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A conditional full frontier modelling for analyzing environmental efficiency and economic growth

Listed author(s):
  • Halkos, George
  • Tzeremes, Nickolaos

By applying conditional and unconditional data envelopment analysis (DEA) models along side with statistical inference using bootstrap techniques; this paper investigates the link between China’s carbon dioxide emissions (CO2) environmental efficiency and its economic growth (measured in GNI per capita) for the time period of 1965 to 2009. The results reveal that China’s changing consumption patterns has caused emissions levels to increase dramatically the last two decades providing clear evidence of a negative effect of China’s GNI per capita increase on its environmental efficiency.

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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 32839.

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Date of creation: 2011
Handle: RePEc:pra:mprapa:32839
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