中国城市住宅售租比时空分异格局及影响机制

以2009～2017年中国336个地级以上城市为基本研究单元,利用空间趋势面和探索性空间回归技术(ESDA)对中国城市住宅售租比的空间分布进行模拟和估计,并利用地理探测器模型从城市的经济因素、人口因素、社会因素和预期因素4大方面探析售租比时空分异的影响机制。结果表明:中国城市住宅售租比整体呈波动式上升的态势,空间分布呈现出"东高西低"、"东热西冷"的阶梯状格局,且住宅价格、住宅租金和售租比均存在明显的空间正相关性和较强的区域集聚性。收入水平和工资水平是影响售租比最大的因素,住宅预期、人口吸引力、租赁户比重、家庭规模、经济预期等也是影响售租比的重要因素,经济因素、人口因素、预期因素和社会因素的解释力依次减弱,4大因素相互联系、相互作用,形成中国售租比的时空分异格局。

Spatial-temporal Differentiation and Influence Mechanism of the Urban Housing Price-to-rent Ratio in China

Abstract：Based on the basic research units of 336 prefecture-level-and-above cities in China from 2009 to 2017，this article uses the spatial regression trend surface and the exploratory spatial data analysis(ESDA) to simulate and estimate the spatial distribution of urban housing price-to-rent ratio of China, and uses the geographical probe model to explore the influence mechanism of the price-to-rent ratio’s spatial-temporal variance from four main aspects: The city’s economic factors, population factors, social factors and expectational factors. The results showed that: the housing price-to-rent ratio in China is in a fluctuating upward trend. The spatial distribution shows the staircase pattern of “high in the east and low in the west” and “hot in the east and cold in the west”. Meanwhile, there exists an obvious spatial positive correlation and a strong regional agglomeration in housing price, rent and price-to-rent ratio. Income level and wage level are the most important factors affecting the price-to-rent ratio. Residential expectations, population attractiveness, proportion of tenants, family size, and economic expectations are also important factors affecting the price-to-rent ratio. The explanatory power of economic factors, population factors, expected factors and social factors is weakened in turn. The four factors are interrelated and interact to form the temporal and spatial distribution pattern of price-to-rent ratio in China.