A more scientific allocation scheme of carbon dioxide emissions allowances: The case from China

Efficient allocation of carbon dioxide (CO2) emissions allowances is essential to the realization of the emissions reduction goal. Using China as an example, this study applies a zero sum gains data envelopment analysis (ZSG-DEA) model to translate the country's reduction target into provincial goals based on the Chinese government's 2020 reduction goal. To evaluate efficiency scores, we employ the Epsilon based measure model that combines radial and non-radial characteristics. Different from prior studies, we emphasize the effect of industrial structure on CO2 emissions and calculate a composite gross domestic product (GDP) index as one of the output variables. By utilizing the ZSG-DEA model and based on China's provincial CO2 emissions allowances as the input variable, the composite GDP index, and the population as the output variable, we obtain an optimal reallocation scheme after four iterations. A comparison between the results and official reduction goals shows that the government should increase CO2 emissions allowances appropriately for most provinces with high proportions (more than 40%) of second industry increment in GDP, thereby carrying implications for policymakers. With China as an example, these findings have global implications as regards developing a more scientific allocation scheme, especially for regions with unbalanced industrial structures. (C) 2019 Elsevier Ltd. All rights reserved.