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Strategies for Better Protection against Catastrophic Risks* Howard Kunreuther, Robert Meyer and Erwann Michel-Kerjan Risk Management and Decision Processes Center The Wharton School - University of Pennsylvania
September 2007 Working Paper # 2007-09-14
* Support from NSF grant number CMS-0527598, the Wharton Risk Management and Decision Processes Center, and the Climate Decision Making Center (CDMC) located in the Department of Engineering and Public Policy (cooperative agreement between the NSF (SES-0345798) and Carnegie Mellon University) is gratefully acknowledged.
_____________________________________________________________________ Risk Management and Decision Processes Center The Wharton School, University of Pennsylvania 3730 Walnut Street, Jon M. Huntsman Hall, Suite 500 Philadelphia, PA 19104 USA Phone: 215-898-4589 Fax: 215-573-2130 http://opim.wharton.upenn.edu/risk/ _____________________________________________________________________
CITATION AND REPRODUCTION This document appears as a Working Paper of the Wharton Risk Management and Decision Processes Center, The Wharton School of the University of Pennsylvania. Comments are welcome and may be directed to the authors. This paper may be cited as: Howard Kunreuther, Robert Meyer and Erwann MichelKerjan, “Strategies for Better Protection against Catastrophic Risks,” Risk Management and Decision Processes Center, The Wharton School of the University of Pennsylvania, September 2007. The views expressed in this paper are those of the author and publication does not imply their endorsement by the Wharton Risk Center and the University of Pennsylvania. This paper may be reproduced for personal and classroom use. Any other reproduction is not permitted without written permission of the authors.
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1. Setting the Stage A New Era of Catastrophes Over the past few years, the losses from natural disasters have expanded dramatically in many developed and developing countries. In countries that benefit from warning systems and effective mitigation programs, consequences are often much lower than in emerging economies that are deprived of such capacity. In southeast Asia, the tsunami in December 2004 surprised everyone and killed more than 280,000 people located on the coastal areas in just a few hours. Mitigation measures were almost nonexistent. But even in a country like the United States, which has extensive experience with natural catastrophes, the 2004 and 2005 hurricane seasons demonstrated the lack of adequate loss reduction measures and emergency preparedness capacity to deal with truly large-scale natural disasters. Katrina killed 1,300 people and forced 1.5 million people to evacuate the affected area – a historical record for the country. Economic damages are estimated in the range of US$150 to $200 billion. The three hurricanes (Katrina, Rita and Wilma) that made landfall in the U.S. during 2005 generated nearly $65 billion of private insurance payments and another $20 billion by the Federal National Flood Insurance Program for flood damage – another historical record. Federal relief to the victims of these catastrophes and for local reconstruction is estimated to be over $125 billion – yet another historical record. The 2005 hurricane season, which followed the four major hurricanes that hit Florida in 2004, has demonstrated a new scale of destruction. Will 2008 and 2009 be even worse? These recent catastrophic events are actually part of a trend that has been observed over the past 20 years. As shown in Table 1, all twenty of the most costly events to the insurance industry occurred after 1987. Furthermore, 10 of them occurred since 2001 (bolded in Table 1), 9 here in the United States. We have entered a new era of large-scale risks. With the exception of the terrorist attacks of September 11, 2001, all of the events in the top 20 were natural disasters. More than 80 percent were weather-related events: hurricanes and typhoons, storms, and floods with nearly three-quarters of the claims paid to victims in the United States. As a result of the significant losses insurers experienced from the hurricanes of 2004 and 2005, companies are reexamining whether they want to continue to provide protection against damage from hurricanes. Homeowners’ policies only cover losses due to wind; flood coverage is provided by a separate insurance policy as part of the National Flood Insurance Program. Companies, such as State Farm, have faced lawsuits contending that they were responsible for covering flood losses from Hurricane Katrina for which they claimed they were not liable. For example, the state of Mississippi charged that insurers were responsible for hurricane damage from Katrina due to surging flood waters caused by the wind. Although State Farm eventually won their case, it was a
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costly process and led to their discontinuing selling new policies on homes and small business in the state. 1 Table 1. The 20 Most Costly Insured Catastrophes in the World, 1970-2006 U.S.$ billion (indexed to 2006)
66.32 35.5 22.9 19.0 13.6 12.9 10.4 8.6 8.4 7.4 7.2 7.0 5.5 5.5 4.9 4.9 4.4 4.1 4.1 3.8
Victims Event Hurricane Katrina 9/11 Attacks Hurricane Andrew Northridge Quake Hurricane Ivan Hurricane Wilma Hurricane Rita Hurricane Charley Typhoon Mireille Hurricane Hugo Winterstorm Daria Winterstorm Lothar Hurricane Frances Storms and floods Winterstorm Vivian Typhoon Bart Hurricane Georges Tropical Storm Alison Hurricane Jeanne Typhoon Songda
Year
(Dead or missing)
1,326 3,025 43 61 124 35 34 24 51 71 95 110 38 22 64 26 600 41 3,034 45
2005 2001 1992 1994 2004 2005 2005 2004 1991 1989 1990 1999 2004 1987 1990 1999 1998 2001 2004 2004
Area of primary damage USA, Gulf of Mexico et al USA USA, Bahamas USA USA, Caribbean et al USA, Gulf of Mexico et al USA, Gulf of Mexico et al USA, Caribbean et all Japan Puerto Rico, USA et al France, UK et al France, Switzerland et al USA, Bahamas France, UK et al Western/Central Europe Japan USA, Caribbean USA USA, Caribbean et al Japan, South Korea
Sources: Wharton Risk Center
These actions raise policy issues as to the role of the private and public sectors in providing adequate coverage to potential victims of future natural disasters. They also highlight the importance of defining adequate policies to encourage or require firms and residents in hazard-prone areas to adopt cost-effective mitigation measures to reduce the damage from these catastrophes. The need for homeowners to invest in these lossreduction measures takes on added significance given the influx of individuals into highrisk areas in recent years. Increasing Development in Hazard-Prone Areas In 1950, about 30 percent of the world’s population – then 2.5 billion people – lived in urban areas. This percentage increased to 50 percent in the year 2000, and United Nations’ projections estimate that this will increase to 60 percent of the 8.3 billion people 1
Such a reaction to a disaster has been observed before. For instance, in California following the Northridge earthquake of January 1994, insurers refused to provide earthquake coverage against future damage from quakes, leading to the formation of the state-operated California Earthquake Authority. 2
Including the $20 billion paid for flood coverage by the NFIP.
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world population by 2025. A direct consequence of this trend is the increasing number of so-called mega-cities, with populations above 10 million located in hazard-prone areas. In 1950, New York City was the only such a mega-city. By 2015, there are estimated to be 26 including Tokyo (29 million inhabitants)3, Shanghai (18 million), New York (17.6 million), and Los Angeles (14.2 million inhabitants). This urbanization and increase in population translates into an increased concentration of exposure to natural disasters. The development of Florida for tourism and retirement is an illustrative example. The population of the state has increased significantly over the past 50 years: 2.8 million inhabitants in 1950, 6.8 million in 1970, 13 million in 1990, and a projected 19.3 million residents in 2010 (a nearly 600 percent increase since 1950) With more individuals living in these areas coupled with an increase in property values of their homes, there is a much higher probability of large scale losses from hurricanes and flooding than 15 years ago. If Hurricane Andrew had occurred in 2007 rather than 1992, it would have inflicted more than twice the economic losses than occurred at the time of the disaster. In the same vein, the large 1926 Miami hurricane that hit the state when Florida was largely unpopulated would inflict more than $100 billion of direct economic damage if it were to happen again today (Wharton Risk Center, 2007). While catastrophes are often labeled low-probability/high-consequence events, recent estimates show that in the case of Florida, the likelihood of future mega-disasters is not low anymore. Indeed, according to Risk Management Solutions, one of the leading catastrophe modeling firms, there is a 25 percent probability that one hurricane or a series of hurricanes inflict at least $5 billion of insured losses in Florida next year, and a 15 percent probability that it will be $15 billion. (Wharton Risk Center, 2007). These figures do not come as a surprise if one looks at the concentration of assets in Florida. Today, nearly 80 percent of insured assets in Florida are located near the coast, the area most subject to hurricane damage. This represents nearly $2 trillion of insured exposure ($1.4 trillion for commercial exposure and $900 billion of residential exposure) (Hartwig, 2006). Figures 1-a and 1-b detail the total insured value located on the coast for several states in the U.S. and the insured coastal exposure as a percentage of statewide insured exposure. Figure 1-b shows that five states have more than 50 percent of statewide insured exposure located on the coast and 11 states have more than 25 percent of statewide insured exposure in such high risk areas. In addition to Florida, New York also has nearly $2 trillion of insured values located directly on the coast. Consider the costal insured value for the top 10 states combined (ranked by that variable). That accounts for more than $6.7 trillion. Such huge concentrations of insured value in highly exposed areas almost guarantees that any major storm that hits these regions will inflict billions if not hundreds of billion dollars of economic losses, unless the residential construction and infrastructures are properly protected by effective mitigation measures. For that very reason, mitigation, land use planning and well-enforced building codes are likely to play a key role in reducing future disaster losses given the increasing development in hazardprone areas.
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The experience of the Kobe earthquake in 1995 highlights the potential for real cataclysms in the region. An even bigger quake in Greater Tokyo could inflict economic loss in the range of $1-to-3 trillion.
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The Natural Disaster Syndrome Recent extreme events have highlighted the challenges associated with reducing losses from hurricanes and other natural hazards due to what one of us has termed the natural disaster syndrome (Kunreuther 1996). Before a disaster, many homeowners, private businesses and the public sector do not voluntarily adopt cost-effective loss-reduction measures. Hence the area is highly vulnerable and unprepared should a severe hurricane or other natural disaster occur. The magnitude of the destruction following a catastrophe often leads public sector agencies to provide disaster relief to victims even if the government claimed it had no intention of doing so prior to the event. This combination of underinvestment in protection prior to the event leading to large disaster losses together with the general taxpayer financing some of the recovery can be critiqued on both efficiency and equity grounds. One of the reasons for the natural disaster syndrome relates to the decision processes of individuals with respect to events such as a Category 3 or 4 hurricane or a major earthquake. Prior to a disaster, many individuals perceive its likelihood as sufficiently low that they argue “It will not happen to me.” As a result, they do not feel the need to invest voluntarily in protective measures, such as strengthening their house or buying insurance. It is only after the disaster occurs that these same individuals claim they were sorry they didn’t undertake protective measures. Kydland and Prescott (1977) in their Nobel Prize winning contribution show that a discretionary policy, which may be optimal given the current situation, may not necessarily result in a socially optimal policy in the longer run. As a specific example of this general proposition, the authors note that unless individuals are initially prohibited from locating in a flood plain, it will be very difficult politically to force these people to leave their homes. In making their decisions to locate there, Kydland and Prescott indicate that these individuals believe that the Corps of Engineers will subsequently build dams and levees if enough people choose to build homes there as well. A large number of homeowners then decide to locate in these high hazard areas for that reason, and the Corps of Engineers is forced to invest in flood control projects.
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Figure 1-a. Total Value of Insured Coastal Exposure as of December 2004 (in $ billion; residential and commercial properties)
Figure 1-b. Insured Coastal Exposure as a Percentage of Statewide Insured Exposure as of December 2004 (residential and commercial properties) Sources: Data from AIR Worldwide
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Kunreuther and Pauly (2006) extend the Kydland-Prescott argument by introducing behavioral considerations into the picture. They contend that if individuals underestimate the likelihood of a future disaster,, it may be important to require homeowners to purchase insurance and have well-enforced rules such as land-use regulations and building codes to avoid the large public sector expenditures following these events. To support this point, they provide empirical evidence that many individuals do not even think about the consequences of a disaster until after a catastrophe occurs, and hence do not invest in protective measures in advance of a disaster. After a large-scale flood, earthquake or hurricane, the government provides some financial assistance to aid the recovery of the unprotected victims. There is extensive evidence that residents in hazard-prone areas do not undertake loss prevention measures voluntarily. A 1974 survey of more than 1,000 California homeowners in earthquake-prone areas revealed that only 12 percent of the respondents had adopted any protective measures (Kunreuther et al. 1978). Fifteen years later, there was little change despite the increased public awareness of the earthquake hazard. In a 1989 survey of 3,500 homeowners in four California counties at risk from earthquakes, only 5 to 9 percent of the respondents in these areas reported adopting any loss reduction measures. (Palm et al. 1990). Burby et al. (1988) and Laska (1991) have found a similar reluctance by residents in flood-prone areas to invest in mitigation measures. In the case of flood damage, Burby (2006) provides compelling evidence that actions taken by the federal government, such as building levees, make residents feel safe when, in fact, they are still targets for catastrophes should the levee be breached or overtopped. This problem is reinforced by local public officials who do not enforce building codes and/or impose land-use regulations to restrict development in high hazard areas. If developers do not design homes so that they are resistant to disasters and individuals do not voluntarily adopt mitigation measures, one can expect large scale losses following a disaster, as evidenced by the property damage to New Orleans caused by Hurricane Katrina. Even after the devastating 2004 and 2005 hurricane seasons, a large number of residents had still not invested in relatively inexpensive loss reduction measures with respect to their property, nor had they undertaken emergency preparedness measures. A survey of 1,100 adults living along the Atlantic and Gulf Coasts undertaken in May 2006 revealed that 83 percent of the responders had taken no steps to fortify their home, 68 percent had no hurricane survival kit and 60 percent had no family disaster plan. (Goodnough, 2006). We feel it is necessary to design sustainable policies based on our understanding of how individuals behave with respect to catastrophic risks. The next section discusses in detail why some individuals do not invest in cost-effective mitigation measures while others do. Section 3 proposes long-term insurance and home improvement loans tied to mortgages to induce individuals to invest in cost-effective mitigation measures. We will show that this program, coupled with well-enforced building codes improves both individual and social welfare.
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2. Behavioral Considerations To examine how individuals deal with catastrophic risks, consider the Lowlands, a hypothetical family whose New Orleans home was destroyed by Hurricane Katrina. They have decided to rebuild their property in the same location but are unsure whether they want to invest in a flood reduction measure (e.g. elevate their home, sealing the foundation of the structure and waterproofing the walls).4 If the flood-proofing measure costs $20,000, should they make the investment? On the surface, the problem would seem a natural candidate for cost-benefit analysis (CBA): the Lowlands should flood-proof their home if the long-term expected benefits of protection exceeded the short-term costs. Were the family to attempt such an analysis they would quickly realize that they lack most of the critical information needed to conduct such a CBA in a meaningful way. For example, the future economic benefits of mitigation conditional on a flood is highly uncertain, as it depends not only on the quality of implementation (which is unobservable) but also on future social and economic factors over which the Lowlands have little control, such as whether neighbors make similar investments, or whether federal disaster relief will be made available following a disaster. The decision is further complicated by the timing of the decision; the optimal mitigation policy might be to postpone the investment until the above ambiguities are resolved. In the absence of analytic guidance, how will the Lowlands make the decision? Central to this paper is the hypothesis that individuals often utilize informal heuristics that have proven useful for guiding day-to-day decisions in more familiar contexts—but that are likely to be unsuccessful when applied to the kind of low-probability, high stakes decisions they are now facing. In the sections below we review the range of informal mechanisms that might be used to make mitigation decisions, and discuss how they might explain the widespread lack of investment illustrated above. Budgeting Heuristics The simplest explanation as to why individuals fail to mitigate in the face of transparent risks is affordability. If the Lowland family focuses on the upfront cost of flood-proofing their house and they have limited disposable income after purchasing necessities, there would be little point in undertaking a cost-benefit analysis regardless of its recommendations. Residents in hazard-prone areas have used this argument explicitly as to why they have limited interest in buying insurance voluntarily. In focus group interviews to determine factors influencing decisions on whether to buy flood or earthquake coverage, one uninsured worker responded to the question “How does one decide how much to pay for insurance?” by responding as follows: A blue-collar worker doesn’t just run up there with $200 [the insurance premium] and buy a policy. The world knows that 90 percent of us live from payday to 4
A discussion of alternative flood reduction measures can be found in Laska (1991; ibid) and Federal Emergency Management Agency (FEMA) (1998), Retrofitting: Six Ways to Prevent Your Home from Flooding Washington, DC: Federal Emergency Management Agency, June.
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payday….He can’t come up with that much cash all of a sudden and turn around and meet all his other obligations.” (Kunreuther et al 1978, p. 113)
The budget constraint for investing in protective measures may extend to higher income individuals if they set up separate mental accounts for different expenditures (Thaler, 1999). Under such a heuristic, a homeowner who is uncertain about the costeffectiveness of mitigation might simply compare the price to that which is typically paid for comparable home improvements. Hence, the $20,000 investment may be seen as reasonable affordable by those who frame it as a large improvement similar to installing a new roof, but unaffordable to those who frame it as a repair similar to fixing a leaky faucet. Making mitigation decisions in this manner does not conform to guidelines implied by CBA, but there is evidence from controlled laboratory experiments that it may not be uncommon. For example, in a study that asked individuals why they were only willing to pay a fixed amount for a dead bolt lock when the lease for the apartment was extended from 1 to 5 years, one respondent said, “$20 is all the dollars I have in the shortrun to spend on a lock. If I had more, I would spend more—-maybe up to $50.” (Kunreuther, Onculer and Slovic (1998) p. 284). Similarly, we suspect that some residents in coastal zones are discouraged from buying and installing storm shutters because the cost exceeds that of the window itself—a logical benchmark expenditure. Biases in temporal planning While individuals’ decisions about mitigation are undoubtedly constrained by considerations of affordability, trade-offs between costs and benefits invariably arise at some level. How skilled are people at performing intuitive CBA? The empirical evidence on how individuals make inter-temporal judgments is not encouraging. Although decisions often follow the directional advice of normative theory (such as by valuing temporally distant events less than immediate ones), they frequently depart from those prescribed by rational theories of inter-temporal choice. Moreover, they depart in a way that collectively discourages far-sighted investments in mitigation. To see this, consider the investment problem faced by the Lowlands. For simplicity, suppose that that the family knows that they will be living in their new home for T years, that each year there is a probability pt of a Katrina-like flood in year t, and that should such an event occur the mitigation measures will reduce losses by an amount B. In this case, the decision to mitigate could be made by observing whether the upfront cost (C) of mitigation is less than the discounted stream of benefits; i.e., if T u (C ) t 1 pt u ( B) t (1) where β is the consumer’s discount rate, and u(x) is the consumer’s utility associated with the benefit (B) or cost (C). While simple in its structure, implicit in (1) are a series of rather strong assumptions about how the Lowlands will value costs and benefits over time. Specifically: 1) all future benefits are evaluated vis-à-vis a constant rate of discounting; 10
2) individuals can estimate future probabilities of flooding in year t accurately 3) the utility function is time-invariant. There is ample evidence that violations of these assumptions will be common. In particular, homeowners are likely to overweight short-term cash expenditures, have distorted beliefs about probabilities, and value common outcomes differently over time. The implications of these biases for mitigation decisions will be reviewed in turn. Under-weighing the future. A fundamental feature of human cognition is that we are influenced more by cues that are concrete and immediate than those that are abstract and delayed. To some extent, of course, rational inter-temporal choice theory prescribes that we should give less weight to distant future outcomes, and this prescription is captured by the constant discount rate β in (1). There is extensive experimental evidence, however, showing that human temporal discounting tends to be hyperbolic, where temporally distant events are disproportionately discounted relative to immediate ones. As an example, people are willing to pay more to have the timing of the receipt of a cash prize accelerated from tomorrow to today than from two days from now to tomorrow Loewenstein and Prelec 1992). The implication of hyperbolic discounting for mitigation decisions is that we are asking residents to invest a tangible fixed sum now to achieve a benefit later that we instinctively undervalue—and one that we, paradoxically, hope never to see at all. The effect of placing too much weight on immediate considerations is that the upfront costs of mitigation will loom disproportionately large relative to the delayed expected benefits in losses over time. A homeowner might recognize the need for mitigation, and see it as a worthwhile investment when it is framed as something to be undertaken a few years from now when both upfront costs and delayed benefits are equally discounted. However, when the time arrives to actually make the investment, a homeowner subject to hyperbolic discounting might well get cold feet. This tendency to shy away from undertaking investments that abstractly seem worthwhile is exacerbated if individuals have the ability to postpone investments— something that would almost always be the case with respect to mitigation. A case in point is the relative lack of preparedness demonstrated by the city of New Orleans and FEMA in advance of Hurricane Katrina in 2005. In this case, the consequences of failing to invest in mitigation—such as developing a workable evacuation plan—could not have been more salient or more temporally proximate; just two months prior to the storm the city engaged in a full-scale simulation that graphically demonstrated what would happen should a hurricane of Katrina’s strength hit the city, and the city was moving into the heart of an active hurricane season (Brinkley 2006). Yet, little was done to remedy known flaws in their preparedness plans. The explanation, we suggest, lies in the fact that the investments could be postponed; the natural instincts that policy makers have to not mitigate because of an aversion for short-term costs became easier to rationalize when it was simply a matter of delaying rather than permanently aborting investments. Emergency planners and the New Orleans Mayor’s office were fully aware of the risks the city faced, and publicly announced their intention to invest the resources needed to mitigate them. But these measures were never enacted for the simple reason that the expenditures were always politically more attractive when presented as part of next year’s budget than this year’s. 11
To see this effect more formally, imagine the Lowlands view the future benefits of mitigation not in terms of a constant discounting schedule, but rather by the hyperbolic discounting function 1 / k for t 0 f (t ) t for t 0
(2)
where 0
