Does the climate-adaptive city pilot policy exacerbate urban sprawl? Evidence from a quasi-natural experiment in China

Although climate-adaptive policies are primarily designed to enhance urban resilience, they may also generate unintended consequences for urban spatial development. However, the impacts of climate-adaptive governance interventions on urban sprawl remain underexplored. This study employs double machine learning method to examine how the climate-adaptive urban pilot policy affects urban sprawl and the underlying mechanisms, using 285 Chinese prefecture-level cities from 2010 to 2021. Results show that pilot policy significantly promotes urban sprawl, a conclusion validated by robustness tests. Fiscal resource allocation and green infrastructure expansion are plausible potential pathways behind this effect, while land use efficiency and intensity show no significant impact. Noticeable heterogeneity exists across city characteristics; the policy generates a stronger sprawl effect in non-central cities than in central cities, and its impacts increase with city size. Along the urbanization gradient, the policy effect follows a U-shaped pattern and is most prominent in highly urbanized areas. Moreover, suggestive evidence points to policy-related spillovers from climate-adaptive pilot contributing to urban sprawl in adjacent regions. Geographically weighted random forest combined with double machine learning further reveals significant positive spatial dependence in urban sprawl across geographically proximate cities, together with substantial cross-city heterogeneity and a distance-decay pattern. These findings offer crucial insights into multi-dimensional impacts of climate-adaptive urban policy, supporting future urban planning and policy-making.