Climate Change and Agricultural Productivity in China: Evidence from Parametric and Robust Nonparametric Frontiers

Climate change poses a major challenge to global food security, making it crucial to understand its effects on agricultural productivity. This paper examines how climate affects agricultural total factor productivity (TFP) in China using both parametric panel models and robust nonparametric order‑m frontiers. We find that higher temperatures in hot seasons are associated with lower agricultural TFP, mainly through reduced technical efficiency rather than slower technical change. This negative relationship remains robust after addressing the statistical issues of standard two-stage DEA procedures. The nonparametric conditional frontier analysis further shows that the climate–efficiency relationship is highly nonlinear and exhibits an inverted‑U shape at some temperature levels, suggesting possible benefits from long-term adaptation policies. Our results underscore the importance of targeted interventions aimed at improving technical efficiency to mitigate the adverse impacts of climate change on China’s agricultural productivity. JEL classification: C22, O47, Q54