Macroeconomic models for predicting indirect impacts of disasters: A review

Interdependencies between critical infrastructures and the economy amplify the effects of damage caused by disasters. The growing interest in impacts beyond physical damage and community resilience has spurred a surge in literature on economic modeling methodologies for estimating indirect economic...

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Main Authors: Tinger Zhu, Charalampos Avraam, Jack W. Baker
Format: Article
Language:English
Published: Elsevier 2025-09-01
Series:Resilient Cities and Structures
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Online Access:http://www.sciencedirect.com/science/article/pii/S277274162500033X
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author Tinger Zhu
Charalampos Avraam
Jack W. Baker
author_facet Tinger Zhu
Charalampos Avraam
Jack W. Baker
author_sort Tinger Zhu
collection DOAJ
description Interdependencies between critical infrastructures and the economy amplify the effects of damage caused by disasters. The growing interest in impacts beyond physical damage and community resilience has spurred a surge in literature on economic modeling methodologies for estimating indirect economic impacts of disasters and the recovery of economic activity over time. In this review, we present a framework for categorizing modeling approaches that assess indirect economic impacts across natural hazards and anthropogenic disasters such as cyber attacks. We first conduct a comparative analysis of macroeconomic models, focusing on the approaches capturing sectoral interdependencies. These include the Leontief Input-Output (I/O) model, the Inoperability Input-Output Model (IIM), the Dynamic Inoperability Input-Output Model (DIIM), the Adaptive Regional Input-Output (ARIO) model, and the Computable General Equilibrium (CGE) model and its extensions. We evaluate their applicability to disaster scenarios based on input data availability, the compatibility of model assumptions, and output capabilities. We also reveal the functional relationships of input data and output metrics across economic modeling approaches for inter-sectoral impacts. Furthermore, we examine how the damage mechanisms posed by different types of disasters translate into model inputs and impact modeling processes. This synthesis provides guidance for researchers and practitioners in selecting and configuring models based on specific disaster scenarios. It also identifies the gaps in the literature, including the need for a deeper understanding of model performance reliability, key drivers of economic outcomes in different disaster contexts, and the disparities in modeling approach applications across various hazard types.
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spelling doaj-art-afe4526e136b43fea1cec6108e5a106f2025-08-20T03:24:56ZengElsevierResilient Cities and Structures2772-74162025-09-014311410.1016/j.rcns.2025.06.003Macroeconomic models for predicting indirect impacts of disasters: A reviewTinger Zhu0Charalampos Avraam1Jack W. Baker2Corresponding author.; Department of Civil and Environmental Engineering, Stanford University, Stanford, CA, United StatesCenter for Urban Science and Progress, New York University, Brooklyn, NY, United StatesDepartment of Civil and Environmental Engineering, Stanford University, Stanford, CA, United StatesInterdependencies between critical infrastructures and the economy amplify the effects of damage caused by disasters. The growing interest in impacts beyond physical damage and community resilience has spurred a surge in literature on economic modeling methodologies for estimating indirect economic impacts of disasters and the recovery of economic activity over time. In this review, we present a framework for categorizing modeling approaches that assess indirect economic impacts across natural hazards and anthropogenic disasters such as cyber attacks. We first conduct a comparative analysis of macroeconomic models, focusing on the approaches capturing sectoral interdependencies. These include the Leontief Input-Output (I/O) model, the Inoperability Input-Output Model (IIM), the Dynamic Inoperability Input-Output Model (DIIM), the Adaptive Regional Input-Output (ARIO) model, and the Computable General Equilibrium (CGE) model and its extensions. We evaluate their applicability to disaster scenarios based on input data availability, the compatibility of model assumptions, and output capabilities. We also reveal the functional relationships of input data and output metrics across economic modeling approaches for inter-sectoral impacts. Furthermore, we examine how the damage mechanisms posed by different types of disasters translate into model inputs and impact modeling processes. This synthesis provides guidance for researchers and practitioners in selecting and configuring models based on specific disaster scenarios. It also identifies the gaps in the literature, including the need for a deeper understanding of model performance reliability, key drivers of economic outcomes in different disaster contexts, and the disparities in modeling approach applications across various hazard types.http://www.sciencedirect.com/science/article/pii/S277274162500033XDisaster indirect impactsMacroeconomic modelsSectoral interdependencies
spellingShingle Tinger Zhu
Charalampos Avraam
Jack W. Baker
Macroeconomic models for predicting indirect impacts of disasters: A review
Resilient Cities and Structures
Disaster indirect impacts
Macroeconomic models
Sectoral interdependencies
title Macroeconomic models for predicting indirect impacts of disasters: A review
title_full Macroeconomic models for predicting indirect impacts of disasters: A review
title_fullStr Macroeconomic models for predicting indirect impacts of disasters: A review
title_full_unstemmed Macroeconomic models for predicting indirect impacts of disasters: A review
title_short Macroeconomic models for predicting indirect impacts of disasters: A review
title_sort macroeconomic models for predicting indirect impacts of disasters a review
topic Disaster indirect impacts
Macroeconomic models
Sectoral interdependencies
url http://www.sciencedirect.com/science/article/pii/S277274162500033X
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