Spatial interactive effects on housing prices in Shanghai and Beijing

Juncong Guo and Xi Qu

Regional Science and Urban Economics, 2019, vol. 76, issue C, 147-160

Abstract: When connected through economic, financial, and policy shocks, cities can be considered to be neighbors in the social-economic sense. Therefore, a spatial correlation may exist in cities that are not geographically contiguous. The paper simultaneously studies the spatial correlation within each city and the spatial interactive effects among different cities on housing prices. We build a spatial autoregressive hedonic pricing model in a system of interrelated networks, which allows for multiple spatial interactive effects among housing units inside the same city and from other cities. For estimation, we propose a two-stage least squares (2SLS) method and the maximum likelihood estimation (MLE). Finite sample properties of these two methods are investigated in a Monte Carlo simulation. After applying these steps to March 2016 housing prices in Shanghai and Beijing, the empirical findings show that the spatial correlations within each city are significantly large, i.e., approximately 0.6–0.8, and spatial interactive effects between the two cities exist, although the magnitude is smaller, i.e., approximately 0.1–0.2.

Keywords: Spatial autoregressive model; Spatial interactive effect; Hedonic housing price (search for similar items in EconPapers)
JEL-codes: C31 C51 R32 (search for similar items in EconPapers)
Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (13)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:regeco:v:76:y:2019:i:c:p:147-160

DOI: 10.1016/j.regsciurbeco.2018.07.006

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