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I Dream of Gini: Measures of Population Concentration and Their Application to US Population Distribution

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

5 Scopus citations

Abstract

The unevenness of population across space may be captured with various measures of inequality; the Lorenz curve, the Gini coefficient, and the Hoover index constitute prime examples of such measures. In this chapter, I first review the history of these measures and then provide a selective review of their use in examining population concentration and deconcentration. Next, I show how the Gini coefficient may be disaggregated to show how population concentration varies within different ranges of population densities. The Gini coefficient is written as a weighted sum of the Hoover indexes for each population density category, where the weights are the proportion of total area in that density category. This disaggregation is applied to the US population for the period 2000–2015. Results show that population deconcentration is occurring among the subset of counties that have high population density and concentration is occurring among counties that have medium population density.

Original languageEnglish
Title of host publicationNew Frontiers in Regional Science
Subtitle of host publicationAsian Perspectives
PublisherSpringer
Pages1-17
Number of pages17
DOIs
StatePublished - 2019

Publication series

NameNew Frontiers in Regional Science: Asian Perspectives
Volume40
ISSN (Print)2199-5974
ISSN (Electronic)2199-5982

Keywords

  • Gini coefficient
  • Hoover index
  • Population deconcentration

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