How Aggregate Growing Season Temperature Metrics May Lead to Overestimation of the Effects of High Temperatures on Crop Yields: Evidence From China

Existing studies generally use “aggregate” temperature measures—such as mean temperature, degree‐days, temperature bins, and piecewise linear functions within the growing season—to estimate the impact of global warming on crop yields. These temperature measures blend temperatures from different phenological stages of crop growth, thereby implicitly assuming that temperatures are additively substitutable within the growing season. However, this assumption contradicts agronomic knowledge, which indicates that crops are more sensitive to temperatures during certain phenological stages. Utilising unique site‐level data on the detailed phenological stages of major crops in China, combined with crop production data and daily weather data, we develop an econometric model with stage‐specific temperature measures. We then compare our estimates with models using traditional aggregate temperature measures. Our results show that adopting an aggregate temperature measure could overestimate the damage of predicted global warming on crop yields by up to two times compared to estimates using stage‐specific temperature measures.