老旧小区试点政策对生态韧性的影响——基于我国256个城市面板数据的实证分析
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湖南财政经济学院

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国家自然科学基金面上项目(42371192);湖南省自然科学基金面上项目(2023JJ30100);湖南省社会科学基金重大项目(23ZDAJ023);湖南省社会科学基金一般项目(23YBA133)


The impact of pilot policies for old residential areas on ecological resilience: an empirical analysis based on panel data from 256 cities in China
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Hunan University of Finance and Economics

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    摘要:

    随着城市化进程的加速,城市更新已成为践行新发展理念、推动经济高质量发展的关键举措,其对生态韧性的影响也逐渐成为关注的焦点。选取中国2000—2022年256个城市数据为样本,采用熵值法构建基于“抵抗—适应—恢复”(RAR)三个维度的生态韧性综合评价体系,运用GIS空间分析技术和三维核密度估计方法,深入揭示生态韧性的时空分异规律,并以老旧小区改造试点政策作为城市更新的准自然实验,构建双重差分模型评估城市更新对生态韧性的影响效应和区域异质性。研究发现:(1)在时序演变上,2011年后生态韧性峰值显著右移,核密度分布形态由“单峰”向“双峰”转变,波峰跨度持续拉大,形成明显的“韧性鸿沟”和多层级分化格局,城市间“马太效应”日益凸显;空间分布上,抵抗韧性低值区域从华北向东北转移,适应韧性空间分布波动明显,恢复韧性则由早期的高低交错分布趋向均衡。(2)老旧小区改造政策能够显著促进生态韧性提升,这一结论在经过平行趋势检验、安慰剂检验等一系列稳健性检验后依然成立,表明城市更新对生态韧性具有积极的促进作用。(3)城市更新对生态韧性的影响存在区域异质性,老旧小区试点政策对经济欠发达的西部和东北城市更新的提升作用更强,东部城市次之,而在中部城市影响较弱。基于以上分析,从构建跨区域生态韧性缓冲带、建立韧性导向的城市更新制度体系、完善多元化投融资机制、强化科技创新支撑、开展中部地区政策瓶颈专项治理等方面提出政策建议,以期为推动城市更新与生态韧性协同发展、实现城市高质量可持续发展提供理论依据和实践路径。

    Abstract:

    With the acceleration of urbanization, urban renewal has become a key initiative for implementing new development philosophies and promoting high-quality economic development. Its impact on ecological resilience has gradually become a focus of attention. Utilizing a sample of data from 256 cities in China spanning from 2000 to 2022, this study employed the entropy method to construct a comprehensive evaluation system for ecological resilience based on the three dimensions of "Resistance-Adaptation-Recovery" (RAR). Using GIS spatial analysis techniques and the three-dimensional kernel density estimation method, it delves into the spatiotemporal differentiation patterns of ecological resilience. Furthermore, treating the pilot policy for renovating old residential neighborhoods as a quasi-natural experiment for urban renewal, a difference-in-differences (DID) model was constructed to assess the impact effect and regional heterogeneity of urban renewal on ecological resilience . The findings reveal that: (1) In terms of temporal evolution, after 2011, the peak value of ecological resilience shifted significantly to the right, and the kernel density distribution morphology transitioned from a "unimodal" to a "bimodal" pattern. The span between peaks continued to widen, forming a noticeable "resilience gap" and a multi-tiered differentiation pattern, with the "Matthew Effect" among cities becoming increasingly prominent . Spatially, low-value areas for resistance resilience shifted from North China to Northeast China, the spatial distribution of adaptation resilience showed significant fluctuations, and the level of recovery resilience tended to balance out from the earlier pattern of interwoven high and low values. (2) The old residential neighborhood renovation policy can significantly promote the enhancement of ecological resilience. This conclusion holds even after a series of robustness tests, including parallel trend tests and placebo tests, indicating that urban renewal has a positive promoting effect on ecological resilience . (3) The impact of urban renewal on ecological resilience exhibits regional heterogeneity. The enhancement effect of the pilot policy is stronger in less economically developed western and northeastern cities, followed by eastern cities, while its impact is weaker in central cities . Based on the above analysis, policy recommendations are proposed, including building cross-regional ecological resilience buffer zones, establishing a resilience-oriented institutional system for urban renewal, improving diversified investment and financing mechanisms, strengthening scientific and technological innovation support, and conducting special governance on policy bottlenecks in the central region. These aim to provide a theoretical basis and practical pathways for promoting the synergistic development of urban renewal and ecological resilience, thereby achieving high-quality and sustainable urban development.

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彭文斌.老旧小区试点政策对生态韧性的影响——基于我国256个城市面板数据的实证分析.生态学报,,(). http://dx. doi. org/10.5846/stxb202504291047

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