International Trade Inoperability Input-Output Model (IT-IIM): Theory and Application

The inoperability input-output model (IIM) has been used for analyzing disruptions due to man-made or natural disasters that can adversely affect the operation of economic systems or critical infrastructures. Taking economic perturbation for each sector as inputs, the IIM provides the degree of econ...

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Bibliographic Details
Published inRisk analysis Vol. 29; no. 1; pp. 137 - 154
Main Authors Jung, Jeesang, Santos, Joost R, Haimes, Yacov Y
Format Journal Article
LanguageEnglish
Published Malden, USA Blackwell Publishing Inc 2009
Blackwell Publishing Ltd
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Summary:The inoperability input-output model (IIM) has been used for analyzing disruptions due to man-made or natural disasters that can adversely affect the operation of economic systems or critical infrastructures. Taking economic perturbation for each sector as inputs, the IIM provides the degree of economic production impacts on all industry sectors as the outputs for the model. The current version of the IIM does not provide a separate analysis for the international trade component of the inoperability. If an important port of entry (e.g., Port of Los Angeles) is disrupted, then international trade inoperability becomes a highly relevant subject for analysis. To complement the current IIM, this article develops the International Trade-IIM (IT-IIM). The IT-IIM investigates the resulting international trade inoperability for all industry sectors resulting from disruptions to a major port of entry. Similar to traditional IIM analysis, the inoperability metrics that the IT-IIM provides can be used to prioritize economic sectors based on the losses they could potentially incur. The IT-IIM is used to analyze two types of direct perturbations: (1) the reduced capacity of ports of entry, including harbors and airports (e.g., a shutdown of any port of entry); and (2) restrictions on commercial goods that foreign countries trade with the base nation (e.g., embargo).
Bibliography:http://dx.doi.org/10.1111/j.1539-6924.2008.01126.x
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ArticleID:RISA1126
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Center for Risk Management of Engineering Systems, University of Virginia, VA, USA.
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ISSN:0272-4332
1539-6924
DOI:10.1111/j.1539-6924.2008.01126.x