Does One Size Fit All? Defining Neighborhood Size in a World of Diverse Metro Areas

Authors: David Folch*, Florida State University
Topics: Population Geography, Spatial Analysis & Modeling, Urban and Regional Planning
Keywords: neighborhood size, microdata, regionalization
Session Type: Paper
Day: 4/11/2018
Start / End Time: 3:20 PM / 5:00 PM
Room: Astor Ballroom III, Astor, 2nd Floor
Presentation File: No File Uploaded


There is a long literature on the role neighborhoods have on the outcomes of individuals. However, operationalizing “neighborhood” remains a tricky matter: when drawn too large (in terms of population), the context can be diluted; and when drawn too small, the context may not be representative. There is further concern that neighborhood size itself may be context dependent, with larger metro areas potentially having inherently larger neighborhoods.

We explore the interaction of neighborhood size and metro area size, and the implication of this interaction on urban analyses. We are focused on metro area comparisons that use data aggregated to neighborhoods within each metro. We do this using newly available geolocated individual level microdata from the US Census Bureau. This restricted-use data provides a latitude/longitude for each American Community Survey respondent. Using 100 metropolitan statistical areas (MSAs), we consider the implication of population size on measures of residential segregation. The tests are operationalized by repeatedly splitting each MSA into neighborhoods of different sizes: first holding the population of each neighborhood constant for all MSAs and then holding the number of neighborhoods constant for all MSAs.

This work will inform users on the role of the modifiable areal unit problem (MAUP) in comparative regional analysis. Specifically, if it is more appropriate to hold population size relatively constant across neighborhoods (as is the model for census tracts) or whether publicly available enumeration units should be grouped (using regionalization for example) so that each metro under comparison has approximately the same number of neighborhoods.

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