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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.

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.

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...

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.

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.

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

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.

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.

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。

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.

Survey under-coverage of top incomes leads to bias in survey-based estimates of overall income inequality. Using income tax record data in combination with survey data is a potential approach to address the problem; we consider here the UK’s pioneering ‘SPI adjustment’ method that implements this idea. Since 1992, the principal income distribution series (reported annually in Households Below Average Income) has been based on household survey data in which the incomes of a small number of ‘very rich’ individuals are adjusted using information from ‘very rich’ individuals in personal income tax return data. We explain what the procedure involves, reveal the extent to which it addresses survey under-coverage of top incomes, and show how it affects estimates of overall income inequality. More generally, we assess whether the SPI adjustment is fit for purpose and consider whether variants of it could be employed by other countries.

Economic inequality is, nowadays, frequently perceived as following a growing trend with impact on political and religious agendas. However, there is a wide range of inequality measures, each of which pointing to a possibly different degree of inequality. Furthermore, regardless of the measure used, it only acknowledges the momentary population inequality, failing to capture the individuals evolution over time. In this paper, several inequality measures were analyzed in order to compare the typical single time instant degree of wealth inequality (population perspective) to the one obtained from the individuals’ wealth mean over several time instants (individuals perspective). The proposed generalization of a simple addictive model, for limited time average of individual’s wealth, allows us to verify that the typically used inequality measures for a given snapshot instant of the population significantly overestimate the individuals’ wealth inequality over time. Moreover, that is more extreme for the ratios than for the indices analyzed.

Using data on U.S. state-level inequality from Frank, Sommeiller, Price, and Saez (2016) and state-level unionization data from Hirsch et al. (2001), this paper shows that unions have a negative impact on income inequality in U.S. states. In particular, higher rates of unionization decreased inequality, as measured by the Gini coefficient, the share of income accruing to the top 1% of earners, and the share of income accruing to the top 10% of earners. The findings are robust across several estimation methods and also when union coverage is used as an alternative to the percent of workers in unions.

We introduce firm and worker heterogeneity into a model of innovation†driven endogenous growth. Individuals who differ in ability sort into either a research activity or a manufacturing sector. Research projects generate new varieties of a differentiated product. Projects differ in quality and the resulting technologies differ in productivity. In both sectors, there is a complementarity between firm quality and worker ability. We study the co†determination of growth and income inequality in both the closed and open economy, as well as the spillover effects of policy in one country to outcomes in others.

This paper presents a simple post-Kaleckian model of distribution and growth that incorporates personal income inequality and interdependent social norms. The model shows in an easily accessible manner that macroeconomic effects of changes in personal and functional income distribution can potentially reinforce or dampen each other. The resulting variety of demand and growth regimes is due to different distributional effects on consumption demand. Therefore, the second part of the paper investigates the empirical relevance of the additional demand regimes by estimating aggregate consumption functions with variables for personal and functional income distribution for the United States and Germany. We find similar effects of functional income distribution for both countries. However, for the US, we find positive long-run effects of personal income inequality on consumption. The effect is strongest for the top 10% income share and the Gini index and less strong for the top 5% and 1% income shares. While this is evidence for relative consumption patterns, it also supports the view that the ?super rich? are a relatively distant class for most people - questioning the notion of expenditure cascades from the very top to the very bottom. In contrast, for Germany we fail to find compelling evidence for effects of personal income distribution.

Inequality's effect on growth remains elusive, largely due to endogeneity, complex interactions, and lead–lag relationships. We revisit this issue by examining the four main channels through which inequality transmits to growth: savings, investment, education, and knowledge production. We construct new panel data for 21 OECD countries spanning 142 years. External communist influence is used as a new time-varying instrument for inequality and the effects of inequality on the outcome variables are made conditional on the stage of financial development. Our results show that inequality hampers growth at low to moderate levels of financial development but has little effect on growth at advanced levels of financial development.

In this article, we consider a stylized dynamic model to describe the economics of a population, expressed by a Langevin-type kinetic equation. The dynamics is defined by a combination of terms, one of which represents monetary exchanges between individuals mutually engaged in trade, while the uncertainty in barter (trade exchange) is modelled through additive and multiplicative stochastic terms which necessarily abide dynamical constraints. The model is studied to estimate three meaningful quantities, the inequality Gini index, the social mobility and the total income of the population. In particular, we investigate the time evolving binary correlations between any two of these quantities.

This paper studies the relationship between income distribution and international integration in a canonical trade setting with one change. In the standard model prices are solely a function of (constant) marginal costs and (constant) elasticities, implying that information on individual incomes are of no value to a firm. To allow a more realistic role for consumer level information, a firm's strategy space is expanded to include non-linear prices. Now profit maximizing firms use information on income distribution to design a product for each income class and set prices to induce each group to optimally select the appropriate option. Equilibrium involves designs below the first best for low income groups and above the first best for high income groups – welfare differences are more exaggerated than income differences. When countries with differing income distributions integrate this has implications for the size of these distortions, influencing the gains from trade both within and across countries. These implications are quantified and shown to be potentially significant factors affecting welfare outcomes from integration – with the consequences more pronounced at lower trade costs. The structure of trade and expenditure patterns that emerge also match a range of empirical findings. These results are driven by firm strategy based on income difference alone as preferences are assumed to be identical and homothetic across countries, placing the distribution of income at the center of the analysis.

This paper 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.

PurposeWhen the policy maker contemplates the current aggregate demand (AD), she/he does so given implicitly the current state of income inequality. And, policy goals should be set based on the distance between this demand and some “optimal” AD from the viewpoint of optimal income inequality. The purpose of this paper is to relate this policy concern to the sources of modern inequality.Design/methodology/approachTo characterize optimality, recent research in inequality reveals that paternalistic inheritance is the decisive source of it. Inequality is the outcome of an intergenerational externality according to which the current entrepreneurs (physical-capital formation agents) bequeath to descendants who use the inheritance as rentiers rather than as entrepreneurs. Several policy measures have been proposed to correct for this externality. Yet, it is found that if the “dynastic” character of inequality is disregarded, the distance between actual and optimal AD will be ever increasing.FindingsPolicy should be addressing the motive of the descendants to act as rentiers, which is found to be easy to attain once the policy maker adopts a natural-resource view of sizeable inheritance and proceeds to reassign property rights over it across generations.Originality/valueOptimality is identified with the Cantorian (total) ordering of the social economy, which is inhibited by the institution of dynastic property rights. One way to deal with this problem is to view inheritance as a depletable natural resource.

The present paper shows the results of an empirical study to prove that income inequality has increased over the past decades. To conduct the study, an income inequality dataset containing 133 countries over the 1990-2014 period was created. The results indicate that globally, income inequality (population-weighted Gini coefficients), on average, increased from 38.6 to 41.8 during that period. They further show the existence of variations in the level of income inequality across regions and groups of countries. The reduction in income inequality, among others, remains one of the key challenges associated with the 2030 Agenda for Sustainable Development. Therefore, in this paper, various transmission mechanisms and drivers of the increasing level of income inequality are identified and possible forward-looking development policies to reduce income inequality are given.

Trust is a good approach to explain the functioning of markets, institutions or society as a whole. It is a key element in almost every commercial transaction over time and might be one of the main explanations of economic success and development. Trust diminishes the more we perceive others to have economically different living realities. In most of the relevant contributions, scholars have taken a macro perspective on the inequality-trust linkage, with an aggregation of both trust and inequality on a country level. However, patterns of within-country inequality and possibly influential determinants, such as perception and socioeconomic reference, remained undetected. This paper offers the opportunity to look at the interplay between inequality and trust at a more refined level. A measure of (generalized) trust emerges from ESS 5 survey which asks "...generally speaking, would you say that most people can be trusted, or that you can't be too careful in dealing with people?". With the use of 2009 EU-SILC data, measurements of income inequality are developed for age-specific groups of society in 22 countries. A sizable variation in inequality measures can be noticed. Even in low inequality countries, like Sweden, income imbalances within certain age groups have the potential to undermine social trust.