Centralized resource allocation with technological progress under a meta-frontier framework: towards China's "Energy-economy-emission" optimization.

Efficient resource allocation is crucial for promoting economic growth and reducing carbon emissions in China. This study develops a new centralized resource allocation approach based on data envelopment analysis (DEA). It incorporates technological progress into the environmental production possibility set and further extends it to a technological heterogeneity setting under a meta-frontier framework. The environmental efficiency of each decision-making unit is encouraged to achieve its future group frontier. The advantage of the proposed method is that, it enhances the forward-looking nature of decision-making, explicitly captures technological heterogeneity within the allocation framework, and improves the incentive compatibility of target setting while maintaining feasibility. It is then applied to optimize China's "energy-economy-emissions" system. The results show that the optimal interprovincial allocation of energy consumption and labor can increase the aggregate economic output of the 30 provinces by 6.95% relative to 2023, while generating a carbon reduction potential of 5,681.17 million tons. In addition, optimal allocation combined with appropriate incentives could further raise economic output in 2024 by 1.8% and reduce emissions by 47.19%. Severe labor misallocation is found between the eastern and central regions. Sensitivity analysis further suggests that policymakers should place moderately greater weight on economic development than on emission reduction. Several managerial implications are derived accordingly.