影响沙特阿拉伯生态足迹的因素:面板数据分析

Abdulaziz Aldegheishem
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摘要

过去几十年来,由于支持经济发展和城市化对能源的需求不断增加,全球环境面临的环境风险也随之增加。人类活动的不断升级消耗了自然资源,加剧了这些环境风险。因此,分析影响生态足迹(EFP)的因素(包括城市化、能源消耗、自然资源、经济增长和技术创新等诸多变量)对于实现可持续发展至关重要。城市化是经济增长的主要驱动力。实现经济发展需要利用自然资源和能源,而自然资源和能源会增加能源消耗总量。因此,重视技术创新对于减少环境消耗潜能值至关重要。尽管影响 EFP 的因素对环境和经济具有重要影响,但这方面的研究却很缺乏,特别是在中东国家,而且研究结果相互矛盾。因此,本研究的主要目的是调查城市化、能源消耗、自然资源、经济增长和技术创新对沙特阿拉伯 EFP 的影响。为此,本研究采用了自回归分布滞后(ARDL)模型,该模型被认为是在变量静止于 I (0) 或 I (1) 阶积分时最合适的计量经济学方法,其依据是从各种国际来源收集的 1990 年至 2022 年期间的数据。无论从长期还是短期来看,实证研究结果表明,城市化、自然资源和技术创新都会降低能源效率指数,而能源消耗和经济增长则会提高能源效率指数。这些结果表明,需要解决能源政策问题,由于经济政策与环境目标之间缺乏联系,经济增长无法降低能源消耗总量。另一方面,研究表明,城市政策和自然资源管理与环境目标之间存在有效联系。这些研究结果对降低环境影响因子有若干重要的政策影响。建议包括通过经济电气化将经济政策与环境目标有效联系起来。此外,还应考虑若干程序,包括用可再生能源取代当前的碳基能源,重新评估能源系统的定价,增加碳基能源税,以及重新评估当前的能源法律法规。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Factors affecting ecological footprint in Saudi Arabia: a panel data analysis
The global environment has witnessed an increase in environmental risks over the last few decades due to the rising demand for energy to support economic development and urbanization. These environmental risks are exacerbated by the escalating human activity that depletes natural resources. Therefore, analyzing factors affecting Ecological Footprint (EFP), which include many variables such as urbanization, energy consumption, natural resources, economic growth, and technological innovation, is essential to achieve sustainable development. Urbanization is a key driver of economic growth. Achieving economic development requires the utilization of natural resources and energy which increase the EFP. Therefore, the focus on technological innovation is essential to reduce the EFP. Despite the critical environmental and economic implications of factors affecting EFP, studies on this area are lacking, especially across Middle Eastern countries, and present contradictory findings. Therefore, the main aim of this study is to investigate the effect of urbanization, energy consumption, natural resources, economic growth, and technological innovation on the EFP in Saudi Arabia. To this end, the study utilizes an autoregressive distributed lag (ARDL) model, which is considered the most suitable econometric approach when variables are stationary at I (0) or integrated of order I (1), based on data collected from various international sources for the period spanning from 1990 to 2022. In both the long run and the short run, empirical findings show that urbanization, natural resources, and technological innovation decrease the EFP, while energy consumption and economic growth increase the EFP. These results reveal that energy policies need to be addressed, and economic growth is unable to lower the EFP due to a lack of connection between economic policies and environmental goals. On the other hand, the study shows that urban policies and the management of natural resources are effectively linked to environmental goals. These findings have several significant policy implications for reducing the EFP. Suggestions include effectively linking economic policies to environmental goals by electrifying the economy. Additionally, several procedures should be considered, including replacing current carbon-based energy with renewable sources, reevaluating the pricing of the energy system, increasing taxes on carbon-based energy, and reassessing current energy laws and regulations.
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