Valuing Mitigation: Real Estate Market Response to Hurricane Loss Reduction Measures

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1. Introduction Insurance companies have been hit hard in the last few years by claims from policyholders because of weather-related hazards such as floods and windstorms. Insured losses from Hurricane Andrew approached $16 billion (IIPLR 1995). However, estimates of potential damage for a storm like Andrew increase to $50 billion if the storm had hit Miami directly. These losses have prompted insurance companies, as well as state insurance boards, to explore incentives to property owners to install better protection for their property and demand construction techniques that minimize damage from storms. The Federal Emergency Management Agency (FEMA) has recently initiated programs to encourage voluntary mitigation by individuals as well as communities. The general consensus by disaster experts has been that home owners will not voluntarily adopt disaster mitigation measures.1 An early paper by Ehrlich and Becker (1972) (hereafter EB) provides a theoretical basis for evaluating mitigation decisions. The authors distinguish between two forms of mitigation: self-insurance and self-protection. The difference between these two terms is subtle but important. A self-insurance type of mitigation investment reduces the damage from a disaster but does not affect the probability of the disaster. In contrast, a selfprotection type of mitigation investment reduces the probability that the disaster will occur. Previous hedonic studies of household disaster mitigation, including those cited in this paper, have focused on self-protection. The agent is willing to pay more for a home that is located in a less dangerous area with lower associated probability of a hit. EB show that market insurance and self-insurance logically serve as substitutes. When market insurance is offered at an actuarially fair rate, there is no financial incentive to adopt self-insurance.2 Fronstin and Holtmann (1994, p. 388) provide evidence that supports this hypothesis. By examining the pattern of damage due to Hurricane Andrew, they find that newer homes suffered proportionately more damage than older homes. As an explanation of their findings, they hypothesize that consumers have substituted homeowners insurance for structurally sound homes that are built to withstand Our study focuses on the value of a self-insurance type of mitigation in a location with a given historical probability of the disaster. The purpose of this study is to examine market price sensitivity of buyers to mitigation on existing homes. This information can assist policymakers in identifying effective incentives and provide necessary information to buyers in terms of the risk inherent with one property versus another. Our goal is to examine resale market price effects of voluntary mitigation measures taken by home owners to protect their property using market price data from a coastal city that is vulnerable to tropical storms and hurricanes. This paper is organized as follows. A short review of the relevant literature is outlined in the next section. This is followed by a description of our data set and the construction of a wind engineering-based structural integrity index. Next we specify the two models to be tested, one model with storm blinds as the mitigation focus variable and the second a construction index model that uses the structural integrity index. We then report results for both models and finish with conclusions and proposed extensions. 2. Review of Literature In a classic paper, EB examine a static model of insurance demand using a state preference approach. They consider market insurance and two forms of risk mitigation. Mitigation efforts can reduce the size of the loss or reduce the probability of the loss. The form that they call self-insurance reduces the size of a loss. Reducing the probability of the loss is referred to as self-protection. Some key results are the following: (i) The incentive to self-insure (loss-reducing mitigation), unlike the incentive to use market insurance, is smaller for rare losses. …