A DEA-based approach for allocation of emission reduction tasks

Abstract

Rapid economic growth has led to increasing pollution emission, leading governments to require emission reductions by specific amounts. The allocation of specific emission reduction tasks has become a significant issue and has drawn the attention of academia. Data envelopment analysis (DEA) has been extended to construct the allocation of emission reduction tasks model. These previous DEA-based approaches have strong assumptions about individual enterprise production. In this paper, we propose a new method to accurately assess the production, using each enterprise’s previously observed production to construct its own production technology plan. With emission permits decreased, the enterprise can have new production strategy based on its own technology. Assuming emission permits can be freely bought and sold, we show how each enterprise can determine the optimal amount of emission allowance that should be used for production, which may leave some allowance to be sold for extra profit or may require the purchase of permits from other firms. Considering the limitation on the total allowance from emission permits, we introduce the concept of satisfaction degree and use it in maximising the minimum enterprise satisfaction degree. Last, a numerical example is presented and an empirical application is given to verify the proposed approach.

Keywords:

• data envelopment analysis
• game theory
• environment
• decision theory
• emission permits
• satisfaction degree