A note on the relationship between top income shares and the Gini coefficient

Alvaredo, Facundo

doi:10.1016/j.econlet.2010.10.008

Cited by 155 publications

(147 citation statements)

References 7 publications

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“…The usual, if not exclusive, focus on equivalised disposable incomes 5 may hide from view 2. This applies in spite of the fact that Gini coefficients and top-income shares may correlate to some extent (Leigh 2007;Alvaredo 2011). 3.…”

Section: Introductionmentioning

confidence: 95%

“…The top-incomes project (Atkinson/Piketty 2007), the OECD (2008;2011), and the GINI research project ) all find growing inequality in many countries (albeit not all and not always). Most of the attention goes to the very top (the top 1 per cent and smaller fractions): very small numbers with extreme riches, especially since Piketty (2014) has succeeded in adding the distribution of wealth, which is much more uneven than the income distribution, to the public debate.…”

Section: Introductionmentioning

confidence: 99%

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Individual earnings and household incomes: mutually reinforcing inequalities?

Salverda

2015

EJEEP

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Inequality's rise and impacts deservedly receive much attention in scientific and public debates, with most of the attention being paid to the very top of the income or wealth distribution. This contribution complements this with a study of the broader top -the top 10 per cent -where labour-market outcomes play a predominant role. However, the analysis still needs to come to terms with the death of the singlebreadwinner model and its replacement with two or more earners in the household. At the same time this brings in the (household distribution of) hours of work as an important new dimension of inequality, in addition to the traditional wage levels. It will be shown, using data for 26 EU countries, that these changes complicate the linkages of wage inequality and income inequality and add to the importance of employee earnings for income inequality. For this analysis, aggregate inequality measures will be put aside in favour of a more detailed consideration across the distributions of earnings and incomes. Some implications for analysis and policy are discussed in the conclusion.

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Section: Introductionmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

Individual earnings and household incomes: mutually reinforcing inequalities?

Salverda

2015

EJEEP

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“…The Gini coefficient developed by Corrado Gini as a way to quantify [39,40] and frequently used index to determine the difference of income distribution in economics [41,42], representing the distribution of social wealth in the static surface [43,44]. Standard application of the Gini coefficient is to show income distribution across groups through time [45].…”

Section: Methodsologiesmentioning

confidence: 99%

Inequality of Carbon Intensity: Empirical Analysis of China 2000–2014

Jiang

2017

Sustainability

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Abstract:On the 3 September 2016, China officially ratified the Paris agreement as the main global producer of carbon emissions. A key of China's commitment is to reduce its carbon intensity by 60-65% between 2005 and 2030. An improved understanding of the inequality of carbon intensity at national-, inter-regional-, and intra-regional scale is a prerequisite for the development of a more cost-effective carbon intensity reduction policy. In this study, we used the Dagum Gini coefficient and its subgroup decomposition method to quantify China's inequality of carbon intensity between 2000 and 2014 based on available and updated data. The results show: (i) The Gini coefficient indicates a rising inequality of the carbon intensity at both national and sub-national scale, suggesting accelerated inequality of carbon intensity at national-, inter-regional, and intra-regional-scale.(ii) The Gini coefficient indicates a rising trend of intra-regional carbon intensity in Central and Western China, while the trend declines for Eastern China. (iii) The Gini coefficient indicates rising carbon intensity between Eastern and Central China, Western and Eastern China, and Central and Western China. (iv) Transvariation intensity occupies a leading role in the increasing national-level carbon intensity Gini coefficient. Ultimately, several policy recommendations are provided.

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“…G, the most commonly-used measure of inequality, is more sensitive to assessing the differentiation of total income [24,25].…”

Section: Assessment Measuresmentioning

confidence: 99%

Spatio-Temporal Characteristics of Rural Economic Development in Eastern Coastal China

Wang

et al. 2015

Sustainability

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Although the regional differences of rural economic development can be easily determined, a challenging problem for research studies regarding rural economic development has been the inter-relatedness between different areas, and this challenge has been noted remarkably little in research data to date. As an empirical investigation, this study analyzes the spatio-temporal characteristics of rural economic development from a period beginning in 1978 to the year 2012, in the eastern coastal region of China. In order to determine the special differentiation characteristics of rural economic development, three indexes, namely the Gini coefficient (G), Tsui-Wang index (TW) and Theil index (T), were employed. To explore the inter-relatedness among the different areas, we selected a spatial autocorrelation model. The results indicated that, to a large extent, rural economic development from 1978 to 2012 in the eastern coastal region of China was greatly influenced, and the per capita annual net income changed significantly, due to the process of rapid urbanization and industrialization. Generally speaking, the annual net income constantly increased, from 87.7 USD in 1978 to 1628.1 USD in 2012. However, the calculation results indicated that the per capita income gap in the same province decreased, while the gap between the provinces presented an aggregate trend. The regional polarization widened continuously. It was also found that the spatial positive autocorrelation for the regional economy was significant, with a waving and ascending trend, and the neighbor effect of regional economic growth was continuously strengthened. Qualitative analysis of the driving mechanism was applied, and it was determined that there are three primary factors affecting the development of the rural regions, namely resource endowments, economic location and policies. OPEN ACCESSSustainability 2015, 7 1543

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A note on the relationship between top income shares and the Gini coefficient

Cited by 155 publications

References 7 publications

Individual earnings and household incomes: mutually reinforcing inequalities?

Individual earnings and household incomes: mutually reinforcing inequalities?

Inequality of Carbon Intensity: Empirical Analysis of China 2000–2014

Spatio-Temporal Characteristics of Rural Economic Development in Eastern Coastal China

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