The effect of climate adaptation policies on productivity: evidence from Chinese cities

Climate adaptation policies are intended to mitigate the damages associated with climate risks and promote sustainable urban development. Using panel data from Chinese cities from 2000 to 2022, this study employs causal inference methods, including the difference-in-differences model and the double-debiased machine learning model, to assess the impact of climate adaptation policies on carbon total factor productivity. The results show that, following the implementation of these policies, carbon total factor productivity in the treatment group increased by approximately 30.90%. Climate adaptation policies improve climate-vulnerable production factors’ adaptability, thereby enhancing labor and capital productivity. Moreover, these policies strengthen the effectiveness of climate mitigation efforts, which raise carbon productivity and boost carbon total factor productivity. Importantly, climate adaptation policies show a preferential effect in regions with higher exposure to extreme climate risks and relatively limited economic capacity, resulting in notably positive policy outcomes. Finally, this research further substantiates these conclusions using the double dual machine learning model.