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E-grāmata: Economic Consequence Analysis of Disasters: The E-CAT Software Tool

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Economic Consequence Analysis of Disasters: The E-CAT Software Tool Palielināt
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This study develops a methodology for rapidly obtaining approximate estimates of the economic consequences from numerous natural, man-made and technological threats. This software tool is intended for use by various decision makers and analysts to obtain estimates rapidly. It is programmed in Excel and Visual Basic for Applications (VBA) to facilitate its use. This tool is called E-CAT (Economic Consequence Analysis Tool) and accounts for the cumulative direct and indirect impacts (including resilience and behavioral factors that significantly affect base estimates) on the U.S. economy. E-CAT is intended to be a major step toward advancing the current state of economic consequence analysis (ECA) and also contributing to and developing interest in further research into complex but rapid turnaround approaches.

The essence of the methodology involves running numerous simulations in a computable general equilibrium (CGE) model for each threat, yielding synthetic data for the estimation of a single regression equation based on the identification of key explanatory variables (threat characteristics and background conditions). This transforms the results of a complex model, which is beyond the reach of most users, into a "reduced form" model that is readily comprehensible. Functionality has been built into E-CAT so that its users can switch various consequence categories on and off in order to create customized profiles of economic consequences of numerous risk events. E-CAT incorporates uncertainty on both the input and output side in the course of the analysis.
1 Introduction
1(8)
1.1 Objectives
1(1)
1.2 The CREATE Economic Consequence Analysis Framework
2(2)
1.3 Reduced Form Analysis
4(1)
1.4 Overview
5(2)
1.5 Conclusion
7(2)
References
8(1)
2 Enumeration of Categories of Economic Consequences
9(10)
2.1 Introduction
9(1)
2.2 Economic Consequence Categories
9(6)
2.3 Application to the Ebola Virus
15(1)
2.4 Estimating the Numerical Values of Biothreat Impact Categories
16(1)
2.5 Conclusion
17(2)
References
17(2)
3 Threat Scenarios and Direct Impacts
19(12)
3.1 Introduction
19(1)
3.2 Earthquakes
19(7)
3.2.1 Conversion to CGE Drivers
21(1)
3.2.2 Enumeration of Impact Categories
21(5)
3.3 Human Pandemic
26(5)
3.3.1 Scenario
26(1)
3.3.2 Conversion to CGE Drivers
26(2)
3.3.3 Enumeration of Impact Categories
28(2)
References
30(1)
4 Computable General Equilibrium Modeling and Its Application
31(36)
4.1 Summary
31(1)
4.2 CGE Modeling
31(1)
4.3 USCGE Model
32(1)
4.4 CGE Drivers Used to Simulate E-CAT Threats
33(4)
4.5 Detailed CGE Analysis of the Human Pandemic Case
37(30)
4.5.1 Modeling Approaches and Results for Individual Impact Categories
38(6)
4.5.2 Discussion of National Results
44(6)
Appendix 4A Calculation of Input Data for Mild and Severe Influenza Outbreaks
50(6)
4.A.1 Without Vaccination
56(3)
4.A.2 With Vaccination
59(5)
References
64(3)
5 User Interface Variables
67(10)
5.1 Summary
67(1)
5.2 User Interface Variable Identification
67(8)
5.3 Randomized Draws of User Interface Variable Combinations
75(1)
5.4 Conversion of Random Draw Combinations to CGE Inputs
75(2)
References
76(1)
6 Estimation of the Reduced Form Coefficients for the E-CAT User Interface
77(10)
6.1 Random Sampling Procedure
77(3)
6.2 CGE Simulation with Loop Function
80(1)
6.3 Econometric Analysis
81(6)
References
85(2)
7 Uncertainty Analysis
87(12)
7.1 Introduction
87(1)
7.2 Overview
87(1)
7.3 Uncertainty Quantification Tasks
88(1)
7.4 Uncertainty Representation
88(1)
7.5 Uncertainty Propagation
89(2)
7.6 Uncertainty Visualization
91(8)
References
96(3)
8 Validation of Computable General Equilibrium Based Models
99(10)
8.1 Introduction
99(1)
8.2 Validation Criteria and Their Application to CGE Models
99(2)
8.3 Model Testing Procedures and CGE Models
101(2)
8.4 Model Validation Applications
103(6)
8.4.1 In-Sample Validation
103(1)
8.4.2 Cross-Validation Test
104(3)
References
107(2)
9 E-CAT User Interface Tool
109(6)
Appendix A USCGE Model Description 115(16)
Appendix B E-CAT User Guide 131(6)
Appendix C The E-CAT Tool Software 137
Adam Rose: Price School of Public Policy and Center for Risk and Economic Analysis of Terrorism Events (CREATE), University of Southern California Fynnwin Prager: College of Business Administration and Public Policy, California State University, Dominguez Hills Zhenhua Chen: Center for Risk and Economic Analysis of Terrorism Events (CREATE), University of Southern California Samrat Chatterjee: Applied Statistics and Computational Modeling, Pacific Northwest National Laboratory Dan Wei: Price School of Public Policy and Center for Risk and Economic Analysis of Terrorism Events (CREATE), University of Southern California Nathaniel Heatwole: Acumen, LLC Eric Warren: Center for Risk and Economic Analysis of Terrorism Events (CREATE), University of Southern California
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