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The present study aims to determine the existence of simultaneous relationship between economic growth, income inequality, fiscal policy, and total trade of the 13 emerging market economies as a group for the period 1980–2010. After establishing the existence of simultaneity between the above relationships, a simultaneous panel model has been formulated and estimated incorporating the nonlinearity among the variables as suggested by the existing literature. An inverted U-shape relationship is evident between (1) economic growth, income inequality, and total trade in economic growth equation, (2) income inequality, economic growth, and per capita income in income inequality equation, and (3) total trade and economic growth in total trade equation. Thus, the existence of a two-way nonlinear relationship is highlighted between economic growth, income inequality, and total trade. Apart from these nonlinear relationships, positive and significant effect of (1) gross capital formation, inflation, population growth, human capital, fiscal policy, monetary policy, and domestic credit to private sector on economic growth; (2) civil liabilities on income inequality; (3) gross capital formation and inflation on total trade; (4) total trade, population growth of those aged 65 years and above, political system on fiscal policy is highlighted. Also, negative and significant effect of (1) fiscal policy on income inequality and (2) income inequality on fiscal policy is revealed.

Using decomposable measures of inequality, the implications of household structure are investigated by examining inequality between and within household groups based on the number of exemptions, which correlates with household size, and the filing status, which correlates with the common forms of household structure, i.e. married, single, head of household. Detailed household income data are used to measure income inequality for both pre-tax/transfer and post-tax/transfer definitions of income. These decompositions provide information about the degree of inequality, both before and after taxes and transfers, which is due to household size and filing status. The bootstrap is employed to construct standard errors for the inequality measures and their decompositions, and hypothesis tests are conducted to determine whether the observed changes in the distribution of income are statistically significant.

The catch word “Globalization” has been defended by advocates for lifting people out of poverty and the inequality in the world. But it has been criticized by opponents for failing to solve the problem of poverty, inequality, and for increasingly creating wealth disparity. This raises the question. The fact is that the contemporary world exhibits very high levels of inequality of income and wealth both between countries and within countries. Wealth inequality is more pronounced than that of income inequality across the globe and within-countries. Evidence suggests that rising inequality and wealth disparity arising out of globalization drive is choking off the potential benefits to the poor. In this backdrop, a composite assessment has been made in the present chapter to answer the question “whether globalization with its particular ideology, the market fundamentalism has benefited many and whether the performance on the distributional front has really been impressive.” From facts and evidence, the study finds that inequalities in income and wealth, also in wages have widened in many developed, developing developed, and developing countries. Technological change and globalization are their main sources.

The financial crisis of 2008 and ensuing recession led to falls in earnings in the United Kingdom, not seen since the Great Depression of the 1930s, and it was only in 2014 that overall household income returned to its pre-crisis levels. At the same time, according to one official measure, income inequality has actually fallen, although different data indicate no change. This situation follows from several factors, notably the continued growth in pensions, higher earnings of lower-income households as these have worked more since the recovery in 2013, and the continued stagnation of earnings in higher income households (even if very high incomes have continued to pull away from the rest of the population). Incomes of younger workers also remain below their pre-crisis peak. This chapter shows, however, that the picture of poverty and inequality in the United Kingdom is far more complex than suggested by the main measure of income inequality. To this end, it begins by reviewing the definitions of poverty and inequality, in order to provide a broader overview of these pressing but complex social problems. The chapter goes on to examine wealth inequalities, the impact of housing costs on inequality and poverty, and it concludes by presenting recent studies suggesting that Brexit may well lead to future rises in inequality, as higher inflation could well hit lower-income households most.

In the United States, there is little difference in annual income inequality and income mobility between the rural and urban sectors of the economy. This forms a sharp contrast with China where income inequality is greater and income mobility lower among rural households than among urban households. When incomes are averaged over three years and when adjustments are made for the size and composition of households, income inequality among all households differs little between China and the United States in the 1990s. Moreover when pooling rural households and urban households and when measuring annual income inequality and income mobility of the pooled households, the mobility of incomes of households in the United States differs little from that in China. Social welfare functions are posited that allow for a trade-off between increases in income and increases in income inequality. These suggest strong increases in well-being for urban households in China. The corresponding changes in rural China and in the United States are smaller. Four sets of data on households are drawn on to document these findings.

This paper produces a comprehensive assessment of income redistribution to the working-age population, covering OECD countries over the last two decades. Redistribution is quantified as the relative reduction in market income inequality achieved by personal income taxes (PIT), employees’ social security contributions, and cash transfers, based on household-level micro-data. A detailed decomposition analysis uncovers the respective roles of size, tax progressivity, and transfer targeting for overall redistribution, the respective role of various categories of transfers for transfer redistribution; as well as redistribution for various income groups. The paper shows a widespread decline in redistribution across the OECD, both on average and in the majority of countries for which data going back to the mid-1990s are available. This was primarily associated with a decline in cash transfer redistribution while PIT played a less important and more heterogeneous role across countries. In turn, the decline in the redistributive effect of cash transfers reflected a decline in their size and in particular by less redistributive insurance transfers. In some countries, this was mitigated by more redistributive assistance transfers but the resulting increase in the targeting of total transfers was not sufficient to prevent transfer redistribution from declining.

Although economic and entrepreneurship scholars have argued that high income inequality has a positive impact on entrepreneurship by increasing the incentives for high quality human capital to take entrepreneurial risk and by enabling talented entrepreneurs to accumulate and reinvest capital into new businesses, we suggest that the relationship between economic inequality and entrepreneurship may be more complex than initially indicated in light of recent research on the topic of social trust and entrepreneurship. We propose that income inequality is likely to have a curvilinear effect on entrepreneurial activity. Although moderate levels of inequality can increase entrepreneurial activity, very high levels of inequality will begin to reduce rates of entrepreneurship due to diminished generalized social trust in the community. Lower generalized social trust decreases the sharing of information and resources leading to fewer entrepreneurial opportunities, and as a result, lower levels of entrepreneurship.

This chapter presents an investigation into the theory of labour market segmentation and income inequality in the Ghanaian mining sector. Mining activity especially gold mining has been a significant component of exports as well as employment and income earning in the three major mining regions of Ghana. While income growth is an economic benefit, the high incomes associated with the mining sector may lead to greater income inequality. This chapter provides an analysis of mining activity and income inequality in the Western, Eastern, and Ashanti regions of Ghana. The application of labour market segmentation and the Gini coefficient (a measure of inequality) for personal income are found to be significantly associated with the type and levels of mining employment. However, this observation is not linear as income inequality initially increases with mining activity before decreasing at medium to high levels of mining employment, thus following a Kuznets curve pattern. Segregating datasets for indigenous and expatriate staff reveals very different patterns of income inequality. It poignantly increases with indigenous and/or local community personnel relative to expatriate technical personnel at high levels of mining employment; income inequality is lower among the local community residents relative to nationals from other regions and/or from neighbouring countries. This means segmented labour markets (SLM) within the mining industry are likely to be a problem as they result in increased income inequality among locales relative to foreign expatriates.

The authors study the difference between multidimensional well-being inequality and income inequality and propose a method to decompose the difference between the Gini coefficients of income and equivalent income (EI), a multidimensional well-being measure that respects individual preferences towards what constitutes a good life. The authors propose a method to decompose the inequality difference into two parts: the vertical and reranking effects. The vertical effect arises from the correlation between income and non-income dimensions, and between income and preferences. The reranking effect arises from the fact that some persons occupy a different position in the EI distribution compared to the income distribution. The authors also propose a detailed decomposition method based on the Shapley value to decompose each of the two effects by non-income dimensions. The authors apply the decompositions using data for 27 countries, considering five non-income dimensions: unemployment, health, housing, crime and environment. The results show that inequality is much higher for EI that the reranking effect accounts for a large part of the inequality difference, and that health is the non-income dimension contributing most to both effects.

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.