Industrial eco-efficiency and its determinants in China: A two-stage approach

China has undergone momentous changes and achieved remarkable economic progress since its economic reform and opening-up in 1978. However, the consequent resource depletion and environmental degradation have seriously restricted China's potential for sustainable industrial development. As a practical tool contributing to sustainable development, the concept of eco-efficiency is considered increasingly important for reducing the trend of resource exhaustion and environmental degradation. This study first evaluated industrial eco-efficiency in 30 Chinese provinces during 2005-2015 using data envelopment analysis (DEA), and then identified the determinants of the resulting eco-efficiency scores using random-effects Tobit regression analysis. The DEA results showed that although China's overall industrial eco-efficiency trend was upward, there were great disparities between provinces. Provinces with high industrial eco-efficiency were mainly distributed across the eastern region, while those in the often economically less developed western region had lower industrial ecoefficiency due to technological deficits and weak environmental policies. The Tobit regression results indicated that internal research and development expenditure in industrial enterprises, per capita gross regional product, and investment in wastewater treatment had positive effects on provincial industrial eco-efficiency. By contrast, the proportion of state-owned enterprises and investment in waste gas treatment had negative impacts. These findings provide valuable insights that can help provinces with low industrial eco-efficiency to pursue high-quality, green development.

Automated summary

China has made significant economic progress since its economic reform and opening-up in 1978, but resource depletion and environmental degradation have hindered sustainable industrial development. The concept of eco-efficiency is considered increasingly important for reducing these trends.