Income Inequality Around the World: Volume 44

Cover of Income Inequality Around the World

Table of contents

(12 chapters)
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Preface

Pages ix-xii
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Abstract

We present a comparison of coverage and values for five inequality data sets that have worldwide or major international coverage and independent measurements that are intended to present consistent coefficients that can be compared directly across countries and time. The comparison data sets are those published by the Luxembourg Income Studies (LIS), the OECD, the European Union’s Statistics on Incomes and Living Conditions (EU-SILC), and the World Bank’s World Development Indicators (WDI). The baseline comparison is with our own Estimated Household Income Inequality (EHII) data set of the University of Texas Inequality Project. The comparison shows the historical depth and range of EHII and its broad compatibility with LIS, OECD, and EU-SILC, as well as problems with using the WDI for any cross-country comparative purpose. The comparison excludes the large World Incomes Inequality Database (WIID) of UNU-WIDER and the Standardized World Income Inequality Database (SWIID) of Frederick Solt; the former is a bibliographic collection and the latter is based on imputations drawn, in part, from EHII and the other sources used here.

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Between 1995 and 2012, the wage distribution of male workers in Brazil shifted to the right and became less dispersed. This paper attempts to identify the reasons for that movement in male wage distribution, focusing on the impact of education expansion on wage distribution. The Oaxaca-Blinder (OB) and Recentered Influence Function (RIF) decomposition results show that both changes in returns on skills and upgrades in the composition of work skills contribute to increases in the average wage and wages at the 10th and 50th percentiles. The shifts in returns to skills had a decreasing impact on wages at the 90th percentile and are identified as the primary force reducing wage inequality. Education expansion had an equalizing impact on wage distribution, primarily through the decline in return to education.

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This paper argues that the assumption of a homogeneous workforce, which is implicitly invoked in the decomposition analysis of changes in welfare indicators, hides the role that schooling and its returns may have on the understanding of these changes. Using Peruvian cross-sectional data for a period of 10 years (2004–2013) and counterfactual simulations, this paper finds that the main factor contributing to poverty reduction has been individuals’ changes in labor earnings, and the role of these changes has been less important in reducing income inequality. The main driving force of reduced income inequality has been the fall in returns to education, which at the same time has been one of the important factors to constraining the period’s remarkable progress in poverty reduction and expansion of the middle class.

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We investigate the reasons why income inequality is so high in Spain in the EU context. We first show that the differential in inequality with Germany and other countries is driven by inequality among households who participate in the labor market. Then, we conduct an analysis of different household income aggregates. We also decompose the inter-country gap in inequality into characteristics and coefficients effects using regressions of the Recentered Influence Function for the Gini index. Our results show that the higher inequality observed in Spain is largely associated with lower employment rates, higher incidence of self-employment, lower attained education, as well as the recent increase in the immigration of economically active households. However, the prevalence of extended families in Spain contributes to reducing inequality by diversifying income sources, with retirement pensions playing an important role. Finally, by comparing the situations in 2008 and 2012, we separate the direct effects of the Great Recession on employment and unemployment benefits, from other more permanent factors (such as the weak redistributive effect of taxes and family or housing allowances, or the roles of education and the extended family).

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The minimum wage has been regarded as an important element of public policy for reducing poverty and inequality. Increasing the minimum wage is supposed to raise earnings for millions of low-wage workers and therefore lower earnings inequality. However, there is no consensus in the existing literature from industrialized countries regarding whether increasing the minimum wage has helped lower earnings inequality. China has recently exhibited rapid economic growth and widening earnings inequality. Since China promulgated new minimum wage regulations in 2004, the magnitude and frequency of changes in the minimum wage have been substantial, both over time and across jurisdictions. The growing importance of research on the relationship between the minimum wage and earnings inequality and its controversial nature have sparked heated debate in China, highlighting the importance of rigorous research to inform evidence-based policy making. We investigate the contribution of the minimum wage to the well-documented rise in earnings inequality in China from 2004 to 2009 by using city-level minimum wage panel data and a representative Chinese household survey, and we find that increasing the minimum wage reduces inequality – by decreasing the earnings gap between the median and the bottom decile – over the analysis period.

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Using longitudinal datasets from Chile and Nicaragua, we compare intragenerational earnings mobility over a decade for two economies with similar inequality levels but divergent positions in equality of opportunities within the Latin American region. Our results suggest that earnings mobility, in terms of origin independence of individual ranking in the earnings distribution, is greater in Chile than in Nicaragua.

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Cover of Income Inequality Around the World
DOI
10.1108/S0147-9121201644
Publication date
2016-08-27
Book series
Research in Labor Economics
Editors
Series copyright holder
Emerald Publishing Limited
ISBN
978-1-78560-943-5
Book series ISSN
0147-9121