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Title: How the marketing of real estate properties explains mortgage applicants by race and income
In this article, we study how the marketing of single-family homes explains the racial and income makeup of mortgage applicants in a neighborhood. We use a case study of the robust housing market of Charlotte, North Carolina, and annual, longitudinal real estate listing advertisements alongside mortgage lending data, to demonstrate how the share of properties advertised a certain way in a neighborhood in 1 year explains shares of mortgage applicants by race and income the following year. We classify property advertisement text using a semi-supervised learning algorithm into five categories following a housing investment and disinvestment to renewal continuum. We find stark racial disparities in mortgage applicants by housing type, even after controlling for income. We find that Black applicants nearly exclusively apply for mortgages in neighborhoods with a high share of properties advertised as disinvested with little profit-making promise. High-income White applicants rise as the share of advertised properties becomes more homogenous.  more » « less
Award ID(s):
2314726
PAR ID:
10599950
Author(s) / Creator(s):
;
Publisher / Repository:
SageJournals
Date Published:
Journal Name:
Environment and Planning B: Urban Analytics and City Science
ISSN:
2399-8083
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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