In the 13th Five-Year Plan, the Chinese government declared that one of the sustainable policy priorities is improving the energy supply composition in order to reduce greenhouse gas emissions. In accordance with the Plan, the Guangdong government subsequently planned to invest in low-carbon energy infrastructure from 2016 to 2020. Using data from Guangdong province and other regions in China for 2007–2016, we propose a two-stage network data envelopment analysis (Network DEA) model to examine the sustainable performance of the Chinese regional/provincial economic system. We postulated that the less sustainable performance of Chinese regional economic systems may be attributed to lower energy productivity performance. However, we found that increased governmental and industrial spending on electricity mix improvement by building new low-carbon power plants created momentum in Guangdong’s economic growth, which experienced an annual rise of roughly 1.16%. Finally, the results from the two-stage Network DEA model showed that Guangdong fared better than other provinces with respect to sustainable performance. Investment in low-carbon energy infrastructure is not only a measure to combat CO2 emission, but could act as the driving force of regional economic systems.
Stochastic p-robust approach to two-stage network DEA model
