Learning from Catastrophes:
Overcoming Myopia through Private-Public Partnerships
Howard C. Kunreuther
kunreuther@wharton.upenn.edu
Risk Management and Decision Processes Center
The Wharton School, University of Pennsylvania
http://opim.wharton.upenn.edu/risk
Presentation at
NCAR Colloquium on Statistical Assessment
of Extreme Weather Phenomena under Climate Change
June 6, 2011
80
Total number of declarations
70
Declarations associated with floods
60
50
40
30
20
10
0
Summary of Key Points
Individuals focus on short-term horizons
• Want immediate return from their adaptation measures
• Often regard potential disasters as below their threshold of
concern
Impact of this behavior
• Failure to invest in adaptation measures prior to a disaster
• Cancel insurance if one doesn’t make a claim for a few years
Proposed strategy
• Well-enforced long-term contracts
• Short-term economic incentives to deal with myopia
2
LEARNING FROM CATASTROPHES
STRATEGIES FOR REACTION AND RESPONSE
2010 – Financial Times Press
AT WAR WITH
THE WEATHER
2009 – MIT Press
Twenty-two of the world’s leading experts in
risk management and disaster recovery identify
the factors that can trigger low-probability,
high-consequence events.
Better understanding how individuals decide whether or not
to protect themselves against natural disasters.

Operating principles that can reduce severe risk
and enhance readiness and resilience.
Key lessons from the financial management of natural
disasters to be applied to other global risks such as
pandemics, financial crises and terrorism.

Written in collaboration with the World Economic
Forum’s Global Agenda Council on Mitigation of
Natural Disasters.

A set of guiding principles for using insurance to deal more
effectively with these events.
Ideas for the private sector, and sustainable public policy
solutions to protect trillions of dollars of assets and the
residents at risk in hazard-prone regions.
Outline of Talk
Part 1: Linking Risk Assessment and Risk Perception with Risk
Management: A Conceptual Framework for Studying Risk
1.
2.
3.
Risk Assessment and Vulnerability Analysis
Risk Perception and Choice
Risk Management Strategies
Part 2: Managing Catastrophic Risks in an Uncertain World
1. A New Era of Catastrophes
2. Benefits of Adaptation Measures and Role of Insurance
3. Strategies for Promoting Adaptation Measures
4. Future Research
5. Summary
4
A Conceptual Framework for Studying Risk
Risk Assessment
& Vulnerability
Analysis
Risk Perception and
Choice
Modeling
of Risks
Public Perceptions
Expert/Layperson Differences
Risk Communication
Statistical
Data Building
Scenarios
Risk Management Strategies
Public-Private Partnerships
5
A Conceptual Framework for Studying Risk
Risk Management Strategies:
Public-Private Partnerships
Information Provision
Incentives
Regulation
Standards
Compensation
Insurance
Liability
Evaluation of Strategies
Impact on Society
Impact on Interested Parties
6
1. Risk Assessment and Vulnerability Analysis
Risk Assessment
– Encompasses estimates of both the chances of a specific set of events
occurring and their potential consequences
– Experts differ in their estimates of the risk
– Find your favorite expert to support your position
Vulnerability Analysis
– Characterize forms of physical, social, political, economic, cultural,
and psychological harms to which individuals and modern societies
are susceptible
– Millions of dollars have already been spent to reduce our vulnerability
Constructing Scenarios
– What are the probabilities of specific events?
– What are the potential consequences?
7
Risk Assessment Questions to Ponder
• What are the chances that New Orleans will have a
Category 3 or higher hurricane in the next 5 years, and
what would be the resulting damage and health impacts?
• What are the chances that there will be another severe oil
spill in the U.S. in the next 5 years and what would be the
health and environmental impacts?
• What is the likelihood of a severe nuclear power accident
somewhere in the United States in the next 10 years, and
what would be the resulting impacts?
• What are the chances that there will be a smallpox epidemic
in the United States in the next five years, and how many
people would be affected?
8
MDR (%)
Modeling Catastrophic Risks
Windspeed
Hazard
Module
Exposure
Module
Vulnerability
Module
Financial
Module
L
O
S
S
 A method to
 The exposure at  Estimating the loss  The financial module
performs the
characterize the
risk – in other
levels given a
convolution of these
hazard in some
words, the
certain magnitude
first three elements
probabilistic
structures that
of hazard
and allows one to
manner
may be damaged  Typically mean loss
create loss estimates
 Magnitude of the  May be a single
ratio given a hazard
that have a certain
event vs. annual
structure, or a
level
probability of
return period
collection of
exceedance
structures
9
Using Exceedance Probability Curves to Depict Risk
Uncertainty in
Probability
Uncertainty in
Loss
Probability
p(L) that losses
will exceed L
95%
Mean
5%
Loss, L (in dollars)
10
Risk Assessment and Vulnerability Analysis
Open Issues and Questions
• How accurately can experts estimate the likelihood and consequences of
damage, injuries and fatalities from disasters of different magnitudes
and intensities?
• Can one characterize the types of uncertainties that currently exist in
assessing risk and suggest ways to improve these estimates in the future?
• What are the expected costs and benefits of undertaking specific riskreducing measures in disaster-prone areas and can one rank them on the
basis of cost effectiveness?
• What are the interdependencies in the system (e.g., infrastructure
damage affecting supply of electricity, water,
telephone/telecommunications, and other services to residences and
businesses) and what are their impacts on indirect damage, health and
environment?
11
2. Risk Perception and Choice
Basic Concepts
• Individuals exhibit systematic biases in processing information
and making choices
– Estimating likelihood of event is influenced by salience
– “It cannot happen to me” before a crisis or disaster occurs
– “It will happen to me” immediately after a crisis or disaster
– “I don’t have to worry” a few months after a crisis or disaster
• Individuals have difficulties learning due to biases and
information processing limitations
12
Explain this behavior:
• I bought my first set of battery cables only after my car
wouldn’t start and I had to be towed. The towing charge was
twice as much as the cost of the battery cables.
• Most homeowners in California purchase earthquake
insurance only after they experienced a quake. When asked
whether the probability of a future event was more likely
than before the disaster most people responded “Less likely.”
• Until seat belt laws were instituted in the United States, most
drivers refused to wear them. When asked why they did not,
a typical response was, “I won’t have an accident.” This
response is consistent with the well-documented finding that
90% percent of all drivers feel they are better than the
average driver.
13
Risk Perception and Choice
Open Issues and Questions
• What role do perceived likelihoods and resulting consequences play
in how people view a particular risk that they may face, such as a
severe hurricane or a flu pandemic?
• How important are emotional factors such as fear, dread and anxiety
in how people perceive these risks and learn over time?
• What role do social networks and social norms play in influencing
risk perception, choice, and learning with respect to low probability
events?
• How can one best communicate information to those at risk so they
are aware of what actions they can take prior to and after a crisis or
disaster?
• What is the role of past experience and the media in influencing risk
perception and choice?
14
3. Risk Management Strategies
Basic Concepts
Policy options for reducing losses and aiding recovery process
–
–
–
–
Economic incentives
Insurance
Well-enforced regulations and standards (e.g., building codes)
Assistance following a disaster or crisis
Relevant roles of public and private sectors in implementing
hazard management strategy
Criteria for evaluating alternative strategies
– Efficiency -- allocating resources to maximize social welfare
– Equity -- concern with fairness and distribution of resources
15
Risk Management Strategies
Open Issues and Questions
• What type of economic incentives would encourage individuals to mitigate the
risks of a disaster and purchase insurance prior to a disaster?
• How does the prospect of federal aid to victims affect protective decisions by
individuals prior to a disaster?
• What are the appropriate roles of standards and regulations in reducing losses
from large-scale disasters?
• What types of financial backstops should be provided by the public sector at
the state and federal levels for dealing with catastrophic losses following future
disasters?
• How can one link different policy tools such as information provision,
economic incentives, insurance, third party inspections, regulations and
standards to achieve the desired objectives of a hazard management strategy?
16
Outline of Talk
Part 1: Linking Risk Assessment and Risk Perception with Risk
Management: A Conceptual Framework for Studying Risk
1.
2.
3.
Risk Assessment and Vulnerability Analysis
Risk Perception and Choice
Risk Management Strategies
Part 2: Managing Catastrophic Risks in an Uncertain World
1. A New Era of Catastrophes
2. Benefits of Adaptation Measures and Role of Insurance
3. Strategies for Promoting Adaptation Measures
4. Future Research
5. Summary
17
1. A New Era of Catastrophes
A radical change in the scale and rhythm of catastrophes
Natural disasters have caused large numbers of fatalities and destruction
in recent years
• Honshu Earthquake (March 2011): Over 10,000 fatalities, 17,000 missing;
estimated damage $183 billion (3% of Japan’s GDP)
• Sichuan Earthquake (May 2008): 70,000 fatalities and 5 million residents homeless
• Hurricane Katrina (Sept. 2005): $81 billion in damage and 1836 fatalities
• Hurricane Ivan (Grenada, Sept. 2004): $889 million in damage (365% of GNP)
Victims complain about receiving substantially less than
the actual costs to repair or rebuild their damaged structures
Public sector and international organizations
(e.g., World Bank) are committed to providing
financial assistance to aid the victims of disasters
18
It’s Been a Busy 17 Months
January 2010:
7.0 Earthquake, Haiti
230,000 Killed, 1,000,000 Homeless
February 2010:
8.8 Quake, Chile
486 Dead, $7Bn Insured Losses
April 2010:
Iceland Volcanic Eruption
Cost to Airlines of Suspension of
European Air Travel: $1.7Bn
May 2010:
Deepwater Horizon spills
5 million barrels of crude in Gulf
Cost to BP to Date: $10Bn
May-July 2010:
Worst Floods in a Decade in China
3,200 dead, 15 million
evacuated,
1.36 million houses destroyed,
$30Bn property damages
November 2010:
Bombing attempt discovered
25
March 2011:
Japan Earthquake, Tsunami, and
Radiation from Nuclear Power Plant
May 2011: Joplin, MO Tornado
Deadliest tornado since 1950
$1-3 billion in damage
Worldwide Evolution of Catastrophes, 1980-2010
Natural catastrophes worldwide 1980 – 2010
Overall and insured losses with trend
(bn US$)
300
250
200
150
100
50
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
Overall losses (in 2010 values)
Insured losses (in 2010 values)
Trend overall losses
Trend insured losses
© 2011 Münchener Rückversicherungs-Gesellschaft, Geo Risks Research, NatCatSERVICE – As at January 2011
2006
2008
2010
Twenty-Five Most Costly Insured Catastrophes Worldwide, 1970–2010
(15 here in the U.S., 11 of these since 2001)
$ BILLION
EVENT
VICTIMS (DEAD OR MISSING)
YEAR
AREA OF PRIMARY DAMAGE
48.6
Hurricane Katrina
1,836
2005
USA, Gulf of Mexico, et al.
37.0
9/11 Attacks
3,025
2001
USA
24.8
Hurricane Andrew
43
1992
USA, Bahamas
20.6
Northridge Earthquake
61
1994
USA
17.9
Hurricane Ike
348
2008
USA, Caribbean, et al.
14.8
Hurricane Ivan
124
2004
USA, Caribbean, et al.
14.0
Hurricane Wilma
35
2005
USA, Gulf of Mexico, et al.
11.3
Hurricane Rita
*
*
*
*
34
2005
USA, Gulf of Mexico, et al.
9.3
Hurricane Charley
*
24
2004
USA, Caribbean, et al.
9.0
Typhoon Mireille
51
1991
Japan
8.0
Maule earthquake (Mw: 8.8)
562
2010
Chile
8.0
Hurricane Hugo
71
1989
Puerto Rico, USA, et al.
7.8
Winter Storm Daria
95
1990
France, UK, et al.
7.6
Winter Storm Lothar
110
1999
France, Switzerland, et al.
6.4
Winter Storm Kyrill
54
2007
Germany, UK, NL, France
5.9
Storms and floods
22
1987
France, UK, et al.
5.9
Hurricane Frances
38
2004
USA, Bahamas
5.3
Winter Storm Vivian
64
1990
Western/Central Europe
5.3
Typhoon Bart
26
1999
Japan
4.7
Hurricane Georges
600
1998
USA, Caribbean
4.4
Earthquake (Mw: 7.0)
0
2010
New Zealand
4.4
Tropical Storm Alison
41
2001
USA
4.4
Hurricane Jeanne
3,034
2004
USA, Caribbean, et al.
4.1
Typhoon Songda
45
2004
Japan, South Korea
3.8
Storms
45
2003
USA
*
*
*
*
*
*
Quiz
How much insured value is located on the
coasts from Texas to Maine
(residential and commercial)?
(1)$1 Trillion
(2)$2 Trillion
(3)$5 Trillion
(4)$10 Trillion
30
US Exposure to Natural Catastrophes
Insured Exposure on the Coasts
(Texas to Maine as of Dec. 2007):
$10 trillion
31
What’s Happening?
The Question of Attribution
Higher degree of urbanization
Huge increase in the value at risk
Population of Florida
2.8 million inhabitants in 1950 -- 6.8 million in 1970 -- 13 million in 1990
19.3 million population in 2010 (590% increase since 1950)
Cost of Hurricane Andrew in 2004 would have been $120bn
Weather patterns
Changes in climate conditions and/or return to a high hurricane cycle?
More intense weather-related events coupled with
increased value at risk will cost more, much more.
What will 2011 bring?
32
2. Benefits of Adaptation Measures and Role of Insurance
Effects of Mitigation on a 500 Year Event
Data on Reduction in Losses from 500-Year Hurricanes in U.S.
180
$160 billion loss
160
140
$82 billion saving with
Adaptation measures in place
Losses (Billions)
120
100
Savings from Mitigation
Remaining Losses
80
60
40
20
0
FL
NY
SC
State
TX
33
Six Climate Scenarios Studied
Model A
Model Type
Statistical Model
Description
An upper-bound projection of future hurricane activity using a statistical
model that represents only the effects of increases in sea surface
temperatures on hurricane activity and uses an upper-bound forecast of
future sea surface temperature from the IPCC model ensemble
(Ranger and Niehorster (2011) scenario name: Abs_SST_max)
Model B
Dynamical Model
Based on a dynamical-model based forecast of future hurricane activity
from Bender et al. 2010 using the global climate model (GCM) GFDLCM2.1.
Model C
Dynamical Model
As above, using MRI-CGAM (Bender et al. 2010)
Model D
Dynamical Model
As above, using MPI-ECHAM5 (Bender et al. 2010)
Model E
Dynamical Model
As above, using UKMO (Bender et al. 2010)
Model F
Statistical Model
A lower-bound projection of future hurricane activity using a statistical
model that represents the effects of changes in the relative sea surface
temperature of the Atlantic Basin. It uses a lower-bound forecast from the
IPCC ensemble
(Ranger and Niehorster (2011) scenario name: Rel_SST_min)
Two Guiding Principles for Insurance
Principle 1: Premiums reflecting risk
Insurance premiums should be based on risk in order to provide signals
to individuals as to the hazards they face and to encourage them to
engage in cost-effective adaptation measures to reduce their
vulnerability to catastrophes. Risk-based premiums should also
reflect the cost of capital insurers need to integrate into their pricing
to assure adequate return to their investors.
Principle 2: Dealing with equity and affordability issues
Any special treatment given to homeowners currently residing in hazardprone areas (e.g., low-income uninsured or inadequately insured
homeowners) should come from general public funding and not
through insurance premium subsidies.
35
Pricing of Hurricane Insurance for Residential Portfolio
Two vulnerability conditions:
• current adaptation: existing status of homes in Florida
• full adaptation: upgrades all homes in Florida to meet current
building code
Generated estimates of Average Annual Loss (AAL) and standard
deviations (σ) under six climate scenarios and two vulnerability
conditions
Determined price of insurance for hard and soft markets (different
competitive pressure, varying cost of capital)
36
Pricing of Hurricane Insurance for Residential Portfolio (cont.)
Premium (PΔ) for a specific layer of coverage (Δ) is given by
the following formula:
PΔ = E(LΔ)(1 +λ) + c·σΔ
- E(LΔ) is the expected loss or AAL
- λ is the loading factor
- σΔ is the standard deviation of a pre-specified portfolio of layer Δ
- c is the degree of risk aversion of the reinsurer. (c=0.4 for soft market
and c=0.7 for a hard market)
- LΔ is the loss distribution for layer Δ.
37
Exceedance Probability (EP) Curve for Different
Layers of Insurance (1990): Current Adaptation
Exceedance Probability (EP) Curve for Different Layers of Insurance (1990): Current Adaptation
6
Some Insurance Pricing Results
39
Pricing of Hurricane Insurance for
Residential Portfolio: Hard Market
Change in Reinsurance Prices over Time and Across Climate Scenarios – Illustration with a Hard Market
40
Pricing of Hurricane Insurance for
Residential Portfolio: Soft Market
Change in Reinsurance Price over Time and Across Climate Scenarios – Illustration with a Soft Market
41
Some Key Findings on the Cost of Insurance
Actuarial price for the baseline case in 1990 (i.e., no climate change) with current
adaptation levels: $13 billion (under hard market conditions)
Price decreases by 54% to $6 billion with full adaptation.
In 2020 among the four dynamic downscaling models for best case scenario,
• actuarial price: $10 billion based on current adaptation levels
• actuarial price: $5 billion with full adaptation.
In 2020 among the four dynamic downscaling models for worst case scenario,
• actuarial price: $14 billion based on current adaptation levels
• actuarial price: $6 billion with full adaptation.
Note: Full adaptation also has a significant impact by reducing the uncertainty and
magnitude of the premiums (i.e., a much narrower pricing range)
42
Some Insurance Coverage Results
43
Insurance Coverage with Current and
Full Adaptation: High Risk Scenario
Percentage of Insurance Coverage by Private Market with Reinsurance (High Estimate)
Insurance Coverage with Current and
Full Adaptation: Low Risk Scenario
Percentage of Insurance Coverage by Private Market with Reinsurance (Low Estimate)
Conclusions
Florida is a poster state for the following reasons:
 Population growth: 2.5 million in 1950, to 19 million in 2011
 Scientific studies indicating changes in climate patterns will likely increase the
intensity of hurricanes and storm surge/flooding in the Atlantic Basin
 Vulnerability of the state to severe hurricanes: 4 in 2004 and 2 in 2005
 Inability of private insurers to provide coverage because prices are highly regulated
(rate suppression)
Price of insurance is a function of market conditions (hard/soft) and climate
change scenarios
Adoption of risk reduction measures can significantly reduce insurance prices
and increase available coverage from the private sector
46
3. Strategies for Promoting Adaptation Measures
Why Individuals, Firms and Countries Do Not Invest in Them
Short Time Horizons (Quick return on investment)
High Short-Term Discount Rates (Hyperbolic discounting)
Misestimating Probability (“It will not happen to me”)
Liquidity and Upfront Costs (“We live from payday to payday”)
Truncated Loss Distribution (Only responsible for small portion of
loss due to disaster relief)
May Move in 2 or 3 Years (Can’t recover costs of adaptation)
Want a level playing field (Need to remain competitive)
47
Encouraging Long-term Thinking
with Short-term Incentives
We may need regulations and well-enforced
standards in order to develop long-term strategies
for encouraging investment in mitigation and
adaptation measures
At the same time, we need financial incentives
to address problems of myopia
48
Adaptation Strategy for Protection Against Natural Disasters
Multi-Year Flood Insurance in the United States
Proposed strategy
Multi-year flood insurance contracts through the
National Flood Insurance Program (NFIP)
Multi-year home improvement loans for mitigating
one’s property
Insurance and loans are tied to the property,
not to the individual
49
Multi-Year Flood Insurance (MYFI)
Rates would reflect risk (Principle 1)
(Need to design accurate flood risk maps)
Insurance vouchers for those needing special treatment (Principle 2)
(Only for those currently residing in flood-prone areas)
Homeowners would have knowledge that they are protected against water
damage from floods and hurricanes
Would avoid insurance cancellation after just 3 or 4 years
50
Multi-Year Flood Insurance Provides Stability to NFIP
It would sustain revenue for the program over time by
having a much larger policy base.
If homeowner moved to another location, the flood policy
would remain with the property unless the new owner did
not have a federally insured mortgage.
Consider requiring everyone in flood prone areas to have
flood insurance. Would ensure spread of risk within the
NFIP program.
51
How MYFI would Encourage Adaptation: An Example
Characteristic of Adaptation Measures
Upfront cost/long-term benefits
Cost of Mitigation – $1,500 to strengthen roof of house
Nature of Disaster
– 1/100 chance of disaster
– Reduction in loss ($27,500)
Expected Annual Benefits:
$275 (1/100 * $27,500)
Annual Discount rate of 10%
52
Expected Benefit-Cost Analysis of Adaptation
Benefits over 30 years
$3,000
$2,500
$2,000
$1,500
Upfront cost of mitigation
$1,000
$500
$0
1
2
3
4
5
8
10
15
20
25
30
53
Linking Multi-Year Home Improvement Loans
with Multi-Year Flood Insurance
Everyone is a Winner:
Homeowner:
Lower total annual payments
Insurer:
Reduction in catastrophe losses and
lower reinsurance costs
Financial institution:
More secure investment due to lower losses
from disaster
General taxpayer:
Less disaster assistance
54
Is there a Demand for Multi-Year Insurance?
Experiments on Demand for Multi-Year Insurance
(2 Period Game with Hurricane Risk)
)
Initial house value: 100,000 talers,
Probability of hurricane in period 1: 1 in 25
Probability of hurricane in period 2 if no hurricane in period 1: 1 in 25
Probability of hurricane in period 2 if hurricane inperiod 1: 1 in 20 (5%)
Loss of house value if hurricane occurs: 50,000 talers
Subjects can buy insurance that protects them hurricane losses
55
Experimental Design: Four Treatments
Treatment 1: Subjects are only offered 1-period contracts
at premiums reflecting risk
Treatment 2: Subjects are offered 1- and 2-period
insurance contracts at premiums reflecting risk
Treatments 3 and 4: Subjects are still offered 1-period
insurance contracts at premiums reflecting risk
Price of 2-period insurance contract is increased by
5% (Treatment 3) and 10% (Treatment 4).
56
Insurance Prices in the Four Treatments
Prices
Treatment 1
Treatment 2
No Hurricane in period 1
2,000
2,000
2,000
2,000
Hurricane in period 1
2,500
2,500
2,500
2,500
2,010
2,110
2,210
Two-period contract
Treatment 3
Treatment 4
57
Percentage of subjects purchasing no insurance, 1-period and
2-period contracts averaged across all 30 games
100%
90%
80%
70%
60%
no insurance
50%
1-period contracts
2-period contracts
40%
30%
20%
10%
0%
treatment 1
treatment 2
treatment 3
treatment 4
4. Future Research
Impact of Climate Change on Multi-Year Insurance Contracts
Pricing of insurance for contracts of 5, 10 and 20 years,
to see how length of time periods impacts on prices
Role of adaptation measures in reducing damage to property
with and without climate change
Types of instruments to cover catastrophic losses
(e.g. reinsurance, cat bonds, federal or state reinsurance) for
59
multi-year insurance and how to price them
4. Future Research
Encouraging Investment in Cost-Effective Adaptation Measures
Determine costs of adaptation measures so one can undertake a meaningful
benefit-cost analysis under different annual discount rates and time horizons.
Examine role that multi-year insurance can play in encouraging investment in
cost-effective adaptation measures
 Make the impact of climate change more salient
 Stretch time horizon with respect to likelihood of disasters occurring (e.g. flood or
hurricane with a 100 year return period (.01 annual likelihood) translates into .22
probability of at least one flood or hurricane in the next 25 years)
 Highlight expected benefits of adaptation and mitigation measures to key interested parties
 Way to tie loans and insurance to the property not the individual through assumable
mortgage contracts or by incorporating these contracts in property taxes
How to bring together key interested parties together to ensure that:
 Interdependencies and externalities are considered in evaluating these measures
 Property is inspected to confirm that adaptation measures are adopted
 Readjust insurance premiums at regular intervals (e.g. 5 years) to reflect new risk estimates
60
5. Summary
The Facts:
New era of “large-scale risks”; huge and still growing concentration
of value in high-risk areas; indication of more devastating disasters in
the future with property and environment damage and health impacts
The Reality:
Individuals are myopic and misperceive risks, so they do not adopt
cost-effective protective measures.
Research and policy questions:
Are multi-year contracts coupled with short-term incentives a way to
encourage investment in mitigation and adaptation measures to reduce
impact of climate change in the future?
What are the challenges and opportunities of developing specific
proposals so they have a chance of being implemented?
61
Selected References
Bender, M. T. Knutson, R. Tuleya, J. Sirutis, G.Vecchi, S. Garner, I. Held. 2010. “Modeled Impact of Anthropogenic Warming on the Frequency of Intense Atlantic
Hurricanes.” Science 22 January, 327 (5964), 454–458.
Bouwer, L.M., Crompton, R.P., Faust, E., Höppe, P., and Pielke, Jr., R. 2007. “Confronting Disaster Losses.” Science, 318, November 2, 753.
Hoyos, C., P. A. Agudelo, P. J. Webster, J. A. Curry. 2006. “Deconvolution of the Factors Contributing to the Increase in Global Hurricane Intensity.” Science 7
April, 312 (5770), 94–97.
Jaffee, D., H. Kunreuther and E. Michel-Kerjan 2010. “Long-term property insurance.” Journal of Insurance Regulation, 29, 166-188.
Knutson, T., J. McBride, J. Chan, K. Emanuel, G. Holland, C. Landsea, I. Held, J. Kossin, A. K. Srivastava, and M. Sugi. 2010. “Tropical Cyclones and Climate
Change.” Nature Geoscience 3, 157–163.
Kunreuther, H., R. J. Meyer, and E. Michel-Kerjan. In press. “Strategies for Better Protection against Catastrophic Risks.” In Behavioral Foundations of Policy, ed.
E. Shafir. Princeton, NJ: Princeton University Press.
Kunreuther, H. and E. Michel-Kerjan. 2009. At War with the Weather: Managing Large-Scale Risks in a New Era of Catastrophes, Cambridge, MA: MIT Press.
Kunreuther, H., E. Michel-Kerjan and N. Ranger 2011. “Insuring Climate Catastrophes in Florida: An Analysis of Insurance Pricing and Capacity under Various
Scenarios of Climate Change and Adaptation Measures.” joint Wharton Risk Center-LSE working paper.
Michel-Kerjan, E. 2010. “Catastrophe Economics: The National Flood Insurance Program.” Journal of Economic Perspectives, 24 (4), 165-186.
Michel-Kerjan, E. and C. Kousky 2010. “Come Rain or Shine: Evidence on Flood Insurance Purchases in Florida.” Journal of Risk and Insurance, 77(2), 369-397.
Michel-Kerjan, E., S. Lemoyne de Forges, and H. Kunreuther. (forthcoming). “Policy Tenure under the National Flood Insurance Program.” Risk Analysis.
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