Characteristics and spatiotemporal evolution of phases, risks, and influencing factors in the Chinese real estate market

doi:10.3969/j.issn.1004-9479.2026.07.20240985

Abstract

Abstract:

China's real estate market is currently undergoing a significant transition. Understanding the characteristics of this market stage and mitigating real estate risks is of paramount importance. This study utilizes panel data from various prefecture-level cities in China (2012–2023) to construct a real estate market risk measurement system and conduct a spatiotemporal evolution analysis of market risk, housing price bubbles, and housing price volatility. Using a time-individual double fixed effects model, the study analyzes the factors influencing real estate market risk across different stages, regions, and representative cities. The results indicate that during the study period, the risk pattern expanded from the south to the north and eventually nationwide. Major city clusters along the eastern coast and the dual-core cities of the Chengdu-Chongqing metropolitan area emerged as prominent risk zones. The housing price bubble pattern showed a gradual contraction from west to east, while the spatial distribution of high-bubble regions remained stable. The northeastern region was the first to show a declining trend in housing prices, followed by a slight recovery in 2017. Nationwide, the housing price growth rate significantly decreased in 2022, with southern regions experiencing a greater decline than northern regions. Influencing factors exhibit significant heterogeneity across different stages and scales. For instance, in eastern regions, housing price levels were significantly negatively correlated with real estate market risk from 2016 to 2019. However, from 2020 to 2023, this relationship shifted to a significant positive correlation.

Key words: real estate market, supply and demand relationship, market risk, spatiotemporal evolution

摘要：

当前我国房地产市场正值重要转型阶段，解读市场阶段特征并防范房地产市场风险具有重要意义。本文利用2012—2023年中国各地级市面板数据，构建房地产市场风险测度体系，对市场风险、房价泡沫、房价波动特征展开时空演变分析，并基于时间个体双固定模型探讨不同阶段、不同区域以及典型城市房地产市场风险的影响因素。研究结果显示：研究期内风险格局经历了由南向北再向全国的拓展过程，东部沿海的主要城市群以及成渝城市群的双核心城市为突出风险区。房价泡沫格局呈现自西向东逐步缩小的趋势，高泡沫区域空间格局稳定。东北地区最早出现房价下跌的趋势，2017年迎来短暂小幅回升，全国范围内房价增长率在2022年大幅下降，南部地区下降幅度大于北部地区。不同阶段、不同尺度下的影响因素存在显著的异质性，如东部地区的房价水平因素在2016—2019年与房地产市场风险呈显著负相关，但在2020—2023年转变为显著正相关。

关键词: 房地产市场, 供求关系, 市场风险, 时空演变

Xin GAO, Chenhao DING, Fengqiuyu WANG. Characteristics and spatiotemporal evolution of phases, risks, and influencing factors in the Chinese real estate market[J]. World Regional Studies, 2026, 35(7): 109-123.

高鑫, 丁晨浩, 王逢秋雨. 中国房地产市场阶段特征与风险时空演变及影响因素分析[J]. 世界地理研究, 2026, 35(7): 109-123.

Figures/Tables 13

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目标层	一级指标	二级指标	三级指标	计算方法	单位
房地产市场风险	内部风险	库存风险	住房空置率	商品房待售面积/总面积	%
		库存风险	土地空置率	未成交土地宗数/总宗数	%
		价格风险	房价增长率	当年房价增长值/上年房价	%
		价格风险	土地成交价格增长率	当年土地成交价格/上年成交价格	%
	外部风险	金融风险	房价泡沫指数	房价/居民可支配收入
			居民杠杆率	年末金融机构人民币各项贷款余额/存款余额	%
			实际利用金额		万元
		环境风险	平均工资		万元
			基础设施	医院、卫生院床位数	张
			常住人口数		万人
		政策风险	房地产市场投资完成额		万元
		政策风险	土地出让价格增长率	当年土地出让价格/上年出让价格	%

目标层	一级指标	二级指标	三级指标	计算方法	单位
房地产市场风险	内部风险	库存风险	住房空置率	商品房待售面积/总面积	%
		库存风险	土地空置率	未成交土地宗数/总宗数	%
		价格风险	房价增长率	当年房价增长值/上年房价	%
		价格风险	土地成交价格增长率	当年土地成交价格/上年成交价格	%
	外部风险	金融风险	房价泡沫指数	房价/居民可支配收入
			居民杠杆率	年末金融机构人民币各项贷款余额/存款余额	%
			实际利用金额		万元
		环境风险	平均工资		万元
			基础设施	医院、卫生院床位数	张
			常住人口数		万人
		政策风险	房地产市场投资完成额		万元
		政策风险	土地出让价格增长率	当年土地出让价格/上年出让价格	%

变量/单位		指标选取	指标含义
被解释变量	房地产市场风险(MSK)
解释变量	经济因素(EC)/%	居民可支配收入/GDP	经济发展水平
	社会因素(SOC)/%	失业率	社会稳定性
	政策因素(PCY)/%	房地产投资占固定资产投资比例	政策规制
	土地因素(LD)/%	土地溢价增长率	土地价格水平
	市场因素(MK)/%	平均房价/GDP	市场房价水平
	环境因素(EMT)/%	城镇化率	城市化水平

变量/单位		指标选取	指标含义
被解释变量	房地产市场风险(MSK)
解释变量	经济因素(EC)/%	居民可支配收入/GDP	经济发展水平
	社会因素(SOC)/%	失业率	社会稳定性
	政策因素(PCY)/%	房地产投资占固定资产投资比例	政策规制
	土地因素(LD)/%	土地溢价增长率	土地价格水平
	市场因素(MK)/%	平均房价/GDP	市场房价水平
	环境因素(EMT)/%	城镇化率	城市化水平

波动增长期（2012—2015）		低风险下降期（2016—2019）		高风险增长期（2020—2023）
城市	变化值	城市	变化值	城市	变化值
淮北市	0.158 7	天津市	-0.226 9	揭阳市	0.089 0
宣城市	0.143 4	中山市	-0.104 7	防城港市	0.087 2
巴彦淖尔市	0.134 1	湛江市	-0.092 3	梧州市	0.085 7
亳州市	0.134 1	贵港市	-0.082 3	朝阳市	0.084 1
铜陵市	0.133 2	本溪市	-0.079 7	乌兰察布市	0.082 2
齐齐哈尔市	0.133 2	新余市	-0.068 5	秦皇岛市	0.082 1
银川市	0.133 0	雅安市	-0.066 8	湛江市	0.081 6
芜湖市	0.130 5	普洱市	-0.066 0	普洱市	0.077 9
黄山市	0.128 7	赤峰市	-0.065 7	河池市	0.075 4
乌海市	0.125 9	无锡市	-0.062 4	威海市	0.072 6