Taxi activity as a predictor of residential rent in New York City
Name
1135875319-MIT.pdf
Size
379.76 KB
Format
Adobe PDF
Checksum (MD5)
e0d485f378217550b4a9f71c4e68b42a
Author(s)
Caporaso, Philip(Philip S.)
Advisor(s)
Alex van de Minne.
Date Issued
2019
Publisher
Massachusetts Institute of Technology
Abstract
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.
Description
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, 2019
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 28-29).
Subjects
Center for Real Estate. Program in Real Estate Development.
MIT Department
Massachusetts Institute of Technology. Center for Real Estate. Program in Real Estate Development
Massachusetts Institute of Technology. Center for Real Estate
Terms of Use
MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
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