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Why is Poverty Higher in Rural America According to the Supplemental Poverty Measure? An Investigation of the Geographic Adjustment

Population Research and Policy Review volume 39, pages 941–975 (2020)Cite this article

A Correction to this article was published on 09 October 2020

This article has been updated

Abstract

Poverty is a key indicator of economic hardship. By providing a geographic adjustment for cost of living, the recently developed Supplemental Poverty Measure has upended long-held views that poverty is higher in rural compared to urban America. In this study, we unpack the geographic adjustment underlying the Supplemental Poverty Measure and find that most of the difference is explained by the median rent index component rather than the housing tenure component. Further, we find that six states (Alabama, Georgia, Kentucky, Mississippi, North Carolina, and Ohio) account for over a third of the nonmetro poverty drop due to the median rent adjustment. We demonstrate that the demographic composition of the rural poor remains relatively unaffected despite this large drop, but find that the prevalence of poverty within demographic groups varies considerably. As a result, while the SPM is largely considered a more complete measure of poverty, the use of the median rent adjustment has important implications for the demographic understanding of rural poverty.

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Change history

  • 09 October 2020

    In the original publication of this article, the article title has been mentioned incorrectly. The correct title provided in this correction.

Notes

  1. Of note, although the OPM thresholds rely on the food budget and is multiplied by three, they are designed to measure the cost of all necessary goods and services; the SPM thresholds represent only the food, shelter, clothing, utilities, and miscellaneous goods. “Important adjustments are made to the resources to reflect other “necessary” expenses that are not included in the SPM thresholds, including taxes, work-related expenses and medical out-of-pocket expenses. These items would have to be added to the SPM thresholds or subtracted from the official thresholds before comparing the two amounts [OPM thresholds and SPM thresholds] (Renwick 2011, p. 11).”

  2. Some have argued against any geographic adjustment, see (Nolan et al. 2017).

  3. See https://www.bls.gov/pir/spm/spm_shares_200518.xlsx.

  4. See https://www.bls.gov/pir/spm/spm_threshold_200518.xlsx.

  5. Other factors include spatially concentrated rural poverty; persistent poverty; work and poverty (e.g., the growth of the working poor); and, access to public welfare and the safety net.

  6. A review of employment, human capital, and the safety net are beyond the scope of this paper, however, critical for understanding poverty in rural America. For example, research has shown an increasing share of the rural poor are out of work (Thiede et al. 2018) and the labor market has provided nonmetro families less protection from poverty compared to metro areas (Slack 2010). Multiple accounts show the safety net programs as a whole, lift greater percentages of rural families out of poverty relative to urban (Nolan et al. 2017; Rothwell and Thiede 2018; Ziliak 2018).

  7. Note that the published SPM rate differs from the PUMS SPM rates.

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Acknowledgements

We are thankful for excellent feedback from participants and organizers of the Annie E. Casey Foundation RUPRI Rural Poverty Research & Policy Fellowship Roundtable Madison, IN May 2019. We are especially thankful for the cartographic help of Jonathan Schroeder and David Van Riper.

Funding

This research supported by funding from the Annie E. Casey Foundation RUPRI Rural Poverty Research & Policy Fellowship, the Agricultural Experiment Station multistate project W4001, support from the Minnesota Population Center (P2C HD041023) funded through a grant from the Eunice Kennedy Shriver National Institute for Child Health and Human Development (NICHD).

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Authors and Affiliations

  1. Institute for Social Research and Data Innovation, University of Minnesota, Minneapolis, USA

    José D. Pacas

  2. School of Social and Behavioral Health Sciences, Oregon State University, Corvallis, USA

    David W. Rothwell

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  1. José D. Pacas
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  2. David W. Rothwell
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Correspondence to José D. Pacas.

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Appendix

Appendix

See Tables

Table 5 Effect of housing tenure and median rent index adjustments on drop in metro-nonmetro poverty rate—2015–2017
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Table 6 Poverty rates and gaps for different demographic groups under different median rent index adjustments, US—2015–2017
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Table 7 Demographic distribution of nonmetro poor under different median rent index adjustment, North Carolina—2015–2017
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Table 8 Demographic distribution of nonmetro poor under different median rent index adjustment, New Mexico—2015–2017
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Table 9 Poverty rates and gaps for different demographic groups under different median rent index adjustments, North Carolina—2015–2017
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Table 10 Poverty rates and gaps for different demographic groups under different median rent index adjustments, New Mexico—2015–2017
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Table 11 Median gross rent, population distribution of nonmetro North Carolina by county—2013–2017
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Table 12 Median gross rent and population distribution of nonmetro New Mexico by county—2013–2017
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Pacas, J.D., Rothwell, D.W. Why is Poverty Higher in Rural America According to the Supplemental Poverty Measure? An Investigation of the Geographic Adjustment. Popul Res Policy Rev 39, 941–975 (2020). https://doi.org/10.1007/s11113-020-09612-9

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Keywords

  • Poverty
  • Supplemental poverty measure
  • Rural
  • Geography