Shaoting Wen

Date of Award

12-2024

Document Type

Thesis

Degree Name

Bachelor of Science

Department

Economics

First Advisor

Dr. Timothy Hamilton

Second Advisor

Dr. Maia K. Linask

Abstract

The traditional monocentric and polycentric city model assumes that people commute to the urban centers/subcenters (UCS) for work and, thus the houses close to the centers have convenience premium in commuting cost which drives up their prices. However, with more and more people switching to hybrid /remote working, average commute cost decreases, leading to the location of UCS and commute time influence less on housing price. This paper revisited the hedonic price model under the polycentric city context with the introduction of kernel density estimation (KDE). By choosing three of the top ten high-remote potentials and three of the top ten low-remote potential metropolitan statistical areas (MSAs) as study areas, and American Census Survey 5-Year data and Points of Interest from OpenStreetMap as the data source. The study examined the change of gradient between average commute time/KDE value and housing prices from 2013-2017 to 2018-2022. The results showed that most MSAs, except San Jose, experience dispersion in urban spatial structure. The slope approached zero for most MSAs with high remote working potential and remained unchanged for those with low potential. Except for MSAs in California, the edge effect may play a role and lead to biased results. The research provided a general scope of urban systems after the boom of remote working.

Download

Included in

Economics Commons

Share

COinS