Modeling the economic costs of disasters and recovery: analysis using a dynamic computable general equilibrium model

Abstract

Abstract. Disaster damages have negative effects on the economy, whereas reconstruction investment has positive effects. The aim of this study is to model economic causes of disasters and recovery involving the positive effects of reconstruction activities. Computable general equilibrium (CGE) model is a promising approach because it can incorporate these two kinds of shocks into a unified framework and furthermore avoid the double-counting problem. In order to factor both shocks into the CGE model, direct loss is set as the amount of capital stock reduced on the supply side of the economy; a portion of investments restores the capital stock in an existing period; an investment-driven dynamic model is formulated according to available reconstruction data, and the rest of a given country's saving is set as an endogenous variable to balance the fixed investment. The 2008 Wenchuan Earthquake is selected as a case study to illustrate the model, and three scenarios are constructed: S 0 (no disaster occurs), S 1 (disaster occurs with reconstruction investment) and S 2 (disaster occurs without reconstruction investment). S 0 is taken as business as usual, and the differences between S 1 and S 0 and that between S 2 and S 0 can be interpreted as economic losses including reconstruction and excluding reconstruction, respectively. The study showed that output from S 1 is found to be closer to real data than that from S 2 . Economic loss under S2 is roughly 1.5 times that under S 1 . The gap in the economic aggregate between S 1 and S 0 is reduced to 3 % at the end of government-led reconstruction activity, a level that should take another four years to achieve under S 2 .

Dynamic Economic Resilience and Economic Recovery from Disasters: A Quantitative Assessment

“…Much attention has been paid to mitigation to prevent the destruction of buildings and infrastructure, but lost economic output, a prominent indicator of “business interruption” (BI), can be even larger than property damage in major disasters, in part because of supply‐chain reactions that radiate outward from the site of the disaster . This is the case for the September 11, 2001, World Trade Center Attacks, Hurricane Katrina, and the Wenchuan earthquake . Mitigation reduces potential BI as a joint product along with its protection of the capital stock, but the potential of dynamic resilience to reduce some of the remaining BI losses has not yet been adequately quantified.…”

Adaptive governance to typhoon disasters for coastal sustainability: A case study in Guangdong, China

“…Given the uncertainty of the catastrophe, the government has to arrange huge temporary relief funds for post-disaster compensation, which will inevitably disturb the annual budget plans for social welfare, education and other important investments that are critical to economic development and social progress. For example, the 2008 Sichuan earthquake in China caused more than $118 billion in direct economic losses, but the number of insured losses was less than $6 billion (Xie et al, 2014b). The loss ratio was approximately 5% and is far below the average international level of 36%.…”

Analysis of employment change in response to hurricane landfalls

“…Approximately 80 % of New Orleans flooded, and the depth of the flood was up to 20 ft (6.1 m) following the landfall of the hurricane. The total economic damage from Hurricane Katrina is around USD 160 billion (in 2019 dollars), nearly 2 times the cost of the previously most expensive hurricane, Hurricane Andrew (Zhang and Peacock, 2009).…”

“…Employment is associated with the level of preparedness for disaster and the ability to take proactive actions. Higher employment in a county, for example, often translates into higher resilience and quicker recovery process through purchasing insurance and upgrading houses (Mayunga, 2007;Xie et al, 2014). Previous research has focused on analyzing the elements of vulnerability and disaster recovery, highlighting the importance of employment status for speeding up the recovery process after a disaster strikes a community (Frazier et al, 2014;Stewart et al, 2014;FEMA, 2018).…”