Taxi activity as a predictor of residential rent in New York City
Author(s)Caporaso, Philip(Philip S.)
Massachusetts Institute of Technology. Center for Real Estate. Program in Real Estate Development.
Alex van de Minne.
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Real estate developers and investors have a vested interest in discovering new techniques for estimating the direction and magnitude of changes in residential rent within a neighborhood. This study hypothesizes, and finds evidence, that taxi activity is a proxy for changing income and neighborhood quality as well as an indicator of gentrification. Novel research is performed to determine if taxi activity is a significant predictor of rents in New York City at the neighborhood level. Nine OLS regression models are created using data about 1,466,234,991 taxi pickups and drop-offs, median rent, and median income across 188 neighborhoods in New York City in the years of 2010-2015. In all nine models, taxi activity is found to be a statistically significant predictor of rent at 99% confidence. This study finds that a I standard deviation positive shock in taxi drop-offs will result in a 0.009% 0.155% higher rent the next year on average.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Thesis: S.M. in Real Estate Development, Massachusetts Institute of Technology, Program in Real Estate Development in conjunction with the Center for Real Estate, 2019Cataloged from PDF version of thesis.Includes bibliographical references (pages 28-29).
DepartmentMassachusetts Institute of Technology. Center for Real Estate. Program in Real Estate Development
Massachusetts Institute of Technology
Center for Real Estate. Program in Real Estate Development.