Measurement of Low Carbon Economy Efficiency with a Three-Stage Data Envelopment Analysis: A Comparison of the Largest Twenty CO2 Emitting Countries

Abstract

This paper employs a three-stage approach to estimate low carbon economy efficiency in the largest twenty CO2 emitting countries from 2000 to 2012. The approach includes the following three stages: (1) use of a data envelopment analysis (DEA) model with undesirable output to estimate the low carbon economy efficiency and calculate the input and output slacks; (2) use of a stochastic frontier approach to eliminate the impacts of external environment variables on these slacks; (3) re-estimation of the efficiency with adjusted inputs and outputs to reflect the capacity of the government to develop a low carbon economy. The results indicate that the low carbon economy efficiency performances in these countries had worsened during the studied period. The performances in the third stage are larger than that in the first stage. Moreover, in general, low carbon economy efficiency in Annex I countries of the United Nations Framework Convention on Climate Change (UNFCCC) is better than that in Non-Annex I countries. However, the gap of the average efficiency score between Annex I and Non-Annex I countries in the first stage is smaller than that in the third stage. It implies that the external environment variables show greater influence on Non-Annex I countries than that on Annex I countries. These external environment variables should be taken into account in the transnational negotiation of the responsibility of promoting CO2 reductions. Most importantly, the developed countries (mostly in Annex I) should help the developing countries (mostly in Non-Annex I) to reduce carbon emission by opening or expanding the trade, such as encouraging the import and export of the energy-saving and sharing emission reduction technology.

Energy Efficiency Improvement Assessment in Africa: An Integrated Dynamic DEA Approach

“…This result reveals that there is no significant difference in the mean efficiencies of the two case scenarios. The results of this study to a large extent confirm the findings of Liu and Liu [59], who estimated the energy performance of the top 20 CO 2 emitting nations. Wang et al [48] also obtained similar findings, assessing the energy efficiency of 25 nations.…”

“…Again, based on CO 2 emission concerns, Liu and Liu [59] employed the three-stage DEA methodological framework to assess the efficiency of the top 20 CO 2 emitting economies from 2000 to 2012 with the incorporation of CO 2 as a bad output. Wang et al [60] developed an integrated super SBM-DEA and Malmquist productivity index (MPI) method to study the energy efficiency estimates of 17 nations.…”

Assessment of the Energy Efficiency Improvement of Twenty-Five Countries: A DEA Approach

“…According to the literature, DEA SBM was frequently applied to deal with the presence of undesirable outputs; for example, the study carried out by Apergis [23] used an SBM to measure the energy efficiency of selected Organisation for Economic Co-operation and Development (OECD) countries. Regarding the concern about CO 2 emissions, Liu and Liu [24] used three-stage DEA in their study to measure the low-carbon economy efficiency of the top 20 largest CO 2 emitters from 2000 to 2012 with the presence of CO 2 emissions as an unwelcome output. Lenz.…”

Is the low‐carbon economy efficient in terms of sustainable development? A global perspective

“…Zhao and Zhong () evaluated the LCEE between different provinces in China by using a three‐stage DEA model with the dynamic Malmquist Productivity Index (MPI), and suggested that the development of LCE requires a transition of the current economic structure. Liu and Liu () employed a three‐stage DEA model in estimating LCEE in the 20 largest CO 2 ‐emitting countries during 2000–2012.…”