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

Author

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  • 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
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    References listed on IDEAS

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    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.

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