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Patterns of Multidimensional Poverty in the United States

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  • David C. Folch
  • Matthew Laird

Abstract

The accurate accounting of where and for whom deprivations occur is fundamental to addressing poverty. In the United States, the official poverty measure considers only a person’s income, although poverty is increasingly understood internationally as a set of multiple, interlinked deprivations. This article introduces a decomposable multidimensional poverty (MDP) measure that addresses these shortcomings by using thirteen American Community Survey microdata indicators to identify education, health, housing, and economic security deprivations for individuals. In 2017, the national poverty rate was 13.7 percent when measured using MDP and 13.1 percent using official poverty. Although similar at the national scale, Hispanic, Asian, and older persons had higher poverty rates using the multidimensional measure, whereas Black and young persons had higher rates when using official poverty. MDP tended to be higher than official poverty in dense urban areas, whereas official poverty tended to be higher in rural areas. Further, MDP was a stronger correlate with COVID-19 death rates than official poverty through the first three waves of the pandemic. The design of MDP recognizes that individuals can experience poverty in different ways and provides a more holistic view of people and places.

Suggested Citation

  • David C. Folch & Matthew Laird, 2024. "Patterns of Multidimensional Poverty in the United States," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 114(2), pages 387-407, February.
  • Handle: RePEc:taf:raagxx:v:114:y:2024:i:2:p:387-407
    DOI: 10.1080/24694452.2023.2265984
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