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

Jiyoung Park (), James E. Moore, Peter Gordon and Harry W. Richardson
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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

Group Decision and Negotiation, 2017, vol. 26, issue 6, No 4, 1125-1144

Abstract: 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.

Keywords: Flexible national interstate economic model; Quasi-experimental model; Economic model; Hurricane; Economic impacts (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/s10726-017-9537-7

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