literacy, among others, notably improved the situation of the bottom part of the population.

We propose that income inequality increases corruption. The rich are likely to both have greater motivation and opportunities to engage in bribery and fraud as one means to preserve and advance their status, privileges, and interests while the poor are more vulnerable to extortion at higher levels of inequality. While countries with authoritarian regimes are likely to have greater levels of corruption on average, the effect of greater inequality on corruption will be higher in democracies, in which the wealthy cannot employ repression and poorer groups are likely to more effectively demand redistribution. Both OLS estimates (for samples of 95 to 122 countries) and IV 2SLS estimates (for samples of 83 to 103 countries) support our arguments, with 2SLS estimates showing stronger statistically significant effects of inequality on corruption, utilizing Transparency International's Corruption Perceptions Index, the World Bank's Control of Corruption Index (average for 1996-2002) and Dollar and Kraay's income inequality data (average Gini for 1950-1999). Surprisingly, the explanatory power of inequality is substantially no less important than conventionally accepted causes of corruption such as economic development. Contrary to conventional wisdom, smaller and not larger government is associated with higher levels of corruption, because higher inequality through corruption is associated with lower tax rates as well as lower government transfers and subsidies.

The Great Recession had a tremendous impact on low-income Americans, in particular Black and Latino Americans. The losses in terms of employment and earnings are matched only by the losses...

Purpose The purpose of this paper is to investigate both linear and/or nonlinear effects of inflation on income inequality and to test the Kuznets hypothesis using panel data of 24 developed countries (DCs) and 66 developing countries (LDCs) observed over the period of 1990–2014. Design/methodology/approach This paper explores the short- and long-run Granger causality relationship between inflation and income inequality using the Toda and Yamamoto (1995) procedure and a Vector Error Correction Model (VECM) approach. The existence of a nonlinear relationship between inflation and income inequality is confirmed implying as inflation rises income inequality decreases. Income inequality then reaches a minimum and then starts rising again. The findings of this paper show the existence of Kuznets “U-shaped” hypothesis between income inequality and real GDP per capita in DCs group, and the existence of Kuznets’ inverted “U-shaped” hypothesis for LDCs group. Findings The results indicate that there is no bi-directional Granger causality between inflation and income inequality in the short-run, but, there is bi-directional Granger causality in the long-run for both the DCs and LDCs group. The results help us to assess the effectiveness of monetary policy in reducing income inequality in both the DCs and LDCs group. As a policy implication, monetary policy is often aimed at controlling the annual rate of inflation in the long-run with a short-run focus on reducing output gaps and creating employment. However, managing inflation may have implications for income inequality. Originality/value This is original research paper which analyzes the “U-shaped” and inverted “U-shaped” paths of income inequality and real GDP per capita for large sample of two group countries including developed and developing countries, respectively. Also, this paper analyzes the nonlinear relationship between inflation and income inequality in two groups. Furthermore, this paper investigates the short- and long-run relationship between variables. The results are important for policy makers.

We show that the transition from an economy characterized by idiosyncratic income shocks and incomplete markets a la Aiyagari (1994) to markets where state-contingent assets are available but costly (in order to purchase a contingent asset, households have to pay a fixed participation cost) leads to a large increase of wealth inequality. Using a standard calibration our model can match a Gini of 0.93 close to the level of wealth inequality observed in the US. In addition, under this level of participation costs, wealth inequality is particularly sensitive to income inequality. We label this phenomenon as the Inequality Accelerator. We demonstrate how costly access to contingent asset-markets generates these effects. The key insight stems from the non-monotonic relationship between wealth and desired degree of insurance, in an economy with participation costs. Poor borrowing constrained households remain uninsured, middle-class households are almost perfectly insured, while rich households decide to self-insure by purchasing risk-free assets. This feature of households' risk management has crucial effects in asset prices, wealth inequality, and social mobility.

This paper holistically addresses the effective (relative) income tax contribution of a given income (or, wealth) group. The widely acclaimed standard in public policy is the absolute benefaction of a given income group in filling up the fiscal coffers. Instead, we focus on the ratio of the average income tax rate of an income group divided by the percentage of national income (or wealth) appropriated by the same income group. In turn, we develop the Fiscal Inequality Coefficient which compares the effective percentage income tax payments of pairs of income (or wealth) groups. Using data for the US, we concentrate on pairs such as the Bottom 90% versus Top 10%, Bottom 99% versus Top 1%, and Bottom 99.9% versus Top 0.1%. We conclude that policy makers with a strong social conscience should re-evaluate the progressivity of the income tax system and make the richest echelons of the income and wealth distributions pay a fairer and higher tax.

Income inequality and house prices have risen sharply in developed countries during 1975–2010. In line with theoretical models, we argue that this co-movement is no coincidence, but that inequality has driven up house prices on the grounds that it raises the aggregate demand for housing. Our results suggest that absolute inequality and house prices in most Organisation for Economic Co-operation and Development (OECD) countries were positively correlated and cointegrated, whereas relative inequality and mean income were not significant long-run determinants. This finding indicates that the surge in OECD house prices in part can be explained by a top-income-induced increase in housing demand, and that it is important to consider the interaction of rising mean income and its relative distribution when studying potential correlates of house prices. Moreover, our results confirm previous findings that the short-term real interest rate also is an important correlate of house prices.

This paper offers one of the first pieces of empirical evidence on the impact of inequality of opportunity on household education investment by using the panel data from China Family Panel Studies (CFPS) in three waves (2010, 2012 and 2014). Our result suggests that inequality of opportunity has a negative effect on household education expenditures. This result is robust to a series of robustness checks. Furthermore, for relatively disadvantaged households (household heads with less education, income, or rural hukou status), inequality of opportunity has a larger negative effect on their education expenditures. Policy suggestions to lower inequality of opportunity may include reducing labor market discrimination based on gender and hukou status, balancing education resources to create more equal educational opportunities, and offering children education subsidies in low-income families.

This paper investigates the impacts of financial development, urbanization, and globalization on income inequality in China by applying a regression-based inequality decomposition approach to panel data on Chinese provinces. Provincial data on urbanization and globalization are combined with new data collected from a unique database of financial development in China compiled at the county level. Our findings suggest that financial development, urbanization, and globalization have a positive impact on income. However, our inequality decomposition suggests that financial development may be particularly important for promoting inclusive growth, since financial development not only stimulates economic growth but is also found to be a factor that reduces inequality.

The issue of income inequality is exacerbating when China experiences rapid economic growth during the past few decades. This paper argues that urban inclusiveness is one of the determinants of income inequality in Chinese cities, because the Hukou system restricts public service to Hukou-registered workers only. The impact of urban inclusiveness on income inequality and the underlying mechanism are discovered by examining how Hukou restriction affects income gap between skilled and unskilled workers and how the preferences on public services and urban inclusiveness vary across skilled and unskilled workers. With the 2005 Inter-Census Population Survey, we find skilled workers care more about public services and urban inclusiveness, so skilled workers are relatively scarce in exclusive cities, who hence can enjoy a higher skill premium, leading to higher income inequality in exclusive cities.

This paper will setup a trade model to explore the impact of the diversity of talent distribution and the technology difference on the pattern of trade (POT) and income inequality of an economy. We find that not only the diversity effect but also the technology effect can matter for the pattern of POT. We demonstrate that, in the free-trade equilibrium, if the technology effect dominates the diversity effect then the country with a more (less) diverse distribution of talent may export the goods produced by a technology with supermodularity (submodularity). In addition, we prove that the relative technology difference will affect income inequality. If the technological advance for the submodular sector S is better than for the supermodular sector C, then income inequality would increase.

In this study, a robust semi-parametric approach which involves combining the empirical distribution and Pareto model is applied for measuring the income distribution in Malaysia based on the survey data of household incomes for the years of 2007, 2009, 2012 and 2014. From our analysis, it is found that the Pareto model is well fitted to the top household incomes for all years considered, suggesting that this model is a suitable parametric distribution to describe the top household incomes in Malaysia. Based on the semi-parametric Gini, generalized entropy and Atkinson indices, it is found that the income inequality shows a decreasing trend over the period, indicating an improvement of income distribution in Malaysia. Moreover, the fitted semi-parametric Lorenz curves show that the economic pie of the high income group reduced slightly after being taken up by the low income group while there is no clear change for the middle household income group.

In times of economic crisis, most countries face the dual challenge of fighting unemployment while restraining social expenditures and closing budget deficits. The spending cuts and lack of employment affect a large number of decisions that have a direct or indirect impact on health. This impact is likely to be unevenly distributed among different groups within the population, and therefore not only health levels may be at risk, but also their distribution. The main purpose of this paper is to explore links between unemployment, economic growth, inequality, and health. We regress a measure of health, the Health Human Development Index (HHDI), against a set of explanatory variables accounting for the countries' economic performance (GDP growth, unemployment, and income inequality), and some institutional factors related to welfare spending and the nature of the health systems for the past three decades. In addition, we explore the causes for different results obtained using an inequality-adjusted HHDI, vs. the unadjusted HHDI. We describe a panel data model, estimated by random effects, for 32 countries from 1980-2010, in five-year intervals. Our conclusion is that the high economic growth observed in the last decades, together with an increase in the levels of income inequality and/or poverty, explain the observed changes of our index, particularly when this indicator is weighted by health inequality. The remaining institutional variables (the share of social spending, health care expenditure, and the type of health systems) show the expected sign but are not statistically significant. A comment on the methodological pitfalls of the approach completes the analysis. © 2014 by the authors; licensee MDPI, Basel, Switzerland.

The growing ageing population in South Korea has further widened income disparity among different working age groups. Experts believe this disparity may even increase in the future and thus a mode of prediction with regard income and inequality may have to be clearly established. This paper intends to measure the current income inequality between prime working age Koreans (working population ages 30 - 59) and the ageing population (ages 60 and above), and to predict the income inequality of these two groups in the future. This paper will also predict income disparity between the two groups in Korea with the introduction of moderate or considerable government intervention. To assess the income inequality between the working and ageing population, this paper acquired data, such as wages and population of different age groups, from multiple credible sources such as the United Nations, Korean Statistics Information Service, OECD, and from other sources. The data ranged from 2006 up until 2018. These data were then converted to gini coefficient with the use of a scoring system. The gini coefficient values from the year 2006 to 2018, obtained from the previous method, were used to measure the trend in income inequality between the working and ageing population and were also used to predict the income inequality in the future. Looking at the gini coefficient values from 2006 to 2018, the values were approaching 0, which suggest that the disparity in income was actually diminishing. And reflecting back to this trend, it suggests that the gini coefficient values in the future would also diminish over time thus, supporting the claim that the income disparity between the working and ageing population would reduce. Moreover, with the implementation of applicable government policies, the gini coefficient values are expected to approach 0 at a much faster rate, which also suggests that government interventions would reduce the income gap between working and ageing population. Despite the beliefs of the expert that income disparity may increase in the future, the result proves that income gap between working and ageing population would diminish in the future, and may diminish more rapidly with potential government intervention. &nbsp

Although measuring income inequality seems straightforward and uncontroversial, methodological issues greatly affect findings. This chapter shows that changes in real median income between 1979 and 2014 across six studies varied from negative 8 percent to positive 51 percent. Furthermore, the share of growth going to the top ten percent during these years in four studies ranged from 31 percent to 100 percent. The first choice that researchers make is choosing a dataset or linked datasets. This choice affects the income sharing unit, be it households, families, individuals, or tax units. The next choice is the definition of income, with the starting point being cash market income only—earnings, dividends, rents, interest payments, or business profits. This total can be expanded by including government cash benefits, employer benefits, the rental value of home ownership, and government and financial services that people don’t pay for. Even after the income concept is chosen, income can be presented as adjusted for family size and either before or after taxes. Finally, adjusting for inflation to change nominal incomes into inflation-adjusted incomes can be performed in a variety of ways.

Drawing on a panel of 29 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 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.

Western governments increasingly place more emphasis on non-income dimensions in measuring national well-being (e.g. the UK, France). Not only averages, but the characteristics of the whole distribution (e.g. inequalities) are taken into consideration. Commonly used data such as life satisfaction, declared health status or level of education, however, are ordinal in nature and the fundamental problem of measuring inequality with ordinal variables exists. Here, a class of multidimensional inequality indices for ordinal data is characterized by inequality axioms and based on the characterization theorem an inequality measure is proposed. The method ensures that the index is also attribute decomposable, that is, we can estimate the contribution to overall inequality from inequality in dimensions and from their association. It was found for the period 1972-2010 in the US, excluding 1985 that inequality in perceived happiness contributed more to overall inequality than health inequality. Joint inequality in health and happiness was signicantly higher in the rst half of the study period (0.3 vs. 0.2). In the 1970s and 1980s most healthy people were also happier and this positive association increased inequality by around 20 percent. This trend was reversed in the late 1980s when the contribution of association became negative. This trend for the healthiest to no longer be the happiest persisted with the exception of three years.

In this paper, we revisit the inequality–growth relationship using an enhanced panel data set with improved inequality data. We explicitly take into account the special role of transition (post-Soviet) countries and add an instrumental variable (IV) estimation to add a causal interpretation to our findings. Our analysis is based on the specification used by Forbes in her 2000 paper, but we also address functional form concerns raised by Banerjee and Duflo three years later. We arrive at three main findings: First, the significant positive association between inequality and economic growth in the full sample is entirely driven by transition countries. Second, this relationship in transition countries is not robust to the inclusion of separate time effects. Lastly, it appears that this association is not causal but rather driven by the particular timing of the transition. Results from IV estimation confirm our interpretation of the observed positive relationship in the overall sample as non-causal.

Given increases in income inequality across rich democracies since the 1980s, we expect public opinion to favor a stronger social policy role of the state as a corrective measure. A basic theory of democracy suggests that public opinion and redistributive social policies are reciprocally causal, therefore, lack of negative public reaction suggests that the public are satisfied with increasing inequality if their preferences did not help it grow in the first place. Theories of welfare state institutions and different trajectories of inequality suggest that the link between opinion and inequality depends on context. Drawing on theories of attitude formation, we use predictive modeling adjusting for the causes of public support for social policy to (a) test for public responsiveness to inequality; and (b) compare how this differs by institutional context. Our analyses use ISSP and WID data between 1980 and 2006. In liberal contexts where inequality expanded monumentally since the 1970s (mostly English-speaking countries), increasing inequality predicts higher support for state provision of social policy. In the coordinated and universalist contexts of Europe, increasing inequality predicts less support for state provision of social policy. The results suggest that the public in liberal societies – which had higher levels of inequality to begin with – reach their limits of inequality, reacting negatively; whereas in coordinated and universalist societies – starting out with comparatively lower inequality levels – they move positively with inequality, suggesting welcome cuts to the redistributive social welfare state.

This paper analyses the role of good governance in fostering pro-poor and inclusive growth. Using a sample of 112 countries over 1975–2012, it shows that growth is generally pro-poor. However, growth has not been inclusive, as illustrated by a decline in the bottom 20 percent of the income distribution. While all features of good governance support income growth and reduce poverty, only government effectiveness and the rule of law are found to enhance inclusive growth. The investigation of the determinants of pro-poor and inclusive growth highlights that education, infrastructure improvement, and financial development are the key factors in poverty reduction and inclusive growth. Relying on the panel smooth transition regression (PSTR) model following Gonzalez, Tersvirta and Dijk (2005), the paper identifies a nonlinear relationship between governance and pro-poor growth, while the impact of governance on inclusive growth appears to be linear.

Why, in some urban communities, do rich and poor households cohabit while, in others, we observe sorting by income? To answer this question I develop a two-community general equilibrium framework of school quality, residential choice and tax decision with probabilistic voting. The model predicts that in highly unequal societies in which households segregate by schooling, low- and high-income households choose to live in the same community. When there is less inequality, we observe the typical sorting by income across communities. The theoretical model suggests that the effect of inequality on the quality of public schooling is ambiguous and depends on the relative endowments of housing in the two communities. When inequality increases, if housing in the community where rich and poor households cohabit is affordable, then an inflow of high-income middle class households towards this community emerges. As a consequence, inequality negatively impacts the quality of public schooling due to an ends-against-the-middle coalition that pushes tax rates down.

From 1917 to 2012, donations by high-income households in the USA have moved inversely with income inequality. This association contradicts historical narratives and prevailing theory, both of which that imply that high-income households donate rising income shares when inequality increases. The negative correlation holds both unconditionally and after conditioning on other explanatory variables, at both the national and US state levels. Low payout ratios of foundations and endowed charities, combined with this observed relationship, imply that differences in charitable giving will tend to entrench, not reduce, inequality across places over time.

Since Piketty’s Capital in the 21st Century in 2014, scientific interest into theimpact of income inequality on society has been on the rise. However, little is known about the mediating role of income inequality in the relationship between market institutions and subjective well-being. Using panel analysis on a sample of 21 OECD countries to test the effects of five different types of economic freedom on income inequality, we find that fiscal freedom, free trade and freedom from government regulation increase income inequality, whereas sound money decreases income inequality. Income inequality is found to have anegative effect on life satisfaction. Mediation tests show that income inequality mediates the influence of fiscal freedom, free trade and freedom from government regulation on life satisfaction.

In this paper, we study how income inequality matters for government borrowing and default decisions. We extend a standard endogenous sovereign debt default model to allow for heterogeneous agents and stochastic variability in the dispersion of income. We calibrate the model to match a number of stylized facts for Argentina. We show that (i) rising income inequality within a country increases the probability of default significantly; (ii) the effect of output shocks is larger than the effect of inequality shocks; (iii) the joint effect of these two shocks can generate a high default probability consistent with the Argentine data; (iv) the model can match the high volatility of consumption by the poor relative to the rich; and (v) more progressive income taxes lead to lower default risk.

The People's Republic of China (PRC) has achieved significant improvements in educational attainment levels since the market-oriented reforms began almost four decades ago. However, there are still educational gaps among different groups and education inequality remains an issue. Addressing urban disparities remains a pertinent matter in optimizing China's transition towards a knowledge-driven economy. This paper investigates education inequality in urban China, using subgroup and regression-based decompositions of inequality of educational attainment, to evaluate whether the determinants to urban education inequality are similar within and across regions. Using the urban datasets from the China Household Income Project surveys for 2013, education inequality was measured for up to 100 cities from 14 provinces. The results reveal heterogeneity in educational attainment, education inequality, and the determinants of education inequality in urban China. Regression-based decompositions of education inequality revealed that the determinants of education inequality are not homogeneous between and within regions and provinces. While the type of middle school and National Higher Education Entrance Examination scores are predominantly among the largest contributors, the size and order of their contributions vary among different regions, provinces and age cohorts. Other major contributing factors varied from parents' occupation to parent's education and parental employment type. The results imply that since cities aren't homogeneous, therefore, they have different contributing factors towards education inequality. The results suggest that location-specific policy targets and priorities may produce more favorable outcomes in reducing education inequality.

This paper investigates trends in educational inequality in China, focusing on the contribution of ‘inequality of opportunity’ to these trends. Utilising the China Family Panel Studies survey for 2010 and 2012, we measure the inequality in individual educational outcomes (measured in years of schooling) in aggregate and for each of ten birth cohorts. We run regressions to identify the key determinants of these outcomes, all of which can be classified as ‘circumstances’ that lie beyond the control of each individual, and which reveal important variations in the magnitude and significance of key determinants across birth cohorts. The results are then used to calculate the share of ‘inequality of opportunity’ in overall educational inequality. The lack of equal opportunity for Chinese people with regard to their educational outcomes is shown to stem primarily from the divisive hukou system, with further significant contributions from father's education, birth cohort, province, parents' Communist Party membership, gender, family size and ethnicity, in that order.

This paper investigates the relationship between the capital share in national income and personal income inequality over the long run. Using a new historical cross-country database on capital shares in 19 countries and data from the World Wealth and Income Database, we find strong long-run links between the aggregate role of capital in the economy and the size distribution of income. Over time, this dependence varies; it was strong both before the Second World War and in the early interwar era, but has grown to its highest levels in the period since 1980. The correlation is particularly strong in Anglo-Saxon and Nordic countries, in the very top of the distribution and when we only consider top capital incomes. Replacing top income shares with a broader measure of inequality (Gini coefficient), the positive relationship remains but becomes somewhat weaker.

Struggles with inequality have been prominent in the Middle East and North Africa in the aftermath of the Arab Spring. This paper examines the extent and drivers of inequality of opportunity in attaining higher education in Egypt, Jordan, and Tunisia. We find that inequality is similarly high in Egypt and Tunisia, but moderate in Jordan. Background characteristics affect attainment even after accounting for test scores, which are themselves influenced by background. Particularly in Egypt and Tunisia, where higher education is free of charge, public spending on higher education is regressive. Thus, a theoretically meritocratic and equitable system perpetuates inequality.

This paper is the first comprehensive empirical study of earnings, income, and consumption inequality in urban China from 1986 to 2009, using unique micro-level data from the Urban Household Survey (UHS). The paper documents a drastic increase in economic inequality for the sample period. The paper finds that consumption inequality closely tracks income inequality, both over time and over the life cycle. The paper believes that the main driver of this co-movement could be a dramatic increase in noninsurable idiosyncratic permanent income shocks after the early 1990s, associated with the economic transition in urban China.

This study explores the effects of patent protection and R&D subsidies on innovation and income inequality using a Schumpeterian growth model with heterogeneous households. We find that although strengthening patent protection and raising R&D subsidies have the same macroeconomic effects of stimulating innovation and economic growth, they have drastically different microeconomic implications on income inequality. Specifically, strengthening patent protection increases income inequality whereas raising R&D subsidies decreases (increases) it if the quality step size is sufficiently small (large). An empirically realistic quality step size is smaller than the threshold, implying a negative effect of R&D subsidies on income inequality. We also calibrate the model to provide a quantitative analysis and find that strengthening patent protection causes a moderate increase in income inequality and a negligible increase in consumption inequality whereas raising R&D subsidies causes a relatively large decrease in both income inequality and consumption inequality.

This paper provides evidence of strong associational effects between economic growth in the manufacturing, agriculture, mining and services sectors and income inequality, measured by an income equality variable, using panel data for Indonesian districts and cities over the period 2000 to 2010. The results show a significantly positive impact of both manufacturing and services shares of GDP on income inequality. The share of agriculture in GDP, however, shows a significantly negative impact on income inequality. The effects are robust to the incorporation of control variables, making a case for considering sectoral differences in policy targeting for achieving inclusive growth. Este articulo proporciona evidencia de los fuertes efectos asociativos entre el crecimiento economico en los sectores manufacturero, agricola, minero y de servicios y la desigualdad de ingresos, medida por una variable de igualdad de ingresos, para lo cual usa datos de panel de distritos y ciudades de Indonesia durante el periodo 2000 a 2010. Los resultados muestran un impacto positivo significativo de la contribucion del sector manufacturero y el de servicios en el PIB en la desigualdad de ingresos. Sin embargo, la contribucion de la agricultura al PIB muestra un impacto negativo significativo en la desigualdad de ingresos. Los efectos se muestran robustos ante la incorporacion de variables de control, lo que justifica que se consideren las diferencias sectoriales en la orientacion de las politicas para lograr un crecimiento inclusivo. 本稿では、2000年~2010年のインドネシアのdistrictとcityのパネルデータを使用して、製造業、農業、鉱業、サービスセクターの経済成長と、所得平等変数で測定した所得不平等との強い因果関係を示すエビデンスを提示する。結果から、GDPの製造業とサービスが占める割合は、所得不平等に有意に正のインパクトを与えることが示されるが、GDPに占める農業の割合は所得不平等に対し、有意に負のインパクトを与えることも示された。この因果関係は、制御変数を代入した場合も頑健であることから、インクルーシブ・グロース (包摂的成長)を実現するための政策目標の設定がセクターによって異なることを考慮することが正しいことが示される。

The relationship between income inequality and long-run economic growth has gained a growing attention in economic research for over decades. This study employed advanced time series techniques to examine the existence of an inverted U-shaped long-run relationship between income inequality and economic growth, using long-span time series data for the United States between the periods 1917–2012. The concepts of summability, balancedness and co-summability was advanced to analyze nonlinear long-run relations among stochastic processes. The empirical results find no evidence in support of nonlinear long-run (inverted U-shaped) relationship for the US, but findings from a vocal set of economists lends strong support and is the basis for the conclusions drawn by this study.

We study household income inequality in both Great Britain and the United States and the interplay between labour market earnings and the tax system. While both Britain and the US have witnessed secular increases in 90/10 male earnings inequality over the last three decades, this measure of inequality in net family income has declined in Britain while it has risen in the US. To better understand these comparisons, we examine the interaction between labour market earnings in the family, assortative mating, the tax and welfare-benefit system and household income inequality. We find that both countries have witnessed sizeable changes in employment which have primarily occurred on the extensive margin in the US and on the intensive margin in Britain. Increases in the generosity of the welfare system in Britain played a key role in equalizing net income growth across the wage distribution, whereas the relatively weak safety net available to non-workers in the US mean this growing group has seen particularly adverse developments in their net incomes.

We explore the relationship between natural disasters and income inequality in Sri Lanka as the first study of this nature for the country. The analysis uses a unique panel data set constructed for the purpose of this paper. It contains district inequality measures based on household income reported in six waves of the Household Income and Expenditure Survey of Sri Lanka during the period between 1990 and 2013, data on disaster affected population and other economic and social indicators. Employing a panel fixed effects estimator, we find that contemporaneous natural disasters and their immediate lags significantly and substantially decrease inequality in per adult equivalent household income as measured by the Theil index. Findings are robust across various inequality metrics, sub-samples and alternative estimators such as Ordinary Least Squares and System GMM. However, natural disasters do not affect household expenditure inequality. Either households behave as if they have a permanent income or all households reduce their expenditure proportionately irrespective of their income level in responding to natural disasters. Natural disasters decrease non-seasonal agricultural and non-agricultural income inequality but increase seasonal agricultural income inequality. Income of richer households is mainly derived from non-agricultural sources such as manufacturing and business activities and non-seasonal agricultural activities. Poorer households have a higher share of agricultural income.

This paper examines the predictive power of a partisan conflict on income inequality. Our study contributes to the existing literature by using the newly introduced nonparametric causality-in-quantile testing approach to examine how political polarization in the United States affects several measures of income inequality and distribution overtime. The study uses annual time-series data between the periods 1917–2013. We find evidence in support of a dynamic causal relationship between partisan conflict and income inequality, except at the upper end of the quantiles. Our empirical findings suggest that a reduction in partisan conflict will lead to a reduction in our measures of income inequality, but this requires that inequality is not exceptionally high.

We use data from the Household Expenditure Survey and Household, Income and Labour Dynamics in Australia Survey to document facts about consumption and income inequality among households in Australia, emphasising the role of the rents imputed to home owners for conclusions about inequality. Consistent with other developed economies, consumption inequality in Australia is lower on average than income inequality. Both have increased since the early 1990s, with income inequality increasing by more. We decompose the trend in income inequality into four components: (i) changes in observed household characteristics; (ii) changes in the returns to unobserved skills; (iii) changes in the size of persistent income shocks; and (iv) changes in the size of transitory income shocks. We find that changes in the size of persistent and transitory income shocks, rather than changes in observed household characteristics, explain most of this trend. Since the middle of the 2000s, the source of income inequality has shifted from transitory to persistent factors, which is consistent with the rise in consumption inequality over the corresponding period. We find that accounting for imputed rents lowers estimates of the level of inequality in Australia, but has a negligible effect on the trends. [ABSTRACT FROM AUTHOR]

The European Union’s Lisbon strategy goal of tackling poverty was a notable failure, while the Europe 2020 strategy’s poverty target is out of reach. Both strategies were based on variants of the ‘at risk of poverty’ indicator, which has an inappropriate and misleading name. We demonstrate theoretically and empirically by cross-section, time series and panel cointegration evidence that the ‘at risk of poverty’ indicator essentially measures income inequality, not poverty. Our calculations show that even after taking into account the positive impact that expected economic growth should have on material deprivation and low work intensity, the Gini coefficient of income inequality would have to fall by 3.5 points in each EU country if the Europe 2020 poverty target is to be reached, which is implausible. The ‘at risk of poverty’ indicator does not satisfy standard axioms set in the literature, while the huge differences between national poverty thresholds make the EU-wide poverty aggregate pointless. The political agreement between EU member states expressed the goal of reducing poverty, not inequality. There are good reasons to aim for lower income inequality, but a political agreement would be needed to set an inequality goal and corresponding policies.

Trends in income inequality are increasingly being discussed by economists and policy makers. In New Zealand, income inequality indices increased during the late 1980s and early 1990s, with limited change thereafter. But little is known about the levels and changes of such indices over prior decades. Based on previously unexplored data from Statistics New Zealand Official Yearbooks and Inland Revenue, this article reports estimates for the Gini index of income inequality for New Zealand from the mid†1930s to the present. Comparisons with estimates for Australia for 1942–2001 reveal some remarkable commonalities.

We investigate the consequences of income inequality on the income tax-to-GDP ratio for 21 OECD countries over a long time period spanning 1870 to 2011. We use several identification strategies, including using unionization as a new IV for inequality. In contrast to predictions from median voter models, we find that rising inequality significantly depresses the income tax ratio. This finding is robust to alternative measures of inequality, treatment for endogeneity, and model specification. The tax ratio increases with the degree of democracy. Inequality also reduces the indirect tax ratio, alters the tax structure, and moderates government spending as a share of GDP.

Purpose Understanding the linkages between poverty and inequality is vital to any sustainable development and poverty reduction strategies. In Ghana, while poverty has reduced significantly over the years, inequality has increased. The purpose of this paper is to examine the linkages between inequality in household expenditure components and overall inequality and poverty in Ghana. Design/methodology/approach Using microdata from the sixth round of the Ghana Living Standards Survey (GLSS 6) conducted in 2012/2013, marginal effects and elasticities were computed for both within- and between-component analysis. Findings The results suggest that, in general, reducing within-component inequality significantly reduces overall poverty and inequality in Ghana, compared with between-component inequality. Specifically, inequality in education and health expenditure components were the largest contributors to overall poverty and inequality. The findings imply that policies directed toward reducing within-component inequality will be more effective. Specifically, the findings of the study corroborate recent policies on education and health in Ghana aimed at inequality within these components. Sustaining and scaling up these policies will be a step in the right direction. Originality/value The study contributes to existing studies in several ways: first, this study becomes the first attempt to examine inequality-poverty nexus using household expenditure components in Ghana. Second, the use of expenditure in place of income is an addition to the literature. Income is usually subject to reporting biases and is minimal in expenditure. Finally, the findings highlight the need for poverty reduction strategies to focus on specific household components including education and health. Blanket interventions may not be effective in reducing inequality and poverty.

In this paper, we assess empirically whether financial inclusion contributes to reducing income inequality when controlling for other key factors, such as economic development and fiscal policy. We conclude that financial inclusion contributes to reducing income inequality to a significant degree, while the size of the financial sector does not. Although our results are still preliminary and constrained by data limitations, they still bear significant policy implications. More specifically, fostering financial inclusion has one more important by-product, which had hardly been analyzed yet, namely reducing income inequality. More specifically, given the broad definition of financial inclusion used in our analysis, promoting financial inclusion implies facilitating the use of credit to low-income households, as well as granting credit to small and medium-sized enterprises.