Taxi activity as a predictor of residential rent in New York City

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.

Department dc:contributor.department

Massachusetts Institute of Technology. Center for Real Estate. Program in Real Estate Development

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2019

Author dc:creator

• Caporaso, Philip(Philip S.)

Advisor dc:contributor.advisor

• Alex van de Minne.

• Center for Real Estate. Program in Real Estate Development.

Statement dc:rights

• 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.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/123616

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/123616