Skip to main navigation Skip to search Skip to main content

Effects of locations, structures and neighbourhoods to housing price: an empirical study in Shanghai, China

  • Vivian W. Y. Tam*
  • , Ivan W. H. Fung
  • , Jing Wang
  • , Mingxue Ma
  • *Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

Since Chinese housing market has been reformed, the increasing housing price has been a focus of the whole society. Shanghai, as the economic and financial center in China, is one of the cities which have the highest housing price. However, the high housing price has gradually become an important economic problem, as it could create huge challenges to maintain a healthy real estate industry in China. A comprehensive understanding of the relationship between housing market and its impactors is in need to control the housing price. This paper will focus on Shanghai housing market and analyse relationship between 12 housing characteristics and housing price, using hedonic price model. It is found that the 12 housing characteristics impact Shanghai housing price differently. This paper could provide newest and largest amount of data as references to researchers and investors who concern about Shanghai housing market, and help government to formulate a proper housing price policy.
Original languageEnglish
Pages (from-to)1288-1307
JournalInternational Journal of Construction Management
Volume22
Issue number7
Online published27 Nov 2019
DOIs
Publication statusPublished - 2022

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities

Research Keywords

  • China
  • Hedonic price model
  • housing characteristics
  • housing price
  • Shanghai

Fingerprint

Dive into the research topics of 'Effects of locations, structures and neighbourhoods to housing price: an empirical study in Shanghai, China'. Together they form a unique fingerprint.

Cite this