The Changing Shape of Global Inequality 1820–2000; Exploring a New Dataset

A new dataset for charting the development of global inequality between 1820 and 2000 is presented, based on a large variety of sources and methods for estimating (gross household) income inequality. On this basis we estimate the evolution of global income inequality over the past two centuries. Two sets of benchmarks about between‐country inequality (the Maddison 1990 benchmark and the recent 2005 ICP round) are taken into account. We find that between 1820 and 1950, increasing per capita income is combined with increasing global inequality. After 1950, global inequality as measured by the Gini coefficient or the Theil index remains more or less constant. It also appears that the global income distribution was uni‐modal in the nineteenth century, became increasingly bi‐modal between 1910 and 1970 with two world wars, a depression and de‐globalization, and was suddenly transformed back into a uni‐modal distribution between 1980 and 2000.     

Can social spending cushion the inequality effect of globalization?

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

Income Level and Income Inequality in the Euro‐Mediterranean Region,C. 14–700

Was the Euro‐Mediterranean region at the time of the Roman Empire and its Western successor states more unequal than the European Union today? We use some scant evidence on personal income distribution within the Empire and differences in average regional incomes to conclude that the Empire was more homogeneous, in terms of regional incomes, than today's EU, and inter‐personal inequality was low. Moreover, income inequality was likely less around year 700 than in Augustus's time. The latter finding contrasts with a view of rising inequality as the Western Roman Empire dissolved.     

Refitting the Kuznets curve using a gender-specific threshold model

Previous studies have reached mixed conclusions regarding the relationship between inequality and per capita income. These studies, however, fail to consider gender differences in income inequality and how these may impact on the relationship between income inequality and per capita income. Using Australian taxation statistics, we derive three sets of Gini coefficients (i.e. female, male and total) for the period 1950–2013. We then examine the relationship between inequality and real per capita income and find that a gender-specific threshold panel regression outperforms three other conventional models. Our findings suggest that ‘one set of coefficients does not fit all’ in that the use of aggregate and constant coefficients may mask variations within, and between, gender inequality over time.     

Do Education and Income Really Explain Inequalities in Health? Applying a Twin Design

We apply a twin design to examine the relationship between health and education and income. The estimated associations between health and education and income, controlling for unobserved endowments, at the twin‐pair level, are lower than estimates obtained via ordinary least‐squares (OLS) on the same sample. Thus, OLS‐based effects of education and income are biased, exaggerating the contribution of education and income to health inequality. The main part of health inequality is explained by within‐twin‐pair fixed effects, incorporating family background and genetic inheritance. It appears that education and income policies have less to offer for reducing health inequality than is usually assumed.     

Measuring lnequality in the Middle East 1990–2016: The World’s Most Unequal Region?

In this paper we combine household surveys, national accounts, income tax data and wealth data in order to estimate income concentration in the Middle East for the period 1990–2016. According to our benchmark series, the Middle East appears to be the most unequal region in the world, with a top decile income share as large as 64 percent, compared to 37 percent in Western Europe, 47 percent in the US and 55 percent in Brazil (see Alvaredo et al. 2018). This is due both to enormous inequality between countries (particularly between oil‐rich and population‐rich countries) and to large inequality within countries (which we probably under‐estimate, given the limited access to proper fiscal data). We stress the importance of increasing transparency on income and wealth in the Middle East, as well as the need to develop mechanisms of regional redistribution and investment.     

Income inequality and financial reform in Asia: the role of human capital

We investigate whether financial reform can reduce income inequality in Asia, with particular emphasis on the role of human capital. Extending Galor and Zeira (1993), we demonstrate that financial reform is effective in reducing income inequality, and the effect is more profound in a country with higher human capital. Using the data for 18 countries in Asia, the region with the most promising financial reform, we confirm our theoretical finding. In addition, among disaggregated financial reforms, lift of credit control, better banking supervision and security market development seem to be significantly associated with reduction of income inequality.     

Income and Wealth Inequality in Asia and the Pacific: Trends,Causes, and Policy Remedies

The Asia–Pacific region's rapid growth and poverty reduction in recent decades have been accompanied by rising income and wealth inequality. Technological progress, globalization, deregulation and market-oriented reform, and financialization have generated many new opportunities, but rewarded capital more than labor, benefited skilled workers more than the unskilled, widened spatial inequality, and produced a growing number of the superrich. For some countries, population aging has also contributed to rising inequality. The present paper provides an update on recent trends of income and wealth inequality in the Asia–Pacific region, examines causes behind rising inequality, and discusses policy actions needed to tackle inequality. It also assesses how the COVID-19 has likely worsened inequality in the region.     

我国居民收入不平等的主要原因：市场还是政府政策？

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

Foreign direct investment and inequality in developing countries: Does sector matter?

Scholars have studied the relationship between inward foreign direct investment (FDI) and within‐country income inequality in cross‐national contexts, but have not empirically investigated how FDI in different sectors might affect inequality in different ways. We use error correction models to analyze sectoral FDI data compiled from UNCTAD investment reports in 60 middle‐income countries from 1989 to 2010, arguing that FDI in services is more likely to be associated with inequality than FDI in other sectors. We argue that skill biases and changes in employment patterns associated with service sector investments can help explain these findings.     

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

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

Economic Growth Evens Out Happiness: Evidence from Six Surveys

In spite of the great U‐turn that saw income inequality rise in Western countries in the 1980s, happiness inequality has fallen in countries that have experienced income growth (but not in those that did not). Modern growth has reduced the share of both the “very unhappy” and the “perfectly happy.” Lower happiness inequality is found both between and within countries, and between and within individuals. Our cross‐country regression results suggest that the extension of various public goods helps to explain this greater happiness homogeneity. This new stylized fact arguably comes as a bonus to the Easterlin paradox, offering a somewhat brighter perspective for developing countries.     

Taking down the wall: Transition and inequality

In this article, we investigate the main determinants of income inequality in the transition countries of Central and Eastern Europe and the Commonwealth of Independent States during the period 1990–2018. To this end, we address a major methodological challenge that lies at the core of the cross‐country literature on income inequality: the potential endogeneity of income per capita, which is largely ignored by most empirical studies. We adopt a two‐pronged empirical strategy by (1) using trading partners’ weighted average real GDP as an instrumental variable and (2) estimating the model via the two‐stage least squares approach for static models and the generalized method of moments estimator for dynamic models. Our empirical findings are consistent with the Kuznets curve that illustrates a nonlinear relationship between income inequality and the level of economic development. We also find that the redistributive impact of fiscal policy is statistically insignificant and taxation and government spending appear to have the opposing effects on income inequality in transition economies over the sample period.     

Income mobility of individuals in China and the United States

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

Policy,Demography, and Market Income Volatility: What Shaped Income Distribution and Inequality in Australia Between 2002 and 2016?

Isolating the impact of policy, demographic shifts, and market volatility on changes in income inequality is of great interest to policymakers. However, such estimation can be difficult due to the complex interactions and evolutions in the social and economic environment. Through an extended decomposition framework, this paper estimates the effect of four main components (policy, demography, market income and other factors) on the year-over-year changes in income inequality in Australia between 2002 and 2016. This was a period marked by substantial policy, population, and economic shifts due to factors such as the mining boom, the global financial crisis and increasing immigration. The framework also incorporates a flexible non-parametric market income model which captures demand-side shock better than a standard parametric model. Our results suggest that market income was the primary driver of income inequality for all segments of the income distribution in Australia over the past 15 years. Policy factors, moreover, have had the largest net impact on reducing inequality overall, especially for lower income earners.     

Why Did Income Inequality in Germany Not Increase Further After 2005?

While income inequality in Germany considerably increased in the years before 2005, this trend stopped after 2005. We address the question of what factors were responsible for the break in the inequality trend after 2005. Our analysis suggests that income inequality in Germany did not continue to rise after 2005 for the following reasons. First, we observe that the general rise in wage inequality that explained a lot of the inequality increase before 2005, became less steep (but did not stop) after 2005. Second, despite further increases in wage inequality after 2005, inequality in annual labour incomes did not increase further after 2005 because increased within‐year employment opportunities compensated otherwise rising inequality in annual labour incomes. Third, income inequality did not fall in a more marked way after 2005 because also the middle and the upper part of the distribution benefited from the employment boom after 2006. Finally, we provide evidence that the effect of a wide range of other factors that are often suspected to have influenced the distribution such as capital incomes, household structures, population ageing, changes in the tax and transfer system and the financial crisis of 2008 did not significantly alter the distribution after 2005.     

The Role of Age and Gender in Educational Expansion: The South Asian Experience in the Global Context

I calculate education Gini coefficients and decompose the overall degree of educational inequality into age, sex, and within‐group components for 171 countries from 1970 to 2010. Doing so enables me to analyze the distributional outcomes of educational expansion. I use South Asia as a case study, as the education distribution in the region is among the most unequal in the world. Generally, educational inequality is decreasing over the observed sample period around the globe. Yet, as improvements are initiated by enhancing the educational opportunities of the young, the gap between cohorts widens in transition phases but vanishes thereafter. Gaps between the sexes are reduced substantially, but widen if either males or females are the first to enter higher education levels. Also, gaps within population subgroups follow a similar trajectory. Instead of a Kuznets‐curve relation, I thus find evidence for educational inequality to evolve in waves as education expands.     

Long term trends in fair and unfair inequality in the United States

This article analyses the microeconomic sources of wage inequality in the United States from 1967–2012. Decomposing inequality into factors categorized by degree of personal responsibility, education explains over twice as much of inequality today as 45 years ago. However, neither hours worked nor education, industry, marital status, or geographical location can explain the rise in income inequality. In fact, ‘unfair’ inequality (income disparity derived from non-responsibility factors) has risen faster than ‘fair’ inequality (income disparity derived from responsibility factors), regardless of the set of variables chosen as fair sources of inequality. We further examine income inequalities within gender and racial groups, finding substantial heterogeneity. Overall, using micro data to understand the sources of inequality and how these changes over time can provide better information for policymakers motivated to combat rising inequality.     

Income Inequality and Political Polarization: Time Series Evidence Over Nine Decades

Rising income inequality and political polarization have led some to hypothesize that the two are causally linked. Properly interpreting such correlations is complicated by multiple factors driving these phenomena, potential feedback between inequality and polarization, measurement issues, and the statistical challenges of modeling non‐stationary variables. We find that a more precise measure of inequality (the inverted Pareto–Lorenz coefficient) is more consistently and statistically related to polarization in the short and long runs than the less precise top 1 percent share of income. We find bi‐directional causality between polarization and inequality, consistent with theoretical conjecture and less formal evidence in previous studies.