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Race, Wealth and Incarceration: Results from the National Longitudinal Survey of Youth

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Abstract

Using the 1979 cohort of the National Longitudinal Study of Youth to explore the interwoven links between race, wealth and incarceration, this study examines the data on race and wealth status before and after incarceration. Data indicate that although higher levels of wealth were associated with lower rates of incarceration, the likelihood of future incarceration still was higher for blacks at every level of wealth compared to the white likelihood, as well as the Hispanic likelihood, which fell below the white likelihood for some levels of wealth. Further, we find that racial wealth gaps existed among those who would be incarcerated in the future and also among the previously incarcerated.

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Fig. 1
Fig. 2

Notes

  1. NLSY79 respondents were separated into three major racial/ethnic groups by survey screeners: Hispanic, black and non-black, non-Hispanic. The “non-black, non-Hispanic” group includes American Indians, Asians, Asian Indians, Pacific Islanders and other non-white identities, including those who self-identified as black or Hispanic (Light and Nandi 2007).

  2. For all results, male-only, female-only or combined estimates are available by request from the authors.

  3. To protect the identities of those in the survey, wealth data in the NLSY79 were top-coded so that values in the top two percentiles would be assigned a capped value for each year. Until 1994, asset values were capped and top-coded, whereas afterward, the top two percent of valid values for net worth were averaged, and that average replaced all values in the top range. Although this change would allow for valid estimations of mean wealth for the total population, no distinctions were made based on race. With uneven numbers of observations from each racial group top-coded, and the true values lost, calculations of racial mean wealth based on the data would not be valid. However, racial wealth data at the quintiles and quartiles, including the median, were unaffected by this top-coding; thus, we examine group wealth distributions through those measures.

  4. Although, of course, since we cannot know the nature of the crime, it may have been the criminal activity that led to the wealth accumulation and later imprisonment.

  5. Although the gaps and trends did persist, data for 2004 and 2008 are omitted as the # of observations in some categories were too few.

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Correspondence to Khaing Zaw.

Appendix

Appendix

See Tables 4, 5, 6, 7 and 8.

Table 4 Tabulations—median wealth by race and future incarceration
Table 5 Tabulations—5-year percentage likelihood of incarceration based on 1985 wealth (incarcerated 1986–1990)—males
Table 6 Tabulations—27-year (maximum data) percentage likelihood of incarceration based on 1985 wealth (incarcerated 1986–2012)—males
Table 7 Tabulations—5-year percentage likelihood of incarceration based on 1985 wealth (incarcerated 1986–1990)—females
Table 8 Tabulations—27-year (maximum data) percentage likelihood of incarceration based on 1985 wealth (incarcerated 1986–2012)—females

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Zaw, K., Hamilton, D. & Darity, W. Race, Wealth and Incarceration: Results from the National Longitudinal Survey of Youth. Race Soc Probl 8, 103–115 (2016). https://doi.org/10.1007/s12552-016-9164-y

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