IDEAS home Printed from https://ideas.repec.org/a/spr/grdene/v26y2017i6d10.1007_s10726-017-9537-7.html
   My bibliography  Save this article

A New Approach to Quantifying the Impact of Hurricane-Disrupted Oil Refinery Operations Utilizing Secondary Data

Author

Listed:
  • Jiyoung Park

    (University at Buffalo, The State University of New York)

  • James E. Moore

    (University of Southern California)

  • Peter Gordon

    (University of Southern California)

  • Harry W. Richardson

    (Autonomous University of the State of Mexico)

Abstract

This study suggests a new framework that empirically quantifies the temporally disaggregate economic impacts. Utilizing only secondary data, including post-event information on concurrent demand and value-added changes in the wake of Hurricanes Katrina and Rita, the framework is used to identify the technological changes in production that actually occurred after a major disruption. Two methodologies are developed for the framework and data analysis: a quasi-experimental model and an economic model. The Holt–Winters time-series approach is used to estimate normal economic trends under the assumption that the two hurricanes had not occurred, and the results are compared to actual trends. The gaps between the estimated and actual trends represent the direct impacts. We utilized the flexible national interstate economic model to construct a month-to-month supply-side version of the national interstate economic model and measure the total economic impacts of Hurricanes Katrina and Rita by month, state and industry, including adaptations. The new framework, which provides estimates of economic impact adaptation process and resilient results, refines the often substantially overstated impacts provided by the application of conventional economic models. The suggested approach can be used to address questions about the effects of time, distance, and industry linkages, and hence the dynamics of conflict activities.

Suggested Citation

  • Jiyoung Park & James E. Moore & Peter Gordon & Harry W. Richardson, 2017. "A New Approach to Quantifying the Impact of Hurricane-Disrupted Oil Refinery Operations Utilizing Secondary Data," Group Decision and Negotiation, Springer, vol. 26(6), pages 1125-1144, November.
  • Handle: RePEc:spr:grdene:v:26:y:2017:i:6:d:10.1007_s10726-017-9537-7
    DOI: 10.1007/s10726-017-9537-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10726-017-9537-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10726-017-9537-7?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Peter R. Winters, 1960. "Forecasting Sales by Exponentially Weighted Moving Averages," Management Science, INFORMS, vol. 6(3), pages 324-342, April.
    2. Adam Rose & Gauri-Shankar Guha, 2004. "Computable General Equilibrium Modeling of Electric Utility Lifeline Losses from Earthquakes," Advances in Spatial Science, in: Yasuhide Okuyama & Stephanie E. Chang (ed.), Modeling Spatial and Economic Impacts of Disasters, chapter 7, pages 119-141, Springer.
    3. William D. Nordhaus, 2006. "The Economics of Hurricanes in the United States," NBER Working Papers 12813, National Bureau of Economic Research, Inc.
    4. JiYoung Park & Peter Gordon & James Moore & Harry Richardson, 2009. "A two-step approach to estimating state-to-state commodity trade flows," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 43(4), pages 1033-1072, December.
    5. S. A. Roberts, 1982. "A General Class of Holt-Winters Type Forecasting Models," Management Science, INFORMS, vol. 28(7), pages 808-820, July.
    6. Park, Jiyoung & Park, Changkeun & Nam, Sangjeong, 2006. "The State-by-State Effects of Mad Cow Disease Using a New MRIO Model," 2006 Annual meeting, July 23-26, Long Beach, CA 21328, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    7. 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)

    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. 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.
    2. 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.
    3. 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.
    4. Baghersad, Milad & Zobel, Christopher W., 2015. "Economic impact of production bottlenecks caused by disasters impacting interdependent industry sectors," International Journal of Production Economics, Elsevier, vol. 168(C), pages 71-80.
    5. 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.
    6. Jan Oosterhaven, 2017. "On the limited usability of the inoperability IO model," Economic Systems Research, Taylor & Francis Journals, vol. 29(3), pages 452-461, July.
    7. Naqvi, Asjad, 2017. "Deep Impact: Geo-Simulations as a Policy Toolkit for Natural Disasters," World Development, Elsevier, vol. 99(C), pages 395-418.
    8. Wenzel, Lars & Wolf, André, 2013. "Protection against major catastrophes: An economic perspective," HWWI Research Papers 137, Hamburg Institute of International Economics (HWWI).
    9. A A Syntetos & J E Boylan & S M Disney, 2009. "Forecasting for inventory planning: a 50-year review," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(1), pages 149-160, May.
    10. Peter Gordon & James E. Moore II & Jiyoung Park & Harry W. Richardson, 2010. "Short-Run Economic Impacts of Hurricane Katrina (and Rita)," CESifo Forum, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 11(02), pages 73-79, July.
    11. Haddad Eduardo Amaral & Okuyama Yasuhide, 2016. "Spatial Propagation of the Economic Impacts of Bombing: The Case of the 2006 War in Lebanon," Review of Middle East Economics and Finance, De Gruyter, vol. 12(3), pages 225-256, December.
    12. Haddad, Eduardo & Teixeira, Eliane, 2013. "Economic Impacts of Natural Disasters in Megacities: The Case of Floods in São Paulo, Brazil," TD NEREUS 4-2013, Núcleo de Economia Regional e Urbana da Universidade de São Paulo (NEREUS).
    13. Peter Gordon & James E. Moore II & Jiyoung Park & Harry W. Richardson, 2010. "Short-Run Economic Impacts of Hurricane Katrina (and Rita)," CESifo Forum, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 11(2), pages 73-79, July.
    14. Hirokazu Tatano & Satoshi Tsuchiya, 2008. "A framework for economic loss estimation due to seismic transportation network disruption: a spatial computable general equilibrium approach," 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. 44(2), pages 253-265, February.
    15. George Athanasopoulos & Ashton de Silva, 2010. "Multivariate exponential smoothing for forecasting tourist arrivals to Australia and New Zealand," Monash Econometrics and Business Statistics Working Papers 11/09, Monash University, Department of Econometrics and Business Statistics.
    16. Hussain, Anwar & Rahman, Muhammad & Memon, Junaid Alam, 2016. "Forecasting electricity consumption in Pakistan: the way forward," Energy Policy, Elsevier, vol. 90(C), pages 73-80.
    17. Suman K SHARMA, 2010. "Socio-Economic Aspects of Disaster’s Impact: An Assessment of Databases and Methodologies," Economic Growth Centre Working Paper Series 1001, Nanyang Technological University, School of Social Sciences, Economic Growth Centre.
    18. Jan G. De Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Monash Econometrics and Business Statistics Working Papers 12/05, Monash University, Department of Econometrics and Business Statistics.
    19. H. Lin & Y. Kuo & D. Shaw & M. Chang & T. Kao, 2012. "Regional economic impact analysis of earthquakes in northern Taiwan and its implications for disaster reduction policies," 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. 61(2), pages 603-620, March.
    20. Li, Qinyun & Disney, Stephen M. & Gaalman, Gerard, 2014. "Avoiding the bullwhip effect using Damped Trend forecasting and the Order-Up-To replenishment policy," International Journal of Production Economics, Elsevier, vol. 149(C), pages 3-16.

    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:spr:grdene:v:26:y:2017:i:6:d:10.1007_s10726-017-9537-7. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.