Assessing the Regional Economic Ripple Effect of Flood Disasters Based on a Spatial Computable General Equilibrium Model Considering Traffic Disruptions

Lijiao Yang; Xinge Wang; Xinyu Jiang; Hirokazu Tatano

doi:10.1007/s13753-023-00500-2

Volume 14 Issue 3

Jul. 2023

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Article Navigation > International Journal of Disaster Risk Science > 2023 > 14(3): 488-505

Lijiao Yang, Xinge Wang, Xinyu Jiang, Hirokazu Tatano. Assessing the Regional Economic Ripple Effect of Flood Disasters Based on a Spatial Computable General Equilibrium Model Considering Traffic Disruptions[J]. International Journal of Disaster Risk Science, 2023, 14(3): 488-505. doi: 10.1007/s13753-023-00500-2

Citation:

Lijiao Yang, Xinge Wang, Xinyu Jiang, Hirokazu Tatano. Assessing the Regional Economic Ripple Effect of Flood Disasters Based on a Spatial Computable General Equilibrium Model Considering Traffic Disruptions[J]. International Journal of Disaster Risk Science, 2023, 14(3): 488-505. doi: 10.1007/s13753-023-00500-2

Citation:

Lijiao Yang, Xinge Wang, Xinyu Jiang, Hirokazu Tatano. Assessing the Regional Economic Ripple Effect of Flood Disasters Based on a Spatial Computable General Equilibrium Model Considering Traffic Disruptions[J]. International Journal of Disaster Risk Science, 2023, 14(3): 488-505. doi: 10.1007/s13753-023-00500-2

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Assessing the Regional Economic Ripple Effect of Flood Disasters Based on a Spatial Computable General Equilibrium Model Considering Traffic Disruptions

doi: 10.1007/s13753-023-00500-2

1. School of Management, Harbin Institute of Technology, Harbin, 150001, China;
2. School of Management, Wuhan University of Technology, Wuhan, 430070, China;
3. Research Institute of Digital Governance and Management Decision Innovation, Wuhan University of Technology, Wuhan, 430070, China;
4. Disaster Prevention Research Institute, Kyoto University, Kyoto, 611-0011, Japan

Funds:

This study was supported by the National Natural Science Foundation of China (Grant Nos. 42177448 and 41907393).

Accepted Date: 2023-05-20

Available Online: 2023-07-03

Publish Date: 2023-06-26

Abstract

Abstract

With growing regional economic integration, transportation systems have become critical to regional development and economic vitality but vulnerable to disasters. However, the regional economic ripple effect of a disaster is difficult to quantify accurately, especially considering the cumulated influence of traffic disruptions. This study explored integrating transportation system analysis with economic modeling to capture the regional economic ripple effect. A state-of-the-art spatial computable general equilibrium model is leveraged to simulate the operation of the economic system, and the marginal rate of transport cost is introduced to reflect traffic network damage post-disaster. The model is applied to the 50-year return period flood in 2020 in Hubei Province, China. The results show the following. First, when traffic disruption costs are considered, the total output loss of non-affected areas is 1.81 times than before, and non-negligible losses reach relatively remote zones of the country, such as the Northwest Comprehensive Economic Zone (36% of total ripple effects). Second, traffic disruptions have a significant hindering effect on regional trade activities, especially in the regional intermediate input—about three times more than before. The industries most sensitive to traffic disruptions were transportation, storage, and postal service (5 times), and processing and assembly manufacturing (4.4 times). Third, the longer the distance, the stronger traffic disruptions’ impact on interregional intermediate inputs. Thus, increasing investment in transportation infrastructure significantly contributes to mitigating disaster ripple effects and accelerating the process of industrial recovery in affected areas.
- Economic ripple effect,
- Floods,
- Spatial computable general equilibrium model,
- Supply chain damage,
- Traffic disruption

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References(58)

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