AI Article Synopsis

  • The study investigates how a lack of temporal information affects the measurement of racial bias in mortgage lending, particularly for Black Americans, by incorporating trends over time and credit scores.
  • It focuses on two metropolitan areas (Boston-Cambridge-Newton and Dallas-Fort Worth) from 1990 to 2020, finding that both had significant changes in mortgage denial odds, with Dallas-Fort Worth showing increased bias while Boston-Cambridge-Newton showed decreased bias.
  • The research highlights that areas historically affected by redlining exhibited the strongest bias persistence; it emphasizes the importance of temporal data in understanding and addressing ongoing discrimination in housing policies.

Article Abstract

According to the uncertain geographic context problem, a lack of temporal information can hinder measures of bias in mortgage lending. This study extends previous methods to: (1) measure the persistence of racial bias in mortgage lending for Black Americans by adding temporal trends and credit scores, and (2) evaluate the continuity of bias in discriminatory areas from 1990 to 2020. These additions create an indicator of persistent structural housing discrimination. We studied the Boston-Cambridge-Newton and Dallas-Fort Worth metropolitan statistical areas to examine distinct historical trajectories and urban development. We estimated the odds of mortgage denial for census tracts. Overall, all tracts in Boston-Cambridge-Newton (N = 1003) and Dallas-Fort Worth (N = 1312) displayed significant change, with greater odds of bias over time in Dallas-Fort Worth and lower odds in Boston-Cambridge-Newton. Historically redlined areas displayed the strongest persistence of bias. Results suggest that temporal data can identify persistence and improve sensitivity in measuring neighborhood bias. Understanding the temporality of residential exposure can increase research rigor and inform policy to reduce the health effects of racial bias.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11461407PMC
http://dx.doi.org/10.1007/s11524-024-00887-3DOI Listing

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