Hasan Kalyoncu University, Gaziantep, Turkey.
Department of Computing and Informatics, Bournemouth University, Bournemouth, UK.
Environ Sci Pollut Res Int. 2022 Nov;29(52):78330-78344. doi: 10.1007/s11356-022-21099-9. Epub 2022 Jun 11.
To a large extent, the theories and concepts behind the effect of ecological footprint have been the paramount concern of the recent literature. Since the rising and falling of environmental degradation have been a continuous issue since the first phase of development, determinants such as economic complexity may play a critical role in achieving long-term sustainable development in the framework of environmental Kuznets curve (EKC) paradigm. Therefore, this research expands on the notion of an EKC paradigm for the world's top ten most complex economies by considering four variables, such as real GDP per capita, electricity consumption, trade openness, and a new putative factor of environmental obstacle, the economic complexity index (ECI). This is one of the first studies to look at the impact of ECI on the ecological footprint of a specific sample from 1998 to 2017. The findings demonstrate a continuous inverted U-shaped link between real GDP per capita, the square of real GDP per capita, and ecological footprint. The EKC hypothesis is found to be valid in the long term in the examined complex economies. The findings of the panel autoregressive distributed lag (ARDL) of the pooled mean group (PMG) and fully modified ordinary least squares (FMOLS) estimations demonstrate that in the long term, electric power usage contributed to the carbon footprints. Furthermore, the economic complexity index and trade openness increase environmental performance over time. To determine if there is causation between the variables, we employ the panel vector error correction model (VECM) framework. Particularly, the results show unidirectional causality running from electric power consumption to ecological footprint and bidirectional causal relationship between (1) economic growth and ecological footprint; (2) square of economic growth and ecological footprint; (3) economic complexity index and ecological footprint; and (4) trade openness and ecological footprint.
在很大程度上，生态足迹效应背后的理论和概念一直是近期文献的首要关注点。自发展的第一阶段以来，环境恶化的起伏一直是一个持续存在的问题，因此，经济复杂性等决定因素可能在环境库兹涅茨曲线（EKC）范式框架内对实现长期可持续发展起到关键作用。因此，本研究通过考虑四个变量（如人均实际 GDP、电力消耗、贸易开放度以及一个新的假定环境障碍因素——经济复杂性指数（ECI）），扩展了全球十大最复杂经济体的 EKC 范式概念。这是首次研究 ECI 对特定样本（1998 年至 2017 年）生态足迹影响的研究之一。研究结果表明，人均实际 GDP、人均实际 GDP 的平方和生态足迹之间存在持续的倒 U 型关系。在考察的复杂经济体中，长期来看 EKC 假设是有效的。面板自回归分布滞后（ARDL）的混合均值组（PMG）和完全修正最小二乘法（FMOLS）估计结果表明，电力使用在长期内对碳足迹有贡献。此外，经济复杂性指数和贸易开放度随着时间的推移提高了环境绩效。为了确定变量之间是否存在因果关系，我们采用面板向量误差修正模型（VECM）框架。具体来说，结果表明，电力消耗与生态足迹之间存在单向因果关系，经济增长与生态足迹之间存在双向因果关系；（2）经济增长的平方与生态足迹；（3）经济复杂性指数与生态足迹；以及（4）贸易开放度与生态足迹。
