Renewable Energy Generation Efficiency of Asian Economies: An Application of Dynamic Data Envelopment Analysis

Abstract

Due to the continuous growth of global energy demand and the urgent pursuit of sustainable development goals, renewable energy development has become a vital strategy to deal with energy challenges and environmental issues. Renewable energy generation efficiency (REGE) around the world has begun to be examined, and ambitious goals with a sense of mission within a predetermined timeline have been set. The goal of this paper is to use the dynamic slacks-based measure (DSBM) data envelopment analysis (DEA) method to obtain the REGE for 44 Asian economies from 2010 to 2021. This paper also uses Tobit regression analysis to explore the factors that may affect the REGE. The empirical results indicate that the REGE in 17 economies reached the efficiency target during this period. When classified by income level, differences in average REGE are observed among high-income, upper-middle-income, lower-middle-income, and low-income economies. Additionally, differences in average REGE exist between tropical and temperate economies when classified by geographic latitude. Furthermore, through the Tobit regression model, we determine that information digitalization, financial openness, technological innovation ability, and renewable energy device capacity share all have significant positive effects on REGE, but life quality and democracy degree have significant negative impacts on REGE. Moreover, it has been found that the REGE scores of Asian economies exhibit a status similar to the middle-income trap. The outcome of the research provides Asian governments and those middle-income economies with ways to enhance REGE. Due to data limitations, this study cannot estimate the convergent solution based on the data of the research sample, and a new advanced Panel Tobit model is required.

Keywords

• DSBM model
• Tobit regression analysis
• middle-income trap
• energy challenge