Does School Integration Generate Peer Effects? Evidence from Boston's Metco Program

By Joshua D. Angrist, Kevin Lang. Social Science Research Network, 2004

789 citations recorded by the source corpus.

Most integration programs transfer students between schools within districts. In this paper, we study Metco, a long-running desegregation program that sends mostly Black students out of the Boston public school district to attend schools in more affluent suburban districts. Metco increases the number of Black students in receiving districts dramatically. Because Metco students have substantially lower test scores than local students, this inflow generates a significant decline in scores, with an especially marked effect on the lower quantiles. This paper investigates the impact of Metco on receiving districts. Aggregate data on schools from districts throughout Massachusetts and micro data from a single large district strongly suggest the impact of Metco is largely a composition effect, since OLS estimates show no impact on average scores in samples of White or non-Metco students. On the other hand, OLS estimates using micro data show some evidence of an effect on the scores of minority 3rd graders in Reading and Language. Instrumental variables estimates for 3rd graders are imprecise but generally in line with OLS. Further analysis shows the negative effects on 3rd graders to be clearly present only for girls. Given the highly localized nature of these results, we conclude that any peer effects from Metco are modest and short-lived.

Subfields: Education, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/05cd3777a08368037b1445455bc3d0e7240b7b17

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Citations in the corpus

Causal diagrams for interference (2014, background): “An example that often arises in the social science literature is the allocation of children to schools or of children to classrooms within schools (Angrist and Lang, 2004; Graham, Imbens and Ridder, 2010; Hong and Raudenbush, 2008).”
Estimation and Selection of Spatial Weight Matrix in a Spatial Lag Model (2019, background): “Examples include the peer effects of learning in classroom (Angrist and Lang 2004; Ammermuller and Pischke 2009), the spread of crime and delinquent behavior (Glaeser, Sacerdote, and Scheinkman 1996) in criminology, and contagion between financial markets (Longstaff 2010).”
Identification of Social Interactions (2011, background): “For instance, Weinberg’s model is consistent with the finding (Angrist and Lang, 2004) that relocating individuals at risk for certain behaviors or outcomes to less risky groups may have little impact because the at-risk individuals may associate differentially with those who engage in risky…”
Peer Effects in the Diffusion of Solar Photovoltaic Panels (2012, background): “Angrist and Lang (2004) and Ammermueller and Pischke (2009) use a similar argument for why reflection does not confound identification in their studies.”
Do Peers Affect Student Achievement? Evidence from Canada Using Group Size Variation (2010, background): “2003, Angrist and Lang 2004). Other studies analyze peer effects at the classroom level (e.g., Kang 2007, Ammermueller and Pischke 2009). The administrative data we use in this study do not provide information on classes or teachers. Therefore, we assume that for each subject the relevant reference ”
Peer Effects in European Primary Schools: Evidence from Pirls (2006, neutral): “These previous literature finds peer effects which range from close to zero (Angrist and Lang, 2004, and Cullen, Jacob and Levitt, 2003) to relatively large (Hoxby, 2000).”
Improving Content Knowledge and Comprehension for English Language Learners: Findings From a Randomized Control Trial (2017, background): “The considerable literature addressing peer effects on learning (e.g., Angrist & Lang, 2004; Gottfried, 2014; Hanushek, Kain, Markman, & Rivkin, 2003) has focused on socioeconomic status and prior achievement in large-scale extant databases.”
Peer effects in Austrian schools (2005, neutral): “…2003, Fertig, 2003, McEwan, 2003, Levin, 2001, Betts and Zau, 2004, Hanushek et al., 2003, Hoxby, 2000, Vigdor and Nechyba, 2004, Robertson and Symons, 2003, Angrist and Lang, 2004) as well as in higher education (Sacerdote, 2000, Winston and Zimmerman, 2003, Arcidiacono and Nicholson, 2003).”