Economic Ripple Effects of Individual Disasters and Disaster Clusters

被引:0
作者
Zhengtao Zhang
Ning Li
Ming Wang
Kai Liu
Chengfang Huang
Linmei Zhuang
Fenggui Liu
机构
[1] Beijing Normal University,Key Laboratory of Environmental Change and Natural Disaster, Ministry of Education
[2] Beijing Normal University,Academy of Disaster Reduction and Emergency Management, Ministry of Emergency Management and Ministry of Education
[3] Beijing Normal University,State Key Laboratory of Earth Surface Processes and Resource Ecology
[4] Beijing Normal University,Faculty of Geographical Science
[5] Beijing Normal University,School of National Safety and Emergency Management
[6] Academy of Plateau Science and Sustainability,undefined
来源
International Journal of Disaster Risk Science | 2022年 / 13卷
关键词
Disaster clusters; Disaster risk management; Economic ripple effects; Indirect economic losses; Input-output model;
D O I
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中图分类号
学科分类号
摘要
Disaster clusters refer to major disasters that cluster in space and time without any linkage, resulting in large direct damage and economic ripple effects (EREs). However, the cumulative EREs caused by a disaster cluster may not be equal to the summation EREs of the individual disasters within a cluster. We constructed a global economic ripple input-output model suitable for the analysis of disaster clusters and demonstrated the extent of this difference with the example of two typical catastrophes that occurred in 2011 (the Great East Japan Earthquake and the Great Thailand Flood), within an interval of only 136 days. The results indicate that: (1) The EREs suffered by 11 of the 35 countries affected (30%) are “1 + 1 > 2”, and “1 + 1 < 2” for 24 of the 35 countries affected (70%). This indicates that there is a significant difference between the cumulative and the summation losses. The difference is related to factors such as trade distance, economic influence of disaster-affected sectors, and trade ties; (2) The EREs are more than two times the direct loss and have an industrial dependence, mostly aggregated in key sectors with strong industrial influence and fast trade times in the industrial chain; and (3) Additional EREs due to the extension of the recovery period will be aggregated in countries with close trade ties to the disaster-affected country, further magnifying the difference.
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页码:948 / 961
页数:13
相关论文
共 165 条
[1]  
Arto I(2015)Global impacts of the automotive supply chain disruption following the Japanese earthquake of 2011 Economic Systems Research 27 306-323
[2]  
Andreoni V(2017)Disaggregating input-output tables in time: The temporal input-output framework Economic Systems Research 29 313-334
[3]  
Cantuche JMR(2003)A framework to quantitatively assess and enhance the seismic resilience of communities Earthquake Spectra 19 733-752
[4]  
Avelino AFT(2008)Disasters, climate change and economic development in Sub-Saharan Africa: Lessons and directions Journal of African Economies 17 27-249
[5]  
Bruneau M(2021)Detection and potential early warning of catastrophic flow events with regional seismic networks Science 374 87-92
[6]  
Chang SE(2021)Economic impacts of storm surge events: Examining state and national ripple effects Climatic Change 166 1-20
[7]  
Eguchi RT(2020)Global supply-chain effects of COVID-19 control measures Nature Human Behaviour 4 577-587
[8]  
Lee GC(2008)An adaptive regional input-output model and its application to the assessment of the economic cost of Katrina Risk Analysis 28 779-799
[9]  
O’Rourke TD(2014)Modeling the role of inventories and heterogeneity in the assessment of the economic costs of natural disasters Risk Analysis 34 152-167
[10]  
Reinhorn AM(2000)Analyzing the recent upward surge in overtime hours Monthly Lab Review 123 30-33