Macroeconomic models for predicting indirect impacts of disasters: A review

Abstract

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.

Keywords

Disaster indirect impacts / Macroeconomic models / Sectoral interdependencies

Relevance to resilience

Understanding the indirect economic impact of disasters is critical for designing effective recovery strategies, informing risk reduction interventions, and strengthening economic resilience. We synthesize the main features of macroeconomic models and damage mechanisms that should be considered when modeling disaster impacts across a range of hazard types. This can guide future modelers in appropriate model selection and application by aligning model characteristics with the specific context, data availability, and analytical goals of different disaster scenarios. We also identify key opportunities to improve current modeling approaches and practices, which can enhance the capacity of models to assess economic resilience and comprehend our understanding of risks posed by future disasters.

CRediT authorship contribution statement

Tinger Zhu: Conceptualization, Formal analysis, Methodology, Writing - original draft, Writing - review & editing. Charalampos Avraam: Conceptualization, Formal analysis, Writing - original draft, Writing - review & editing. Jack W. Baker: Supervision, Writing - review & editing.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

This work was supported by the Stanford Graduate Fellowship, the Center for Urban Science and Progress at New York University, and the National Science Foundation under award number CMMI-2053014. The views and opinions expressed in this paper are those of the authors alone.

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