Recently, there has been growing concern about the impacts of geopolitical tension as well as economic and political uncertainties on the decision-making process of governments when it comes to allocating resources for renewable energy R&D. This paper employs the panel autoregressive distributed lag (ARDL), cross-sectional panel autoregressive distributed lag (CS-ARDL) and Fully Modified Ordinary Least Squares (FMOLS) technique to examine the impacts of geopolitical risk, economic and political uncertainties, renewable energy technologies innovations, government financial affordability and CO2 emissions on government spending on renewable energy research and development projects. The novel aspects of the panel ARDL and CS-ARDL methodologies lie in their ability to capture both short-run and long-run dynamics within a panel data framework, as well as their ability to provide a more comprehensive understanding of the relationships under investigation. The empirical results presented in this paper indicate that in the face of ongoing geopolitical tension, as well as economic and political uncertainties, financially capable governments continue to increase their investments in renewable energy R&D in the long run. This strategic move aims to safeguard the supply of renewable energy, uphold economic and political policy credibility, maintain a first-mover advantage, and establish control over the intellectual property rights associated with renewable energy technology.

中文翻译：

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对可再生能源研发项目的公共投资：地缘政治风险的作用，以及经济和政治的不确定性


近年来，人们越来越担心地缘政治紧张局势以及经济和政治不确定性对政府在分配可再生能源研发资源时的决策过程的影响。本文采用面板自回归分布式滞后 （ARDL）、横截面面板自回归分布式滞后 （CS-ARDL） 和完全修改的普通最小二乘法 （FMOLS） 技术来研究地缘政治风险、经济和政治不确定性、可再生能源技术创新、政府财政负担能力和二氧化碳排放对政府可再生能源研发项目支出的影响。面板 ARDL 和 CS-ARDL 方法的新颖之处在于它们能够在面板数据框架内捕获短期和长期动态，以及它们能够更全面地理解所调查的关系。本文提出的实证结果表明，面对持续的地缘政治紧张局势以及经济和政治的不确定性，从长远来看，财政能力强的政府将继续增加对可再生能源研发的投资。这一战略举措旨在保障可再生能源的供应，维护经济和政治政策的可信度，保持先发优势，并建立对与可再生能源技术相关的知识产权的控制。