IDEAS home Printed from https://ideas.repec.org/a/wly/riskan/v33y2013i10p1908-1923.html
   My bibliography  Save this article

Modeling Imbalanced Economic Recovery Following a Natural Disaster Using Input‐Output Analysis

Author

Listed:
  • Jun Li
  • Douglas Crawford‐Brown
  • Mark Syddall
  • Dabo Guan

Abstract

Input‐output analysis is frequently used in studies of large‐scale weather‐related (e.g., Hurricanes and flooding) disruption of a regional economy. The economy after a sudden catastrophe shows a multitude of imbalances with respect to demand and production and may take months or years to recover. However, there is no consensus about how the economy recovers. This article presents a theoretical route map for imbalanced economic recovery called dynamic inequalities. Subsequently, it is applied to a hypothetical postdisaster economic scenario of flooding in London around the year 2020 to assess the influence of future shocks to a regional economy and suggest adaptation measures. Economic projections are produced by a macro econometric model and used as baseline conditions. The results suggest that London's economy would recover over approximately 70 months by applying a proportional rationing scheme under the assumption of initial 50% labor loss (with full recovery in six months), 40% initial loss to service sectors, and 10–30% initial loss to other sectors. The results also suggest that imbalance will be the norm during the postdisaster period of economic recovery even though balance may occur temporarily. Model sensitivity analysis suggests that a proportional rationing scheme may be an effective strategy to apply during postdisaster economic reconstruction, and that policies in transportation recovery and in health care are essential for effective postdisaster economic recovery.

Suggested Citation

  • 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.
  • Handle: RePEc:wly:riskan:v:33:y:2013:i:10:p:1908-1923
    DOI: 10.1111/risa.12040
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/risa.12040
    Download Restriction: no

    File URL: https://libkey.io/10.1111/risa.12040?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Hallegatte, Stephane & Hourcade, Jean-Charles & Dumas, Patrice, 2007. "Why economic dynamics matter in assessing climate change damages: Illustration on extreme events," Ecological Economics, Elsevier, vol. 62(2), pages 330-340, April.
    2. Terry Barker & Bernie Fingleton & K. Homenidou & R. Lewney, 2001. "The Regional Cambridge Multisectoral Dynamic Model of the UK Economy," Advances in Spatial Science, in: Graham Clarke & Moss Madden (ed.), Regional Science in Business, chapter 5, pages 79-96, Springer.
    3. 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.
    4. Satoshi Tsuchiya & Hirokazu Tatano & Norio Okada, 2007. "Economic Loss Assessment due to Railroad and Highway Disruptions," Economic Systems Research, Taylor & Francis Journals, vol. 19(2), pages 147-162.
    5. 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.
    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. 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.
    2. Yagi, Michiyuki & Managi, Shunsuke, 2023. "The spillover effects of rising energy prices following 2022 Russian invasion of Ukraine," Economic Analysis and Policy, Elsevier, vol. 77(C), pages 680-695.
    3. Michiyuki Yagi & Shigemi Kagawa & Shunsuke Managi & Hidemichi Fujii & Dabo Guan, 2020. "Supply Constraint from Earthquakes in Japan in Input–Output Analysis," Risk Analysis, John Wiley & Sons, vol. 40(9), pages 1811-1830, September.
    4. 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.
    5. 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.
    6. 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.
    7. Xiaoxiang Xu & Mingqiu Liao, 2022. "Prediction of China’s Economic Structural Changes under Carbon Emission Constraints: Based on the Linear Programming Input–Output (LP-IO) Model," Sustainability, MDPI, vol. 14(15), pages 1-13, July.
    8. 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.
    9. 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.
    10. Yagi, Michiyuki & Managi, Shunsuke, 2021. "Global supply constraints from the 2008 and COVID-19 crises," Economic Analysis and Policy, Elsevier, vol. 69(C), pages 514-528.
    11. Scott Thacker & Scott Kelly & Raghav Pant & Jim W. Hall, 2018. "Evaluating the Benefits of Adaptation of Critical Infrastructures to Hydrometeorological Risks," Risk Analysis, John Wiley & Sons, vol. 38(1), pages 134-150, January.

    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. 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.
    2. Hallegatte, Stephane, 2012. "Modeling the roles of heterogeneity, substitution, and inventories in the assessment of natural disaster economic costs," Policy Research Working Paper Series 6047, The World Bank.
    3. Naqvi, Asjad, 2017. "Deep Impact: Geo-Simulations as a Policy Toolkit for Natural Disasters," World Development, Elsevier, vol. 99(C), pages 395-418.
    4. 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.
    5. 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.
    6. Iman Rahimi Aloughareh & Mohsen Ghafory Ashtiany & Kiarash Nasserasadi, 2016. "An Integrated Methodology For Regional Macroeconomic Loss Estimation Of Earthquake: A Case Study Of Tehran," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 61(04), pages 1-24, September.
    7. 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.
    8. Pradeep V. Mandapaka & Edmond Y. M. Lo, 2023. "Assessing Shock Propagation and Cascading Uncertainties Using the Input–Output Framework: Analysis of an Oil Refinery Accident in Singapore," Sustainability, MDPI, vol. 15(2), pages 1-24, January.
    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. Wenzel, Lars & Wolf, André, 2013. "Protection against major catastrophes: An economic perspective," HWWI Research Papers 137, Hamburg Institute of International Economics (HWWI).
    11. K. Jenkins, 2013. "Indirect economic losses of drought under future projections of climate change: a case study for Spain," 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. 69(3), pages 1967-1986, December.
    12. Henriet, Fanny & Hallegatte, Stephane, 2008. "Assessing the Consequences of Natural Disasters on Production Networks: A Disaggregated Approach," Coalition Theory Network Working Papers 46657, Fondazione Eni Enrico Mattei (FEEM).
    13. Asjad Naqvi & Franziska Gaupp & Stefan Hochrainer-Stigler, 2020. "The risk and consequences of multiple breadbasket failures: an integrated copula and multilayer agent-based modeling approach," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 42(3), pages 727-754, September.
    14. 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.
    15. 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.
    16. Hoffmann, Christin, 2019. "Estimating the benefits of adaptation to extreme climate events, focusing on nonmarket damages," Ecological Economics, Elsevier, vol. 164(C), pages 1-1.
    17. Trond G. Husby & Elco E. Koks, 2017. "Household migration in disaster impact analysis: incorporating behavioural responses to risk," 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. 87(1), pages 287-305, May.
    18. Paul Raschky, 2007. "Estimating the effects of risk transfer mechanisms against floods in Europe and U.S.A.: A dynamic panel approach," Working Papers 2007-05, Faculty of Economics and Statistics, Universität Innsbruck.
    19. Masato Yamazaki & Atsushi Koike & Yoshinori Sone, 2018. "A Heuristic Approach to the Estimation of Key Parameters for a Monthly, Recursive, Dynamic CGE Model," Economics of Disasters and Climate Change, Springer, vol. 2(3), pages 283-301, October.
    20. 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.

    More about this item

    Statistics

    Access and download statistics

    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:wly:riskan:v:33:y:2013:i:10:p:1908-1923. 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: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1111/(ISSN)1539-6924 .

    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.