Department of Economics, Strathclyde Business School, University of Strathclyde, Glasgow, G40 QU2, UK.
Department of Economics & Aberdeen Centre for Research in Energy Economics and Finance (ACREEF), University of Aberdeen Business School, Aberdeen, AB24 3QY, UK.
Environ Sci Pollut Res Int. 2022 Dec;29(58):87426-87445. doi: 10.1007/s11356-022-21729-2. Epub 2022 Jul 9.
This study examines the impact of economic policy uncertainty (EPU) and ecological innovation on carbon (CO) emissions in a panel of 18 developed countries from 2005 to 2018 using second-generation time-series panel data techniques. We use three robust long-run estimators, namely two-stage least squares (2SLS), panel generalised method of moments (GMM) and generalised least squares (GLS), to resolve heterogeneity, endogeneity and simultaneity in the panels. We further performed causality tests to ascertain the direction of causality between the variables. Our estimations suggest three innovative findings. First, economic growth contributes significantly and positively to CO emissions; however, this happens at an optimal level of growth after which carbon emission reduces, indicating that our sample exhibits an inverted U-shaped environmental Kuznets curve (EKC) relationship. Second, the impact of EPU on CO emissions is diverse: high levels of EPU have a significant influence on CO emissions only in high-polluting countries but not in low-polluting ones. Thirdly, research and development (R&D), foreign direct investment (FDI), urbanisation and renewable energy (RE) usage were also found to have varying effects on CO emissions. These findings highlight the heterogeneous relationship between carbon emissions and economic indicators even in advanced economies, as the pollution haven hypothesis (PHH) holds true in high-pollution countries while the pollution halo effect holds for low-pollution ones. A key policy implication of this work is that the quest to mitigate emissions should not be a one-size-fits-all approach because not every country's urbanisation rate, FDI inflows, R&D and renewable energy consumption directly affect CO emissions in the face of economic policy uncertainties.
本研究利用 2005 年至 2018 年期间来自 18 个发达国家的面板第二代时间序列面板数据技术,考察了经济政策不确定性(EPU)和生态创新对碳(CO)排放的影响。我们使用了三种稳健的长期估计量,即两阶段最小二乘法(2SLS)、面板广义矩法(GMM)和广义最小二乘法(GLS),以解决面板数据中的异质性、内生性和同时性问题。我们进一步进行了因果关系检验,以确定变量之间的因果关系方向。我们的估计得出了三个创新性的发现。首先,经济增长对 CO 排放有显著的正向贡献;然而,只有在增长达到最佳水平后,碳排放才会减少,这表明我们的样本呈现出倒 U 型环境库兹涅茨曲线(EKC)关系。其次,EPU 对 CO 排放的影响是多样化的:高水平的 EPU 仅对高污染国家的 CO 排放有显著影响,而对低污染国家则没有影响。第三,研究与开发(R&D)、外国直接投资(FDI)、城市化和可再生能源(RE)的使用也被发现对 CO 排放有不同的影响。这些发现强调了即使在发达经济体中,碳排放与经济指标之间的关系也是异质的,因为污染避难所假说(PHH)在高污染国家成立,而污染光环效应在低污染国家成立。这项工作的一个关键政策含义是,减排的努力不应该是一刀切的方法,因为在经济政策不确定性面前,并非每个国家的城市化率、FDI 流入、R&D 和可再生能源消费都直接影响 CO 排放。