Spatial analysis of high school dropout: The role of race, poverty, and outliers in New York City

A major problem in urban areas, dropping out of high school is often related to a host of student-level factors, like poverty, race, gender, and behavior. Studies also find that social factors like school context and peer beliefs influence this phenomenon. However, these studies on social factors are limited by the non-inclusion of spatial data, which are important given how neighborhood dropout rates may be associated with adjacent neighborhoods. To address this gap, the present research suggests a method for analyzing spatial patterns of dropping out and the role of race, poverty, and outliers. Using exploratory spatial data analysis of New York City census tracts (n = 2216), the study finds significant spatial clusters for high school dropouts, racial minority population, and low-income areas. However, co-location patterns of dropping out and race/poverty suggest smaller core clusters, and outlier-detection for areas with dropout rates different from adjacent neighborhoods suggest that higher concentrations of minorities and poverty do not automatically lead to higher levels of dropout. Implications include resource allocation and contextualized support for high dropout clusters, and investigation of outlier neighborhoods.