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Extreme Risk Analysis of Interdependent Economic and Infrastructure Sectors
Author(s) -
Lian Chenyang,
Santos Joost R.,
Haimes Yacov Y.
Publication year - 2007
Publication title -
risk analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.972
H-Index - 130
eISSN - 1539-6924
pISSN - 0272-4332
DOI - 10.1111/j.1539-6924.2007.00943.x
Subject(s) - interdependence , consumption (sociology) , economic sector , set (abstract data type) , risk analysis (engineering) , risk management , econometrics , economics , computer science , business , economy , social science , management , sociology , political science , law , programming language
Willful attacks or natural disasters pose extreme risks to sectors of the economy. An extreme‐event analysis extension is proposed for the Inoperability Input‐Output Model (IIM) and the Dynamic IIM (DIIM), which are analytical methodologies for assessing the propagated consequences of initial disruptions to a set of sectors. The article discusses two major risk categories that the economy typically experiences following extreme events: (i) significant changes in consumption patterns due to lingering public fear and (ii) adjustments to the production outputs of the interdependent economic sectors that are necessary to match prevailing consumption levels during the recovery period. Probability distributions associated with changes in the consumption of directly affected sectors are generated based on trends, forecasts, and expert evidence to assess the expected losses of the economy. Analytical formulations are derived to quantify the extreme risks associated with a set of initially affected sectors. In addition, Monte Carlo simulation is used to handle the more complex calculations required for a larger set of sectors and general types of probability distributions. A two‐sector example is provided at the end of the article to illustrate the proposed extreme risk model formulations.