文献类型： 外文期刊

作者： Xiao Gu;Xiaohan Gu;Weizheng Wang;Difei Hu

作者机构：

关键词： China JEL Classification: O13;GDP;P28;Political risk index;public-private partnership investment in energy;Q42;Q43;renewable electricity output;renewable energy consumption

期刊名称： Politicka Ekonomie

ISSN： 0032-3233

年卷期： 2024 年 72 卷 2 期

页码：

收录情况： SSCI（2024版）

摘要： In the pursuit of sustainable development, economies such as China are placing a paramount emphasis on significantly augmenting the utilization of renewable energy sources. This marks a departure from conventional research approaches that solely focused on macroeconomic determinants while investigating patterns of renewable energy consumption. Thus, this research pursues to witness the relationship between the political risk index (PRI), renewable electricity output (RELOP), public-private partnership investment in energy (PPINENR), and renewable energy consumption (RECNS) in China from 1984 to 2022. For data estimations, this study utilizes time series methods, which include DF-GLS and Johansen cointegration for unit root and long-run equilibrium with FMOLS, DOLS and CCR as primary methods. The research also employs the least squares method with break years and robust least squares as robustness check methods while for causal relationships, we deploy the Granger causality approach. The outcomes assert that variables are found stationary at differences and long-run equilibrium is confirmed among variables. The empirical estimations predict that GDP and PPINENR reduce the RECNS in China in both short and long term. Furthermore, PRI and RELOP enhance renewable energy consumption in the short as well as long run. Therefore, policymakers should mostly focus on the encouraging role of PPINENR towards renewable electricity to enhance RECNS in developing economies, particularly in China. To achieve the targets of COP27, China should increase its focus on the efficient utilization of public-private partnership investments and also manage the political risks in the economy to promote renewable energy consumption and achieve a sustainable environment. Moreover, the causality analysis unearths that PRI could be utilized along with other variables to enhance RECNS in China. The robustness check asserts similar and robust outcomes.

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