IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i18p7347-d410264.html
   My bibliography  Save this article

Direct and Indirect Loss Evaluation of Storm Surge Disaster Based on Static and Dynamic Input-Output Models

Author

Listed:
  • Xue Jin

    (School of Economics, Ocean University of China, Qingdao 266100, China
    Institute for the Oceans and Fisheries, University of British Columbia, 2202 Main Mall, Vancouver, BC V6T 1Z4, Canada
    Ocean Development Research Institute, Major Research Base of Humanities and Social Sciences of Ministry of Education, Ocean University of China, Qingdao 266100, China)

  • U. Rashid Sumaila

    (Institute for the Oceans and Fisheries, University of British Columbia, 2202 Main Mall, Vancouver, BC V6T 1Z4, Canada
    School of Public Policy and Global Affairs, University of British Columbia, 2202 Main Mall, Vancouver, BC V6T 1Z4, Canada
    Institute for Environment and Development (LESTARI), Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, Malaysia)

  • Kedong Yin

    (Institute of Marine Economy and Management, Shandong University of Finance and Economics, Jinan 250014, China
    School of Management Science and Engineering, Shandong University of Finance and Economics, Jinan 250014, China)

Abstract

Storm surge disaster is one of the biggest threats to coastal areas. Over the years, it has brought serious losses to the economy and environment of China’s coastal areas. In this paper, Guangdong Province is taken as the research object to evaluate the damage caused by storm surge disasters. First of all, regarding the three-industry classification standards of the National Bureau of Statistics, combined with the storm surge disaster assessment index system, the 10-sector storm surge disaster loss input-output table is compiled and analyzed. Secondly, the indirect economic losses of storm surge disasters between 2007–2017 are determined by calculating the direct and indirect consumption coefficients. Thirdly, based on the static input-output model, considering the time factor, the dynamic input-output model of storm surge disaster assessment is established to calculate the cumulative output loss under different recovery periods (30 days, 90 days, 120 days, 180 days, 360 days). The results indicate that: (1) the losses, after a storm surge, in the agricultural economy have the greatest impact on the manufacturing sector, and conversely, they have less effect on the science, education and health service sectors; as well as the construction sector; (2) taking the industry with the biggest loss ratio as an example, the recovery of damaged industries is relatively rapid in the early stage and tends to be stable in the later stage of recovery; (3) the total output loss calculated using the static input-output model is greater than that computed using the dynamic input-output model. Researching the assessment of the direct and indirect loss due to storm surge disasters is of great value and practical significance for the scientific and rational planning of the country’s production layout, the maintenance of social and economic stability and the protection of life and property.

Suggested Citation

  • Xue Jin & U. Rashid Sumaila & Kedong Yin, 2020. "Direct and Indirect Loss Evaluation of Storm Surge Disaster Based on Static and Dynamic Input-Output Models," Sustainability, MDPI, vol. 12(18), pages 1-25, September.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:18:p:7347-:d:410264
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/18/7347/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/12/18/7347/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Xi Hu & Raghav Pant & Jim W. Hall & Swenja Surminski & Jiashun Huang, 2019. "Multi-Scale Assessment of the Economic Impacts of Flooding: Evidence from Firm to Macro-Level Analysis in the Chinese Manufacturing Sector," Sustainability, MDPI, vol. 11(7), pages 1-18, April.
    2. Sam Cole, 1997. "CLOSURE IN COLE'S REFORMULATED LEONTIEF MODEL: A Response to R. W. Jackson, M. Madden, and H. A. Bowman," Papers in Regional Science, Wiley Blackwell, vol. 76(1), pages 29-42, January.
    3. Dejian Yu, 2015. "Intuitionistic fuzzy theory based typhoon disaster evaluation in Zhejiang Province, China: a comparative perspective," 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. 75(3), pages 2559-2576, February.
    4. Enliang Guo & Jiquan Zhang & Xuehui Ren & Qi Zhang & Zhongyi Sun, 2014. "Integrated risk assessment of flood disaster based on improved set pair analysis and the variable fuzzy set theory in central Liaoning Province, 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. 74(2), pages 947-965, November.
    5. Stéphane Hallegatte & Nicola Ranger & Olivier Mestre & Patrice Dumas & Jan Corfee-Morlot & Celine Herweijer & Robert Wood, 2011. "Assessing climate change impacts, sea level rise and storm surge risk in port cities: a case study on Copenhagen," Climatic Change, Springer, vol. 104(1), pages 113-137, January.
    6. Xianwu Shi & Shan Liu & Saini Yang & Qinzheng Liu & Jun Tan & Zhixing Guo, 2015. "Spatial–temporal distribution of storm surge damage in the coastal areas of 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. 79(1), pages 237-247, October.
    7. Andrew Dyck & U. Sumaila, 2010. "Economic impact of ocean fish populations in the global fishery," Journal of Bioeconomics, Springer, vol. 12(3), pages 227-243, October.
    8. A. Rao & P. Chittibabu & T. Murty & S. Dube & U. Mohanty, 2007. "Vulnerability from storm surges and cyclone wind fields on the coast of Andhra Pradesh, India," 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. 41(3), pages 515-529, June.
    9. Andre F. T. Avelino & Sandy Dall'erba, 2019. "Comparing the Economic Impact of Natural Disasters Generated by Different Input–Output Models: An Application to the 2007 Chehalis River Flood (WA)," Risk Analysis, John Wiley & Sons, vol. 39(1), pages 85-104, January.
    10. Elco E. Koks & Mark Thissen, 2016. "A Multiregional Impact Assessment Model for disaster analysis," Economic Systems Research, Taylor & Francis Journals, vol. 28(4), pages 429-449, October.
    11. Manik Mahapatra & R. Ratheesh & A. S. Rajawat, 2017. "Storm surge vulnerability assessment of Saurashtra coast, Gujarat, using GIS techniques," 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. 86(2), pages 821-831, March.
    12. Barbara Neumann & Athanasios T Vafeidis & Juliane Zimmermann & Robert J Nicholls, 2015. "Future Coastal Population Growth and Exposure to Sea-Level Rise and Coastal Flooding - A Global Assessment," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-34, March.
    13. Hu, Xi & Pant, Raghav & Hall, Jim W. & Surminski, Swenja & Huang, Jiashun, 2019. "Multi-scale assessment of the economic impacts of flooding: evidence from firm to macro-level analysis in the Chinese manufacturing sector," LSE Research Online Documents on Economics 100534, London School of Economics and Political Science, LSE Library.
    14. Robert L. Ceres & Chris E. Forest & Klaus Keller, 2017. "Understanding the detectability of potential changes to the 100-year peak storm surge," Climatic Change, Springer, vol. 145(1), pages 221-235, November.
    15. Guizhi Wang & Rongrong Chen & Jibo Chen, 2017. "Direct and indirect economic loss assessment of typhoon disasters based on EC and IO joint 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. 87(3), pages 1751-1764, July.
    16. Shuo Yang & Xin Liu & Qiang Liu, 2016. "A storm surge projection and disaster risk assessment model for China coastal areas," 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. 84(1), pages 649-667, October.
    17. Trond G. Husby & Elco E. Koks, 2017. "Household migration in disaster impact analysis: incorporating behavioural responses to risk," 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(1), pages 287-305, May.
    18. Sadri, Arif Mohaimin & Ukkusuri, Satish V. & Gladwin, Hugh, 2017. "Modeling joint evacuation decisions in social networks: The case of Hurricane Sandy," Journal of choice modelling, Elsevier, vol. 25(C), pages 50-60.
    19. Ming Li & Fan Zhang & Samuel Barnes & Xiaohong Wang, 2020. "Assessing storm surge impacts on coastal inundation due to climate change: case studies of Baltimore and Dorchester County in Maryland," 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. 103(2), pages 2561-2588, September.
    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. Xue Jin & Ussif Rashid Sumaila & Kedong Yin & Zhichao Qi, 2021. "Evaluation of the Policy Effect of China’s Environmental Interview System for Effective Air Quality Governance," IJERPH, MDPI, vol. 18(17), pages 1-20, August.
    2. Pradeep V. Mandapaka & Edmond Y. M. Lo, 2023. "Assessing Shock Propagation and Cascading Uncertainties Using the Input–Output Framework: Analysis of an Oil Refinery Accident in Singapore," Sustainability, MDPI, vol. 15(2), pages 1-24, January.
    3. Zhixia Wu & Xiazhong Zheng & Yijun Chen & Shan Huang & Wenli Hu & Chenfei Duan, 2023. "Urban Flood Loss Assessment and Index Insurance Compensation Estimation by Integrating Remote Sensing and Rainfall Multi-Source Data: A Case Study of the 2021 Henan Rainstorm," Sustainability, MDPI, vol. 15(15), pages 1-18, July.
    4. Yanfang Lyu & Yun Xiang & Dong Wang, 2023. "Evaluating Indirect Economic Losses from Flooding Using Input–Output Analysis: An Application to China’s Jiangxi Province," IJERPH, MDPI, vol. 20(5), pages 1-17, March.

    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. Ke Wang & Yongsheng Yang & Genserik Reniers & Quanyi Huang, 2021. "A study into the spatiotemporal distribution of typhoon storm surge disasters in 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. 108(1), pages 1237-1256, August.
    2. Xue Jin & Xiaoxia Shi & Jintian Gao & Tongbin Xu & Kedong Yin, 2018. "Evaluation of Loss Due to Storm Surge Disasters in China Based on Econometric Model Groups," IJERPH, MDPI, vol. 15(4), pages 1-19, March.
    3. Xiaotong Sui & Mingzhao Hu & Haoyun Wang & Lingdi Zhao, 2023. "Improved elasticity estimation model for typhoon storm surge losses in 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. 116(2), pages 2363-2381, March.
    4. Matteo Coronese & Davide Luzzati, 2022. "Economic impacts of natural hazards and complexity science: a critical review," LEM Papers Series 2022/13, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    5. Anton Pichler & J. Doyne Farmer, 2022. "Simultaneous supply and demand constraints in input–output networks: the case of Covid-19 in Germany, Italy, and Spain," Economic Systems Research, Taylor & Francis Journals, vol. 34(3), pages 273-293, July.
    6. Rui Huang & Arunima Malik & Manfred Lenzen & Yutong Jin & Yafei Wang & Futu Faturay & Zhiyi Zhu, 2022. "Supply-chain impacts of Sichuan earthquake: a case study using disaster input–output 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. 110(3), pages 2227-2248, February.
    7. Luciano Raso & Jan Kwakkel & Jos Timmermans, 2019. "Assessing the Capacity of Adaptive Policy Pathways to Adapt on Time by Mapping Trigger Values to Their Outcomes," Sustainability, MDPI, vol. 11(6), pages 1-16, March.
    8. Apurba Roy & Ilan Noy, 2023. "Impact of extratropical cyclones, floods, and wildfires on firms’ financial performance in New Zealand," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 25(4), pages 493-574, October.
    9. Sérgio Barreiros Proença & Francesca Dal Cin & Cristiana Valente Monteiro & Maria Inês Franco & Maria Matos Silva & Nawaf Saeed Al Mushayt, 2023. "The Urban Public Space between Land and Sea: The Case of Quarteira, Portugal," Land, MDPI, vol. 12(3), pages 1-15, February.
    10. Anamaria Bukvic & Guillaume Rohat & Alex Apotsos & Alex de Sherbinin, 2020. "A Systematic Review of Coastal Vulnerability Mapping," Sustainability, MDPI, vol. 12(7), pages 1-26, April.
    11. Francesca Dal Cin & Martin Fleischmann & Ombretta Romice & João Pedro Costa, 2020. "Climate Adaptation Plans in the Context of Coastal Settlements: The Case of Portugal," Sustainability, MDPI, vol. 12(20), pages 1-19, October.
    12. Mathews, Shilpita & Surminski, Swenja & Roezer, Viktor, 2021. "The risk of corporate lock-in to future physical climate risks: the case of flood risk in England and Wales," LSE Research Online Documents on Economics 112807, London School of Economics and Political Science, LSE Library.
    13. Vinzenz Peters & Jingtian Wang & Mark Sanders, 2023. "Resilience to extreme weather events and local financial structure of prefecture-level cities in China," Climatic Change, Springer, vol. 176(9), pages 1-21, September.
    14. Thomas David Pol & Jochen Hinkel, 2019. "Uncertainty representations of mean sea-level change: a telephone game?," Climatic Change, Springer, vol. 152(3), pages 393-411, March.
    15. Mathew E. Hauer & Dean Hardy & Scott A. Kulp & Valerie Mueller & David J. Wrathall & Peter U. Clark, 2021. "Assessing population exposure to coastal flooding due to sea level rise," Nature Communications, Nature, vol. 12(1), pages 1-9, December.
    16. Steven A. McAlpine & Jeremy R. Porter, 2018. "Estimating Recent Local Impacts of Sea-Level Rise on Current Real-Estate Losses: A Housing Market Case Study in Miami-Dade, Florida," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 37(6), pages 871-895, December.
    17. Mathews, Shilpita & Surminski, Swenja & Roezer, Viktor, 2021. "The risk of corporate lock-in to future physical climate risks: the case of flood risk in England and Wales," LSE Research Online Documents on Economics 112801, London School of Economics and Political Science, LSE Library.
    18. Xilin Zhang & Dongdong Chu & Jicai Zhang, 2021. "Effects of nonlinear terms and topography in a storm surge model along the southeastern coast of China: a case study of Typhoon Chan-hom," 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. 107(1), pages 551-574, May.
    19. Xiaobing Yu & Hong Chen & Chenliang Li, 2019. "Evaluate Typhoon Disasters in 21st Century Maritime Silk Road by Super-Efficiency DEA," IJERPH, MDPI, vol. 16(9), pages 1-10, May.
    20. Sem J. Duijndam & W. J. Wouter Botzen & Liselotte C. Hagedoorn & Philip Bubeck & Toon Haer & My Pham & Jeroen C. J. H. Aerts, 2023. "Drivers of migration intentions in coastal Vietnam under increased flood risk from sea level rise," Climatic Change, Springer, vol. 176(2), pages 1-22, February.

    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:gam:jsusta:v:12:y:2020:i:18:p:7347-:d:410264. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.