Exploring the Spillover Effects of Urban Renewal on Local House Prices Using Multi-Source Data and Machine Learning: The Case of Shenzhen, China

Xiaojun Li, Jieyu Wang, Ke Luo, Yuanling Liang and Shaojian Wang ()
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Xiaojun Li: Guangzhou Urban Planning & Design Survey Research Institute, Guangzhou 510060, China
Jieyu Wang: Guangdong Provincial Key Laboratory of Urbanization and Geo-Simulation, School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China
Ke Luo: Guangzhou Urban Planning & Design Survey Research Institute, Guangzhou 510060, China
Yuanling Liang: Guangzhou Urban Planning & Design Survey Research Institute, Guangzhou 510060, China
Shaojian Wang: Guangdong Provincial Key Laboratory of Urbanization and Geo-Simulation, School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China

Land, 2022, vol. 11, issue 9, 1-16

Abstract: Urban renewal is a current hotspot for research in the field of urban geography and urban planning. However, few studies have been able to quantify the impact of urban renewal on local house prices. Taking Shenzhen as an example, this paper measures the added premium effect of urban renewal on local house prices through econometric models and multi-source data and explores the spillover effect of urban renewal on house prices using an integrated model based on machine learning and Geo-detector analysis. The main findings are: (1) Shenzhen’s urban renewal had a significant positive premium effect on the unit transaction price of local housing. (2) The population characteristics and the accessibility to transport in the context of urban renewal are the main drivers for premiums on house prices. (3) There is spatial heterogeneity with respect to the housing premium effect due to urban renewal, among which optimization of the density of the road network is most closely associated with the premium effects. The interaction of the road density network and the population density of particular streets drives the medium premium effect. Our findings have important implications for refinements in management practices for urban renewal in the context of the housing market.

Keywords: urban renewal; house prices; premium; machine learning; Shenzhen (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:gam:jlands:v:11:y:2022:i:9:p:1439-:d:902845

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