School Neighborhood Poverty Estimates

EDGE’s school neighborhood poverty estimates rely on household economic data from the U.S. Census Bureau’s American Community Survey (ACS) and EDGE’s public school geocodes to estimate the income-to-poverty ratio for neighborhoods around school buildings. Unlike neighborhood poverty estimates created from survey responses collected for predefined geographic areas like census tracts, EDGE’s school neighborhood poverty estimates are spatially interpolated demographic estimates (SIDE), i.e., estimates that predict conditions at specific point locations based on the ACS survey responses nearest to those locations. This approach allows SIDE estimates to extract new value from existing data sources to create indicators of neighborhood conditions. The economic conditions of school neighborhoods may be different from the economic conditions in neighborhoods where students live. However, the economic condition of the neighborhood around a school may impact schools, just as the conditions of neighborhood schools may impact local neighborhoods. The school neighborhood poverty estimates provide an additional indicator to help identify these local conditions.

School Neighborhood Poverty Estimates (311 KB)

Additional Resources

Geverdt, D. and Nixon, L. (2018). Sidestepping the box: Designing a supplemental poverty indicator for school neighborhoods (NCES 2017-039) (1.54 MB). U.S. Department of Education. Washington, DC: National Center for Education Statistics.

Gribov, A. & Krivoruchko, K. (2020). Empirical Bayesian kriging implementation and usage. Science of the Total Environment. 722 (2020), 137290. https://doi.org/10.1016/j.scitotenv.2020.137290

Krivoruchko, K. & Gribov, A. (2019). Evaluation of empirical Bayesian kriging. Spatial Statistics. 32 (2019), 100368. https://doi.org/10.1016/j.spasta.2019.100368