College of Economics and Management, Northwest Agricultural and Forestry University, Yangling, Xianyang, China.
College of Economics, Sichuan Agricultural University, Chengdu, China.
Environ Sci Pollut Res Int. 2020 Apr;27(12):13575-13589. doi: 10.1007/s11356-019-07501-z. Epub 2020 Feb 6.
Increasing population and food demand has led to steadily declining resources as a result of over-exploitation and fossil fuel consumption that cause air contamination and reduce soil fertility. Therefore, this study aimed to investigate the correlation between air pollution, energy consumption, and the contribution of agriculture to national GDP. Secondary study data covering two decades were collected from different sources, and an autoregressive distributed lag (ARDL) bounds testing model was employed to determine long-run and short-run correlations. First, the unit root test was used to determine the stationarity of variables, and results showed that variables were integrated at level, ARDL co-integration equation estimation, which rejected the null hypothesis at less than 5% significance level. Further, based on the results of the ARDL bounds testing model, F-statistic values exceeded the upper bound value. This entire model was adjusted at a speed of -2.364 towards long-run equilibrium. In addition, CUSUM test and CUSUMSQ test results confirmed the goodness of fit of this model. In light of the resulting policy implications, the Chinese government may consider measures to improve the agricultural industry to meet the food demand for the fast-growing population while maintaining a healthy environment and safeguarding the available limited resources for future generations.
人口增长和粮食需求的增加导致资源不断减少,这是由于过度开采和化石燃料消耗造成的空气污染和土壤肥力下降。因此,本研究旨在探讨空气污染、能源消耗以及农业对国民生产总值的贡献之间的相关性。本研究从不同来源收集了涵盖二十年的二手研究数据,并采用自回归分布滞后 (ARDL) 边界检验模型来确定长期和短期相关性。首先,使用单位根检验来确定变量的稳定性,结果表明变量在水平上是整合的,ARDL 协整方程估计在 5%的显著性水平下拒绝了零假设。此外,根据 ARDL 边界检验模型的结果,F 统计量值超过了上限值。整个模型以 -2.364 的速度向长期均衡调整。此外,CUSUM 检验和 CUSUMSQ 检验结果证实了该模型的拟合优度。鉴于由此产生的政策影响,中国政府可能会考虑采取措施改善农业,以满足快速增长的人口对粮食的需求,同时保持健康的环境和保护未来几代人可用的有限资源。