To deal with the increasing number of climate disasters and the negative impacts of climate change, cities need to improve their climate resilience. This may influence the process of industrial ecological transformation. This paper uses the pilot policy of the climate‐resilient city construction (CRCC) in 2017 as a natural experiment. Using data from 278 cities in China from 2012 to 2021, we use the difference‐in‐differences (DID) model to explore the impact of climate governance on the industrial ecological transformation (IET). The results are as follows. First, climate governance actions can promote the industrial ecological transformation, and this positive effect is still significant after robustness tests. Second, the mechanism suggests that climate‐resilient city construction facilitates the industrial ecological transformation of cities by promoting technological advancement and improving urban energy efficiency. Third, there is obvious heterogeneity in the impact of climate‐resilient city construction on industrial ecological transformation. It has a stronger effect in non‐old industrial bases and central cities. In addition, we further examined the results using the double machine learning model (DML). This paper provides an important reference for improving the regional coordinated development mechanism of climate policies and continuously promoting the climate‐resilient city construction.

Climate policy is crucial in shaping global responses to environmental challenges and steering societies towards sustainable and resilient futures. Thus, in research study, we examine the impacts of Economic (ECONF), Environmental (ENVF), Social (SOCF), and Governance (GOVNF) factors, as well as the combined (ECON-ESG) factors, on Climate Policy Uncertainty (CPU) at the global level. The new ECON-ESG form of sustainability, defined in this study, refers to the holistic approach to sustainability by including economic factors (ECON) to traditional ESG factors. Empirical findings reveal that while environmental (E) and social (S) factors worsen the CPU, economic factors (ECON) improve it in the long run. Governance (G) factors have no impact on the CPU. While a 1 % increase in E and S increases the CPU by 22 % and 27 %, the same percentage increase in ECON decreases it by 40 %. These results clearly show that analyses conducted only through the conventional form of ESG may be insufficient and inaccurate in analyzing the effects on the CPU. Our study's result should not be considered limited to the CPU only, and it will be helpful to use this proposed form, ECON-ESG, as a more comprehensive sustainability concept in sustainability studies since it also incorporates economic factors. This approach will enable policymakers to look at climate policies through a holistic sustainability lens with ECON-ESG. These results show that policymakers should adopt a holistic sustainability approach that includes economic factors when shaping climate policies.