土地收储

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涉及专项债收储土地,二季度以来爆发式增长
Zheng Quan Shi Bao· 2025-05-15 11:17
Core Insights - The scale of land acquisition using special bonds by local governments has seen explosive growth since the second quarter of this year, with a total planned acquisition amount reaching 391.8 billion yuan across 171 cities by May 13 [1][2] - The proposed land acquisition area in April alone reached 71,980 hectares, exceeding the total for the first quarter in both area and amount [1][2] - If the planned land acquisitions are realized, it could lead to a year-on-year increase of at least 54% in new housing transaction area for the first four months of 2025, significantly reducing the new housing inventory cycle by over two months [1][5] Land Acquisition Scale - As of May 13, 2023, 171 cities have announced plans for land acquisition using special bonds, with a total acquisition amount of 391.8 billion yuan, including 1,575 residential land plots valued at 225 billion yuan and covering 65,650 hectares [2][3] - The majority of the planned acquisitions are concentrated in third and fourth-tier cities, which account for 84% of the total area and 74% of the total acquisition price [3] Market Dynamics - The land acquisition strategy is seen as a new model for cities to reduce inventory, with the theoretical construction area from the planned residential land exceeding 130 million square meters, which is more than half of the estimated new housing sales for the first four months [5] - If all planned acquisitions are executed, 14 cities could see a reduction in inventory cycles by over one year, with some cities potentially reducing their cycles by more than three years [5] Recommendations for Implementation - It is suggested that local authorities accelerate the transformation of planned acquisitions into actual acquisitions to shift the policy focus from stabilizing expectations to stabilizing the market [6] - A transparent information mechanism should be established to detail land ownership, regional distribution, and development progress, allowing for precise identification of inventory pressure across different city sectors [6]