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NatPar: Natural Parametric Modeling

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  • Hirbod Assa

Abstract

We develop natural parametric (NatPar) insurance as the natural next step from natural-catastrophe (NatCat) modelling: the same hazard-exposure-vulnerability-finance machinery, with a parametric index made contractual in place of indemnity loss adjustment. Our aim is practical - a standard approach inspired by how the catastrophe-insurance industry already operates, not another optimal-contract criterion. This delivers two payoffs. First, it fixes how reporting is formulated: NatPar contracts are reported in the native NatCat language (annual average loss, EP/AEP/OEP curves, return-period levels), complemented with two-sided basis-exceedance diagnostics (BEP+/-) elevated to the central status the EP curve holds for losses - the canonical distributional view of basis risk, not a supplementary number. Second, the same standard shows how the tail is reallocated between insuree and insurer. A frost case study yields the central result: it is about time, not average. Holding a contract AAL-neutral, the bounded payout cannot follow the unbounded exposure tail, so equalising the mean separates over- and under-payment across return periods: the insuree gains at short horizons while the insurer sheds the deep tail past a crossover of several decades. This reverses under tail dependence - when regions reach extremes jointly, bounded payouts stack and the insurer reabsorbs the deep tail.

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  • Hirbod Assa, 2026. "NatPar: Natural Parametric Modeling," Papers 2608.24871, arXiv.org.
  • Handle: RePEc:arx:papers:2608.24871
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    References listed on IDEAS

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    1. Nathaniel D. Jensen & Christopher B. Barrett & Andrew G. Mude, 2016. "Index Insurance Quality and Basis Risk: Evidence from Northern Kenya," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 98(5), pages 1450-1469.
    2. Ghada Elabed & Marc F. Bellemare & Michael R. Carter & Catherine Guirkinger, 2013. "Managing basis risk with multiscale index insurance," Agricultural Economics, International Association of Agricultural Economists, vol. 44(4-5), pages 419-431, July.
    3. Doron Sonsino & Uri Benzion & Galit Mador, 2002. "The Complexity Effects on Choice with Uncertainty — Experimental Evidence," Economic Journal, Royal Economic Society, vol. 112(482), pages 936-965, October.
    4. Doron Sonsino & Marvin Mandelbaum, 2001. "On Preference for Flexibility and Complexity Aversion: Experimental Evidence 1," Theory and Decision, Springer, vol. 51(2), pages 197-216, December.
    5. Raviv, Artur, 1979. "The Design of an Optimal Insurance Policy," American Economic Review, American Economic Association, vol. 69(1), pages 84-96, March.
    6. Bourget, Mathilde & Boudreault, Mathieu & Carozza, David A. & Boudreault, Jérémie & Raymond, Sébastien, 2024. "A data science approach to climate change risk assessment applied to pluvial flood occurrences for the United States and Canada," ASTIN Bulletin, Cambridge University Press, vol. 54(3), pages 495-517, September.
    7. Zhang, Jinggong & Tan, Ken Seng & Weng, Chengguo, 2019. "Index Insurance Design," ASTIN Bulletin, Cambridge University Press, vol. 49(2), pages 491-523, May.
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