[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2018i1p126-d193432.html
   My bibliography  Save this article

Integrated Assessment of Economic Losses in Manufacturing Industry in Shanghai Metropolitan Area Under an Extreme Storm Flood Scenario

Author

Listed:
  • Weijiang Li

    (School of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai 200234, China)

  • Jiahong Wen

    (School of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai 200234, China)

  • Bo Xu

    (Department of Geography and Environmental Studies, California State University San Bernardino, San Bernardino, CA 92407, USA)

  • Xiande Li

    (School of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai 200234, China)

  • Shiqiang Du

    (School of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai 200234, China)

Abstract
In this paper, we developed an integrated methodology for assessing asset damage, production capacity loss, and inter-sector ripple loss using the depth-damage curve, Cobb-Douglas production function and Input-Output model. We applied this methodology to the detailed individual manufacturing firms in Shanghai under an extreme storm floods scenario to simulate the disaster impact propagation from local individual firms to the entire industrial system and comprehensively estimate the resulting economic losses and their spatial distribution. Our results show that given no floodwall protection, a 1000-year storm flood scenario would cause direct asset damage of US $21 billion to the Shanghai manufacturing industry, including fixed asset damage of US $12 billion and inventory damage of US $9 billion. Due to the shortage of input productive factors of asset and labor, it would further lead to production capacity loss of US $24 billion. In addition, affected manufacturing industry would indirectly result in ripple loss of US $60 billion among dependent sectors, which has a significant amplifier effect. Our results have important implications for reasonable cost-benefit analysis of structural flood control measures in coastal areas, as well as for manufacturing firm location planning and resilience strategy decision-making.

Suggested Citation

  • Weijiang Li & Jiahong Wen & Bo Xu & Xiande Li & Shiqiang Du, 2018. "Integrated Assessment of Economic Losses in Manufacturing Industry in Shanghai Metropolitan Area Under an Extreme Storm Flood Scenario," Sustainability, MDPI, vol. 11(1), pages 1-19, December.
    • Handle: RePEc:gam:jsusta:v:11:y:2018:i:1:p:126-:d:193432
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/1/126/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/11/1/126/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. H. Moel & J. Aerts, 2011. "Effect of uncertainty in land use, damage models and inundation depth on flood damage estimates," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 58(1), pages 407-425, July.
    2. Stephane Hallegatte & Colin Green & Robert J. Nicholls & Jan Corfee-Morlot, 2013. "Future flood losses in major coastal cities," Nature Climate Change, Nature, vol. 3(9), pages 802-806, September.
    3. Carrera, Lorenzo & Standardi, Gabriele & Bosello, Francesco & Mysiak, Jaroslav, 2014. "Assessing Direct and Indirect Economic Impacts of a Flood Event Through the Integration of Spatial and Computable General Equilibrium Modelling," Climate Change and Sustainable Development 186681, Fondazione Eni Enrico Mattei (FEEM).
    4. Lijiao Yang & Yoshio Kajitani & Hirokazu Tatano & Xinyu Jiang, 2016. "A methodology for estimating business interruption loss caused by flood disasters: insights from business surveys after Tokai Heavy Rain in Japan," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 84(1), pages 411-430, November.
    5. S. Balica & N. Wright & F. Meulen, 2012. "A flood vulnerability index for coastal cities and its use in assessing climate change impacts," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 64(1), pages 73-105, October.
    6. Jonkman, S.N. & Bockarjova, M. & Kok, M. & Bernardini, P., 2008. "Integrated hydrodynamic and economic modelling of flood damage in the Netherlands," Ecological Economics, Elsevier, vol. 66(1), pages 77-90, May.
    7. Wei Zhang & Gabriele Villarini & Gabriel A. Vecchi & James A. Smith, 2018. "Urbanization exacerbated the rainfall and flooding caused by hurricane Harvey in Houston," Nature, Nature, vol. 563(7731), pages 384-388, November.
    8. Adam Rose, 2004. "Economic Principles, Issues, and Research Priorities in Hazard Loss Estimation," Advances in Spatial Science, in: Yasuhide Okuyama & Stephanie E. Chang (ed.), Modeling Spatial and Economic Impacts of Disasters, chapter 2, pages 13-36, Springer.
    9. Choong-Sung Yi & Jin-Hee Lee & Myung-Pil Shim, 2010. "GIS-based distributed technique for assessing economic loss from flood damage: pre-feasibility study for the Anyang Stream Basin in Korea," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 55(2), pages 251-272, November.
    10. Jidong Wu & Ning Li & Stéphane Hallegatte & Peijun Shi & Aijun Hu & Xueqin Liu, 2012. "Regional indirect economic impact evaluation of the 2008 Wenchuan Earthquake," Post-Print hal-00716669, HAL.
    11. Stéphane Hallegatte, 2008. "An Adaptive Regional Input‐Output Model and its Application to the Assessment of the Economic Cost of Katrina," Risk Analysis, John Wiley & Sons, vol. 28(3), pages 779-799, June.
    12. Jun Li & Douglas Crawford‐Brown & Mark Syddall & Dabo Guan, 2013. "Modeling Imbalanced Economic Recovery Following a Natural Disaster Using Input‐Output Analysis," Risk Analysis, John Wiley & Sons, vol. 33(10), pages 1908-1923, October.
    13. Adam Rose & Shu‐Yi Liao, 2005. "Modeling Regional Economic Resilience to Disasters: A Computable General Equilibrium Analysis of Water Service Disruptions," Journal of Regional Science, Wiley Blackwell, vol. 45(1), pages 75-112, February.
    14. Yoshio Kajitani & Hirokazu Tatano, 2014. "Estimation Of Production Capacity Loss Rate After The Great East Japan Earthquake And Tsunami In 2011," Economic Systems Research, Taylor & Francis Journals, vol. 26(1), pages 13-38, March.
    15. Jun Wang & Wei Gao & Shiyuan Xu & Lizhong Yu, 2012. "Evaluation of the combined risk of sea level rise, land subsidence, and storm surges on the coastal areas of Shanghai, China," Climatic Change, Springer, vol. 115(3), pages 537-558, December.
    16. Yasuhide Okuyama, 2007. "Economic Modeling for Disaster Impact Analysis: Past, Present, and Future," Economic Systems Research, Taylor & Francis Journals, vol. 19(2), pages 115-124.
    17. Stéphane Hallegatte, 2008. "An adaptive regional input-output model and its application to the assessment of the economic cost of Katrina," Post-Print hal-00716550, HAL.
    18. E. E. Koks & M. Bočkarjova & H. de Moel & J. C. J. H. Aerts, 2015. "Integrated Direct and Indirect Flood Risk Modeling: Development and Sensitivity Analysis," Risk Analysis, John Wiley & Sons, vol. 35(5), pages 882-900, May.
    19. Nie, Huihua & Jiang, Ting & Yang, Rudai, 2012. "A Review and Reflection on the Use and Abuse of Chinese Industrial Enterprises Database," MPRA Paper 50945, University Library of Munich, Germany.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xinmeng Shan & Jiahong Wen & Min Zhang & Luyang Wang & Qian Ke & Weijiang Li & Shiqiang Du & Yong Shi & Kun Chen & Banggu Liao & Xiande Li & Hui Xu, 2019. "Scenario-Based Extreme Flood Risk of Residential Buildings and Household Properties in Shanghai," Sustainability, MDPI, vol. 11(11), pages 1-18, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Rui Huang & Arunima Malik & Manfred Lenzen & Yutong Jin & Yafei Wang & Futu Faturay & Zhiyi Zhu, 2022. "Supply-chain impacts of Sichuan earthquake: a case study using disaster input–output analysis," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 110(3), pages 2227-2248, February.
    2. E. E. Koks & M. Bočkarjova & H. de Moel & J. C. J. H. Aerts, 2015. "Integrated Direct and Indirect Flood Risk Modeling: Development and Sensitivity Analysis," Risk Analysis, John Wiley & Sons, vol. 35(5), pages 882-900, May.
    3. Aaron B. Gertz & James B. Davies & Samantha L. Black, 2019. "A CGE Framework for Modeling the Economics of Flooding and Recovery in a Major Urban Area," Risk Analysis, John Wiley & Sons, vol. 39(6), pages 1314-1341, June.
    4. David Mendoza‐Tinoco & Yixin Hu & Zhao Zeng & Konstantinos J. Chalvatzis & Ning Zhang & Albert E. Steenge & Dabo Guan, 2020. "Flood Footprint Assessment: A Multiregional Case of 2009 Central European Floods," Risk Analysis, John Wiley & Sons, vol. 40(8), pages 1612-1631, August.
    5. Matteo Coronese & Davide Luzzati, 2022. "Economic impacts of natural hazards and complexity science: a critical review," LEM Papers Series 2022/13, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    6. Stéphane Hallegatte, 2014. "Modeling the Role of Inventories and Heterogeneity in the Assessment of the Economic Costs of Natural Disasters," Risk Analysis, John Wiley & Sons, vol. 34(1), pages 152-167, January.
    7. Otto, Christian & Willner, Sven Norman & Wenz, Leonie & Frieler, Katja & Levermann, Anders, 2017. "Modeling loss-propagation in the global supply network: The dynamic agent-based model acclimate," OSF Preprints 7yyhd, Center for Open Science.
    8. Lorenzo Carrera & Gabriele Standardi & Francesco Bosello & Jaroslav Mysiak, 2014. "Assessing Direct and Indirect Economic Impacts of a Flood Event Through the Integration of Spatial and Computable General Equilibrium Modelling," Working Papers 2014.82, Fondazione Eni Enrico Mattei.
    9. Selerio, Egberto & Maglasang, Renan, 2021. "Minimizing production loss consequent to disasters using a subsidy optimization model: a pandemic case," Structural Change and Economic Dynamics, Elsevier, vol. 58(C), pages 112-124.
    10. Hu, Xi & Pant, Raghav & Hall, Jim W. & Surminski, Swenja & Huang, Jiashun, 2019. "Multi-scale assessment of the economic impacts of flooding: evidence from firm to macro-level analysis in the Chinese manufacturing sector," LSE Research Online Documents on Economics 100534, London School of Economics and Political Science, LSE Library.
    11. H. Moel & B. Jongman & H. Kreibich & B. Merz & E. Penning-Rowsell & P. Ward, 2015. "Flood risk assessments at different spatial scales," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 20(6), pages 865-890, August.
    12. Xi Hu & Raghav Pant & Jim W. Hall & Swenja Surminski & Jiashun Huang, 2019. "Multi-Scale Assessment of the Economic Impacts of Flooding: Evidence from Firm to Macro-Level Analysis in the Chinese Manufacturing Sector," Sustainability, MDPI, vol. 11(7), pages 1-18, April.
    13. Mattia Amadio & Jaroslav Mysiak & Lorenzo Carrera & Elco Koks, 2016. "Improving flood damage assessment models in Italy," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 82(3), pages 2075-2088, July.
    14. Zhengtao Zhang & Ning Li & Peng Cui & Hong Xu & Yuan Liu & Xi Chen & Jieling Feng, 2019. "How to Integrate Labor Disruption into an Economic Impact Evaluation Model for Postdisaster Recovery Periods," Risk Analysis, John Wiley & Sons, vol. 39(11), pages 2443-2456, November.
    15. Jidong Wu & Mengqi Ye & Xu Wang & Elco Koks, 2019. "Building Asset Value Mapping in Support of Flood Risk Assessments: A Case Study of Shanghai, China," Sustainability, MDPI, vol. 11(4), pages 1-19, February.
    16. David Nortes Martínez & Frédéric Grelot & Pauline Bremond & Stefano Farolfi & Juliette Rouchier, 2021. "Are interactions important in estimating flood damage to economic entities? The case of wine-making in France," Post-Print hal-03609616, HAL.
    17. Irfan Ahmed & Claudio Socci & Rosita Pretaroli & Francesca Severini & Stefano Deriu, 2022. "Socioeconomic spillovers of the 2016–2017 Italian earthquakes: a bi-regional inoperability model," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(1), pages 426-453, January.
    18. Liu, Huan & Tatano, Hirokazu & Pflug, Georg & Hochrainer-Stigler, Stefan, 2021. "Post-disaster recovery in industrial sectors: A Markov process analysis of multiple lifeline disruptions," Reliability Engineering and System Safety, Elsevier, vol. 206(C).
    19. Jie Zhang & Meng Lu & Lulu Zhang & Yadong Xue, 2021. "Assessing indirect economic losses of landslides along highways," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 106(3), pages 2775-2796, April.
    20. Severin Reissl & Alessandro Caiani & Francesco Lamperti & Tommaso Ferraresi & Leonardo Ghezzi, 2024. "A regional input-output model of the COVID-19 crisis in Italy: decomposing demand and supply factors," Economic Systems Research, Taylor & Francis Journals, vol. 36(1), pages 100-130, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:11:y:2018:i:1:p:126-:d:193432. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.