Deciding Whether to Invest in Mitigation Measures: Evidence From Florida

Published date01 June 2013
DOIhttp://doi.org/10.1111/j.1539-6975.2012.01484.x
AuthorKathleen A. McCullough,James M. Carson,David M. Pooser
Date01 June 2013
C
The Journal of Risk and Insurance, 2013, Vol. 80, No. 2, 309-327
DOI: 10.1111/j.1539-6975.2012.01484.x
DECIDING WHETHER TO INVEST IN MITIGATION
MEASURES:EVIDENCE FROM FLORIDA
James M. Carson
Kathleen A. McCullough
David M. Pooser
ABSTRACT
Prior research provides theoretical insight into factors likely to impact the
decision to mitigate such as the degree of risk aversion, the cost of market
insurance, and the cost of self-insurance. We provide empirical evidence re-
lated to several hypotheses from the self-insurance literature on the decision
to mitigate.
INTRODUCTION
Property damage caused by natural disasters has increased dramatically over time,
both in the United States and globally. Worldwide since 2000, economic losses from
natural disasters total more than $600 billion ($300 billion insured), principally as
a result of the 2004, 2005, and 2008 hurricane seasons (see Kunreuther and Michel-
Kerjan, 2009).1
As discussed by Ehrlich and Becker (1972), two types of mitigation to reduce the
potential loss to property are self-protection (which aims to reduce the frequency
of loss, such as relocating from a hurricane-prone area) and self-insurance (which
aims to reduce the severity of loss, such as installing hurricane shutters on a home).
Because mitigation via relocation often is not a viable option, we focus on mitigation
associated with reducing loss severity, that is, self-insurance.
James M. Carson is Daniel P. Amos Distinguished Professor of Insurance, Terry College of
Business, University of Georgia. He can be contacted via e-mail: jcarson@uga.edu. Kathleen A.
McCullough is State Farm Insurance Professor of Risk Management and Insurance, College of
Business, Florida State University.David M. Pooser is Assistant Professor of Risk Management
and Insurance at St. John’s University’s School of Risk Management. Support for this research
is gratefully acknowledged from the Florida Catastrophic Storm Risk Management Center.The
authors thank the editor and the anonymous referees for helpful comments. The authors also
thank Pat Maroney,Lori Medders, Chuck Nyce, and Harris Schlesinger, as well as participants
at presentations at the Southern Risk and Insurance Association meeting and at the University
of Georgia for their comments. All errors are, of course, the responsibility of the authors.
1This increase in property values at risk and property damage in the United States is especially
true for coastal states. See the Insurance Information Institute’s website for details on some of
the catastrophes that have caused the largest insured losses.
309
310 THE JOURNAL OF RISK AND INSURANCE
Prior research has focused on theoretical aspects of the decision to mitigate (e.g.,
Ehrlich and Becker, 1972; Dionne and Eeckhoudt, 1985; Kelly and Kleffner, 2003).2
While these studies have provided a strong theoretical framework for decisions to
mitigate, research in this area often has been limited by the lack of available data for
empirical testing.3We contribute to this literature by providing empirical evidence
related to several hypotheses on the decision to mitigate. These include the risk aver-
sion hypothesis (e.g., Dionne and Eeckhoudt, 1985), which suggests that higher levels
of risk aversion lead to a higher likelihood of mitigation as well as more extensive
mitigation measures once the decision is made; the substitution hypothesis, which
suggests that self-insurance and market insurance are substitutes (e.g., Ehrlich and
Becker, 1972; Briys and Schlesinger, 1990); and the preservation hypothesis, which
suggests that individuals will seek to preserve and protect both their home and those
residing in their home through self-insurance measures.4We also examine various
hypotheses associated with factors impacting the mitigation decision, including char-
acteristics of the homeowner,potential premium reductions, and the behavior of other
homeowners in the area, outlined below.
Our unique data set has a large, heterogeneous pool of individuals (with respect
to risk, income, and risk aversion) participating in a state-based program for home
mitigation. As a preview of the results, we find empirical support for each of the
hypotheses related to self-insurance behavior. From a public policy perspective, this
research provides insight on characteristics of homeowners who are morelikely to re-
spond to mitigation incentives, which is an area especially important for policymakers
and regulators.
The article is organized as follows. In the next section we discuss our sample, data,
and hypotheses, followed by a description of the methodology. We then present and
discuss the results from our empirical analysis, and in the final section we summarize
and conclude the article.
DATA,SAMPLE,AND HYPOTHESES
Data and Sample
The sample is based on a large database of homes with varying exposure to catas-
trophes related to the My Safe Florida Home (MSFH) program.5The database
contains records of home inspections, grant applications, mitigation expenditures,
2Several other findings from theoretical work are discussed in the hypotheses section below.
3Empirical studies in this area include Peacck (2003) and Peacock, Brody, and Highfield (2005)
who use survey data to observe mitigation expenditures and risk perception. Cicchetti and
Dubin (1994) measure levels of risk aversion and self-insurance using data on telephone
line insurance contracts. We are aware of no other studies that explicitly observe and test
hypotheses on mitigation expenditures or on the propensity to mitigate.
4As discussed later, this hypothesis is drawn from several studies including Kleindorfer and
Kunreuther (1999), Kunreuther and Kleffner (1992), Kunreuther (2006), and Lee (1998).
5The program aimed to help Floridians identify potential weaknesses in their homes and
make structural improvements to strengthen their homes by providing funding for free home
hurricane mitigation inspections and subsidized home improvement grants. Funding was
providedfor up to 400,000 inspections and at least 35,000 grants. The inspections were available
to any homeowner living in a single-family home. The grants were available to homeowners
for qualifying expenses in homes with insured values up to $300,000. Mitigation grants were

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