Dynamic evolution of spatial distribution of energy factor allocation efficiency: industrial sector in China

The gap between the efficient state of resources and the inefficient state of real allocation is significant, and how to quantify factor allocation efficiency is a key issue. Factor distortions and inter-factor mismatches can have significant effects on economic growth. Energy is one of the major production factors. Properly incorporating it into the framework is especially critical to measuring the efficiency of factor allocation in the industrial sector. We used Dagum's decomposition of the Gini coefficient and spatial Markov chain to reveal the dynamic spatial pattern of energy factor allocation using input–output data for China's industrial economic sectors from 2003 to 2017. The results showed that the distortions of the energy factor were more severe than those of labor factor during the study period and did not improve significantly. The primary driver of distortions was between-group inequality, with the enormous difference between Eastern–Western regions. Spatial factors played an influential role in the evolution of the distorted state of energy factors, and neighbors with low distortion levels can lead to more efficient resource allocation. These findings can assist decision-makers develop policies to improve factor allocation efficiency from a spatial perspective.