Understanding the factors affecting environmental efficiency and technology inequality of Chinese cities: insights from production assumptions in data envelopment analysis

Production assumptions play dominant roles in the modeling of data envelopment analysis (DEA). Few studies systematically investigate how the production assumptions in DEA influence the environmental efficiency and technology inequality measurements. This study aims to fill this research gap. The representative categories of production assumptions are considered, that is, disposability and returns to scale (RTS). Based on the given disposability and RTS, the corresponding DEA models are proposed. The proposed models are then applied to measure the environmental efficiency and technology inequality of Chinese cities. Fixed effects panel models are further adopted to explore the effect mechanism of production assumptions. The main findings are summarized as follows: (1) disposability and RTS have significant influences on the environmental efficiency of Chinese cities. Managerial disposability considers innovation efficiency and variable RTS captures scale efficiency; (2) disposability affects the technology inequality measurement, while the RTS has no significant impact. Managerial disposability is more sensitive to technological progress compared with natural and weak disposability; (3) the average efficiency is less than 0.803 and the efficiency Theil index is less than 0.04, indicating the environmental efficiency and technology inequality of Chinese cities are at low levels; (4) To improve efficiency, Chinese cities should decrease labor and increase capital. To mitigate technology inequality, the cities should decrease energy under managerial disposability, and decrease capital and labor under weak disposability.