Frontiers in Sustainable Food Systems (Aug 2024)
Do agricultural credit, wheat, and rice production impact environmental quality? Novel evidence from China’s mega agricultural regions
Abstract
Gaining a comprehensive understanding of the carbon emissions cycle in the atmosphere resulting from agricultural activities is crucial for assessing its influence on environmental quality. This study used panel datasets covering the period from 1990–2022 to investigate the influence of wheat and rice production on environmental quality in the six mega agricultural provinces of China namely Anhui, Hebei, Hubei, Henan, Jiangsu, and Sichuan. Study employed several econometric approaches such as Cross-Sectional Dependency tests, unit root and cointegration tests, Panel Mean Group Autoregressive Distributed Lag (PMG-ARDL), Panel Quantile (PQ) and Panel Least Square (PLS) regression analysis for the robustness of the findings. The empirical findings of PMG-ARDL model reveal that rice production positively increases CO2 emissions in the long run. The variables fertilizers usage, agricultural water consumption and agricultural credit also have positive impact on CO2 emission in the long run. Further, short-term results reveal that all the concerned variables positively contribute to increase the CO2 emissions. The PQR results illustrate that rice and wheat production, fertilizer consumption, agricultural water usage, agricultural credit and agricultural GDP have positive and significant impact on CO2 emission across the quantiles. Additionally, PLS outcomes show positive and significant association between wheat productivity, agricultural credit, fertilizer and agricultural GDP on CO2 emissions. The Dumitrescu and Hurlin (D–H) panel causality show unidirectional association among: carbon emission → pesticides use, carbon emission → temperature, and carbon emission → agricultural GDP. A significant bidirectional causal association was found between: carbon emission ↔ rice production, carbon emission ↔ wheat production, carbon emission ↔ fertilizers use, carbon emission ↔ agricultural water use, and carbon emission ↔ agricultural credit. These findings contribute to the understanding of the drivers of CO2 emissions in agriculture and provide valuable insights for policymakers aiming to mitigate environmental impacts while promoting sustainable agriculture, resilience, financial support to encourage green technology and implement robust monitoring mechanisms to protect quality of environment and agricultural sustainability.
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