Affirmatively Furthering Fair Housing's Boundary Problem

Keywords: affordable housing, urban geography, planning, applied geography
Session Type: Virtual Paper Abstract
Day: Friday
Session Start / End Time: 2/25/2022 05:20 PM (Eastern Time (US & Canada)) - 2/25/2022 06:40 PM (Eastern Time (US & Canada))
Room: Virtual 45

Abstract

Prior to recent rule changes, which are still being revised as of this writing, state and local jurisdictions charged by the federal government with Affirmatively Furthering Fair Housing (AFFH) have been required to perform regular analyses of impediments (AIs) to identify barriers to fair housing in their territories. One of the AI's core elements is the delineation racially or ethnically concentrated areas of poverty (R/ECAPs). Traditionally, jurisdictions completing AIs identify these R/ECAPs using data measured at locations wholly within their jurisdictional borders, ignoring surrounding communities. Doing so provides local decision-makers with key knowledge of spaces in their jurisdictions where housing security might be relatively problematic. Crucially, however, performing these analyses on a piecemeal, jurisdiction-by-jurisdiction basis can reinforce, rather than reverse, the processes that produce residential segregation and concentrated poverty. This paper offers an example of how such an outcome might occur using information drawn from the most recent (February 2020) attempt at producing a Countywide, regional AI in Erie County, NY, home to the City of Buffalo. The distribution of R/ECAPs calculated for that AI on a jurisdiction-by-jurisdiction basis are compared to R/ECAP distributions that result from spatial analyses that ignore municipal boundaries and operate on the entire study area. The thought exercise offers several insights that can inform the ongoing debates surrounding AFFH rule changes, which are expected to take place in 2022.