Total-factor industrial eco-efficiency and its influencing factors in China: A spatial panel data approach

China's rapid economic growth and industrialization process has inevitably led to severe resource depletion and environmental degradation. Therefore, establishing total-factor industrial eco-efficiency (TFIEE) and probing into its influencing factors has great significance for improving overall eco-efficiency and the level of sustainable development. In this study, we evaluated the total-factor industrial eco-efficiency of 30 Chinese provinces grouped into eight regions in the period of 2006-2015 using a modified super-efficiency SBM-DEA model in which capital, labor, energy and water are adopted as inputs; and industrial value-added and industrial waste (soot & dust, solid wastes, waste water, waste gas) are treated as a desirable output and an undesirable output, respectively. Global and local Moran's indexes were used to analyze the spatial autocorrelation of TFIEE at both the national and regional levels. A panel spatial autoregressive (SAR) model was also proposed to study how technology and government interference affect TFIEE. We find that the ranking of TFIEE shows a descending order from the coast to the inland of China, which is consistent with the development levels of the regions in China. The Moran's index reveals that TFIEE shows a spatially positive autocorrelation from a national perspective. However, there exists no spatial autocorrelation for central China from a regional perspective, reflecting the cutting-off effect on the linkage of TFIEE between the eastern and western areas of China. We also find that TFIEE is positively correlated with technological progress and negatively correlated with government interference. Finally, policy implications were summarized to guide the green transition of the industrial sector in China. (C) 2019 Elsevier Ltd. All rights reserved.