2017
DOI: 10.1080/2330443x.2017.1360813
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Is the Gini Index of Inequality Overly Sensitive to Changes in the Middle of the Income Distribution?

Abstract: The Gini index is the most commonly used measure of income inequality. Like any single summary measure of a set of data, it cannot capture all aspects that are of interest to researchers. One of its widely reported flaws is that it is supposed to be overly sensitive to changes in the middle of the distribution. By studying the effect of small transfers between households or an additional increment in income going to one member of the population on the value of the index, this claim is reexamined. It turns out … Show more

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Cited by 37 publications
(15 citation statements)
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“…Gini coefficients range from 0 (perfectly proportionate distribution) to 1 (perfectly disproportionate distribution). While there is some debate about the strengths and limitations of Gini as a metric of inequality (Gastwirth 2017), it is the most commonly used measure of inequality in the production of pollution literature. Industry membership is defined using the 2012 six-digit NAICS code, a field included within the TRI database.…”
Section: Methodsmentioning
confidence: 99%
“…Gini coefficients range from 0 (perfectly proportionate distribution) to 1 (perfectly disproportionate distribution). While there is some debate about the strengths and limitations of Gini as a metric of inequality (Gastwirth 2017), it is the most commonly used measure of inequality in the production of pollution literature. Industry membership is defined using the 2012 six-digit NAICS code, a field included within the TRI database.…”
Section: Methodsmentioning
confidence: 99%
“…For instance, falls in overall poverty levels in England have not been experienced equally among all demographic groups, 62 while the measure of income inequality used in our analyses (the Gini coefficient) has been criticised as being insufficiently sensitive to change. 63 We have been unable to locate evidence specifically for people with mental health problems regarding change over time in levels of unemployment, work precarity, disposable income, benefits sanctions, living alone or similar variables, with which to interrogate our hypotheses in more depth. Eighth, we used a single source of data for each population-level indicator used as potential explanatory variables, to allow comparisons of change over time.…”
Section: Discussionmentioning
confidence: 99%
“…Second, the Gini approach cannot pinpoint the underlying reasons for voting differences across provinces (for example, whether it is a compositional effect, provincial effect, and so forth). Third, although the Gini method has become the most common measure of nationalization, there are debates regarding whether it should be standardized to account for the number and size of jurisdictions (see Bochsler, 2010; Golosov, 2016; Jones and Mainwaring, 2003) and whether the measure is overly sensitive to changes in the middle of the distribution (see Gastwirth, 2017). Finally, the measures of supply and demand presented here are not completely independent of one another: a party can win votes only where it fields a candidate; parties are most likely to field candidates where they think they will win votes; and the more candidates a party fields, the more votes it will win.…”
Section: Discussionmentioning
confidence: 99%