Abstract: To investigate the existence of a property market bubble in China and its contagion characteristics, panel data from 35 large and medium-sized Chinese cities over the period 2012—2023 were utilized. A house price-to-rent ratio sequence was constructed, and the generalized sup augmented Dickey-Fuller (GSADF) test was applied to identify the presence of housing bubbles and their start and end points. Four typical urban agglomerations and three specific time points were further selected, and a time-varying parameter vector autoregressive (TVP-VAR) model was employed to examine the dynamic contagion effects of house price bubbles in core cities on other cities. The GSADF test results indicate that housing price bubbles are prevalent across the 35 large and medium-sized cities, although there are regional variations in the number of bubbles, the periods in which they occur, and their duration. Some cities remain in the bubble continuation phase, whilst others may re-enter a new phase of bubble accumulation under the stimulus of accommodative macro-control policies. The TVP-VAR model results show that the contagion of housing price bubbles exhibits a hierarchical diffusion pattern centered on Shenzhen, spreading sequentially from first-tier to new first-tier to second-tier cities, with a spatial stepwise attenuation pattern declining from the eastern to the central and western regions. Regarding the drivers of contagion, geographical proximity emerges as the primary cause of short-term bubble chain reactions, whilst economic interdependence serves as the core driver of long-term deep contagion. Based on these findings, policy recommendations are proposed from three dimensions: strengthening regulatory measures in core cities, optimizing the evaluation mechanism for regulatory policies, and enhancing policy timeliness. Theoretical support and empirical evidence are provided for assessing the effectiveness of regulatory policies, implementing differentiated macroeconomic controls, and preventing systemic financial risks.