Competitive Pricing, Basis Risk, Take-Up and Affordability: An Equilibrium Comparison of Parametric and Indemnity Insurance
Escalating hurricane losses and insurer retrenchment are increasing interest in alternative risk-transfer mechanisms. This study extends the STARR (Stakeholder-based Tool for the Analysis of Regional Risk) computational equilibrium framework to evaluate how different insurance contract designs perform in a spatially explicit coastal housing market. We compare parametric insurance with traditional indemnity coverage for nearly 300,000 single-family households in eastern North Carolina, solving jointly for pricing, take-up, and insurer equilibrium behavior.
We find that parametric contracts are generally less efficient on a per-dollar-loss basis because of basis risk. However, they become cost-competitive in the highest-risk zones and when indemnity administrative costs rise. Market outcomes reflect adverse selection: households with higher expected losses are more likely to purchase parametric coverage despite its lower loss-matching efficiency, implying that pricing and participation must be determined jointly in equilibrium.
Trigger choice is critical. Wind-based triggers track realized losses substantially better than flood-based triggers, which exhibit larger basis risk and deeper underinsurance. When affordability constraints are incorporated, participation increases overall, but insurer margins compress and optimal reinsurance strategies shift toward earlier attachment.
Overall, parametric insurance emerges as a viable complement to indemnity coverage, particularly as a mechanism for rapid post-disaster liquidity, rather than a universal substitute.
Bio: Linda Nozick earned a Ph.D. in systems engineering from the University of Pennsylvania and is a professor in the School of Civil and Environmental Engineering at Cornell University. She is a recipient of the NSF Career Award and a Presidential Early Career Award for Scientists and Engineers (PECASE) and was appointed twice by President Barack Obama to the U.S. Nuclear Waste Technical Review Board (NWTRB). Her research develops mathematical and computational models to support decisions in complex, often networked infrastructure systems. Her work spans transportation, electric power system resilience, and natural hazard risk, with a focus on how uncertainty, behavior, and policy shape outcomes in real-world markets and networks. She blends optimization, simulation, and equilibrium modeling to design and evaluate infrastructure investments, operational strategies, and risk-transfer mechanisms. Recent research examines coastal hazard risk and insurance market design, including parametric products, affordability, and reinsurance, and advances tools such as STARR to support regional risk analysis and policy evaluation. Across these areas, she is committed to translating rigorous modeling into actionable insights for planners, utilities, insurers, and policymakers.