粤港澳大湾区住房租金的空间差异与影响因素

以粤港澳大湾区58个县区单元的住房平均租金为基本数据,通过“住房租金等级金字塔”构建、租金空间格局展示、空间自相关分析、跨境租金差距对比、售租比研究等方法总结粤港澳大湾区住房租金的空间差异格局与特征。从“租赁需求+城市基本面”的理论视角构建由新增人口、人均住房面积、收入水平、经济水平、产业结构、学历结构组成的租金差异影响因素模型。通过模型对比,采用空间滞后模型测度粤港澳大湾区住房租金的主要影响因素,并基于地理探测器分析其因素的影响强度差异。结果表明,粤港澳大湾区住房租金总体呈现以港澳与珠三角九市之间的境内外差异为主、以广深核心区与其他区域差异为辅的双层次差异格局。跨境租金差异程度最高,广州、深圳、珠海的“售租比”较高;收入水平、经济水平、人均住房面积和产业结构对粤港澳大湾区的住房租金差异有显著影响,其中,收入水平的影响强度最高。

Spatial differentiation and influencing factors of housing rents in the Guangdong-Hong Kong-Macao Greater Bay Area

"Livability" is at the core of building a high-quality living circle in the Guangdong-Hong Kong-Macao Greater Bay Area (GHMGBA), and the excessive housing burden costs have become an important obstacle to livability. The differentiation of the rental market is an indispensable and important part of the housing market in the GHMGBA and is inseparable from the creation of a livable life circle. Based on the average housing rent of 58 counties in the GHMGBA, this study summarizes the patterns and characteristics of the spatial differences in housing rents through the construction of a “grading pyramid of housing rents”, and displays the spatial pattern of housing rents through spatial autocorrelation analysis, cross-border rent gap comparison, and price-to-rent ratio analysis. From the theoretical perspective of leasing demand and urban fundamentals, this study constructs a model of factors influencing rent differences, consisting of population growth, per capita housing area, income level, economic level, industrial structure, and education structure. Through model comparison, a spatial lag model was used to measure the main factors influencing the housing rents in the GHMGBA. Based on the geographical detector, the study further analyzed the differences in the intensity of the factors' influence. The results showed that the housing rents in the GHMGBA generally presented a two-level difference pattern. The pattern was dominated by domestic and foreign differences between Hong Kong, Macao, and nine cities in the Pearl River Delta, as well as the differences between the core areas of Guangzhou, Shenzhen, and other regions. The cross-border rent difference was the highest. Higher price-to-rent ratios were observed in Guangzhou, Shenzhen, and Zhuhai. Income level, economic level, per capita housing area, and industrial structure had a significant impact on housing rent differences in the GHMGBA. Among them, income level had the highest impact intensity. This study responds to cross-border regional differences within the country from the perspective of housing rent. Cross-border differences are not only reflected in the population′s economic, income, and institutional levels, but also in the housing rent. The key issue for the regional linkage development of the housing market in the GHMGBA and the construction of a livable and quality living area is the coordinated development across borders.