Study on Development of Renewable Energy in Rural China and Driven Factors Based on A DEA Model

Abstract

In November in 2009, China announced a new carbon intensity reduction target in 2020 year to manifest the commitment of the Chinese government to dealing with climate change. The development of renewable energy is not only an important measure to accelerate the adjustment of energy structure, but also a key measure to decrease the Carbon emissions. This paper firstly introduces the theory of Data Envelopment Analysis. Then, we establish a development prospects model of Chinese rural renewable energy, and make a empirical analysis based on the data of Chinese 27 provinces for the year 2012. The results show that development of most rural renewable energy is not perfect, there is a big space for development. Furthermore, the finding shows that input indicators, including population, consumption and education are the main factors that affect the development of renewable energy in rural China.