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A Study of Total-Factor Energy Efficiency for Regional Sustainable Development in China: An Application of Bootstrapped DEA and Clustering Approach

Author

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  • Yang Li

    (Department of International Trade, Takming University of Science and Technology, Taipei 11451, Taiwan)

  • An-Chi Liu

    (College of Business Administration, Fujian Business University, Fuzhou 350016, China)

  • Shu-Mei Wang

    (Department of Bio-Industry Communication and Development, National Taiwan University, Taipei 10617, Taiwan)

  • Yiting Zhan

    (New Huadu Business School, Minjiang University, Fuzhou 350108, China)

  • Jingran Chen

    (New Huadu Business School, Minjiang University, Fuzhou 350108, China)

  • Hsiao-Fen Hsiao

    (New Huadu Business School, Minjiang University, Fuzhou 350108, China)

Abstract

Total-factor energy efficiency (TFEE) is widely used to measure energy efficiency under the data envelopment analysis (DEA) framework, but the efficiencies obtained from DEA are structurally biased upward, and thus TFEE tends to overestimate energy efficiency. This research thus applies the bootstrapped DEA approach to correct the bias of TFEE. Using a dataset consisting of 30 provinces of China in the period 2016–2019, the bootstrapped-based test supports technology with variable returns to scale. The biased-corrected TFEE also indicates that energy consumption on average can be scaled down by 42.36%, rather than the biased value of 19.4%. The bootstrapped clustering partitions provinces into three groups: Cluster 1, with Guizhou as the representative medoid, includes half of the superior coastal provinces in terms of actual energy consumption and TFEE and half of the competitive inland provinces, whereas Cluster 3 outperforms Cluster 2 in terms of TFEE, but the actual energy consumption is higher, with Shandong and Hebei as the representative medoids, respectively. Lastly, empirical results imply that the northeast and central regions need more government attention and resources to practice sustainable development and improve TFEE.

Suggested Citation

  • Yang Li & An-Chi Liu & Shu-Mei Wang & Yiting Zhan & Jingran Chen & Hsiao-Fen Hsiao, 2022. "A Study of Total-Factor Energy Efficiency for Regional Sustainable Development in China: An Application of Bootstrapped DEA and Clustering Approach," Energies, MDPI, vol. 15(9), pages 1-13, April.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:9:p:3093-:d:800485
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    as
    1. Romer, Paul M, 1986. "Increasing Returns and Long-run Growth," Journal of Political Economy, University of Chicago Press, vol. 94(5), pages 1002-1037, October.
    2. Chang, Tzu-Pu & Hu, Jin-Li, 2010. "Total-factor energy productivity growth, technical progress, and efficiency change: An empirical study of China," Applied Energy, Elsevier, vol. 87(10), pages 3262-3270, October.
    3. William W. Cooper & Lawrence M. Seiford & Joe Zhu (ed.), 2011. "Handbook on Data Envelopment Analysis," International Series in Operations Research and Management Science, Springer, number 978-1-4419-6151-8, January.
    4. Honma, Satoshi & Hu, Jin-Li, 2009. "Total-factor energy productivity growth of regions in Japan," Energy Policy, Elsevier, vol. 37(10), pages 3941-3950, October.
    5. Woo, Chungwon & Chung, Yanghon & Chun, Dongphil & Seo, Hangyeol & Hong, Sungjun, 2015. "The static and dynamic environmental efficiency of renewable energy: A Malmquist index analysis of OECD countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 367-376.
    6. World Commission on Environment and Development,, 1987. "Our Common Future," OUP Catalogue, Oxford University Press, number 9780192820808.
    7. Gössling, Stefan & Peeters, Paul & Ceron, Jean-Paul & Dubois, Ghislain & Patterson, Trista & Richardson, Robert B., 2005. "The eco-efficiency of tourism," Ecological Economics, Elsevier, vol. 54(4), pages 417-434, September.
    8. Zhou, P. & Ang, B.W., 2008. "Linear programming models for measuring economy-wide energy efficiency performance," Energy Policy, Elsevier, vol. 36(8), pages 2901-2906, August.
    9. Bertani, Filippo & Ponta, Linda & Raberto, Marco & Teglio, Andrea & Cincotti, Silvano, 2021. "The complexity of the intangible digital economy: an agent-based model," Journal of Business Research, Elsevier, vol. 129(C), pages 527-540.
    10. Jin-Li Hu & Chih-Hai Yang & Chiang-Ping Chen, 2014. "R&D Efficiency And The National Innovation System: An International Comparison Using The Distance Function Approach," Bulletin of Economic Research, Wiley Blackwell, vol. 66(1), pages 55-71, January.
    11. Chang, Ming-Chung, 2013. "A comment on the calculation of the total-factor energy efficiency (TFEE) index," Energy Policy, Elsevier, vol. 53(C), pages 500-504.
    12. Jin-Li Hu & Tzu-Pu Chang, 2016. "Total-Factor Energy Efficiency and Its Extensions: Introduction, Computation and Application," International Series in Operations Research & Management Science, in: Joe Zhu (ed.), Data Envelopment Analysis, chapter 0, pages 45-69, Springer.
    13. Mariam Camarero & Juana Castillo & Andrés Picazo-Tadeo & Cecilio Tamarit, 2013. "Eco-Efficiency and Convergence in OECD Countries," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 55(1), pages 87-106, May.
    14. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    15. Ouellette, Pierre & Vierstraete, Valerie, 2004. "Technological change and efficiency in the presence of quasi-fixed inputs: A DEA application to the hospital sector," European Journal of Operational Research, Elsevier, vol. 154(3), pages 755-763, May.
    16. Joseph G. Hirschberg & Jenny N. Lye, 2001. "Clustering in a Data Envelopment Analysis Using Bootstrapped Efficiency Scores," Department of Economics - Working Papers Series 800, The University of Melbourne.
    17. William W. Cooper & Lawrence M. Seiford & Joe Zhu, 2011. "Data Envelopment Analysis: History, Models, and Interpretations," International Series in Operations Research & Management Science, in: William W. Cooper & Lawrence M. Seiford & Joe Zhu (ed.), Handbook on Data Envelopment Analysis, chapter 0, pages 1-39, Springer.
    18. Hall, Bronwyn H. & Mairesse, Jacques, 1995. "Exploring the relationship between R&D and productivity in French manufacturing firms," Journal of Econometrics, Elsevier, vol. 65(1), pages 263-293, January.
    19. Yang, Jun & Cheng, Jixin & Zou, Ran & Geng, Zhifei, 2021. "Industrial SO2 technical efficiency, reduction potential and technology heterogeneities of China's prefecture-level cities: A multi-hierarchy meta-frontier parametric approach," Energy Economics, Elsevier, vol. 104(C).
    20. Zhang, Xing-Ping & Cheng, Xiao-Mei & Yuan, Jia-Hai & Gao, Xiao-Jun, 2011. "Total-factor energy efficiency in developing countries," Energy Policy, Elsevier, vol. 39(2), pages 644-650, February.
    21. Zhang, Bing & Bi, Jun & Fan, Ziying & Yuan, Zengwei & Ge, Junjie, 2008. "Eco-efficiency analysis of industrial system in China: A data envelopment analysis approach," Ecological Economics, Elsevier, vol. 68(1-2), pages 306-316, December.
    22. Léopold Simar & Paul W. Wilson, 1998. "Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models," Management Science, INFORMS, vol. 44(1), pages 49-61, January.
    23. Shi, Guang-Ming & Bi, Jun & Wang, Jin-Nan, 2010. "Chinese regional industrial energy efficiency evaluation based on a DEA model of fixing non-energy inputs," Energy Policy, Elsevier, vol. 38(10), pages 6172-6179, October.
    24. Simar, Leopold & Wilson, Paul W., 2002. "Non-parametric tests of returns to scale," European Journal of Operational Research, Elsevier, vol. 139(1), pages 115-132, May.
    25. Hu, Jin-Li & Wang, Shih-Chuan, 2006. "Total-factor energy efficiency of regions in China," Energy Policy, Elsevier, vol. 34(17), pages 3206-3217, November.
    26. Timo Kuosmanen & Mika Kortelainen, 2005. "Measuring Eco‐efficiency of Production with Data Envelopment Analysis," Journal of Industrial Ecology, Yale University, vol. 9(4), pages 59-72, October.
    27. Zhou, P. & Ang, B.W. & Poh, K.L., 2008. "A survey of data envelopment analysis in energy and environmental studies," European Journal of Operational Research, Elsevier, vol. 189(1), pages 1-18, August.
    28. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    29. Fare, Rolf, et al, 1989. "Multilateral Productivity Comparisons When Some Outputs Are Undesirable: A Nonparametric Approach," The Review of Economics and Statistics, MIT Press, vol. 71(1), pages 90-98, February.
    30. Amin, Gholam R. & Emrouznejad, Ali & Rezaei, S., 2011. "Some clarifications on the DEA clustering approach," European Journal of Operational Research, Elsevier, vol. 215(2), pages 498-501, December.
    31. Ruizhi Pang & Xuejie Bai & Knox Lovell (ed.), 2018. "Energy, Environment and Transitional Green Growth in China," Springer Books, Springer, number 978-981-10-7919-1, April.
    32. Li, Yang, 2020. "Analyzing efficiencies of city commercial banks in China: An application of the bootstrapped DEA approach," Pacific-Basin Finance Journal, Elsevier, vol. 62(C).
    33. Scheel, Holger, 2001. "Undesirable outputs in efficiency valuations," European Journal of Operational Research, Elsevier, vol. 132(2), pages 400-410, July.
    34. Rajiv D. Banker, 1993. "Maximum Likelihood, Consistency and Data Envelopment Analysis: A Statistical Foundation," Management Science, INFORMS, vol. 39(10), pages 1265-1273, October.
    35. Lucas, Robert Jr., 1988. "On the mechanics of economic development," Journal of Monetary Economics, Elsevier, vol. 22(1), pages 3-42, July.
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