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Estimating the Potential Impact of Combined Race and Ethnicity Reporting on Long-Term Earnings Statistics

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  • Kevin L. McKinney
  • John M. Abowd

Abstract

We use place of birth information from the Social Security Administration linked to earnings data from the Longitudinal Employer-Household Dynamics Program and detailed race and ethnicity data from the 2010 Census to study how long-term earnings differentials vary by place of birth for different self-identified race and ethnicity categories. We focus on foreign-born persons from countries that are heavily Hispanic and from countries in the Middle East and North Africa (MENA). We find substantial heterogeneity of long-term earnings differentials within country of birth, some of which will be difficult to detect when the reporting format changes from the current two-question version to the new single-question version because they depend on self-identifications that place the individual in two distinct categories within the single-question format, specifically, Hispanic and White or Black, and MENA and White or Black. We also study the USA-born children of these same immigrants. Long-term earnings differences for the 2nd generation also vary as a function of self-identified ethnicity and race in ways that changing to the single-question format could affect.

Suggested Citation

  • Kevin L. McKinney & John M. Abowd, 2024. "Estimating the Potential Impact of Combined Race and Ethnicity Reporting on Long-Term Earnings Statistics," NBER Working Papers 32758, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:32758
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    1. Deborah Wagner & Mary Lane, 2014. "The Person Identification Validation System (PVS): Applying the Center for Administrative Records Research and Applications’ (CARRA) Record Linkage Software," CARRA Working Papers 2014-01, Center for Economic Studies, U.S. Census Bureau.
    2. John M. Abowd & Bryce E. Stephens & Lars Vilhuber & Fredrik Andersson & Kevin L. McKinney & Marc Roemer & Simon Woodcock, 2009. "The LEHD Infrastructure Files and the Creation of the Quarterly Workforce Indicators," NBER Chapters, in: Producer Dynamics: New Evidence from Micro Data, pages 149-230, National Bureau of Economic Research, Inc.
    3. Hahn, Joyce K. & Hyatt, Henry R. & Janicki, Hubert P., 2021. "Job ladders and growth in earnings, hours, and wages," European Economic Review, Elsevier, vol. 133(C).
    4. Sonya Ravindranath Waddell & John M. Abowd & Camille Busette & Mark Hugo Lopez, 2022. "Measuring race in US economic statistics: what do we know?," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 57(4), pages 181-190, October.
    5. John M. Abowd & Kevin L. McKinney & Nellie L. Zhao, 2018. "Earnings Inequality and Mobility Trends in the United States: Nationally Representative Estimates from Longitudinally Linked Employer-Employee Data," Journal of Labor Economics, University of Chicago Press, vol. 36(S1), pages 183-300.
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    More about this item

    JEL classification:

    • J15 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Minorities, Races, Indigenous Peoples, and Immigrants; Non-labor Discrimination
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

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