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Undesirable Epsilon-Based Model DEA Application for Chinese Natural Disaster Mitigation Efficiency

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Listed:
  • Ying Li
  • Hongyi Cen
  • Tai-Yu Lin
  • Yung-ho Chiu

Abstract

As natural disasters cause significant damage, many countries have developed disaster mitigation plans to reduce losses. Because China has frequent natural disasters in its geographically diverse territory, over the past few decades, the Chinese government has promulgated regulations and developed plans to mitigate the loss of life and property in natural disasters. To analyze the natural disaster mitigation efficiency in 27 Chinese provinces, this article employed a modified Epsilon-Based Measure (EBM) Data Envelopment Analysis (DEA) model. It was found that while Sichuan, Guangdong, Hebei, Shandong, and Chongqing had good efficiencies, there were significant variances across the provinces, and, in general, significant improvements were needed. Previous natural disaster efficiency research has examined disaster management and performance evaluations, employed static DEA models, and tended to ignore the radial and non-radial characteristics. Therefore, this article is the first comprehensive examination of recent natural disaster mitigation efficiencies in Chinese provinces.

Suggested Citation

  • Ying Li & Hongyi Cen & Tai-Yu Lin & Yung-ho Chiu, 2021. "Undesirable Epsilon-Based Model DEA Application for Chinese Natural Disaster Mitigation Efficiency," SAGE Open, , vol. 11(3), pages 21582440211, August.
    • Handle: RePEc:sae:sagope:v:11:y:2021:i:3:p:21582440211040776
    DOI: 10.1177/21582440211040776
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    References listed on IDEAS

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    1. 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.
    2. Klomp, Jeroen, 2014. "Financial fragility and natural disasters: An empirical analysis," Journal of Financial Stability, Elsevier, vol. 13(C), pages 180-192.
    3. Keerthiratne, Subhani & Tol, Richard S.J., 2018. "Impact of natural disasters on income inequality in Sri Lanka," World Development, Elsevier, vol. 105(C), pages 217-230.
    4. 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.
    5. Honma, Satoshi & Hu, Jin-Li, 2014. "A panel data parametric frontier technique for measuring total-factor energy efficiency: An application to Japanese regions," Energy, Elsevier, vol. 78(C), pages 732-739.
    6. Satoshi Honma & Jin-Li Hu, 2018. "A meta-stochastic frontier analysis for energy efficiency of regions in Japan," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 7(1), pages 1-16, December.
    7. Li, Lan-Bing & Hu, Jin-Li, 2012. "Ecological total-factor energy efficiency of regions in China," Energy Policy, Elsevier, vol. 46(C), pages 216-224.
    8. Marto, Ricardo & Papageorgiou, Chris & Klyuev, Vladimir, 2018. "Building resilience to natural disasters: An application to small developing states," Journal of Development Economics, Elsevier, vol. 135(C), pages 574-586.
    9. Albala-Bertrand, J. M., 1993. "Natural disaster situations and growth: A macroeconomic model for sudden disaster impacts," World Development, Elsevier, vol. 21(9), pages 1417-1434, September.
    10. 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.
    11. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
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