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Race and Earnings Mobility in the US

Abstract

We investigate the racial differences in positional and directional earning mobility for blacks and whites using seven 6-year longitudinal samples drawn from the Panel Study of Income Dynamics, extending from 1973 through 2015. Positional mobility comparisons are mixed for the proportion of each sample moving to a higher earnings category but reveal a higher percentage of blacks than whites trapped in the bottom 25% of the distribution of earnings. Directional mobility comparisons show that the mean increase from the initial to final earnings distribution was significantly greater for whites than for blacks throughout 1973–85 and 1997–2009. A breakdown of these findings by gender reveals that they arise primarily from the labor market experience of black men, who face more severe racial disparities in positional and directional earning mobility than black women. Overall, these findings on intragenerational earning mobility are in line with recent research on intergenerational mobility in the US.

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Fig. 1
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Notes

  1. Chetty et al. (2020) find no racial disparities in either wages or hours of work for white and black women, which implies no racial disparity in earnings for women

  2. Chakravarty et al. (2020) use PSID data to examine racial differences in intergenerational mobility. Racial disparities in earnings have received more attention, e.g., Brown (1984), Bound and Freeman (1992), Fryer Jr (2011), Hirsch and Winters (2014), Bayer and Charles (2018), Lahiri (2018), and others

  3. The CNEF is managed at the College of Education and Human Ecology at the Ohio State University (Columbus, OH, USA). See https://cnef.ehe.osu.edu/

  4. To study the medium-term mobility of earnings, we initially intended to take 5-year intervals but there was no data for 2000 and 2010 since the PSID database become bi-annual in 1995. For this reason, we took intervals of six years. Nonetheless, the results for the intervals 1975–1980, 1980–1985, 1985–1990 and 1990–1995 (available from the authors upon request) were quite similar to the results for the intervals 1973–1979, 1979–1985, 1985–1991, and 1991–1997 that are shown here

  5. Earnings include wages and salary from all employment—including training programs, primary and secondary jobs, and self-employment, plus bonuses, overtime, and commissions. To obtain real earnings we use the Consumer Price Index (base year: 2010)

  6. Sample weights indicate how many persons in the population are represented by a given observation in the sample. Mobility measures are weighted in the terminal year of comparison (Burkhauser et al. 1997)

  7. The value of a distributional perspective is also clear from the findings for the gender variable. There we see, within the same interval, both positive and negative significant differences in different percentile groups extending from 1973 through 1985

  8. The third and fourth mobility concepts in Jäntti and Jenkins (2015) are motivated by different concerns. Mobility as an equalizer of longer-term income is really concerned with inequality, and whether it diminishes as the income time horizon lengthens. We make a brief reference to this concept later in the paper. Mobility as risk or flux treats income fluctuations as undesirable, because a risk-averse individual prefers a less volatile income stream. This concept does not fit our application

  9. With a sample size approaching the US population, Chetty et al. (2020) can use percentiles as income groups. Our sample size is far smaller, so must use broader income categories

  10. Fields and Ok (1999) also proposed an alternative measure that replaces the initial and final earnings in Eq. (3) with their logarithms, which is designed to incorporate a preference for “propoor” growth. While this preference may be desirable in many applications, it seems inappropriate here. Suppose that blacks are in lower positions in the initial earnings distribution and have smaller earnings gains during a period than whites. Taking logarithms would compress the gains of whites more than of blacks and make the disparities appear smaller. In an earlier version of this paper we applied the alternative measure and found that it erases some of the racial disparities

  11. We use these percentiles instead of a set of regular intervals (for example, deciles or quintiles) because we want to know what happens at the two tails of the earnings distribution—the poorest 10% and the richest 10%—without considering too many intervals. For example, if we use deciles, we will have to double the number of intervals under consideration (from 5 to 10) without adding much information to our main results

  12. The row total is slightly less than 10% due to rounding error

  13. One path to upward mobility for blacks has been illuminated by Marsh et al. (2007), who highlight a growing segment of the black “middle class” formed by those who are single and living alone (i.e., without children). The notion of the middle class has long been associated with a married couple with children, but that idea has diverted attention from a new group experiencing upward mobility

  14. High school dropout rates are higher for blacks than for whites and the disparity is greater among males than among females (Kim et al. 2015). Furthermore, the dropout rates for blacks are highest during the first 2 years. Blacks are also underrepresented in four-year institutions of higher education and have degree completion rates about half of that for whites (DeAngelo et al. 2011)

  15. Fryer Jr (2011) finds that, after controlling for educational achievement (Armed Forces Qualifying Test scores), wages are still lower for black men than white men, but the situation is different for black and white women. Indeed, in the National Longitudinal Survey of Youth (1979 cohort), black women earn higher wages than white women after controlling for educational achievement. Gould (2020) finds that the decline in manufacturing employment widened racial disparities for both men and women

  16. We also computed stochastic mobility matrices separately for white and black men and performed dominance comparisons of the cumulative conditional probabilities of moving out of the bottom earnings category (similar to those shown in Table 5b for whites and blacks overall). In 3 of the 7 intervals (1979–85, 1997–2003, and 2003–09), we find dominance relations favoring white men, with crossings in the other 4 intervals. These findings differ from the comparisons of blacks and whites overall in Table 7, where all 7 intervals yielded crossings

  17. For an overview of the difficulties, see the articles by Darity Jr and Mason (1998), Arrow (1998), Heckman (1998), and Loury (1998) in the Journal of Economic Perspectives

  18. From a historical perspective, there are good reasons for having terms for racism with fluid meanings. Racism has taken different forms at different times, as slavery, Jim Crow laws, and the war on drugs illustrate (Alexander 2020). Even within the much shorter period covered by our PSID samples, the mechanism responsible for racial disparities could have changed. Fryer Jr (2011) offers evidence that the first explanation we consider—racial discrimination in labor markets—has been declining in importance over time

  19. A higher propensity toward criminal behavior can be seen in a classic study by Wilson (1987, 22), who (citing statistics from the U.S. Department of Justice) reports that, “Only one of nine persons in the United States is black; yet in 1984 nearly one of every two persons arrested for murder and nonnegligent manslaughter was black … Furthermore, 61% of all persons arrested for robbery and 38% of those arrested for aggravated assault in 1984 were black.” Even so, the persons arrested for these crimes were a small fraction of the black population in the United States. The formulation of Loury’s theory reminds us of the statistical discrimination theory proposed earlier by Phelps (1972)

  20. A criminal record would, of course, make subsequent upward earnings mobility more difficult

  21. For a formal analysis, see Calvó-Armengol and Jackson (2004, 2007) and Jackson (2014)

  22. Chetty et al. (2020, 716) note that, “21% of black men born to the lowest-income families are incarcerated on a given day, as compared with 6% of white men”

  23. The same report includes other recommendations like those made in this paper (expanding early childhood education, reducing incarceration rates for non-violent crimes such as those associated with the war on drugs) and more (e.g., strengthening the safety net where it helps the poorest children, paid parental leave during the first year, and expanding the Move to Opportunity experiment)

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Acknowledgements

We acknowledge the helpful suggestions of Pedro Salas-Rojo, three anonymous referees, and participants in presentations at the 89th and 90th annual meetings of the Southern Economic Association. Responsibility for any error is the authors’ alone.

Availability of data

The data for this study is available from the authors upon request.

Code availability

The software code for this study is available from the authors upon request.

Funding

Juan Gabriel Rodríguez acknowledges financial support of the Ministerio de Ciencia e Innovación (Spain) under project PID2019-104619RB-C42 and Comunidad de Madrid (Spain) under project H2019/HUM-5793-OPINBI-CM.

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Correspondence to Lester A. Zeager.

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Bishop, J.A., Rodríguez, J.G. & Zeager, L.A. Race and Earnings Mobility in the US. J Econ Race Policy 4, 166–182 (2021). https://doi.org/10.1007/s41996-021-00082-5

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Keywords

  • Racial disparities
  • Labor earnings
  • Positional and directional mobility
  • United States
  • Longitudinal analysis