Using Linear Regression to Examine Bias in Home Valuation

Presenter: Madelyn Elena Williams

Co-Presenter(s):
Serina Cabrea, Anabel Camarena, Dirk Tolson, Joseph Immel, Salvador Ochoa, Sydney Hernadez,

Presenter Status: Undergraduate student

Academic Year: 22-23

Semester: Spring

Faculty Mentor: Option 22

Department: Mathematics

Funding Source/Sponsor: LSAMP

President's Strategic Plan Goal: Connectivity and Community Engagement

Screenshot URL: https://drive.google.com/uc?id=19DqYv3Hrn4_6FdOJ6Iq2MVc_P6wEuKh4

Abstract:
In a capitalist society, the main tool to determine someone’s wealth is to look at the price on their home. But the price of a home, however, seems to not be weighted the same for all individuals. Home valuation has been determined historically by a percentage of the value of the home in the past transactions. But due to redlining and possible bias from home appraisers, given the lack of diversity among them, enduring bias in home valuation has negatively impacted communities of color. We explore bias through a series of ordinary linear regression models and use the recently released data set shared in the article, \emph{Appraised: The Persistent Evaluation of White Neighborhoods as More Valuable Than Communities Color}, written by Howell & Korver-Glenn (2022).