Paper: arXiv 2506.18895

Authors: Fallou Niakh, Arthur Charpentier, Caroline Hillairet, Philipp Ratz

Abstract

We consider an economy composed of different risk profile regions wishing to be hedged against a disaster risk using multi-region catastrophe insurance. Such catastrophic events inherently have a systemic component; we consider situations where the insurer faces a non-zero probability of insolvency. To protect the regions against the risk of the insurer’s default, we introduce a public-private partnership between the government and the insurer. When a disaster generates losses exceeding the total capital of the insurer, the central government intervenes by implementing a taxation system to share the residual claims. In this study, we propose a theoretical framework for regional participation in collective risk-sharing through tax revenues by accounting for their disaster risk profiles and their economic status.

Complexity vs Empirical Score

  • Math Complexity: 7.0/10
  • Empirical Rigor: 3.0/10
  • Quadrant: Lab Rats — theoretically deep, empirically untested

Why this score: The paper provides a strong, mathematically rigorous economic theoretical framework for disaster risk sharing using utility theory and taxation mechanisms. However, it lacks empirical backtesting or real-world data validation, relying instead on algorithmic and numerical simulations to illustrate its theoretical properties.

Research Flowchart

  flowchart TD
    A["Research Goal: Design regional DRF framework via public-private risk-sharing & taxation"] --> B["Inputs: Regional Risk Profiles, Economic Status & Insurer Capital"]
    B --> C["Model Insurer Default Risk & Systemic Disaster Losses"]
    C --> D["Design PPP Mechanism: Insurer covers capital; Government taxes residual losses"]
    D --> E["Formulate Taxation & Collective Risk-Sharing Optimization"]
    E --> F["Outcomes: Equitable tax-based risk-sharing framework protecting against insurer insolvency"]

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1 of 58 cited works are in the corpus; resolved via arXiv source bundles, Semantic Scholar and OpenAlex. Corpus-wide: 2518 linked papers.