Evaluating the impact of agricultural economic quality and energy consumption on greenhouse gas emissions: Evidence from China's major grain-producing regions

Our current study employs the entropy method to construct agricultural economic quality indicators based on three aspects: economic scale, economic structure, and economic growth rate. Using the panel data of 13 main grain-producing provinces of China from 1995 to 2020. We used the panel autoregressive distributed lag model (ARDL) and heterogeneous panel Granger causality test to empirically analyze the relationship between agricultural economic quality, agricultural energy consumption, and agricultural greenhouse gas emissions while also exploring the regional heterogeneity. The results show that (1) The Environmental Kuznets Curve is observed in the pattern of agricultural greenhouse gas emissions in major grain producing areas. (2) Agricultural energy consumption positively impacts greenhouse gas emissions in both the short and long term, with a more substantial impact over time. (3) The heterogeneous panel Granger causality test reveals two-way causal relationship between agricultural energy consumption and greenhouse gas emissions, and between agricultural energy consumption and agricultural economic growth quality. Additionally, there is one-way causal relationship from agricultural economic quality to agricultural greenhouse gas emissions. (4) Regional heterogeneity analysis indicates that agricultural energy consumption contributes to reduction in agricultural greenhouse gas emissions in the northern region, whereas in southern regions, agricultural economic quality is positively associated with agricultural greenhouse gas emissions. This research highlights the importance of optimizing the agricultural energy structure, promoting high-quality development of the agricultural economy, and developing region-specific emission reduction strategies to achieve sustainable agricultural development.