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

  • Peter A. RogersonEmail author
Part of the New Frontiers in Regional Science: Asian Perspectives book series (NFRSASIPER, volume 40)


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.


Gini coefficient Hoover index Population deconcentration 



I would like to thank Xiang Ye for his assistance with the figures.


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© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Departments of Geography and Biostatistics, Wilkeson HallUniversity at BuffaloBuffaloUSA

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