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More Likely to Be Poor Whatever the Measure: Working-Age Persons with Disabilities in the United States

Author

Listed:
  • Debra L. Brucker
  • Sophie Mitra
  • Navena Chaitoo
  • Joseph Mauro

Abstract

type="main"> This article examines whether disability is a correlate of poverty when poverty is measured using (1) the official poverty measure; (2) the supplemental poverty measure (SPM); and (3) two multidimensional poverty measures created by the authors. Data from the Current Population Survey are used to explore the relationship between poverty and disability for each measure. Differences across disability status were tested for statistical significance. Disability is associated with poverty, irrespective of the poverty measure under use. The gap in poverty rates between persons with and without disabilities is smaller when using the SPM as compared to the official poverty measure. The gap in poverty rates between persons with and without disabilities is highest when using multidimensional poverty measures. Working-age persons with disabilities are more likely to be poor whatever the measure under use. They are a disadvantaged group in the United States.

Suggested Citation

  • Debra L. Brucker & Sophie Mitra & Navena Chaitoo & Joseph Mauro, 2015. "More Likely to Be Poor Whatever the Measure: Working-Age Persons with Disabilities in the United States," Social Science Quarterly, Southwestern Social Science Association, vol. 96(1), pages 273-296, March.
    • Handle: RePEc:bla:socsci:v:96:y:2015:i:1:p:273-296
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    References listed on IDEAS

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    Cited by:

    1. Katie M. Jajtner & Sophie Mitra & Christine Fountain & Austin Nichols, 2020. "Rising Income Inequality Through a Disability Lens: Trends in the United States 1981–2018," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 151(1), pages 81-114, August.
    2. Brandon Vick, 2020. "Measuring Multi-Dimensional Deprivation Among U.S. Veterans," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 150(1), pages 191-218, July.
    3. Nicola Fortune & Bernadette Curryer & Hannah Badland & Jennifer Smith-Merry & Alexandra Devine & Roger J. Stancliffe & Eric Emerson & Gwynnyth Llewellyn, 2022. "Do Area-Level Environmental Factors Influence Employment for People with Disability? A Scoping Review," IJERPH, MDPI, vol. 19(15), pages 1-16, July.
    4. Sophie Mitra & Debra Brucker, 2019. "Monitoring multidimensional poverty in the United States," Economics Bulletin, AccessEcon, vol. 39(2), pages 1272-1293.
    5. Maître, Bertrand & Curristan, Sarah & Russell, Sarah, 2022. "Intergenerational poverty in Ireland," Research Series, Economic and Social Research Institute (ESRI), number RS150, June.
    6. Nicola Fortune & Ankur Singh & Hannah Badland & Roger J. Stancliffe & Gwynnyth Llewellyn, 2020. "Area-Level Associations between Built Environment Characteristics and Disability Prevalence in Australia: An Ecological Analysis," IJERPH, MDPI, vol. 17(21), pages 1-15, October.
    7. Bruno Cheli & Achille Lemmi & Nicoletta Pannuzi & Andrea Regoli, 2019. "From the TFR to the IFR approach for the multidimensional analysis of poverty and living conditions," Discussion Papers 2019/252, Dipartimento di Economia e Management (DEM), University of Pisa, Pisa, Italy.
    8. Jack Gettens & Alexis Henry, "undated". "Making Ends Meet: How Low-Income DI Beneficiaries Meet Their Needs," Mathematica Policy Research Reports 074a72cac45146fdbd8db37e1, Mathematica Policy Research.
    9. Katie M Jajtner, 2020. "Work‐Limiting Disability and Intergenerational Economic Mobility," Social Science Quarterly, Southwestern Social Science Association, vol. 101(5), pages 2001-2016, September.

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