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Race, Ethnicity, and Measurement Error

Author

Listed:
  • Meyer, Bruce D.

    (University of Chicago)

  • Mittag, Nikolas

    (CERGE-EI)

  • Wu, Derek

    (University of Virginia)

Abstract

Large literatures have analyzed racial and ethnic disparities in economic outcomes and access to the safety net. For such analyses that rely on survey data, it is crucial that survey accuracy does not vary by race and ethnicity. Otherwise, the observed disparities may be confounded by differences in survey error. In this paper, we review existing studies that use linked data to assess the reporting of key programs (including SNAP, Social Security, Unemployment Insurance, TANF, Medicaid, Medicare, and private pensions) in major Census Bureau surveys, aiming to extract the evidence on differences in survey accuracy by race and ethnicity. Our key finding is a strong and robust, but previously largely unnoticed, pattern of greater measurement error for Black and Hispanic individuals and households relative to whites. As the dominant error is under-reporting for a wide variety of programs, samples, and surveys, the implication is that the safety net better supports minority groups than the survey data suggest, through higher program receipt and greater poverty reduction. These biases in survey estimates are large in many cases examined in the literature. We conclude that racial and ethnic minorities are inadequately served by our large household surveys and that researchers should cautiously interpret survey-based estimates of racial and ethnic differences in program receipt and post-benefit income. We briefly discuss paths forward.

Suggested Citation

  • Meyer, Bruce D. & Mittag, Nikolas & Wu, Derek, 2024. "Race, Ethnicity, and Measurement Error," IZA Discussion Papers 17349, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp17349
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    References listed on IDEAS

    as
    1. Celhay, Pablo & Meyer, Bruce D. & Mittag, Nikolas, 2021. "Errors in Reporting and Imputation of Government Benefits and Their Implications," IZA Discussion Papers 14396, Institute of Labor Economics (IZA).
    2. Raj Chetty & Nathaniel Hendren & Maggie R Jones & Sonya R Porter, 2020. "Race and Economic Opportunity in the United States: an Intergenerational Perspective [“Intergenerational Mobility of Immigrants in the US Over Two Centuries,”]," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 135(2), pages 711-783.
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    4. Randall Akee & Maggie R. Jones & Sonya R. Porter, 2019. "Race Matters: Income Shares, Income Inequality, and Income Mobility for All U.S. Races," Demography, Springer;Population Association of America (PAA), vol. 56(3), pages 999-1021, June.
    5. Charles Courtemanche & Augustine Denteh & Rusty Tchernis, 2019. "Estimating the Associations between SNAP and Food Insecurity, Obesity, and Food Purchases with Imperfect Administrative Measures of Participation," Southern Economic Journal, John Wiley & Sons, vol. 86(1), pages 202-228, July.
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    7. Elira Kuka & Bryan A. Stuart, 2021. "Racial Inequality in Unemployment Insurance Receipt and Take-Up," NBER Working Papers 29595, National Bureau of Economic Research, Inc.
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    More about this item

    Keywords

    race; ethnicity; survey error; safety net; government programs;
    All these keywords.

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • 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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