Erik HeitfieldThis paper examines how model uncertainty affects the price of catastrophe risk insurance. We use unique data on expected loss rate projections from seven hurricane risk models approved by regulators for use in Florida property insurance rate setting to quantify model uncertainty. By combining these data with newly published information on local property insurance markets, we are able to empirically test the relationship between model uncertainty and insurance premiums across Florida ZIP codes and over time. Controlling for confounding variables and time-invariant latent factors that may be correlated with observed variables, we find strong empirical support for the hypothesis that greater dispersion among model forecasts leads to higher homeowners insurance premiums. Our findings suggest that, had model dispersion been ten percent lower than that observed in 2021, a typical Florida homeowner would have saved $50 to $90 on her annual homeowners insurance premium.
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