Optimal path for controlling CO2 emissions in China: A perspective of efficiency analysis
This paper examines the optimal control of CO2 emissions from a perspective of efficiency analysis. Several centralized data envelopment analysis (DEA) models are introduced to study the optimal allocation of CO2 emissions under spatial, temporal and spatial–temporal allocation strategies, respectiv...
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Veröffentlicht in: | Energy economics 2014-09, Vol.45, p.99-110 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | This paper examines the optimal control of CO2 emissions from a perspective of efficiency analysis. Several centralized data envelopment analysis (DEA) models are introduced to study the optimal allocation of CO2 emissions under spatial, temporal and spatial–temporal allocation strategies, respectively. The models have been used to determine the optimal paths for controlling CO2 emissions at provincial and regional levels in China. A sensitivity analysis of the optimal path on the emission control coefficient under spatial–temporal allocation strategy is further carried out. Our empirical results show that more developed regions should take emission reduction responsibility earlier than less developed regions in China. Of the three allocation strategies, spatial–temporal allocation strategy seems to be a better choice for achieving the optimal control of CO2 emissions at country level since it is more encompassing by allowing both timing and spatial substitutions. It is also found that there exists an inverted U-shape relationship between the aggregate optimal GDP and the emission control coefficient, which shows that modest emission reduction policy might be more appropriate for China in order to achieve the joint goals of economic development and CO2 emission reduction.
•The optimal control of CO2 emissions in China is examined.•Centralized DEA models are used to allocate CO2 emissions under different strategies.•More developed regions should implement emission reduction earlier.•Modest emission reduction policy could be more appropriate for China. |
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ISSN: | 0140-9883 1873-6181 |
DOI: | 10.1016/j.eneco.2014.06.019 |