Skip to main content
SpringerLink
Log in

The Enduring Significance of Ethno-Racial Inequalities in Poverty in the U.S., 1993–2017

Population Research and Policy Review volume 41, pages 1049–1083 (2022)Cite this article

Abstract

Ethno-racial inequality in poverty is an enduring but misunderstood problem. Most prior research relies on the flawed official poverty measure, data with underreported income, and models omitting essential predictors. Using the Current Population Survey, we adjust for benefit underreporting and estimate levels and trends in both relative and Supplemental Poverty Measure poverty rates for ethno-racial groups relative to White individuals in the U.S. from 1993 to 2017. We then focus on the five most recent years (2013–2017) and decompose Black–White, Latino–White, and Asian–White poverty gaps. We expand prior decomposition analyses by better incorporating employment and geographic context and better measuring immigration. Our findings show ethno-racial inequalities in poverty declined from 1993 to 2017 but remained large. Our estimates of relative poverty reveal that millions more Black and Latino individuals are poor than with the official measure—even after adjusting for benefit underreporting. By 2013–2017, Black and Latino individuals remain about twice as likely to be poor as White individuals. By contrast, the evidence is mixed on Asian–White differences. Decomposition results show employment explains the largest share of the Black–White gap, whereas immigration matters most for the Latino–White and Asian–White gaps. Geographical context also explains a significant portion of each racial gap and is particularly central to Asian–White gaps. Compared to prior decompositions, which would explain roughly half of the Black–White gap in poverty, our models explain more than three quarters. Beyond the novel empirical description, this study encourages structural, political, and critical race theories of poverty over behavioral explanations.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

USD 39.95

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Fig. 1
Fig. 2

Notes

  1. To this point, a recent controversial commentary in Society, “Poverty and Culture” by Lawrence Mead (2020) led national poverty center directors to write a public statement calling for a correction of the lack of understanding of racial inequality in poverty. See https://www.irp.wisc.edu/a-statement-from-former-directors-of-the-institute-for-research-on-poverty-about-research-on-poverty-and-race/.

  2. Specifically, we use the Urban Institute’s Transfer Income Model, version 3 (TRIM3) imputations to account for underreporting of means-tested income transfers such as Supplemental Nutrition Assistance Program (SNAP) and Social Security Insurance (SSI). We provide more details in the Methods section below. A description of the TRIM3 model is available online at http://trim3.urban.org/.

  3. The CPS ASEC refers to individuals from Latin American countries as “Hispanic.” We use the term “Latino” to signify that these individuals are of Latin American origins rather than from any Spanish-speaking country (“Hispanic”).

  4. For example, the OPM counts Old Age Survivor’s Insurance and Temporary Assistance for Needy Families (TANF) as income, but omits near cash benefits like the Supplemental Nutritional Assistance Plan (SNAP), housing subsidies, childcare vouchers, and tax credits like the Earned Income Tax Credit (EITC). By 2017, SNAP and EITC were each more than four times as large as TANF. Unfortunately, even when using more defensible relative measures, scholars tend to continue to use the OPM’s flawed definition of income (Iceland, 2019; Takei & Sakamoto, 2011; Thiede et al., 2017).

  5. We follow Golash-Boza’s (2016) definition of racism as both an ideology (i.e., the idea humans can be separated into distinct biology groups and can be hierarchically ordered) and structure (i.e., the micro- and macro-level practices that subordinate those groups believed to be inferior).

  6. While Asians have also experienced employment discrimination, this has lessened in the Post-Civil Rights era (Hilger, 2016), particularly relative to Blacks and Latinos.

  7. TRIM3 matches administrative records on TANF/SNAP caseloads across states to impute benefits back into the survey data. While the uncorrected CPS survey data misses about half of TANF/SNAP cash transfers (Meyer & Mittag, 2019), Parolin (2019a) demonstrates that the unadjusted CPS in 2015 fails to account for 47.4% of SNAP benefits, 54.6% of TANF benefits, and 11.5% of SSI benefits. In contrast, the TRIM3-adjusted CPS captures 88.7% of SNAP benefits, 85.2% of TANF benefits, and 98.1% of SSI benefits in 2015. The TRIM3 is, thus, a substantial improvement over the uncorrected CPS.

  8. Iceland (2019) includes most of these variables. However, we advantageously identify the lead earner rather than the arbitrarily identified household head. Smaller differences are that he controls for sex, only includes age and age squared, distinguishes between high school degrees and some college, and controls for household size but omits the count of over 65 members. None of these change our conclusions. Larger differences—and clear advantages of our measures—are his omission of employment and measuring geographical context only with dummies for four regions and a binary measure of residing in a metro area. Despite arguing family structure is pivotal for the Black–White gap, he only measures whether a household is a female-headed family or “other family” (reference = married couple). Despite arguing immigration is pivotal for the Latino–White gap, he omits citizenship status, and only measures nativity.

  9. In analyses not shown, we experimented with estimating the decompositions on three-year rather than five-year moving averages across the entire period. We found the results were sensitive to business cycles (e.g., unsurprisingly, employment became less important when only including good economic years), hence we used a broader time window.

  10. For instance, Appendix Table 7 in 2017 shows with the OPM, Black individuals are 249% more likely to be poor than Whites individuals, Latino individuals are 215% more likely, and Asian individuals are 118% more likely.

  11. Similarly, using the OPM, Iceland (2019) finds the White-Asian difference in poverty to be too small to meaningfully decompose in his models of 1979 and 2015.

References

  • Albrecht, D. E., Albrecht, C. M., & Murguia, E. (2005). Minority concentration, disadvantage, and inequality in the nonmetropolitan United States. Sociological Quarterly, 46(3), 503–523.

    Article  Google Scholar 

  • Allard, S. W. (2017). Places in need: The changing geography of poverty. Russell Sage Foundation.

    Google Scholar 

  • Amato, P. R., & Maynard, R. A. (2007). Decreasing nonmarital births and strengthening marriage to reduce poverty. The Future of Children, 17(2), 117–141.

    Article  Google Scholar 

  • Baker, R. S. (2015). The changing association among marriage, work, and child poverty in the United States, 1974–2010. Journal of Marriage and Family, 77(5), 1166–1178.

    Article  Google Scholar 

  • Baker, R. S. (2020). Why is the American South Poorer? Social Forces, 99(1), 126–154.

    Article  Google Scholar 

  • Bane, M. J., & Ellwood, D. T. (1986). Slipping into and out of poverty: The dynamics of spells. The Journal of Human Resources, 21, 1–23.

    Article  Google Scholar 

  • Bany, J. A., Robnett, B., & Feliciano, C. (2014). Gendered black exclusion: The persistence of racial stereotypes among daters. Race Social Problems, 6(3), 201–213.

    Article  Google Scholar 

  • Billingsley, A. (1994). Climbing Jacob’s Ladder: The enduring legacies of African-American families. Simon and Schuster.

    Google Scholar 

  • Bloome, D., & Muller, C. (2015). Tenancy and African american marriage in the Postbellum South. Demography, 52(5), 1409–1430.

    Article  Google Scholar 

  • Bloome, D., & Ang, S. (2020). Marriage and Union Formation in the United States: Recent trends across racial groups and economic backgrounds. Demography, 57(5), 1753–1786.

    Article  Google Scholar 

  • Brady, D. (2019). Theories of the causes of poverty. Annual Review of Sociology, 45, 155–175.

    Article  Google Scholar 

  • Brady, D., Finnigan, R., & Hübgen, S. (2017). Rethinking the risks of poverty: A framework for analyzing and comparing prevalences and penalties. American Journal of Sociology, 123(3), 740–786.

    Article  Google Scholar 

  • Brown, S. L. (2010). Marriage and child well-being: Research and policy perspectives. Journal of Marriage and Family, 72(5), 1059–1077.

    Article  Google Scholar 

  • Bryant, C. M., Wickrama, K. A. S., Bolland, J., Bryant, B. M., Cutrona, C. E., & Stanik, C. E. (2010). Race matters, even in marriage: Identifying factors linked to marital outcomes for African Americans. Journal of Family Theory & Review, 2(3), 157–174.

    Article  Google Scholar 

  • Calnitsky, D. (2018). Structural and individualistic theories of poverty. Sociology Compass, 12(5), e12640. https://doi.org/10.1111/soc4.12640

    Article  Google Scholar 

  • Chen, W.-H., & Corak, M. (2006). Child poverty and changes in child poverty. Demography, 45, 537–553.

    Article  Google Scholar 

  • Choi, K. H., & Tienda, M. (2017). Marriage-market constraints and mate-selection behavior: Racial, ethnic, and gender differences in intermarriage. Journal of Marriage and Family, 79(2), 301–317.

    Article  Google Scholar 

  • Citro, C. F., & Michael, R. T. (1995). Measuring poverty: A new approach. The National Academies Press.

    Google Scholar 

  • Clark, K. B. (1965). Dark Ghetto. Harper and Row.

    Google Scholar 

  • Cohen, P. N., & Pepin, J. R. (2018). Unequal marriage markets: sex ratios and first marriage among black and white women. Socius: Sociological Research for a Dynamic World, 4, 1–10.

    Article  Google Scholar 

  • Council of Economic Advisers. (2014). The war on poverty 50 years later: A progress report. Executive Office of the President, Washington, D.C. https://obamawhitehouse.archives.gov/sites/default/files/docs/50th_anniversary_cea_report_-_final_post_embargo.pdf.

  • Cross, C. J. (2020). Racial/ethnic differences in the association between family structure and children’s education. Journal of Marriage and Family, 82(2), 691–712.

    Article  Google Scholar 

  • Curtis, K. J., & O’Connell, H. A. (2017). Historical racial contexts and contemporary spatial differences in racial inequality. Spatial Demography, 5(2), 73–97.

    Article  Google Scholar 

  • Eads, A., & Tach, L. (2016). Wealth and inequality in the stability of romantic relationships. RSF: the Russell Sage Foundation Journal of the Social Sciences, 2(6), 197–224.

    Article  Google Scholar 

  • Eggebeen, D. J., & Lichter, D. T. (1991). Race, family structure, and changing poverty among American children. American Sociological Review, 56(6), 801–817.

    Article  Google Scholar 

  • Ellwood, D. T., & Jencks, C. (2004). The uneven spread of single-parent families: what do we know? Where do we look for answers? In K. Neckerman (Ed.), Social inequality (pp. 3–77). Russell Sage Foundation.

    Google Scholar 

  • Fairlie, R. W. (2005). An extension of the Blinder-Oaxaca decomposition technique to logit and probit models. Journal of Economic and Social Measurement, 30(4), 305–316.

    Article  Google Scholar 

  • Fields, K. E., & Fields, B. J. (2014). Racecraft: The Soul of Inequality in American Life. London: Verso Trade.

    Google Scholar 

  • Fox, C. (2004). The changing color of welfare? How whites’ attitudes toward latinos influence support for welfare. American Journal of Sociology, 110(3), 580–625.

    Article  Google Scholar 

  • Fox, L., Wimer, C., Garfinkel, I., Kaushal, N., Nam, J., & Waldfogel, J. (2015). Trends in deep poverty from 1968 to 2011: The influence of family structure, employment patterns, and the safety net. RSF: the Russell Sage Foundation Journal of the Social Sciences, 1(1), 14–34.

    Article  Google Scholar 

  • Frankel, N. (1999). Freedom’s women: Black women and families in civil war era Mississippi. Indiana University Press.

    Google Scholar 

  • Fullerton, A. S., & Dixon, J. C. (2009). Racialization, asymmetry, and the context of welfare attitudes in the American States. Journal of Political & Military Sociology, 37(1), 95–120.

    Google Scholar 

  • Gaddis, S. M. (2015). Discrimination in the credential society: An audit study of race and college selectivity in the labor market. Social Forces, 93(4), 1451–1479.

    Article  Google Scholar 

  • Garfinkel, I., & McLanahan, S. (1986). Single mothers and their children: A New American Dilemma. Urban Institute Press.

    Google Scholar 

  • Golash-Boza, T. (2016). A critical and comprehensive sociological theory of race and racism. Sociology of Race and Ethnicity, 2(2), 129–141.

    Article  Google Scholar 

  • Gradín, C. (2012). Poverty among minorities in the United States: Explaining the racial poverty gap for Blacks and Latinos. Applied Economics, 44(29), 3793–3804.

    Article  Google Scholar 

  • Harknett, K., & McLanahan, S. S. (2004). Racial and ethnic differences in marriage after the birth of a child. American Sociological Review., 69(6), 790–811.

    Article  Google Scholar 

  • Haskins, R. (2009). Moynihan was right: Now what? The Annals of the American Academy of Political and Social Science, 621, 281–314.

    Article  Google Scholar 

  • Hattery, A., & Smith, E. (2007). Social stratification in the new/old south: The influences of racial segregation on social class in the deep south. Journal of Poverty, 11(1), 55–81.

    Article  Google Scholar 

  • Hilger, N. (2016). Upward mobility and discrimination: The case of Asian Americans. (No. w22748.) National Bureau of Economic Research.

  • Hill, S. A. (2006). Marriage among African American Women: A gender perspective. Journal of Comparative Family Studies, 37(3), 421–440.

    Article  Google Scholar 

  • Hunter, T. (2017). Bound in wedlock: Slave and free black marriage in the nineteenth century. Belknap Press of Harvard University Press.

    Book  Google Scholar 

  • Iceland, J. (2005). Measuring poverty: Theoretical and empirical considerations. Measurement: Interdisciplinary Research and Perspectives, 3(4), 199–235.

    Google Scholar 

  • Iceland, J. (2019). Racial and ethnic inequality in poverty and affluence, 1959–2015. Population Research and Policy Review, 38, 615–654.

    Article  Google Scholar 

  • Jann, B. (2008). A Stata implementation of the Blinder-Oaxaca decomposition. Stata Journal, 8(4), 453–479.

    Article  Google Scholar 

  • Kail, B. L., & Dixon, M. (2011). The uneven patterning of welfare benefits at the twilight of AFDC: Assessing the influence of institutions, race, and citizen preferences. The Sociological Quarterly, 52(3), 376–399.

    Article  Google Scholar 

  • Lenhardt, R. A. (2014). Marriage as Black citizenship? Hastings Law Journal, 66(5), 1317–1364.

    Google Scholar 

  • Lichter, D. T. (1997). Poverty and inequality among children. Annual Review of Sociology, 23, 121–145.

    Article  Google Scholar 

  • Lichter, D. T., Parisi, D., & Taquino, M. C. (2012). The geography of exclusion: Race, segregation, and concentrated poverty. Social Problems, 59(3), 364–388.

    Article  Google Scholar 

  • Lichter, D. T., Qian, Z., & Crowley, M. L. (2005). Child poverty among racial minorities and immigrants: Explaining trends and differentials. Social Science Quarterly, 86(s1), 1037–1059.

    Article  Google Scholar 

  • Lin, A. C., & Harris, D. R. (Eds.). (2008). The colors of poverty: Why racial and ethnic disparities persist. Russell Sage Foundation.

    Google Scholar 

  • Ludwig-Dehm, S. M., & Iceland, J. (2017). Hispanic concentrated poverty in traditional and new destinations, 2010–2014. Population Research and Policy Review, 36(6), 833–850.

    Article  Google Scholar 

  • Luxembourg Income Study (LIS). (2017). The LIS User Guide. Retrieved December 21, 2019 from http://www.lisdatacenter.org/wp-content/uploads/files/data-lis-guide.pdf.

  • Manduca, R. (2019). The contribution of national income inequality to regional economic divergence. Social Forces, 98, 622–648.

    Article  Google Scholar 

  • Manning, W. D., & Brown, S. (2006). Children’s Economic Well-Being in Married and Cohabiting Parent Families. Journal of Marriage and Family, 68(2), 345–362.

    Article  Google Scholar 

  • Maralani, V. (2013). The demography of social mobility: Black-White differences in the process of educational reproduction. American Journal of Sociology, 118(6), 1509–1558.

    Article  Google Scholar 

  • Martinez, G., Daniels, K., & Chandra, A. (2012). Fertility of men and women aged 15–44 years in the United States: National Survey of Family Growth, 2006–2010. National Health Statistics Reports, 51(1), 1–28.

    Google Scholar 

  • Massey, D. S., & Denton, N. (1993). American Apartheid: Segregation and the making of the underclass. Harvard University Press.

    Google Scholar 

  • McCall, L. (2001). Complex inequality: Gender, class and race in the new economy. Routledge Press.

    Google Scholar 

  • McLanahan, S., & Percheski, C. (2008). Family structure and the reproduction of inequalities. Annual Review of Sociology, 34, 257–276.

    Article  Google Scholar 

  • Meyer, B. D., & Mittag, N. (2019). Using linked survey and administrative data to better measure income: Implications for poverty, program effectiveness, and holes in the safety net. American Economic Journal: Applied Economics, 11(2), 176–204.

    Google Scholar 

  • Meyer, B. D., Mok, W. K. C., & Sullivan, J. X. (2015). Household surveys in crisis. Journal of Economic Perspectives, 29(4), 199–226.

    Article  Google Scholar 

  • Michener, J. (2018). Fragmented democracy. Cambridge University Press.

    Book  Google Scholar 

  • Mouw, T. (2000). Job relocation and the racial gap in unemployment in Detroit and Chicago, 1980 to 1990. American Sociological Review, 65(5), 730–753.

    Article  Google Scholar 

  • Nolan, L., Garfinkel, I., Kaushal, N., Nam, J., Waldfogel, J., & Wimer, C. (2016). Trends in child poverty by race/ethnicity: New evidence using an anchored historical supplemental poverty measure. Journal of Applied Research on Children: Informing Policy for Children at Risk, 7, 3.

    Google Scholar 

  • O’Connell, H. A. (2012). The impact of slavery on racial inequality in poverty in the contemporary U.S. South. Social Forces, 90(3), 713–734.

    Article  Google Scholar 

  • O’Connor, A. (2001). Poverty Knowledge. Princeton University Press.

    Book  Google Scholar 

  • Oliver, M. L., Shapiro, T. M., & Shapiro, T. (2006). Black wealth, white wealth: A new perspective on racial inequality. Routledge.

    Google Scholar 

  • Pager, D. (2003). The mark of a criminal record. American Journal of Sociology, 108(5), 937–975.

    Article  Google Scholar 

  • Pager, D., Western, B., & Bonikowski, B. (2009). Discrimination in a low-wage labor market: A field experiment. American Sociological Review, 74, 777–799.

    Article  Google Scholar 

  • Parker, K., Horowitz, J., & Mahl, B. (2016). On views of race and inequality, Blacks and Whites are worlds apart. Washington, D.C. Pew Research Center. Retrieved July 30, 2020, from https://www.pewsocialtrends.org/2016/06/27/on-views-of-race-and-inequality-blacks-and-whites-are-worlds-apart/.

  • Parolin, Z. (2019a). The effect of benefit underreporting on estimates of poverty in the United States. Social Indicators Research, 144, 869–898.

    Article  Google Scholar 

  • Parolin, Z. (2019b). Temporary assistance for needy families and the Black-White child poverty gap in the United States. Socio-Economic Review, mwz025. https://doi.org/10.1093/ser/mwz025.

    Article  Google Scholar 

  • Patterson, O. (2019). The denial of slavery in contemporary American Sociology. Theory and Society, 48, 903–914.

    Article  Google Scholar 

  • Paul, M., Darity, W., Jr., Hamilton, D., & Zaw, K. (2018). A path to ending poverty by way of ending unemployment: A federal job guarantee. RSF: the Russell Sage Foundation Journal of the Social Sciences, 4(3), 44–63.

    Article  Google Scholar 

  • Quillian, L., Pager, D., Hexel, O., & Midtbøen, A. H. (2017). Meta-analysis of field experiments shows no change in racial discrimination in hiring over time. Proceedings of the National Academy of Sciences, 114(41), 10870–10875.

    Article  Google Scholar 

  • Quillian, L., Lee, J. J., & Oliver, M. (2020). Evidence from field experiments in hiring shows substantial additional racial discrimination after the callback. Social Forces. https://doi.org/10.1093/sf/soaa026

    Article  Google Scholar 

  • Rainwater, L., & Smeeding, T. M. (2003). Poor kids in a rich country: America’s children in comparative perspective. Russell Sage Foundation.

  • Raley, R. K., Sweeney, M. M., & Wondra, D. (2015). The growing racial and ethnic divide in U.S. marriage patterns. The Future of Children., 25(2), 89–109.

    Article  Google Scholar 

  • Ray, V. (2019). A theory of racialized organizations. American Sociological Review, 84(1), 26–53.

    Article  Google Scholar 

  • Rank, M. R. (2005). One nation, underprivileged: Why American poverty affects us all. Oxford University Press.

  • Reece, R. L. (2020). Whitewashing slavery: Legacy of slavery and white social outcomes. Social Problems, 67(2), 304–323.

    Article  Google Scholar 

  • Reskin, B. (2012). The race discrimination system. Annual Review of Sociology, 38, 17–35.

    Article  Google Scholar 

  • Roberts, D. E. (2017). Killing the black body: Race, reproduction, and the meaning of liberty (20th ed.). Vintage.

  • Ruggles, S. (1994). The origins of African-American family structure. American Sociological Review, 59(1), 136–151.

    Article  Google Scholar 

  • Sakamoto, A., Goyette, K. A., & Kim, C. H. (2009). Socioeconomic attainments of Asian Americans. Annual Review of Sociology, 35, 255–276.

    Article  Google Scholar 

  • Semega, J., Kollar, M., Creamer, J., & Mohanty, A. (2019). Income and Poverty in the United States: 2018. U.S. Census Bureau, Current Population Reports. Retrieved July 30, 2020 from https://www.census.gov/library/publications/2019/demo/p60-266.html.

  • Sharkey, P. (2013). Stuck in place: Urban neighborhoods and the end of progress toward racial equality. University of Chicago Press.

  • Sites, W., & Parks, V. (2011). What do we really know about racial inequality? Labor markets, politics, and the historical basis of black economic fortunes. Politics & Society, 39(1), 40–73.

    Article  Google Scholar 

  • Smeeding, T. M. (2016). Poverty measurement. In D. Brady & L. M. Burton (Eds.), The Oxford handbook of the social science of poverty (pp. 21–46). Oxford University Press.

    Google Scholar 

  • Snipp, C. M. (1996). Understanding race and ethnicity in rural America. Rural Sociology, 61, 125–142.

    Article  Google Scholar 

  • Stoll, M. A., Holzer, H. J., & Ihlanfeldt, K. R. (2000). Within cities and suburbs: Racial residential concentration and the spatial distribution of employment opportunities across sub-metropolitan areas. Journal of Policy Analysis and Management, 19(2), 207–231.

    Article  Google Scholar 

  • Sullivan, D. H., & Ziegert, A. L. (2021). Family poverty in Black and White: Results from a new poverty measure. The Review of Black Political Economy. https://doi.org/10.1177/00346446211006152.

    Article  Google Scholar 

  • Takei, I., & Sakamoto, A. (2011). Poverty among Asian Americans in the 21st century. Sociological Perspectives, 54(2), 251–276.

    Article  Google Scholar 

  • Thiede, B. C., Lichter, D. T., & Sanders, S. R. (2015). America’s working poor: Conceptualization, measurement, and new estimates. Work and Occupations, 42(3), 267–312.

    Article  Google Scholar 

  • Thiede, B. C., Kim, H., & Slack, T. (2017). Marriage, work, and racial inequalities in poverty: Evidence from the United States. Journal of Marriage and Family, 79(5), 1241–1257.

    Article  Google Scholar 

  • Thiede, B. C., & Brooks, M. M. (2018). Child poverty across immigrant generations in the United States, 1993–2016: Evidence using official and supplemental poverty measures. Demographic Research, 39(40), 1065–1080.

    Article  Google Scholar 

  • Thomas, A., & Sawhill, I. (2005). For love and money? The impact of family structure on family income. The Future of Children, 15(2), 57–74.

    Article  Google Scholar 

  • Tomaskovic-Devey, D., & Roscigno, V. J. (1996). Racial economic subordination and White gain in the U.S. South. American Sociological Review, 61(4), 565–589.

    Article  Google Scholar 

  • Weller, C. E. (2019). African Americans Face Systematic Obstacles to Getting Good Jobs. Center for American Progress. Washington, DC. Retrieved July 30, 2020 from https://www.americanprogress.org/issues/economy/reports/2019/12/05/478150/african-americans-face-systematic-obstacles-getting-good-jobs/.

  • Williams, D. T. (2019). A call to focus on racial domination and oppression: A response to ‘racial and ethnic inequality in poverty and affluence, 1959–2015.’ Population Research and Policy Review., 38(5), 655–663.

    Article  Google Scholar 

  • Williams, D. T. (2021). Rethinking black families in poverty: postcolonial critiques and critical race possibilities. In L. L. Martin (Ed.), Introduction to Africana demography (pp. 143–164). Brill.

    Google Scholar 

  • Williams, D. T., & Baker, R. S. (2021). Family structure, risks, and racial stratification in poverty. Social Problems, spab018. https://doi.org/10.1093/socpro/spab018.

    Article  Google Scholar 

  • Wilson, W. J. (1987). The truly disadvantaged. University of Chicago Press.

    Google Scholar 

  • Wimberley, R. C. (2010). It’s our most rural region; It’s the poorest; it’s the black belt south; and it needs our attention. Journal of Rural Social Sciences, 25(2), 175–182.

    Google Scholar 

Download references

Acknowledgements

We thank Courtney Boen, Camille Z. Charles, Chenoa Flippen, John Iceland, Wendy Roth, and Arthur Sakamoto for comments and suggestions.

Author information

Authors and Affiliations

  1. University of Pennsylvania, 3718 Locust Walk, 218 McNeil Building, Philadelphia, PA, 19104, USA

    Regina S. Baker

  2. University of California, Riverside, Riverside, USA

    David Brady

  3. WZB Berlin Social Science Center, Berlin, Germany

    David Brady

  4. Bocconi University, Milan, Italy

    Zachary Parolin

  5. Columbia University, New York, USA

    Zachary Parolin

  6. University of Tennessee, Knoxville, USA

    Deadric T. Williams

Authors
  1. Regina S. Baker
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. David Brady
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zachary Parolin
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Deadric T. Williams
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Regina S. Baker.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix

Appendix

See Figs. 3, 4

Fig. 3
figure 3

Poverty rates by race/ethnicity relative to White individuals by year (50% median). These poverty estimates include the Transfer Income Model, version 3 (TRIM3)

Full size image
Fig. 4
figure 4

Poverty rates by race/ethnicity relative to White individuals by year (SPM w/TRIM3). These poverty estimates include the Transfer Income Model, version 3 (TRIM3)

Full size image

and Tables 4, 5, 6, 7, 8, 9, 10, 11, 12, 13.

Table 4 Sample means by race/ethnicity (2013–2017)
Full size table
Table 5 Descriptive characteristics for full population (2013–2017)
Full size table
Table 6 Poverty rates by race/ethnicity and year
Full size table
Table 7 Official poverty (OPM) rates by race/ethnicity and year
Full size table
Table 8 Estimates of racial differences in black and white poverty when accounting for incarcerated population (relative poverty measure)
Full size table
Table 9 Fairlie logistic regression decomposition of differences in poverty by race (Native American vs. White), 2013–2017
Full size table
Table 10 Fairlie logistic regression decomposition of differences in poverty by race (Black vs White), 2013–2017
Full size table
Table 11 Fairlie logistic regression decomposition of differences in poverty by race (Latino vs White), 2013–2017
Full size table
Table 12 Fairlie logistic regression decomposition of differences in poverty by race (Asian vs White), 2013–2017
Full size table
Table 13 Fairlie logistic regression decomposition of differences in poverty by race (Native American vs White), 2013–2017
Full size table

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Baker, R.S., Brady, D., Parolin, Z. et al. The Enduring Significance of Ethno-Racial Inequalities in Poverty in the U.S., 1993–2017. Popul Res Policy Rev 41, 1049–1083 (2022). https://doi.org/10.1007/s11113-021-09679-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11113-021-09679-y

Keywords

search

Navigation