Impact of labor and energy allocation imbalance on carbon emission efficiency in China's industrial sectors

Greenhouse gas emission is the focus of global climate change concerns. The change in industrial structure can impact carbon emission efficiency (CEE) by affecting labor and energy input. However, there is an obvious imbalance of labor and energy allocation within China's industrial sectors. Here, we use the super-slacks-based model data envelopment analysis (Super-SBM-DEA) to calculate the CEE of 32 industrial sectors and adopt the Tobit model to analyze the impact of industrial allocation imbalance on CEE. The results show that the overall industry and manufacturing CEE is still at a low level, with an average CEE of 0.53. The industrial sectors with higher CEE are these sectors with advanced innovative technology and low energy consumption. The results of the Tobit model show that the imbalance of labor and energy allocation is the key factor limiting carbon emission efficiency improvement. Furthermore, the imbalance of labor allocation hurts the CEE of labor-intensive sectors. The coefficient of labor allocation imbalance (distL) is-2.483, and the inflow of labor can improve the CEE of non-labor-intensive sectors. The CEE of energy-intensive sectors is sensitive to the imbalance of energy alloca-tion, the marginal impact of energy allocation imbalance (distE) is-2.296. Improving energy efficiency is a key task to reduce carbon emissions in sectors relying on energy input. But for non-energy-intensive sectors, opti-mizing energy allocation has a limited effect on reducing carbon emissions. This research can provide insights for emerging economies to coordinate carbon reduction and industrial transformation.