Data Sheet 1_Promote or inhibit: how climate policy uncertainty may shape extreme weather’s impact on grain production.pdf

IntroductionWhile existing research recognizes that policy conditions can influence the link between climate change and agricultural output, a critical question has long been overlooked—even if policy direction is correct, if policies are volatile and unpredictable, they can themselves become a source of risk. How this policy uncertainty alters the relationship between climate change and agricultural production lacks in-depth exploration in academia. This study aims to fill this critical gap by specifically revealing how Climate Policy Uncertainty (CPU) moderates the effects of temperature and precipitation on grain yields.
MethodsThis study employs panel data from 286 prefecture-level cities in China spanning 2001–2020. Based on the C-D production function, it adopts an economic-climate interaction model, incorporates CPU as a moderating variable, and conducts empirical tests using regression method.
ResultsThere exists a significant inverse U-shaped relationship between climatic factors and grain yields. However, when CPU increases, this relationship curve becomes significantly steeper, meaning the negative impact of extreme climate on grain yields is amplified. In other words, policy instability may exacerbate the destructive force of climate change. Further regional analysis reveals that this “amplification effect” of CPU is more prominent in non-major grain-producing areas: in the north, it primarily intensifies the precipitation-yield relationship, while in the south, it amplifies the temperature-yield relationship. It is noteworthy that in non-climate adaptation pilot cities, CPU exhibits a more pronounced negative moderating effect.
DiscussionThe core implication of this research is that in the face of climate change, the clarity, coherence, and predictability of policies are themselves a crucial form of adaptive capacity. Ensuring policy stability can effectively stabilize farmers’ production expectations and incentivize long-term investments to combat climate risks. Further, the results also underscore the necessity of driving systemic transformation to convert external risks into endogenous drivers, then CPUs’ responses can be internalized as assets against future extreme weather within a risk framework in the future. Ultimately, anchoring climate-policy regimes in stable, Nature-Based Solutions—especially by advancing them across the Global South—offers a scalable pathway to turn policy uncertainty into ecological and social resilience.