关键词: 房地产市场风险, 风险形成机制, 复杂网络, TOP1等级网络

Abstract: Preventing and defusing risks in the real estate sector is essential for maintaining national economic stability. The key lies in clarifying the intrinsic interrelationships among real estate risk factors and uncovering the underlying risk formation mechanisms. This paper proposes a node importance evaluation method that integrates node degree and constraint coefficients to address the limited discriminative power of traditional network analysis methods in identifying critical factors. By applying a TOP1 network to filter key interaction paths among risk factors, it reveals how risks emerge and compares the risk structures across different cities. The results indicate that consumer purchasing power and the availability of development funds are the core determinants of real estate market risk nationwide. However, city-level heterogeneity exists. In first-tier cities, risk is predominantly driven by land prices, whereas in second-tier cities, urbanization levels play a more significant role. Specifically, the key risk pathways in first-tier cities exhibit a “chain-like” structure (land price→consumer purchasing power→economic development level→land supply), while in other cities, the structure is more “star-shaped”, with consumer purchasing power as the central hub directly linked to multiple influencing factors.

Key words: real estate market risks, formation mechanism of risks, complex networks, TOP1 ranking network