IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v91y2018i2d10.1007_s11069-017-3142-6.html
   My bibliography  Save this article

Evaluation of the moderate earthquake resilience of counties in China based on a three-stage DEA model

Author

Listed:
  • Yang Liu

    (University of Science and Technology of China)

  • Jiuchang Wei

    (University of Science and Technology of China)

  • Jia Xu

    (University of Science and Technology of China)

  • Zhe Ouyang

    (Nanjing University of Finance and Economics)

Abstract

China has been struck by earthquakes at all scales, and such quakes have resulted in enormous human and property losses. Previous studies have mainly focused on large-scale earthquakes. However, small-scale quakes can also have long-term impacts. This study sheds light on moderate earthquakes with magnitudes ranging from 5.0 to 7.0. It aims to evaluate county resilience to moderate earthquakes based on 102 moderate quakes that occurred in Mainland China during 2002–2014. To overcome the shortcomings of traditional data envelopment analysis (DEA) evaluation methods, this study adopts a three-stage super-efficient DEA model to evaluate the resilience of counties that have been struck by moderate earthquakes. Moreover, it identifies socioeconomic factors that can effectively affect county resilience. Results suggest that most counties in China that have been struck by moderate earthquakes exhibit low efficiency and resilience. The research uses Tobit regression to demonstrate that insurance intensity, hospital beds, teledensity, government financial expenditure, and disaster experience can efficiently improve county resilience to moderate earthquakes, which indicates the future improvement direction of local resilience. Moreover, a region with a high frequency of moderate quakes displays relatively low efficiency and resilience. Considerable attention and effort should be afforded to these areas.

Suggested Citation

  • Yang Liu & Jiuchang Wei & Jia Xu & Zhe Ouyang, 2018. "Evaluation of the moderate earthquake resilience of counties in China based on a three-stage DEA model," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 91(2), pages 587-609, March.
    • Handle: RePEc:spr:nathaz:v:91:y:2018:i:2:d:10.1007_s11069-017-3142-6
    DOI: 10.1007/s11069-017-3142-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11069-017-3142-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11069-017-3142-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
    2. Horwich, George, 2000. "Economic Lessons of the Kobe Earthquake," Economic Development and Cultural Change, University of Chicago Press, vol. 48(3), pages 521-542, April.
    3. Mingze Li & Jun Lv & Xin Chen & Nan Jiang, 2015. "Provincial evaluation of vulnerability to geological disaster in China and its influencing factors: a three-stage DEA-based analysis," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 79(3), pages 1649-1662, December.
    4. Gorman, Michael F. & Ruggiero, John, 2008. "Evaluating US state police performance using data envelopment analysis," International Journal of Production Economics, Elsevier, vol. 113(2), pages 1031-1037, June.
    5. H. Fried & C. Lovell & S. Schmidt & S. Yaisawarng, 2002. "Accounting for Environmental Effects and Statistical Noise in Data Envelopment Analysis," Journal of Productivity Analysis, Springer, vol. 17(1), pages 157-174, January.
    6. Nahra, Tammie A. & Mendez, David & Alexander, Jeffrey A., 2009. "Employing super-efficiency analysis as an alternative to DEA: An application in outpatient substance abuse treatment," European Journal of Operational Research, Elsevier, vol. 196(3), pages 1097-1106, August.
    7. Susan L. Cutter & Bryan J. Boruff & W. Lynn Shirley, 2003. "Social Vulnerability to Environmental Hazards," Social Science Quarterly, Southwestern Social Science Association, vol. 84(2), pages 242-261, June.
    8. Roger Feldman & Bryan Dowd & Scott Leitz & Lynn A. Blewett, 1997. "The Effect of Premiums on the Small Firm's Decision to Offer Health Insurance," Journal of Human Resources, University of Wisconsin Press, vol. 32(4), pages 635-658.
    9. Matthew E. Kahn, 2005. "The Death Toll from Natural Disasters: The Role of Income, Geography, and Institutions," The Review of Economics and Statistics, MIT Press, vol. 87(2), pages 271-284, May.
    10. Philippe Artzner & Freddy Delbaen, 1995. "Default Risk Insurance And Incomplete Markets1," Mathematical Finance, Wiley Blackwell, vol. 5(3), pages 187-195, July.
    11. Zhu, Joe, 2001. "Super-efficiency and DEA sensitivity analysis," European Journal of Operational Research, Elsevier, vol. 129(2), pages 443-455, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Richard S. J. Tol, 2021. "The Economic Impact of Climate in the Long Run," World Scientific Book Chapters, in: Anil Markandya & Dirk Rübbelke (ed.), CLIMATE AND DEVELOPMENT, chapter 1, pages 3-36, World Scientific Publishing Co. Pte. Ltd..
    2. Ying Li & Yung‐ho Chiu & Tai‐Yu Lin & Hongyi Cen & Yabin Liu, 2021. "Evaluation of natural disaster treatment efficiency in 27 Chinese provinces," Natural Resources Forum, Blackwell Publishing, vol. 45(3), pages 256-288, August.
    3. Richard S. J. Tol, 2022. "State capacity and vulnerability to natural disasters," Chapters, in: Mark Skidmore (ed.), Handbook on the Economics of Disasters, chapter 20, pages 434-457, Edward Elgar Publishing.
    4. Haoran Su & Chang Liu & Donghui Dai & Wenkai Chen & Zhen Zhang & Yaowu Wang, 2023. "Distribution Characteristics and Influencing Factors of the National Comprehensive Disaster-Reduction Demonstration Community in China," Land, MDPI, vol. 12(8), pages 1-30, August.
    5. Pankaj Dutta & Aayush Jain & Asish Gupta, 2020. "Performance analysis of non-banking finance companies using two-stage data envelopment analysis," Annals of Operations Research, Springer, vol. 295(1), pages 91-116, December.
    6. Qing Yang & Lingmei Fu & Xingxing Liu & Mengying Cheng, 2018. "Evaluating the Efficiency of Municipal Solid Waste Management in China," IJERPH, MDPI, vol. 15(11), pages 1-23, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mingze Li & Jun Lv & Xin Chen & Nan Jiang, 2015. "Provincial evaluation of vulnerability to geological disaster in China and its influencing factors: a three-stage DEA-based analysis," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 79(3), pages 1649-1662, December.
    2. Jungmin Lim & Mark Skidmore, 2019. "Flood Fatalities in the United States: The Roles of Socioeconomic Factors and the National Flood Insurance Program," Southern Economic Journal, John Wiley & Sons, vol. 85(4), pages 1032-1057, April.
    3. Feng Dong & Ruyin Long & Zhengfu Bian & Xihui Xu & Bolin Yu & Ying Wang, 2017. "Applying a Ruggiero three-stage super-efficiency DEA model to gauge regional carbon emission efficiency: evidence from China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 87(3), pages 1453-1468, July.
    4. Guan, Jiancheng & Chen, Kaihua, 2012. "Modeling the relative efficiency of national innovation systems," Research Policy, Elsevier, vol. 41(1), pages 102-115.
    5. Noy, Ilan & Vu, Tam Bang, 2010. "The economics of natural disasters in a developing country: The case of Vietnam," Journal of Asian Economics, Elsevier, vol. 21(4), pages 345-354, August.
    6. Giuliano Masiero & Michael Santarossa, 2020. "Earthquakes, grants, and public expenditure: How municipalities respond to natural disasters," Journal of Regional Science, Wiley Blackwell, vol. 60(3), pages 481-516, June.
    7. Davlasheridze, Meri & Fisher-Vanden, Karen & Allen Klaiber, H., 2017. "The effects of adaptation measures on hurricane induced property losses: Which FEMA investments have the highest returns?," Journal of Environmental Economics and Management, Elsevier, vol. 81(C), pages 93-114.
    8. Heger, Martin Philipp & Neumayer, Eric, 2019. "The impact of the Indian Ocean tsunami on Aceh’s long-term economic growth," Journal of Development Economics, Elsevier, vol. 141(C).
    9. Tam Bang Vu & Calvin Luscombe & Shaun McKim, 2014. "Natural Disasters in Japan and Tourism in Developing Countries: The Case of the Pacific Islands," Journal of Empirical Economics, Research Academy of Social Sciences, vol. 3(2), pages 98-107.
    10. Robert A. Baade & Robert Baumann & Victor Matheson, 2007. "Estimating the Economic Impact of Natural and Social Disasters, with an Application to Hurricane Katrina," Urban Studies, Urban Studies Journal Limited, vol. 44(11), pages 2061-2076, October.
    11. Noy, Ilan & Yonson, Rio, 2016. "A survey of the theory and measurement of economic vulnerability and resilience to natural hazards," Working Paper Series 19394, Victoria University of Wellington, School of Economics and Finance.
    12. Nuri Ozgur DOGAN & Can Tansel TUGCU, 2015. "Energy Efficiency in Electricity Production: A Data Envelopment Analysis (DEA) Approach for the G-20 Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 5(1), pages 246-252.
    13. Martina Kirchberger, 2014. "Natural Disasters and Labour Markets," Economics Series Working Papers WPS/2014-19, University of Oxford, Department of Economics.
    14. Matthew A. COLE & Robert J R ELLIOTT & OKUBO Toshihiro & Eric STROBL, 2013. "Natural Disasters and Plant Survival: The impact of the Kobe earthquake," Discussion papers 13063, Research Institute of Economy, Trade and Industry (RIETI).
    15. Eduardo Cavallo & Ilan Noy, 2009. "The Economics of Natural Disasters: A Survey," Research Department Publications 4649, Inter-American Development Bank, Research Department.
    16. Tavana, Madjid & Ebrahimnejad, Ali & Santos-Arteaga, Francisco J. & Mansourzadeh, Seyed Mehdi & Matin, Reza Kazemi, 2018. "A hybrid DEA-MOLP model for public school assessment and closure decision in the City of Philadelphia," Socio-Economic Planning Sciences, Elsevier, vol. 61(C), pages 70-89.
    17. Padli, Jaharudin & Habibullah, Muzafar & Abdul Hamid, Baharom & Musa, Haslina, 2019. "Mitigating Fatalities and Damages Due to Natural Disasters: Do Human Development and Corruption Matters?," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 53(2), pages 153-164.
    18. Avkiran, Necmi K., 2007. "Stability and integrity tests in data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 41(3), pages 224-234, September.
    19. Michael Berlemann & Max Steinhardt & Jascha Tutt, 2015. "Do Natural Disasters Stimulate Individual Saving? Evidence from a Natural Experiment in a Highly Developed Country," SOEPpapers on Multidisciplinary Panel Data Research 763, DIW Berlin, The German Socio-Economic Panel (SOEP).
    20. Jahanshahloo, Gholam Reza & Junior, Helcio Vieira & Lotfi, Farhad Hosseinzadeh & Akbarian, Darush, 2007. "A new DEA ranking system based on changing the reference set," European Journal of Operational Research, Elsevier, vol. 181(1), pages 331-337, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:nathaz:v:91:y:2018:i:2:d:10.1007_s11069-017-3142-6. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.