Economic impacts of natural hazards and complexity science: A critical review

Extreme natural hazards represent, together with crises and wars, the most disruptive phenomena for economic activity. Their economic impact has been shown to be remarkable, long-lasting, and growing over time, though the exact mechanisms at stake are challenging to isolate and quantify. As these trends are likely to endure as global warming becomes more severe, the need for appropriate modeling of both short and long-run impacts of natural disasters is becoming increasingly pressing. Building on a mounting number of empirical works, we here provide a critical review of the modeling approaches traditionally employed in the related literature. Although with notable exceptions, conventional methods are generally based on Input-Output or Computational General Equilibrium models. These approaches, while analytically sound, are structurally ill-suited to capture certain aspects of natural hazard consequences. Systemic responses to such extreme events are typically characterized by complex interactions among heterogeneous agents, adaptive behavior, and out-of-equilibrium dynamics. We here argue that complexity methods can represent a valid alternative to bridge this policy-relevant gap. In particular, Agent-Based Models offer a powerful toolkit to account for non-linear geographical and temporal interdependencies, the presence of hysteresis and path dependency, the impact of technology changes, and can be fruitfully employed as laboratories for adaptation and mitigation policies.