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The aim of this paper is to extend a theoretical model due to Ljungqvist and data from a sample of 19 developing economies to empirically test it.

Data for all variables are from the 2005 Human Development Report and the 2006 World Development Report. The author applies the least‐squares estimation technique in a multivariate linear regression.

Based on data from the World Bank and the United Nations Development Programme, the paper uses a sample of 19 developing economies and finds that cross‐country variations in income/consumption inequality may be explained by inequality of investment in human capital as measured by inequalities in child health as well as inequality in education and by inequality in the distribution of land as measured by the land Gini index.

Assuming a population consisting of skilled laborers, unskilled laborers, educators/health care personnel, and farmers, the paper shows that starting from an initial distribution of assets and in the absence of a perfect capital market along with human capital exhibiting increasing returns it is possible to have persistent inequality in the distribution of income or consumption. Regression results also are consistent with the theoretical implication of the model as the extent of inequality in land distribution and in access to education as well as inequalities in child health do linearly influence income or consumption inequality as measured by the ratio of the share of income or consumption accounted for by the richest quintile to that of the poorest quintile. As a result, if governments in developing countries aim to reduce inequality, they need to implement programs designed to reduce inequalities in child health by allowing children from the poorest of the poor to get fully immunized, which in turn would lead to a reduction in infant and child mortality and in education by providing low‐income families with means so that their children have better access to education. Government land policies, on the other hand, that succeed in reducing inequality in land distribution in developing countries, may be beneficial in terms of lessening income/expenditure inequality. Finally, while the present model does not test for the impact that improving capital markets would have, it stands to reason that improving capital markets could also have an impact on decreasing inequality.

In this paper the author uses a model due to Ljungqvist to show that individuals are relatively wealthy because they either own a fixed input such as land or they are able to invest in human capital, which in turn allow them to earn sufficient rent or labor income to remain wealthy. On the other hand, poor people either do not own land or are not capable of investing in human capital, and, as a result, earn low incomes and remain poor. This joint causation of factor endowment or human capital investment and income helps explain income distribution. Using data from the United Nations Development Programme and the World Bank for a sample of 19 developing economies, it is found that cross‐country variations in income/consumption inequality may be explained by inequality of investment in human capital as measured by inequalities in child health as well as well as inequality in education and by inequality in the distribution of land as measured by the land Gini index. These results will help governments in developing countries identify areas that need to be improved upon in order to reduce income/consumption inequality.

This chapter examines the impact of education on income inequality in 18 Latin American countries between 2000 and 2010. This period has raised interest in the academic community because inequality has fallen across the region, after several years of consistent high levels. Employing the novel technique proposed by Firpo, Fortin, and Lemieux (2007), the author’s research provides a detailed decomposition of inequality. Three main findings emerge from the author’s results: First, the expansion of education increases inequality in six countries but reduces inequality in four countries. Second, the changes in returns to education are the driving component of the effects of education on inequality. Those countries where education contributes to a fall in inequality are those where the returns to education fell at the top of the income distribution. Third, the rise in the average years of education, considered alone, had an inequality-increasing effect in most of the countries under analysis.

Does education still serve as a great equalizer today? Does today’s worldwide expansion of schooling foster a global economic convergence? These questions need fresh answers at this time of growing concern over inequality. Past studies have abundantly documented the effects of schooling on within-country inequality, but we know little about corresponding effects on between-country inequality. We fill this gap by drawing on two innovations. The first is to formulate a theory of global inequality that integrates international differences in both the quantity and quality of education. The second, methodological, innovation is to propose and apply a method for decomposing trends in global inequality in GDP in terms of five social forces that include the quantity and quality of schooling. Analyses focus on the 1990–2010 period. The results confirm the continued salience of education: Trends in education account for as much as 80% of the 1990–2010 decline in between-country GDP inequality. However, we find a declining significance of “quantity” over “quality.” In sum, education remains salient as a global equalizer but its salience increasingly depends on bridging international differences in school quality.

In large parts of the world, income inequality has been rising in recent decades. Other regions have experienced declining trends in income inequality. This raises the question of which mechanisms underlie contrasting observed trends in income inequality around the globe. To address this research question in an empirical analysis at the aggregate level, we examine a global sample of 73 countries between 1981 and 2010, studying a broad set of drivers to investigate their interaction and influence on income inequality. Within this broad approach, we are interested in the heterogeneity of income inequality determinants across world regions and along the income distribution. Our findings indicate the existence of a small set of systematic drivers across the global sample of countries. Declining labour income shares and increasing imports from high-income countries significantly contribute to increasing income inequality, while taxation and imports from low-income countries exert countervailing effects. Our study reveals the region-specific impacts of technological change, financial globalisation, domestic financial deepening and public social spending. Most importantly, we do not find systematic evidence of education’s equalising effect across high- and low-income countries. Our results are largely robust to changing the underlying sources of income Ginis, but looking at different segments of income distribution reveals heterogeneous effects.

The aim is to assess how a policy of tertiary education for all affects the shape of the unconditional earnings distribution.

The paper discusses the quantile-regression literature looking at the link between education and wage inequality, also proving new evidence based on unconditional quantile regressions.

The findings support the idea that a policy of tertiary education for all increases the overall level of wage inequality.

The research has implications for public policy and administration. Among the limitations, the paper does not deal with distributional aspects related to other outcomes (e.g. health outcomes) of the policy of interest.

The analysis highlights a series of potential government interventions aimed at reducing the wage-inequality externalities of the policy of interest.

A policy of tertiary education for all, by itself, is not useful to fight wage inequality.

This paper belongs to the small group of studies using unconditional quantile regressions to study the link between education and wage inequality. It is the first study specifically looking at the distributional effects of a policy of tertiary education for all.

The purpose of the paper is to examine the nature and extent of gender and spatial inequalities in educational attainment in Ghana.

The paper uses the education Gini coefficient, computed on the basis of years of schooling of individuals, to assess education inequality in Ghana.

The paper finds evidence of gender and spatial inequality in education in Ghana. In particular, the three northern regions have lower education attainment as well as higher education Gini coefficients compared to the rest of the country. The paper finds evidence of intra‐gender and intra‐spatial inequalities in education attainment in Ghana, with females contributing proportionately more to the within‐inequality component of the education Gini. The paper also finds a positive correlation between poverty incidence and education inequality.

The research finds a positive correlation between poverty incidence and education inequality but requires an econometric analysis to make inferences regarding causality.

The findings call for the design and implementation of policies not only to address between‐gender and spatial inequities in education in Ghana, but also to tackle within‐gender and within‐spatial inequalities. The positive correlation between poverty incidence and education inequality implies the need to create greater equity in educational opportunities across the country.

The need for changes in attitudes, values and cultural practices that put girls at a disadvantage when it comes to education.

One important and new finding of the paper is the existence of intra‐gender and intra‐spatial inequalities in education attainment in Ghana, with females contributing proportionately more to the within‐inequality component of the education Gini.

The objectives of this study are threefold: firstly, to measure the impact of educational inequality on income inequality, and per capita income; secondly, to measure the impact of gender inequality in education on income inequality, per capita income and educational inequality; and lastly, to test the Kuznets inverted U-shape hypothesis between inequality in education and average year of schooling.

The study has adopted the Marin and Psacharopoulos (1976) model of human capital in which income earned by an individual can be estimated as a function of number of year spent in schooling or education. Gini coefficient is used as a measure of income inequality, while inequality in education is measured by Gini index of educational inequality. Gender inequality in education is measured by the difference between male and female enrolment ratios as a proportion of male enrolment. The study utilizes the data of six South Asian countries, i.e. Bangladesh, India, Maldives, Nepal, Pakistan and Sri Lanka from 1980 to 2010 at five-year average and employs fixed effect model (FEM) and random effect model (REM) for estimation.

Result suggests that educational inequality and average year of schooling have positive and significant impact on income inequality. Primary (basic) education and tertiary (higher) education reduce income inequality, while secondary education widens income inequality. Negative relationship exists between educational inequality and per capita income. Unequal distribution of education among boys and girls at primary level increases income inequality, while reduces income inequality at tertiary level. Gender inequality in secondary and tertiary level of education reduces per capita income, while unequal distribution of education among boys and girls further increases the educational inequality. Kuznets inverted U-shape hypothesis does not hold between education expansion and educational inequality, while weak U-shape relationship exists in South Asian countries.

Government has to provide free education in poor regions and makes employment programs to reduce the income and educational inequality respectively, while to remove gender inequality in education it is necessary to build more schools especially for girls. Government has to launch different online education programs for expansion in education at all levels.

This study adds to the literature by analyzing whether the inequality in income increases (decreases) due to increase (decrease) in educational and gender inequality in South Asian countries. This study contributes in the existing literature by developing a measure of educational and gender inequality in education in South Asian countries.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-04-2020-0226.

The purpose of this paper is to measure inequality in education and examine how socioeconomic factors affect education inequality in Albania and Nepal.

Using large household survey data sets the authors calculate income-related inequality in education and decompose the inequality into factors that determine educational attainment. The decomposition procedure establishes the role played by two sets of factors: elasticities of education demand with respect to its determinants; and inequalities in those determinants. The paper then proposes a new mechanism to quantify the effects of policy simulations regarding income, urbanization, and distance to school on education inequality.

Both the countries show significant inequality in education. Educational attainment in Albania and Nepal is determined by socioeconomic, demographic and geographic factors of which three are particularly significant in affecting inequality – income, urbanization and distance to school.

While schooling for most individuals is largely financed by public subsidy in the countries, attainment is also likely affected by the price of education services and cost of health care. Identification of those factors in the context of more comprehensive data will enable researchers in future to draw firmer conclusions.

The proposed method can help to identify cost-effective and sustainable policies to reduce socioeconomic inequality in education in developing countries.

Reduction in education inequality can lead to higher income and better health which are instrumental in uplifting the poor in developing countries.

This is the first paper to measure education inequality using a concentration index and to propose a new mechanism to show the effect of simulated policies on education inequality.

Despite the rapid progress and developments in education and health all over the world, gender inequality is still an important issue in many parts of the world. Girls benefit less from education opportunities than boys, and it causes gender inequality. The same situation is also valid for health. While gender inequality is still an issue even in developed countries, it is more serious in the least developed and developing countries. Therefore, there is a need to reduce gender inequality through government intervention. The aim of this study is to examine the effect of government's health and education expenditures on gender inequality in the least developed and developing countries with panel data analysis. The study covers 24 countries for the 2010–2017 period. As a result of the analysis, it has been observed that the government's health expenditures reduce gender inequality, while education expenditures increase gender inequality. This finding indicates that education expenditures of governments do not reach girls in the least developed and developing countries. However, GDP per capita is the most important factor in reducing gender inequality.

The reduction of income inequality and the ways to fight against it are source of debate among scientific communities and policymakers. Rents from natural resources that African countries are endowed with remain one way to cope with income inequality, but its influence on income inequality is mixed. Thus, the purpose of this paper is to explore the direct and indirect transmission mechanisms through which natural resources rents can affect income inequality in sub-Saharan Africa.

This study obtained data on income inequality from the Standardised World Income Inequality Data database, natural resources rents from World Bank’s Development Indicators and education from United Nations Development Programme for the period 1990–2018. It was analysed using system generalised method of moments.

The results of this study showed that natural resources rents solely increased income inequality, but its interaction with education significantly reduced income inequality.

These findings suggest that the reduction of income inequality by natural resources rents passes through a good education system in sub-Saharan African countries.

In previous studies, authors analysed the role of education in the relationship between natural resources rents and income inequality by inserting the two variables separately in the model. But in this paper, the author analysed the role of education in the relationship between natural resources rents and income inequality by using the interaction of natural resources rents and education.