Capitalization of Flood Insurance and Risk Perceptions in Housing Prices: An Empirical Agent‐Based Model Approach

Abstract

Federally regulated or insured lenders in the United States are mandated to require flood insurance on properties that are located in areas at high risk of flooding. Despite the existence of this mandatory flood insurance requirement, take‐up rates for flood insurance have been low, and the federal government's exposure to uninsured property losses from flooding remains substantial. Meanwhile, the value of capital at risk varies significantly with flood events and changing risk perceptions, which necessitates mechanisms that stabilize these dynamics. In this article we discuss how a scenario of complete insurance uptake, under various risk attitudes, affects the value of properties in the 100‐year and 500‐year flood zones. Our results indicate that an increase in flood insurance uptake may provide such a mechanism by lowering the value of capital at risk in the flood zone consistently, independent of homeowners' risk attitudes. We apply an empirical adaptive agent‐based model to examine the capitalization of insurance costs, risk premiums, and their interaction in housing prices. Our approach combines widely‐used empirical hedonic analysis with the computational economic framework. We highlight the usefulness of our method in capturing the marginal implicit price of homeowners' preferences that may change over time and separately assess the effect of various factors and policies on property values, illustrating the agent‐based modeling as a valuable complement to traditional hedonic analysis.