<p>Given the complex urban internal spatial structure, the housing market in megacities is usually not a unified one but consists of multiple local submarkets. Compared to the housing purchase/sales market, rental housing market segmentation is more intricate due to specific rental demands and seasonal market fluctuations. This paper fills the literature gap by detecting general determinants and seasonal variations of rental prices, proposing a conceptual framework, and presenting an effective approach of rental submarkets identification. The global regression model confirmed the general effects of location, job accessibility, amenities and built environment on housing rental prices. A significant seasonal effect was observed in the rental market. The multiscale geographically weighted regression model suggested the spatially varying effects of various hedonic attributes. The local relationship between housing rents and hedonic attributes is determined greatly by the accessibility to the main function of the local area. Rental submarkets were identified based on the dominant factors influencing rents in local areas. The submarkets dominated by centre-location and the submarkets dominated by job accessibility cover most areas. There are few local premiums for amenities and no amenity-dominated submarkets. Finally, the improved approach to identifying urban housing submarkets and the optimisation of zoning housing policies were discussed.</p>

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Examining Rental Housing Market Segmentation in Chinese Megacities: The Case of Beijing

  • Jiajie Liu,
  • Tao Liu,
  • Guangzhong Cao

摘要

Given the complex urban internal spatial structure, the housing market in megacities is usually not a unified one but consists of multiple local submarkets. Compared to the housing purchase/sales market, rental housing market segmentation is more intricate due to specific rental demands and seasonal market fluctuations. This paper fills the literature gap by detecting general determinants and seasonal variations of rental prices, proposing a conceptual framework, and presenting an effective approach of rental submarkets identification. The global regression model confirmed the general effects of location, job accessibility, amenities and built environment on housing rental prices. A significant seasonal effect was observed in the rental market. The multiscale geographically weighted regression model suggested the spatially varying effects of various hedonic attributes. The local relationship between housing rents and hedonic attributes is determined greatly by the accessibility to the main function of the local area. Rental submarkets were identified based on the dominant factors influencing rents in local areas. The submarkets dominated by centre-location and the submarkets dominated by job accessibility cover most areas. There are few local premiums for amenities and no amenity-dominated submarkets. Finally, the improved approach to identifying urban housing submarkets and the optimisation of zoning housing policies were discussed.