现在和未来:农业是否影响沙特阿拉伯王国的经济增长和环境?

Abda Emam
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引用次数: 3

摘要

全球气候变化是一个至关重要的环境问题。全球变暖主要是由二氧化碳(CO2)排放水平引起的。农业生产是导致二氧化碳产生和环境退化的众多经济活动之一。在本研究中,我们旨在揭示农业生产(枣生产)对农业国内生产总值(AGDP)和环境(CO2排放)的影响。我们收集了1990年至2019年期间不同资源的枣产量、AGDP和二氧化碳排放量的数据。为了分析数据,我们使用了Engle-Granger两步法、自回归分布滞后(ARDL)界分析方法、回归分析和预测检验。全修正普通最小二乘(FMOLS)和动态普通最小二乘(DOLS)分析的结果有助于证实ARDL模型的结果。结果表明,农业生产总值与枣产量、二氧化碳排放量与枣产量之间存在长期关系。第一个结果是理论的结果,导致经济增长,而第二个结果表明对环境的负面影响。为了确定哪些生产因素导致了这一负结果,我们进行了回归分析,结果表明,用电量系数(自变量)在解释二氧化碳排放的变异性方面是正的,并且非常显著。回归分析结果还显示,研究期间农业通过增加CO2排放对环境产生负向影响。预测分析结果显示,2020 - 2026年CO2排放量呈下降趋势。研究结果使我们建议,为了促进经济增长,应该增加枣产量,同时同步使用可再生能源。政府也应该通过增加可再生电力在总电力消耗中的份额来加强和继续维持环境的努力。
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Present and future: Does agriculture affect economic growth and the environment in the Kingdom of Saudi Arabia?
Global climate change is a crucial environmental issue. Worldwide warming is primarily caused by carbon dioxide (CO2) emission levels. Agricultural production is among many economic activities driving CO2 creation and environmental degradation. In this study, we aim to disclose the effect of agricultural production (date production) on the agricultural gross domestic product (AGDP) and the environment (CO2 emissions). We collected data on date production, AGDP and CO2 emissions from different resources covering the period from 1990 to 2019. To analyse the data, we used the Engle-Granger two-step procedure, autoregressive distributed lag (ARDL) bounds methods of analysis, regression analysis and forecasting tests. Results from fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) analyses helped confirm the results of the ARDL model. The results revealed that there are long-run relationships between AGDP and date production and between CO2 emissions and date production. The first result is consequent with theory and leads to economic growth, whereas the second result indicates a negative effect on the environment. To ascertain which production factors were responsible for this negative result, we ran a regression analysis, and the results indicated that the coefficient of electricity consumption (independent variable) was positive and highly significant in explaining the variability of CO2 emissions. The results of the regression analysis also showed that agriculture affected the environment negatively through increasing CO2 emissions during the study period. Forecasting analysis results showed a decrease in CO2 emissions for the period from 2020 to 2026. The study results lead us to recommend that, to increase economic growth, date production should be increased along with the synchronised use of renewable sources of electricity. The governmental effort to sustain the environment also should be increased and continued through increasing the share of renewable electricity in total electricity consumption.
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