Evaluation of indirect loss from hypothetical catastrophes in two regions with different economic development levels in China

Xie, Wei; Li, N.; Wu, Jidong; Liu, X.-Q.

doi:10.5194/nhess-12-3325-2012

Cited by 15 publications

(6 citation statements)

References 26 publications

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“…Indirect damage has been estimated using either statisticbased approaches (e.g., Kajitani and Tatano, 2014;Yang et al, 2016) or model-based approaches, notably inputoutput (IO) models (Hallegatte, 2008;Van der Veen et al, 2003;Hallegatte, 2014;Crawford-Brown et al, 2013;Xie et al, 2012), computable general equilibrium (CGE) models (Xie et al, 2014;Rose and Liao, 2005;OCDE, 2014) or a combination of the two (Donaghy et al, 2007;Rose and Krausmann, 2013;Santos et al, 2014;Hallegatte and Ghil, 2008). Both families have their own strengths and weaknesses.…”

Section: Introductionmentioning

confidence: 99%

Are interactions important in estimating flood damage to economic entities? The case of wine-making in France

Martínez

Grelot

Brémond

et al. 2021

Nat. Hazards Earth Syst. Sci.

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Abstract. Estimating flood damage, although crucial for assessing flood risk and for designing mitigation policies, continues to face numerous challenges, notably the assessment of indirect damage. It is widely accepted that damage other than direct damage can account for a significant proportion of total damage. Yet due to scarcer data sources and lack of knowledge on links within and between economic activities, indirect impacts have received less attention than direct impacts. Furthermore, attempts to grasp indirect damage through economic models have not gone below regional levels. Even though local communities can be devastated by flood events without this being reflected in regional accounts, few studies have been conducted from a microeconomic perspective at local level. What is more, the standard practices applied at this level of analysis tackle entities but ignore how they may be linked. This paper addresses these two challenges by building a novel agent-based model of a local agricultural production chain (a French cooperative wine-making system), utilized as a virtual laboratory for the ex ante estimation of flood impacts. We show how overlooking existing interactions between economic entities in production chains can result in either overestimation (double counting) or underestimation (wrong estimation of the consequences for the activity) of flood damage. Our results also reveal that considering interactions requires thorough characterization of their spatial configuration. Based on both the application of our method and the results obtained, we propose balanced recommendations for flood damage estimation at local level.

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Section: Introductionmentioning

confidence: 99%

Are interactions important in estimating flood damage to economic entities? The case of wine-making in France

Martínez

Grelot

Brémond

et al. 2021

Nat. Hazards Earth Syst. Sci.

View full text Add to dashboard Cite

show abstract

“…Additionally, with the deepening understanding of disaster losses as well as the demands of the insured, overall disaster losses, including both direct economic loss (DEL) and indirect economic loss (IEL), have attracted increasing attention. According to lots of discussions and a wide range of studies (Brookshire et al 1997;Haimes et al 2005;Xie et al 2012;Koks et al 2014), the DEL is the short-term physical damage caused by the disaster when it occurs and the physical impacts that occur after the disaster (Cochrane 1997). The IEL includes other losses that occur due to factors such as disruptions in trade between economic departments, supply-demand imbalances and dislocations between forward output and backward supply caused by the physical damage (FEMA 2001).…”

Section: Introductionmentioning

confidence: 99%

Allocating assistance after a catastrophe based on the dynamic assessment of indirect economic losses

Zhang

Hong

et al. 2019

Nat Hazards

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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.

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“…Because indirect economic loss can increase, it can even outnumber direct economic loss along with the economic development, which underscores the significance of being able to capture the ripple effects accumulated along interregional and interindustrial linkages. The Input-Output (IO) model (Hallegatte et al, 2010;Wu et al, 2012;Hallegatte, 2014;Zhou et al, 2014;Xia et al, 2016) and the computable general equilibrium (CGE) model (Rose and Liao, 2005;Guivarch et al, 2009;Xie et al, 2013;Rose, 2015) are two representative models which are commonly used to assess indirect economic loss.…”

Section: Introductionmentioning

confidence: 99%

Assessment of the ripple effects and spatial heterogeneity of total losses in the capital of China after a great catastrophic shock

Zhang

Xie

et al. 2017

Nat. Hazards Earth Syst. Sci.

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Abstract. The total losses caused by natural disasters have spatial heterogeneity due to the different economic development levels inside the disaster-hit areas. This paper uses scenarios of direct economic loss to introduce the sectors' losses caused by the 2008 Wenchuan earthquake (2008 WCE) in Beijing, utilizing the Adaptive Regional Input–Output (ARIO) model and the Inter-regional ripple effect (IRRE) model. The purpose is to assess the ripple effects of indirect economic loss and spatial heterogeneity of both direct and indirect economic loss at the scale of the smallest administrative divisions of China (streets, villages, and towns). The results indicate that the district of Beijing with the most severe indirect economic loss is the Chaoyang District; the finance and insurance industry (15, see Table 1) of Chaowai Street suffers the most in the Chaoyang District, which is 1.46 times that of its direct economic loss. During 2008–2014, the average annual GDP (gross domestic product) growth rate of Beijing was decreased 3.63 % by the catastrophe. Compared with the 8 % of GDP growth rate target, the decreasing GDP growth rate is a significant and noticeable economic impact, and it can be efficiently mitigated by increasing rescue effort and by supporting the industries which are located in the seriously damaged regions.

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Evaluation of indirect loss from hypothetical catastrophes in two regions with different economic development levels in China

Cited by 15 publications

References 26 publications

Are interactions important in estimating flood damage to economic entities? The case of wine-making in France

Are interactions important in estimating flood damage to economic entities? The case of wine-making in France

Allocating assistance after a catastrophe based on the dynamic assessment of indirect economic losses

Assessment of the ripple effects and spatial heterogeneity of total losses in the capital of China after a great catastrophic shock

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