Enhancing clean energy financial policies: Financing efficiency of new energy industry based on DEA-BCC-Malmquist-Tobit Model
Keywords:
new energy enterprises; financing efficiency; evaluate; influencing factorAbstract
The “double carbon” objective presents opportunities for new energy enterprises, though financing efficiency remains a significant challenge. This paper assesses the financing efficiency of 153 new energy enterprises from 2017 to 2021 using DEA-BCC (Differential Evolution Algorithm-Bias Corrected and Accelerated) and DEA-Malmquist models, providing both static and dynamic perspectives. The Tobit model is employed to analyze the factors influencing financing efficiency, with a case study on Shanghai Electric. Key findings include: (1) New energy enterprises and Shanghai Electric show diversified financing channels (internal financing, debt, equity, and financial support) with a positive trend. (2) Despite this, their financing remains inefficient. From 2017 to 2021, only about 15% of new energy enterprises achieved DEA effectiveness, with overall financing efficiency impacted by changes in scale efficiency. Dynamic analysis shows an overall improvement, but low efficiency persists. For Shanghai Electric, while its comprehensive technical efficiency was optimal between 2017 and 2020, it declined in 2021 due to suboptimal scale efficiency. Low technical progress and scale efficiency contributed to this inefficiency. (3) Factors affecting financing efficiency include enterprise size, green technology innovation, capital structure, government support, and employee quality. For new energy enterprises, scale is inversely related to financing efficiency, while the other factors positively influence it. For Shanghai Electric, enterprise size, employee quality, capital structure, and government support significantly impact its financing efficiency.
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