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Inequality in the Developing World

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Nguyễn Gia Hào

Academic year: 2023

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The institute's mandate is to conduct applied research and policy analysis of structural changes affecting developing and transition economies, to provide a forum to promote policies leading to robust, equitable and environmentally sustainable growth, and to promote capacity building and education in economic and social policy. World Institute for Development Economics Research at the United Nations University (UNU-WIDER), Katajanokanlaituri 6B, 00160 Helsinki, Finland. Inequality is at the heart of the UN's mandate and is one of the seventeen goals of the 2030 Agenda for Sustainable Development.

While global inequality generally declined towards the end of the twentieth century, inequality within countries has risen steadily since the turn of the century, providing the basis for intense public and academic debate, to the extent that it has become a mainstream policy issue of many countries and across multilateral agencies. In turn, the WIID increased the volume of the voice for analytical research into disparities between countries and within countries. The team developed the preliminary set of notes from this meeting into a five-page draft research proposal originally intended for nine of the world's largest countries (Brazil, China, France, India, Mexico, Russia, South Africa, the UK, and the US).

Finn Tarp, then Director of UNU-WIDER, was invited to join the team, and a large number of potential project collaborators were invited to a workshop on the sidelines of the UNU-WIDER Mapping the Future of Development Economics conference held in Helsinki on 17-19 more than 40 percent of the world's population and attitudes towards global issues of inequality.

INEQUALIT Y IN A BROADER CONTEXT 10. Economic Inequality and Subjective Well-Being Across the World 233

SYNTHESIS AND POLICY IMPLICATIONS

Clark is director of research at CNRS and professor of economics at the Paris School of Economics. Andrej Cupak works as a data expert and research associate at the LIS Cross-National Data Center in Luxembourg. Conchita D'Ambrosio is Professor of Economics at the Department of Behavioral and Cognitive Sciences at the University of Luxembourg.

Murray Leibbrandt holds the National Research Foundation Chair in Poverty and Inequality Research at the University of Cape Town and is a senior research fellow of UNU-WIDER. Teresa Munzi is Director of Operations of the LIS Cross-National Data Center in Luxembourg, where she is responsible for managing and overseeing all activities in the LIS office. Vimal Ranchhod is a professor at the School of Economics and deputy director of the Labor and Development research unit in Southern Africa.

He is co-chair of the High-Level Expert Group on the Measurement of Economic Performance and Social Progress at the OECD. Finn Tarp is a professor of development economics at the University of Copenhagen and was director of UNU-WIDER from 2009 to 2018.

INTRODUCTION

This idea, which had its roots in the work of the classical economists of the eighteenth century, generally. 1 Project results can be accessed at www.wider.unu.edu/project/inequality-giants. Using these rich data sources, various decomposition techniques and the use of regression analyzes facilitated the identification of the main drivers of inequality.

This is extremely important, and unlike the measurement and analysis of poverty, a focus on inequality requires the inclusion of the full distribution of well-being. Whether the country has already started moving along the downward part of the Kuznets curve will depend on the direction of future reforms. This is linked to rising labor market inequality and to strong returns to capital income sources found only at the top of the income distribution.

Economic Mobility Across Generations Around the World', a 2018 World Bank report, which was one of the first attempts to analyze the critical issue of social mobility in the developing world. Read alongside the detailed interrogations of global and national inequalities in the preceding chapters, this chapter provides a grounded platform for discussing the policies needed to address inequality and promote inclusive development in the contemporary world.

GLOBAL INEQUALITY AND INEQUALITY

Average growth rate (annual difference in logs) Growth in relative inequality (annual difference in relative log Gini index). Indeed, inequality is falling in half (59/119) of the countries with positive growth on average in Figure 2.3. PPPs are systematically revised from time to time in light of new price surveys across countries (as used to estimate PPPs) and methodological changes.

This is a source of downward bias in the prevailing measures of the between-country component of global inequality. Milanovic (2013) and Lakner and Milanovic (2016a) provide an informative picture of the development of income distribution in the world. This is an implication that there is no Lorenz dominance in Figure 2.6.27.

For the purposes of this chapter, Figure 2.7a shows an update of the estimates in Ravallion (2016b). The decline after 2007 was gradual for the share of the top 10 percent, but sudden for the share of the top 1 percent, which was concentrated in 2008 and 2009. Here we use the shares of the top 10 percent and the top 1 percent and the Gini coefficient.

Differences between the inequality trends for income and wealth are most evident in the series for the share of the top 1 percent. For the Gini coefficient, the between-country component is approximately twice the level of the within-country term. As might be expected, disaggregating the share of the top 1 percent gives a very different outcome.

For the share of the top 1 per cent. there is even evidence that the rise in wealth inequality accelerated in the wake of the global financial crisis. Broadly speaking, the size of the (negative) between-country component is roughly double the contribution of the (positive) within-country component, although the contributions are equal (and thus almost net to zero) for the share of the top 1 per cent. To make it easier for the reader, we briefly recall the definition of the main inequality indicators we will use in the analysis.

The income shares observed in Figure 4.6 show that most of the gains from growth went to the richest 10 percent (although the LIS data underestimate this share due to the inability to capture the highest incomes as detectable when compared to the WID top income data). While the income shares of the top 10 percent show a downward trend in the LIS survey data, tax records show.

Figure 2.1 shows the series of global inequality measures from Bourguignon (2016).
Figure 2.1 shows the series of global inequality measures from Bourguignon (2016).

INEQUALITY IN FIVE DEVELOPING GIANTS

1 The Brazilian component of the UNU-WIDER project Inequality in the Giants consists of seven studies co-authored by Marcelo Neri (FGV, lead), Tiago Bonomo (FGV), Marcos Hecksher (IPEA), Cecilia Machado (FGV), Valdemar Neto (FGV), JoséFioPeori (FGV), JoséFioPeori (Camera) and Rozane Siqueira (UFPE). In these studies, we provide a description and an interpretation of the main causes of changes in income distribution in Brazil in the last twenty-five years. The rest of the chapter attempts to fill in the gaps about changes in income distribution in the previous literature.

Combining them with household surveys gives a clearer picture of the upper end of the income distribution. A difference of -2.60 percent in favor of the bottom 40% of the population is a useful measure of equality trends. The vast majority of the empirical literature on income distribution in developing countries uses household surveys.3 Brazil established this tradition in the early 1970s.

Once again, fixed effects explain most (75.9 per cent) of the drop in inequality observed between 2001 and 2015. The basic model with basic socio-demographic categories explains 25.8 per cent. In 2015, 2.9 percent of the (weighted) sample had a household income per inhabitant changed by the imputation procedure.

After the combination of PNAD and PIT, the poorest 60 percent of the adult population continued to increase their share of total income. This article summarizes the main results of the Brazilian component of the UNUWIDER project 'Inequality in the Giants'. Most of the decline in inequality was driven by income inequality, which has been dominated by corporate effects, at least in the formal sector.

Minimum wage increases have had a direct effect on fiscal accounts without much impact on the lower end of the income distribution. This pattern is evident in the growth incidence curves of household income per capita between various rounds of the CHIP survey (Figure 6.2). After that, the effects of the one-child policy began to set in, causing a noticeable slowdown in growth in the labor supply after 2000.

Poverty in Palanpur was widespread in the early years of the survey—in the 1950s and 1960s, more than 80 percent of the population was classified as poor. In a recent global study, Narayan et al. 2018) identifies India as the country with the lowest rates of intergenerational mobility in the world.

Figure 6.1  China’s Gini coefficient
Figure 6.1 China’s Gini coefficient

Hình ảnh

Figure 2.1 shows the series of global inequality measures from Bourguignon (2016).
Figure 2.2   Inequality within the developing world Source: Author’s calculations using PovcalNet.
Figure 2.3 provides an update to Ravallion (2004) using an extra ten or more  years of survey data, thus capturing the higher growth rates we have seen since  2000; the median date of the second survey in the 144 spells is 2012
Figure 2.4  Global inequality for various weights on (log) national mean income Source: Based on Ravallion (2018b).
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