Sector sustainability on fossil fuel power plants across Chinese provinces: Methodological comparison among radial, non-radial and intermediate approaches under group heterogeneity

Abstract

Data Envelopment Analysis (DEA) has been widely applied to the performance analysis of energy and environment. This study compares empirical differences from using the three approaches by considering group heterogeneity under two disposability concepts. A main message to be conveyed to the audience is that it is necessary for us to avoid a methodological bias (i.e. different methodologies produce different results), often occurring in empirical works. The methodological concern is important for DEA applications, in particular when guiding a large policy issue related to energy and environment. To document the research importance, this study applies the three DEA approaches to examine the sector sustainability of fossil fuel power plants in China’s coastal and inland provinces. Our conclusions are threefold. First, Chinese provinces have paid attention to their operational efficiencies for economic developments under governmental catching-up policy. Second, coastal provinces outperform inland ones in terms of their operational efficiencies. Thus, there is a regional imbalance between the two province groups. The Chinese government needs to allocate resources and technology (e.g. clean coal technology) to inland provinces so that their fossil fuel power plants can attain high operational efficiencies and enhance the level of sector sustainability. Finally, these power plants in all provinces have been operating under governmental regulations and international pressure on air pollution. As a consequence, this study cannot find any major difference in their environmental efficiencies.