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

This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.

Bibliographic Details
Main Author: Caporaso, Philip(Philip S.)
Other Authors: Alex van de Minne.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2020
Subjects:
Online Access:https://hdl.handle.net/1721.1/123616
_version_ 1811075705300058112
author Caporaso, Philip(Philip S.)
author2 Alex van de Minne.
author_facet Alex van de Minne.
Caporaso, Philip(Philip S.)
author_sort Caporaso, Philip(Philip S.)
collection MIT
description This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
first_indexed 2024-09-23T10:10:17Z
format Thesis
id mit-1721.1/123616
institution Massachusetts Institute of Technology
language eng
last_indexed 2024-09-23T10:10:17Z
publishDate 2020
publisher Massachusetts Institute of Technology
record_format dspace
spelling mit-1721.1/1236162020-03-24T04:00:43Z Taxi activity as a predictor of residential rent in New York City Caporaso, Philip(Philip S.) Alex van de Minne. Massachusetts 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 Center for Real Estate. Program in Real Estate Development. 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). 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. by Philip Caporaso. S.M. in Real Estate Development S.M.inRealEstateDevelopment Massachusetts Institute of Technology, Program in Real Estate Development in conjunction with the Center for Real Estate 2020-01-23T17:00:25Z 2020-01-23T17:00:25Z 2019 2019 Thesis https://hdl.handle.net/1721.1/123616 1135875319 eng 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. http://dspace.mit.edu/handle/1721.1/7582 29 pages application/pdf n-us-ny Massachusetts Institute of Technology
spellingShingle Center for Real Estate. Program in Real Estate Development.
Caporaso, Philip(Philip S.)
Taxi activity as a predictor of residential rent in New York City
title Taxi activity as a predictor of residential rent in New York City
title_full Taxi activity as a predictor of residential rent in New York City
title_fullStr Taxi activity as a predictor of residential rent in New York City
title_full_unstemmed Taxi activity as a predictor of residential rent in New York City
title_short Taxi activity as a predictor of residential rent in New York City
title_sort taxi activity as a predictor of residential rent in new york city
topic Center for Real Estate. Program in Real Estate Development.
url https://hdl.handle.net/1721.1/123616
work_keys_str_mv AT caporasophilipphilips taxiactivityasapredictorofresidentialrentinnewyorkcity