Can official development assistance promote renewable energy in sub-Saharan Africa countries? A matter of institutional transparency of recipient countries

被引:12
|
作者
Guo, Jiaqi [1 ]
Wang, Qiang [1 ,2 ]
Li, Rongrong [1 ,2 ]
机构
[1] China Univ Petr East China, Sch Econ & Management, Qingdao 266580, Peoples R China
[2] Xinjiang Univ, Sch Econ & Management, Urumqi 830046, Peoples R China
基金
中国国家自然科学基金;
关键词
Causal identification; Double machine learning; Official development assistance; Renewable energy development; CARBON EMISSIONS; IMPACT; AID;
D O I
10.1016/j.enpol.2024.113999
中图分类号
F [经济];
学科分类号
02 ;
摘要
While there are many researches on the impact of official development assistance (ODA) on energy, economic, and environmental in sub-Saharan African countries (SSA), the question of whether ODA promotes renewable energy development in SSA countries remains open and countries. To better understand the relationship between ODA and renewable energy development in SSA, a unique advantage in causality identification technique, Double machine learning (DML) approach is developed. The results show that ODA has a positive impact on the renewable energy development of SSA countries. And a recipient country with a sound management system and a transparent policy environment is more conducive to the positive impact of aid. Reform of aid systems should aim to foster the growth potential of African countries and take full advantage of the positive feedback loop between aid and the renewable energy development. Recipient countries need to make the process of aid implementation as open and transparent as possible in order to dispel the suspicion of donors.
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页数:11
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