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Racial Segregation and School Poverty in the United States, 1999–2016

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Abstract

Research over the past decade suggests that racial segregation appears to have the largest implications for students’ achievement when linked to racial differences in exposure to school poverty. This paper provides a summary and update to prior literature describing patterns and trends of racial differences in school poverty rates from the 1998–1999 through 2015–2016 school years. We describe black-white and Hispanic-white differences in school poverty rates within U.S. school districts, metropolitan areas, states, and the nation over this nearly 20-year period. We find that while exposure to poverty in schools has risen dramatically, racial differences in exposure to school poverty have been relatively stable during this time. These average trends, however, belie meaningful variability among places. Places serving large proportions of minority students have larger but declining average racial differences in exposure to school poverty. Large school districts also have larger average racial differences in exposure and have been experiencing increases in this measure over time.

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Notes

  1. For examples, see Harris (2019) and Yglesias (2019).

  2. For example, see Shapiro (2019).

  3. These deductions assume monotonicity in the relationship between \(\Delta\) and each factor (racial segregation, economic segregation, and FRPL rates).

  4. Authors calculations using data from the U.S. Census Bureau (https://www.census.gov/data.html).

  5. The CCD data is available for download here:https://www.census.gov/data.html).

  6. We begin our panel in the 1998–1999 school year because CCD began reporting reduced lunch in addition to free lunch in this year; in prior years, only data on free lunch was provided.

  7. The imputation model is described in detail in Fahle et al. (2019).

  8. The 2013 MSA definitons are available for download here: https://www.census.gov/programs-surveys/metro-micro/geographies/geographic-reference-files.2013.html

  9. In most years, the CCD reports the latitude and longitude for each school. In years when that data is unavailable, we use street addresses to find schools’ latitude and longitude using—opencagegeo—in Stata (Zeigermann 2016).

  10. The TigerLine shapefiles are available for download here: https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.htmlIn states that have separate elementary and secondary districts, we use the secondary school boundaries for schools that start in 9th grade or later or start in 6th grade or later and end in 10th grade or later. All other schools are treated as if they are part of an elementary district.

  11. This restriction is only relevant for school districts. We use imputation to fill-in missing data; however, for school districts that opened or closed during our panel, we will not have complete data.

  12. For more information visit: https://www.fns.usda.gov/nslp/community-eligibility-provision-resource-center

  13. We removed the Washington–Arlington–Alexandria MSA, despite it not being flagged by the RMSE measure, because the District of Columbia’s FRPL data are erratic.

  14. In the 2013–2014 school year, the FRPL rate in DC jumped to 1.0 from 0.57 in the 2012–2013 year. The rate stayed at 0.99 in the 2014–2015 school year, but then dropped again to 0.73 in the 2015–2016 school year. While these were the largest shifts, there were other years in which the FRPL rate changed by approximately 10–15 percentage points (1999–2000 to 2000–2001, 2000–2001 to 2000–2002, and 2010–2011 to 2011–2012).

  15. Note that all removals for erratic data are made at the unit-level. In practice, districts or MSAs that were removed in their samples still contribute data to the state and national samples.

  16. The standard deviations are calculated as the square root of the \({\tau }_{00}\) and \({\tau }_{11}\) parameters.

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Acknowledgements

We thank Belen Chavez for excellent research assistance. Some of the data used in this paper was provided by the National Center for Education Statistics (NCES). The research described here was supported by grants from the Spencer Foundation (Award 201500058), the William T. Grant Foundation (Award 186173), and the Bill and Melinda Gates Foundation. The opinions expressed here are ours and do not represent views of NCES, the Institute of Education Sciences, or the U.S. Department of Education.

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Correspondence to Erin M. Fahle.

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Fahle, E.M., Reardon, S.F., Kalogrides, D. et al. Racial Segregation and School Poverty in the United States, 1999–2016. Race Soc Probl 12, 42–56 (2020). https://doi.org/10.1007/s12552-019-09277-w

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