Spatial Heterogeneity in Temperature Elasticity of Agricultural Economic Production in Xinjiang Province, China

Agricultural production is significantly impacted by climate change. Owing to its arid and warm climate, investigating the impacts of climate change on agricultural production in Xinjiang Province can help improve resilience and designate adaptive responses for the agricultural sector. On the basis of agricultural output data at the county level in Xinjiang from 1990–2019, we used the feasible generalized least squares (FGLS), panel-corrected standard errors (PCSE), and double machine learning (DML) model to study the spatial heterogeneity in temperature elasticity of agricultural economic production. The results revealed that there is an inverted U-shape of temperature impact on agricultural economic production. The presented temperature elasticity in county level showed that regions with negative temperature elasticities are primarily located in the mainstream of the Tarim basin and the Turpan basin in southern Xinjiang. The SHapley Additive exPlanations (SHAP) analysis was further incorporated to elucidate the impact of different factors on the spatial heterogeneity in temperature elasticity. The results indicated that temperature is the most substantial factor influencing temperature elasticity, with labor and precipitation following in sequence. In particular, increased precipitation in arid and hot regions could alleviate the heat stress and lead to a positive temperature elasticity prediction. These findings provide a scientific basis for spatial heterogeneity in the response of agricultural economic production to climate change, and help identify priority regions for achieving Sustainable Development Goals (SDGs) 1 and 2.