治理质量对可再生能源和不可再生能源消费的影响:可解释的决策框架

IF 3.4 3区 经济学 Q1 ECONOMICS
Futian Weng, Dongsheng Cheng, Muni Zhuang, Xin Lu, Cai Yang
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引用次数: 0

摘要

本研究基于 SHapely Additive exPlanations 方法,分析了治理质量(六个方面:政府效率、腐败控制、发言权和问责制、监管质量、政治稳定和无暴力、法治)对可再生能源和不可再生能源消费预测的影响,以实现模型分析和可解释性。实证结果表明,在 E-7 和 G-7 国家中,治理质量的六个方面对不可再生(可再生)能源消费预测的时变贡献差异很大。国家内部治理质量的时变贡献具有异质性和非对称性,尤其是 E-7 国家(G-7 国家)中的印度(德国)。国家间治理质量的预测贡献分布在 G-7 国家比 E-7 国家更加离散。我们的研究结果对于政策制定者和投资者通过治理质量提高可再生能源消费水平,从而克服基于国家本身的环境挑战具有重要意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The effects of governance quality on renewable and nonrenewable energy consumption: An explainable decision frame

This study analyzes the effect of governance quality (six aspects: government effectiveness; control of corruption; voice and accountability; regulatory quality; political stability and absence of violence; and rule of law) on the renewable and nonrenewable energy consumption prediction based on the SHapely Additive exPlanations method for model analysis and interpretability. The empirical findings indicate that the time-varying contributions of six aspects of governance quality on nonrenewable (renewable) energy consumption predicting vary greatly in E-7 and G-7 countries. The time-varying contribution of governance quality within countries is heterogeneous and asymmetrical, especially India (Germany) in E-7 countries (G-7 countries). The prediction contribution distribution of governance quality between countries is more discrete in G-7 countries than E-7 countries. Our results are of great importance to policymakers and investors for enhancing the renewable energy consumption level in overcoming environmental challenges based on the country itself through governance quality.

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来源期刊
CiteScore
5.40
自引率
5.90%
发文量
91
期刊介绍: The Journal of Forecasting is an international journal that publishes refereed papers on forecasting. It is multidisciplinary, welcoming papers dealing with any aspect of forecasting: theoretical, practical, computational and methodological. A broad interpretation of the topic is taken with approaches from various subject areas, such as statistics, economics, psychology, systems engineering and social sciences, all encouraged. Furthermore, the Journal welcomes a wide diversity of applications in such fields as business, government, technology and the environment. Of particular interest are papers dealing with modelling issues and the relationship of forecasting systems to decision-making processes.
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