Allocating assistance after a catastrophe based on the dynamic assessment of indirect economic losses
Zhang, Zhengtao2,3; Li, Ning1,3,4,6; Xu, Hong4; Feng, Jieling1,3,6; Chen, Xi1,3,6; Gao, Chao5; Zhang, Peng7
刊名NATURAL HAZARDS
2019-10-01
卷号99期号:1页码:17-37
关键词Natural disaster Indirect economic loss Direct economic loss Input-output model Earthquake Risk management
ISSN号0921-030X
DOI10.1007/s11069-019-03679-0
通讯作者Li, Ning(ningli@bnu.edu.cn)
英文摘要In 2008, Wenchuan earthquake shook Sichuan Province in China. The questions of how to value the economic loss that would result if a catastrophe were to occur in Capital Beijing and how long the recovery period would last have long been topics of concern for the government and the public. This study envisions an earthquake similar to the Wenchuan earthquake occurring in Beijing and examines the differences in indirect economic loss and recovery periods between Beijing and the Wenchuan earthquake using the same loss rate. An improved input-output model is used to evaluate the indirect losses. The results show that (1) Beijing experiences greater indirect loss than Sichuan. When both regions suffer a direct loss of USD 100, Beijing suffers USD 12 more in indirect loss than does Sichuan. (2) The reconstruction period of Beijing is shortened by at least 5 months, and indirect loss is reduced by 27.1% if the assistance level increases from 120 to 150% of that provided to Sichuan. (3) High assistance efficiencies can effectively reduce total losses, but increasing the efficiency of strength is more efficient than improving the efficiency of time in Beijing. Five sectors in Beijing are firstly needed to be assisted to recover, which can help other sectors to recover more quickly and efficiently through industrial linkages. Dynamic assessment of indirect loss in this study may help the government better understand the quantitative impact of disasters and allocate assistance resources more efficiently in Beijing.
资助项目National Key Research and Development Program of China[2016YFA0602403] ; Beijing Municipal Natural Science Foundation[9172010] ; National Natural Science Foundation of China[41505134] ; National Natural Science Foundation of China[41871024] ; Youth fund of Natural Science Foundation of Hebei Province[D2015507046]
WOS关键词INPUT-OUTPUT MODEL ; CLIMATE-CHANGE ; FLOOD RISK ; IMPACT ; EFFICIENCY ; DISASTERS ; DROUGHT ; REGIONS ; POLICY ; SCALE
WOS研究方向Geology ; Meteorology & Atmospheric Sciences ; Water Resources
语种英语
出版者SPRINGER
WOS记录号WOS:000489750300002
资助机构National Key Research and Development Program of China ; Beijing Municipal Natural Science Foundation ; National Natural Science Foundation of China ; Youth fund of Natural Science Foundation of Hebei Province
内容类型期刊论文
源URL[http://ir.igsnrr.ac.cn/handle/311030/132095]  
专题中国科学院地理科学与资源研究所
通讯作者Li, Ning
作者单位1.Beijing Normal Univ, Minist Educ, Beijing 100875, Peoples R China
2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China
3.Beijing Normal Univ, Fac Geog Sci, Key Lab Environm Change & Nat Disaster, MOE, Beijing 100875, Peoples R China
4.Beijing Normal Univ, Fac Geog Sci, State Key Lab Earth Surface Proc & Resource Ecol, Beijing 100875, Peoples R China
5.Ningbo Univ, Dept Geog & Spatial Informat Techn, Ningbo 315211, Zhejiang, Peoples R China
6.Beijing Normal Univ, Acad Disaster Reduct & Emergency Management, Minist Emergency Management, Beijing 100875, Peoples R China
7.Armed Police Acad, Dept Fire Commanding, Langfang, Hebei, Peoples R China
推荐引用方式
GB/T 7714
Zhang, Zhengtao,Li, Ning,Xu, Hong,et al. Allocating assistance after a catastrophe based on the dynamic assessment of indirect economic losses[J]. NATURAL HAZARDS,2019,99(1):17-37.
APA Zhang, Zhengtao.,Li, Ning.,Xu, Hong.,Feng, Jieling.,Chen, Xi.,...&Zhang, Peng.(2019).Allocating assistance after a catastrophe based on the dynamic assessment of indirect economic losses.NATURAL HAZARDS,99(1),17-37.
MLA Zhang, Zhengtao,et al."Allocating assistance after a catastrophe based on the dynamic assessment of indirect economic losses".NATURAL HAZARDS 99.1(2019):17-37.
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