School of Economics, Sichuan University, China.
University of Swat, Saidu Sharif, Khyber Pakhtunkhwa, PK 19130, Pakistan.
J Environ Manage. 2020 Oct 1;271:111028. doi: 10.1016/j.jenvman.2020.111028. Epub 2020 Jul 8.
This study provides new empirical evidence on the determinants of renewable energy consumption in the case of OECD economies over the period from 1990 to 2017. To examine the long run relationship among variables of renewable energy consumption and its determinants, this study uses the Durbin Hausman group mean cointegration test. The long-run and short-run coefficients are estimated via the cross-sectional Autoregressive Distributive Lag (CS-ARDL) method. The significant cointegration vector confirms the long-run equilibrium among the variables presented in the model. The results show that income, human capital, energy productivity, energy prices, and eco-innovation are important factors in explaining renewable energy consumption. This study adopts the Augmented Mean Group (AMG) method to check the robustness of the model. The results are found to be consistent with the estimates of the cross-sectional Autoregressive Distributive Lag Model method. To offer viable solutions to environmental problems and to achieve the targets set in the Paris Climate Agreement, policies and strategies should be devised to increase the share of renewable energy in the overall energy mix.
本研究提供了新的经验证据，说明在 1990 年至 2017 年期间经合组织经济体可再生能源消费的决定因素。为了检验可再生能源消费及其决定因素变量之间的长期关系，本研究使用了 Durbin Hausman 组均值协整检验。通过横截面自回归分布滞后（CS-ARDL）方法估计长期和短期系数。显著的协整向量证实了模型中呈现的变量之间的长期均衡。结果表明，收入、人力资本、能源生产力、能源价格和生态创新是解释可再生能源消费的重要因素。本研究采用广义平均组（AMG）方法来检验模型的稳健性。结果与横截面自回归分布滞后模型方法的估计结果一致。为了解决环境问题并实现《巴黎气候协定》设定的目标，应制定政策和战略来提高可再生能源在总能源组合中的份额。
