Many US school districts exhibit high levels of racial segregation within their schools, prompting policy proposals intended to encourage the equal racial representation of students in classrooms. While these policies are frequently met with legal challenges and substantial pushback from affected parents, to what extent students themselves benefit from improved school integration remains a matter of debate. While some research questions the role of school resources in shaping student outcomes (Hanushek 1986), other research points to school input disparities as important drivers of racial inequality in adulthood (Card and Krueger 1992, Chetty et al. 2014, Elango et al. 2016, Card et al. 2018) and suggests that attempts to reduce these disparities, particularly through integration, may increase economic mobility (Biasi 2019). At the same time, responses to such policies by non-minority students and parents aiming to avoid integrated classrooms may contribute to segregation in US cities and hamper the effectiveness of the relevant policies (Shertzer and Walsh 2016).
While a large literature has examined statistical associations between levels of school segregation and student outcomes, these approaches are unable to determine if the associations are causal or represent broader effects, such as school resources, that distinguish schools with high versus low levels of segregation. Several research papers have estimated the effects of integration per se by focusing on court orders meant to desegregate schools that were not tied to school resource levels. Following the landmark Supreme Court Brown v. Board of Education ruling in 1954, most large school districts in the US were placed under orders that mandated they reduce the level of racial segregation in their schools. Guryan (2004) demonstrated with US Census data that these orders reduced the number of Black secondary-school dropouts, and Johnson (2011) used a small dataset to suggest that these effects extended into adulthood (see also Johnson 2019 for these results in book form, along with a broader discussion of which school reforms improve student outcomes).
Our research adds evidence to this debate by providing the most comprehensive national assessment to date on the long-run impacts of court-ordered desegregation on adult socioeconomic outcomes. We utilise large-scale and restricted data on children’s long-run educational and economic outcomes from the 2000 Census and the 2001–2015 waves of the American Community Survey and Social Security records in conjunction with a hand-collected dataset of county-level timings of desegregation orders. Our empirical approach complements other recent work, such as Bailey et al. (2021), who used similar data and found substantial long-run positive effects on human capital and economic self-sufficiency associated with the rollout of the Head Start programme. To isolate the causal effect of earlier exposure to school desegregation on adult outcomes, we compare children who were born in the same birth cohort in the same birth state, but in different birth counties, so that they were exposed to desegregation orders at different ages. We then compare these effects to children who were exposed to orders at age 17, for whom we would expect no change in outcomes due to their already having completed their secondary school education.
We report our main results in Figure 1, using index variables that summarise improvements in human capital (i.e. schooling) and economic self-sufficiency (factors related to employment and earnings). Results are shown separately for Blacks and whites and for individuals born in and out of the South.
Figure 1 The long-run impacts of school desegregation on human capital (HC) and economic self-sufficiency (ESS)
Figures 1a and 1b demonstrate that among African Americans from the South, indicated with red triangles, earlier exposure to desegregation had large positive effects on human capital and economic self-sufficiency. Compared to exposure at age 17, being born five years prior to a desegregation order is associated with a 0.4 standard deviation increase in the human capital index and a 0.5 standard deviation increase in the economic self-sufficiency index. The fact that the effects begin phasing in before age five likely reflects the court orders themselves frequently taking at least five years to be fully implemented. Notably, we do not detect any additional declines or improvements in outcomes for African Americans who were older than age 17 when exposed to the orders, which is reassuring given that individuals in this range did not have differential exposure to the orders because they had all already graduated. Due to the index variables being potentially different to interpret, we also report results for the individual variables that go into the indexed outcomes. Compared to individuals who were exposed to desegregation at age 17, African Americans who were born five years before such court orders experienced a 15 percentage point increase in the likelihood of graduating from secondary school, a 10 percentage point increase in the likelihood of employment, and a 30% increase in earnings. However, the effects for college completion and incarceration are insignificant. Additional analyses indicate that the effects we uncover are fairly homogenous between men and women but appear larger in counties with higher pre-court-order levels of racial inequality.
The same figures indicate that earlier exposure to desegregation orders did not have a significant impact (either substantively or statistically) for white Southerners. However, Figures 1c and 1d present the results from Northern counties: in stark contrast to patterns in the South, we do not observe any association between earlier exposure to desegregation orders and improvements in adult outcomes for Black Northerners. While our data are limited in their ability to assess the mechanisms driving this result, increased baseline segregation rates in the South is a potential explanation. Additionally, families in the North may have responded to the orders in ways that ingrained segregation at a de-facto instead of a de-jure level (as was the case in the South), for instance by migrating to suburban school districts or enrolling in private schools.
Overall, while our results suggest that desegregation efforts in the South were remarkably potent in improving Black outcomes, the distinct absence of effects outside the South strongly suggest that there are limitations to the efficacy of integration initiatives in certain contexts. This calls into question whether ongoing or future interventions are likely to be effective when they do not constitute such a transformative change to local education systems or where effective paths to avoiding integrated schools are available to white families.
Bailey, M, S Sun and B Timpe (2021), “Head Start’s long-run impacts on human capital and labour-market outcomes”, VoxEU.org, 06 June.
Biasi, B (2019), “School finance equalization increases intergenerational mobility”, VoxEU.org, 24 April.
Card, D, C Domnisoru and L Taylor (2018), “Invest in public education to increase intergenerational mobility”, VoxEU.org, 06 October.
Card, D and A Krueger (1992), “School Quality and Black-White Relative Earnings: A Direct Assessment”, The Quarterly Journal of Economics, 107(1): 151–200.
Chetty, R, N Hendren, P Kline and E Saez (2014), “Where is the land of opportunity? Intergenerational mobility in the US”, VoxEU.org, 04 February.
Elango, S, J L Garcia, J Heckman and A Hojman (2016), “Early childhood education and social mobility”, VoxEU.org, 12 January.
Guryan, J (2004), “Desegregation and Black Dropout Rates”, American Economic Review, 94(4): 919–943.
Hanushek, E (1986), “The Economics of Schooling: Production and Efficiency in Public Schools”, Journal of Economic Literature 24(3): 1141–1177.
Johnson, R C (2011), “Long-Run Impacts of School Desegregation and School Quality”, NBER Working Paper 16664.
Johnson, R C (2019), Children of the Dream: Why School Integration Works, Basic Books.
Shertzer, A and R Walsh (2016), “Why US cities are segregated by race: New evidence on the role of ‘white flight’”, VoxEU.org, 19 May.