Abstract
China’s rapid urbanization has driven significant economic growth, but has also resulted in resource depletion, ecological degradation, and inefficient land use, collectively hindering sustainable development. In response, pilot policies for “low-carbon cities” and “carbon emissions trading” have been implemented to enhance urban land use efficiency. This study evaluates the green land use efficiency of 282 prefectural-level cities in China from 2006 to 2023, using the non-expected output super-efficiency SBM model. Some cities serve as pilot sites for both “low-carbon cities” and “carbon emissions trading.” A multi-period Difference-in-Differences model is employed to empirically assess the impact and mechanisms of this “dual-pilot” policy on green land use efficiency. The findings indicate the following: (1) The dual-pilot policy significantly improves green land use efficiency, with coordinated implementation yielding greater efficiency gains than single-policy approaches. (2) Mechanism analysis suggests that these policies enhance efficiency by promoting technological innovation and industrial agglomeration. (3) Heterogeneity analysis reveals that the policy’s impact is stronger in western regions, cities with high human capital, large urban centers, areas with stringent environmental regulations, and non-resource-dependent cities. (4) Spatial econometric analysis shows that while low-carbon policies improve local land use efficiency, they also create a siphoning effect on neighboring areas, with positive impacts observed within a 100–600 km range, diminishing and turning negative beyond 600 km. These insights provide a valuable framework for sustainable urban planning, emphasizing the importance of adaptive, context-sensitive policy design in addressing complex ecological and economic challenges.
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Liu, Z., Wei, Y., Liao, R., Yamaka, W., & Liu, J. (2025). Synergistic Effects of Dual Low-Carbon Pilot Policies on Urban Green Land Use Efficiency: Mechanisms and Spatial Spillovers Through Difference-in-Differences and Spatial Econometric Analysis. Land, 14(4). https://doi.org/10.3390/land14040882
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