The National Equity Research Database
*Names in bold indicate Presenter
To address these issues, we have developed the National Equity Research Database (NERD), a national, longitudinal database of nearly 300 ACS indicators based on the ACS Summary Files. All indicators are available for multiple geographic summary levels, 1- and 5-year data. 156 of the 300 indicators are available by race/ethnicity. The data are available for all census tracts in the country and over time; the most recent data is based on 2018 ACS estimates.
Crucially, we generate estimates for local, historically defined city neighborhoods. Using a tract-to-neighborhood crosswalk, we aggregate tract data up to city neighborhoods, as defined and understood by local stakeholders. The resulting estimates apply to locally meaningful geographies and have acceptable margins of error, even when broken down by race/ethnicity. We have created and publicly released neighborhood level for the City of Boston, available here: https://icyfp.brandeis.edu/research/nerd/. In addition to the 300 longitudinal indicators for neighborhoods, NERD Boston also includes estimates for reference geographies, including the City of Boston and 197 municipalities in the Boston Metro Area, and the Commonwealth of Massachusetts.
To calculate Boston neighborhood estimates, we aggregated data from 178 tracts to 17 neighborhoods. Margins of error for neighborhood estimates are substantially smaller compared to their tract-level counterparts. For example, the median 90% margin of error across all neighborhood-level percentage estimates for non-Hispanic Whites is 3.2 percentage points and 6.0 percentage points for persons of color (individuals who are not non-Hispanic whites). At the census tract level, the corresponding statistics are 10.2 and 17.6 percentage points, respectively.
We are currently generating similar datasets for other cities, redeveloping our web platform for hosting and visualizing the data, and incorporating the 2018 Summary Files.
- Noelke_NERDBostonUserGuide.pdf (281.1KB)