Extreme weather events pose a growing threat to agricultural production and food security. Using a panel of 221 prefecture-level cities in China with annual observations from 2010 to 2023, the study develops an agricultural economic resilience index covering resistance, recovery, and adaptation and applies a double machine learning approach to estimate the effects of climate shocks on resilience. Climate shocks are decomposed into low temperatures, high temperatures, precipitation, and drought to examine their differentiated impacts. From an adaptive investment perspective, three mitigation pathways are tested: fiscal support for agriculture, factor productivity, and agricultural industrialization. Extreme climate shocks significantly weaken agricultural economic resilience. Extreme drought exhibits a positive effect, contrary to conventional expectations. Fiscal support and agricultural industrialization effectively buffer these negative impacts, while factor productivity’s buffering effect exhibits a long-term lag. Non-grain-producing regions are more vulnerable and suffer larger losses from climate shocks. This study offers fresh evidence on the climate-resilience nexus and provides implications for aligning climate governance, fiscal support, and agricultural industrialization in China. The main limitation is that farm-level adaptive investment is not directly observed.
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Wang et al. (2026) studied this question.
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