Environmental Application of Carbon Abatement Allocation by Data Envelopment Analysis

China’s commitment to significantly reducing carbon emissions faces the twin challenges of focusing on costly reduction efforts, whilst preserving the rapid growth that has defined the country’s recent past. However, little work has been able to meaningfully reflect the collaborative way in which provinces are assigned targets on a subnational regional basis. Suggesting a meta-frontier allocation approach by using data envelopment analysis (DEA), this chapter introduces the potential collaboration between heterogeneous industrial units to the modelling framework. Our theoretical work exposits the roles collectives of industrial decision making units may play in optimizing against multiple target functions, doing so whilst recognizing the two objectives of income maximization and pollution abatement cost minimization. Considering the period 2012–2014, we illustrate clearly how China’s three regional collaborations interact with the stated aims of national policy. Developed eastern China may take on greater abatement tasks in the short term, thus freeing central and western China to pursue the economic growth which will then support later abatement. Policymakers are thus given a tool through which an extra layer of implementation can be evaluated between the national allocation and setting targets for regional individual decision making units. China’s case perfectly exemplifies the conflicts which must be accounted for if the most economical and efficient outcomes are to be achieved.