A Resampling Slack-Based Energy Efficiency Analysis: Application in the G20 Economies
Dan Wu,
Ching-Cheng Lu,
Pao-Yu Tang,
Miao-Ling Wang and
An-Chi Yang
Additional contact information
Dan Wu: Teaching Center, Zhejiang Open University, 42 Jiaogong Road, Hangzhou 310012, China
Pao-Yu Tang: Center for General Education, National Open University, No.172, Zhongzheng Road, Luzhou District, Xinbei City 247031, Taiwan
Miao-Ling Wang: Department of Applied Economics, Fo Guang University, No.160, Linwei Road, Jiaosi 262307, Taiwan
An-Chi Yang: Department of Economics, Soochow University, No. 56, Section 1, Kueiyang Street, Chungcheng District, Taipei City 100, Taiwan
Energies, 2021, vol. 15, issue 1, 1-14
Abstract:
In order to have a sustainable economic and social development, it is important to balance economic growth and ecological environmental damage. In this article, we used the resampling model under the triangular distribution to evaluate energy efficiency, because the input/output value may have measurement errors, time lag factors, arbitrariness, and other problems, causing their own DMU to change. After these factors were taken into consideration, the resampled input/output was estimated because a super-SBM efficiency value was placed in the confidence interval. From the past-present data, for the estimated data change, the time weight was provided according to the Lucas series, and the super-SBM was time-weighted. We applied this model to a dataset of G20 economies from 2010 to 2014. To the best of our knowledge, very few studies have applied the DEA method with resampling to analyze energy efficiency. Thus, our study contributes to the methodologies for energy efficiency evaluation. We found that the overall average energy efficiency is 0.653, with substantial differences between developed economies and developing economies. The most important finding is that neither overestimation nor underestimation occurred when sampling was repeated one thousand times using 95% and 80% confidence intervals, confirming the robustness of the super-SBM model. The less energy-efficient economies should adjust their energy policies appropriately and develop new clean energy technologies in the future.
Keywords: G20; triangular distribution; past-present model; energy efficiency; resample super-SBM (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://www.mdpi.com/1996-1073/15/1/67/pdf (application/pdf)
https://www.mdpi.com/1996-1073/15/1/67/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:15:y:2021:i:1:p:67-:d:708980
Access Statistics for this article
Energies is currently edited by Ms. Agatha Cao
More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().