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The Use and Misuse of Income Data and Extreme Poverty in the United States

Author

Listed:
  • Bruce D. Meyer
  • Derek Wu
  • Victoria R. Mooers
  • Carla Medalia
Abstract
Recent research suggests that rates of extreme poverty, commonly defined as living on less than $2/person/day, are high and rising in the United States. We re-examine the rate of extreme poverty by linking 2011 data from the Survey of Income and Program Participation and Current Population Survey, the sources of recent extreme poverty estimates, to administrative tax and program data. Of the 3.6 million non-homeless households with survey-reported cash income below $2/person/day, we find that more than 90% are not in extreme poverty once we include in-kind transfers, replace survey reports of earnings and transfer receipt with administrative records, and account for the ownership of substantial assets. More than half of all misclassified households have incomes from the administrative data above the poverty line, and several of the largest misclassified groups appear to be at least middle class based on measures of material well-being. In contrast, the households kept from extreme poverty by in-kind transfers appear to be among the most materially deprived Americans. Nearly 80% of all misclassified households are initially categorized as extreme poor due to errors or omissions in reports of cash income. Of the households remaining in extreme poverty, 90% consist of a single individual. An implication of the low recent extreme poverty rate is that it cannot be substantially higher now due to welfare reform, as many commentators have claimed.

Suggested Citation

  • Bruce D. Meyer & Derek Wu & Victoria R. Mooers & Carla Medalia, 2019. "The Use and Misuse of Income Data and Extreme Poverty in the United States," NBER Working Papers 25907, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:25907
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    Cited by:

    1. Jeff Larrimore & Jake Mortenson & David Splinter, 2020. "Presence and Persistence of Poverty in US Tax Data," NBER Chapters, in: Measuring Distribution and Mobility of Income and Wealth, pages 383-409, National Bureau of Economic Research, Inc.
    2. Jeehoon Han & Bruce D. Meyer & James X. Sullivan, 2020. "Income and Poverty in the COVID-19 Pandemic," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 51(2 (Summer), pages 85-118.
    3. Gaetano Basso & Giovanni Peri, 2020. "Internal Mobility: The Greater Responsiveness of Foreign-Born to Economic Conditions," Journal of Economic Perspectives, American Economic Association, vol. 34(3), pages 77-98, Summer.
    4. Dean Jolliffe & Juan Margitic & Martin Ravallion & Laura Tiehen, 2024. "Food stamps and America's poorest," American Journal of Agricultural Economics, John Wiley & Sons, vol. 106(4), pages 1380-1409, August.
    5. James X. Sullivan, 2020. "A Cautionary Tale of Using Data From the Tail," Demography, Springer;Population Association of America (PAA), vol. 57(6), pages 2361-2368, December.
    6. Meyer, Bruce D. & Mittag, Nikolas, 2021. "An empirical total survey error decomposition using data combination," Journal of Econometrics, Elsevier, vol. 224(2), pages 286-305.
    7. Theloudis, Alexandros, 2021. "Consumption inequality across heterogeneous families," European Economic Review, Elsevier, vol. 136(C).
    8. Aliprantis, Dionissi & Carroll, Daniel R. & Young, Eric R., 2024. "What explains neighborhood sorting by income and race?," Journal of Urban Economics, Elsevier, vol. 141(C).
    9. James X. Sullivan, 2020. "Another Plea for Caution When Using Survey Income Data From the Far-Left Tail," Demography, Springer;Population Association of America (PAA), vol. 57(6), pages 2377-2381, December.
    10. Yixia Cai & Timothy Smeeding, 2019. "Deep and Extreme Child Poverty in Rich and Poor Nations: Lessons from Atkinson for the Fight Against Child Poverty," LIS Working papers 780, LIS Cross-National Data Center in Luxembourg.
    11. John Iceland & Claire Kovach & John Creamer, 2021. "Poverty and the Incidence of Material Hardship, Revisited," Social Science Quarterly, Southwestern Social Science Association, vol. 102(1), pages 585-617, January.
    12. David Brady & Zachary Parolin, 2020. "Further Analyses Reinforce Our Conclusions About Extreme Poverty," Demography, Springer;Population Association of America (PAA), vol. 57(6), pages 2369-2376, December.
    13. Yixia Cai & Timothy Smeeding, 2020. "Deep and Extreme Child Poverty in Rich and Poor Nations: Lessons from Atkinson for the Fight Against Child Poverty," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 6(1), pages 109-128, March.
    14. Vincent A. Fusaro & David Seith, 2024. "When Cash Safety Nets Fade: SNAP-Participating Households with Children Without Cash Income," Journal of Family and Economic Issues, Springer, vol. 45(2), pages 470-483, June.

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    More about this item

    JEL classification:

    • C42 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Survey Methods
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • I38 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Government Programs; Provision and Effects of Welfare Programs

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