[Paper Review] When does a disaster become a systemic event? Estimating indirect economic losses from natural disasters

Sebastian Poledna, Stefan Hochrainer‐Stigler+9 more|arXiv (Cornell University)|Jan 29, 2018

Complex Systems and Time Series Analysis19 citations

TL;DR

This paper proposes a novel integrated model combining a probabilistic flood damage catastrophe model with a large-scale macroeconomic agent-based model (ABM) to estimate indirect economic losses from natural disasters. By simulating millions of economic agents using detailed national data, it reveals that disasters exceeding 5% of capital stock trigger irreversible economic decline, with short-term growth boosts from reconstruction outweighed by long-term losses beyond a resilience threshold.

ABSTRACT

Reliable estimates of indirect economic losses arising from natural disasters are currently out of scientific reach. To address this problem, we propose a novel approach that combines a probabilistic physical damage catastrophe model with a new generation of macroeconomic agent-based models (ABMs). The ABM moves beyond the state of the art by exploiting large data sets from detailed national accounts, census data, and business information, etc., to simulate interactions of millions of agents representing \\emph{each} natural person or legal entity in a national economy. The catastrophe model introduces a copula approach to assess flood losses, considering spatial dependencies of the flood hazard. These loss estimates are used in a damage scenario generator that provides input for the ABM, which then estimates indirect economic losses due to the event. For the first time, we are able to link environmental and economic processes in a computer simulation at this level of detail. We show that moderate disasters induce comparably small but positive short- to medium-term, and negative long-term economic impacts. Large-scale events, however, trigger a pronounced negative economic response immediately after the event and in the long term, while exhibiting a temporary short- to medium-term economic boost. We identify winners and losers in different economic sectors, including the fiscal consequences for the government. We quantify the critical disaster size beyond which the resilience of an economy to rebuild reaches its limits. Our results might be relevant for the management of the consequences of systemic events due to climate change and other disasters.

Motivation & Objective

• To address the scientific gap in estimating indirect economic losses from natural disasters, which are currently unreliable and inconsistent.
• To develop a high-resolution simulation framework that links environmental hazards with macroeconomic outcomes at the level of individual agents.
• To quantify the threshold size of disaster damage beyond which economic resilience is lost and long-term growth is dominated by direct losses.
• To identify sector-specific winners and losers, including fiscal impacts on government, across different disaster magnitudes.
• To provide actionable insights for post-disaster management and climate resilience planning under increasing disaster frequency.

Proposed method

• A copula-based probabilistic model estimates spatially dependent flood losses across Austria, capturing local hazard dependencies.
• A damage-scenario generator translates physical damage estimates into targeted shocks to individual agents (households, firms, government) in the ABM.
• The ABM simulates interactions among 10 million agents representing individuals and legal entities, using detailed national accounts, census, and business data.
• The model is calibrated to Austria’s 2013 economy and simulates time series of GDP, consumption, investment, and inflation with high fidelity.
• Indirect economic effects are measured as deviations in GDP from a baseline scenario, isolating losses and gains from reconstruction.
• Simulations are executed on a high-performance supercomputer to handle the computational load of large-scale agent interactions.

Experimental results

Research questions

• RQ1 At what level of direct physical damage does a disaster transition from a localized event to a systemic economic shock?
• RQ2 How do indirect economic effects—both losses and gains—vary with disaster size, particularly in the short, medium, and long term?
• RQ3 What is the critical threshold of capital destruction beyond which economic resilience is lost and recovery becomes unsustainable?
• RQ4 Which economic sectors and agents experience the greatest gains or losses following a disaster, and how does this affect government fiscal capacity?
• RQ5 To what extent do reconstruction-driven multiplier effects offset initial economic contractions in the aftermath of large-scale disasters?

Key findings

• Moderate disasters induce small but positive short- to medium-term indirect economic effects, while long-term impacts are negative.
• Large-scale disasters trigger immediate and sustained negative economic responses, despite a delayed positive stimulus from reconstruction activities.
• A critical threshold exists at approximately 5% of total capital stock destruction, beyond which economic resilience collapses and recovery is no longer viable.
• The temporary economic boost from reconstruction occurs with a delay of at least one quarter, following initial capital and income losses.
• The model identifies clear winners and losers across sectors, with significant fiscal implications for government due to changes in tax revenue and public spending.
• The study demonstrates for the first time a quantitative, data-driven link between physical disaster size and systemic economic outcomes using a full-scale ABM.