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The size distribution of income, or income inequality, has long been a concern to scholars in many disciplines tor different reasons. Statisticians have approached the distribution of income among individuals as a stochastic process. Economists have sought to explain income distribution by means, of economic and institutional factors. More recently, economists have been interested in the effects of economic growth and government policies on income distribution. Sociologists and political scientists have thought of income inequality as a major source of social revolt or political violence.

Cross-country studies have shown that higher costs to starting a business tend to reduce entrepreneurship (Chambers and Munemo, 2019) and that an unfavorable environment for business can increase poverty and income inequality (Chambers et al., 2019a; Djankov et al., 2018). Building on the current literature, the authors test whether barriers to starting a business at the state and city level in the USA are associated with changes in entrepreneurship and income inequality.

Measures of entrepreneurship (establishment entry rate and exit rate) are regressed on measures of barriers to entry in a cross-section of 50 states as well as a cross-section of 73 cities in the USA. Further, the authors regress measures of income inequality on measures of barriers to entry using the same two cross-sections. State level data on barriers to entry are from Teague (2016), published in the Journal of Entrepreneurship and Public Policy. City level data on barriers to starting a business are from the Doing Business in North America (DBNA) dataset.

Results show that there is a negative and significant association between barriers to starting a business and the rate of firm exit. A standard deviation increase in barriers to entry is associated with a five percent decrease in the firm exit rate at the state level. The authors find only limited evidence that barriers to entry are associated with income inequality.

Despite a large volume of scholarship on how regulation and barriers to entry influence entrepreneurship, no study (to the authors’ knowledge) has investigated how general entry regulation affects the entry or exit rate of establishments at the state or municipal level in the USA.

This paper empirically examines the inequalities related to social class and income using individual self‐reported health status data. Health inequalities are estimated by different indexes using individual standardised and unstandardised health status data. The population was divided into income and social class, respectively. From this two main results are obtatined: inequalities are sensitive to the health status variable and the social position variable employed. It was found that significant health related social class inequalities were insignificant when income was employed as a reference variable.

Measures of inequality determine the effectiveness of social and economic policies aimed at reducing inequality and to design effective intervention policies. The purpose of this paper is to focus on poverty reduction and welfare improving impacts of reducing income inequality in the case of Fiji. Using Fiji's Household Income and Expenditure Survey 2002‐2003, a comprehensive analysis is used to measure the level of inequality by household income, quintile income distribution, decomposition of inequality by ethnicity and regional groups, and the household income inequality by source of income.

Several statistical techniques have been applied to investigate the degree of inequality in the household income. These include the Gini coefficient, the Nelson ratio, the concentration index and the Atkinson index. An evaluation by ethnicity, regions and household income sources reflects the level of inequality, and concerns for policies and governance.

The results show that urban households, in particular, experience greater inequalities, in both positive and normative terms. The Indo‐Fijian households experience greater income inequalities than the Fijian households. Decomposition results for the separate factor income components also indicate major sources of inequality. These findings clearly establish that Fiji still has a long way to go in reducing the income gaps between the rich and the poor in both rural and urban households.

The paper is a first study that estimates various measures of inequality in the case of Fiji. The implication of the empirical findings suggests that Fiji is unlikely to achieve its Millennium Development Goal of halving poverty rate by 2015 due to the large income differentials by ethnicity and in the urban‐rural areas.

The purpose of this paper is to aim at taking a closer look at the decline in the inequality of the distribution of four health variables, infant and child mortality, child stunting and underweight, that took place in various Southeast Asian countries during the past 25 years. More specifically its goal is to check the extent to which this decline in health inequality, as well as the overall reduction in infant and child mortality, in child stunting and underweight, affected the poorest wealth quintile of the population of these countries.

In the first part of the paper the author presents a systematic comparison of the values taken by various consistent measures of the inequality of health attainments and shortfalls for several countries in Southeast Asia and for four health indicators: infant mortality, child mortality, child stunting and underweight. The second part of the paper uses the concept of Shapley decomposition to determine the respective impacts of the decrease in the average value of these health variables and in the inequality of their distribution on the reduction observed for each of these variables in the lowest wealth quintile.

During the period examined there was an important decline infant and child mortality as well as in child stunting and underweight in all countries of Southeast Asia for which data were available. As far as the poorest wealth quintile is concerned this decline was mostly the consequence of the overall decline in these health variables rather than to the reduction of the inequality of their distribution.

Data were available for only four health variables and for many countries data were available for only one period.

A decline in health inequality should be considered as an important aspect of poverty reduction.

Development should not be limited to its economic components. A broader view of development is indispensable.

This study is probably one of the first ones to provide the reader with data on the reduction in health inequality in Southeast Asia as well as on the impact of this decline on the poorest wealth quintile.

This article aims to measure inequality of income and opportunities at the national and state levels in Brazil, highlighting their acceptable and unacceptable components.

To this end, a lower-bound estimate of income inequality (MLD) and inequality of opportunity (IOp) was developed using data from the National Household Sample Survey between 2001 and 2014.

It shows that the disparity of income measured by the MLD decreased 26.7 percent, while IOp measured by the IOp decreased 25.6 percent during that period. The decline in total inequality can be attributed to a 48.5 percent decrease of its unfair component and 51.5 percent decrease of its fair component. The average income of the most disadvantaged group (non-white women working in the informal sector) is shown to be only 29.5 percent of the income of the most advantaged group (formally employed white men). The groups at the greatest disadvantage were most benefited by the increase in income.

Beyond comparisons among countries, analysis at the subnational level make it possible to identify how the process that generates inequality acts in each state, revealing patterns undetected in the aggregate analysis. Its decomposition generates two products that are useful to policy-makers. The first is a base estimate of the degree of IOp present in society, which may be expressed as an indicator of the degree of IOp. The second examines the portion of total inequality attributable to IOp.

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 paper uses a lifetime income simulation model to examine the effects on inequality and progressivity of extending the time period over which income is measured. The income tax schedule typically displays increasing marginal rates, and there is a substantial amount of relative income mobility, along with a systematic variation in average incomes over the life cycle of the cohort. Simulations show that progressivity and inequality measures can often move in opposite directions, both over time for annual accounting periods, and as the length of period is gradually increased. The relationship between summary measures is complicated by the role of the aggregate tax ratio, in addition to the re‐ranking that can occur in the larger period framework. Some tax structures are found to increase in progressivity, while others show less progressivity, as the time period increases. Re‐ranking is found to increase as the accounting period increases: it is higher and increases more rapidly as the accounting period is increased for tax structures displaying more steeply rising rate structures.

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.

With the recognition that generating economic growth is not the same as sustaining it, the challenge to catch-up and growth literature is discerning between these processes. Recent research suggests that the decline in the frequency of “shrinking” episodes is more important for long-term development than higher growth rates. By using a framework centred around social capabilities, this study aims to investigate the effects of income inequality and poverty on economic shrinking frequency, as opposed to previous literature that has exclusively had a growth focus. The aim is to investigate how and why some societies might be more resilient to economic shrinking.

The research is a quantitative study, and the authors build a longitudinal data set including 23 developing countries throughout 42 years to test the paper’s purpose. This study uses country and period fixed-effects specifications as well as cross-sectional graphical representations to investigate the relationship between proxies of economic inclusivity and the frequency of shrinking episodes.

The authors demonstrate that while inclusive societies are more resilient to shrinking overall, it is changes in poverty levels, but not changes in income inequality, that appear to be correlated with economic shrinking frequency. Inequality, while still an important element to explain countries’ growth potential as an initial condition, does not seem to make the sample more resilient to shrinking. The authors conclude that the mechanisms in which poverty and inequality are correlated with the catch-up process must run through different channels. Ultimately, processes that explain growth may intersect but not always overlap with the ones that explain resilience to shrinking.

The need for inclusive growth in long-term development has been championed for decades, yet inclusion has seldom been explored from the shrinking perspective. Though poverty reduction is already an important mainstream political objective, this paper differentiates itself by providing an alternate viewpoint of why this is important. Income inequality could have more of an economic growth limiting effect, while poverty reduction could be required to build resilience to economic shrinking. Developing countries will need both growth and resilience to shrinking, to catch-up with higher-income economies, which policymakers might need to balance carefully.