1. 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 kunreuther@wharton.upenn.edu http://opim.wharton.upenn.edu/risk Presentation at NCAR Colloquium on Statistical Assessment of Extreme Weather Phenomena under Climate Change June 6, 2011

2. 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

3. AT WAR WITH THE WEATHER Better understanding how individuals decide whether or not to protect themselves against natural disasters. A set of guiding principles for using insurance to deal more effectively with these events. Key lessons from the financial management of natural disasters to be applied to other global risks such as pandemics, financial crises and terrorism. 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. LEARNING FROM CATASTROPHES STRATEGIES FOR REACTION AND RESPONSE 2010 – Financial Times 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.  Operating principles that can reduce severe risk and enhance readiness and resilience.  Written in collaboration with the World Economic Forum’s Global Agenda Council on Mitigation of Natural Disasters. 2009 – MIT Press

4. Outline of Talk Part 1: Linking Risk Assessment and Risk Perception with Risk Management: A Conceptual Framework for Studying Risk 1. Risk Assessment and Vulnerability Analysis 2. Risk Perception and Choice 3. 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

5. A Conceptual Framework for Studying Risk Statistical Data Building Scenarios Risk Perception and Choice Public Perceptions Expert/Layperson Differences Risk Communication Risk Assessment & Vulnerability Analysis Modeling of Risks Risk Management Strategies Public-Private Partnerships 5

6. Risk Management Strategies: Public-Private Partnerships Information Provision Incentives Regulation Standards Compensation Insurance Liability Evaluation of Strategies Impact on Society Impact on Interested Parties A Conceptual Framework for Studying Risk 6

7. 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

8. 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

9. Modeling Catastrophic Risks 9  A method to characterize the hazard in some probabilistic manner  Magnitude of the event vs. annual return period  The exposure at risk – in other words, the structures that may be damaged  May be a single structure, or a collection of structures Hazard Module Exposure Module LOSSLOSSLOSSLOSS Financial Module  The financial module performs the convolution of these first three elements and allows one to create loss estimates that have a certain probability of exceedance  Estimating the loss levels given a certain magnitude of hazard  Typically mean loss ratio given a hazard level Vulnerability Module

10. Using Exceedance Probability Curves to Depict Risk Uncertainty in Probability Uncertainty in Loss 95% Mean Probability p(L) that losses will exceed L 5% Loss, L (in dollars) 10

11. 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 risk- reducing 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

12. 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 2. Risk Perception and Choice Basic Concepts

13. 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

14. 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

15. 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

16. 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

17. Outline of Talk Part 1: Linking Risk Assessment and Risk Perception with Risk Management: A Conceptual Framework for Studying Risk 1.Risk Assessment and Vulnerability Analysis 2.Risk Perception and Choice 3.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

18. 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

19. It’s Been a Busy 17 Months

20. January 2010: 7.0 Earthquake, Haiti 230,000 Killed, 1,000,000 Homeless

21. February 2010: 8.8 Quake, Chile 486 Dead, $7Bn Insured Losses

22. April 2010: Iceland Volcanic Eruption Cost to Airlines of Suspension of European Air Travel: $1.7Bn

23. May 2010: Deepwater Horizon spills Cost to BP to Date: $10Bn 5 million barrels of crude in Gulf

24. May-July 2010: Worst Floods in a Decade in China 3,200 dead, 15 million evacuated, 1.36 million houses destroyed, $30Bn property damages

25. 25 November 2010: Bombing attempt discovered

26. March 2011: Japan Earthquake, Tsunami, and Radiation from Nuclear Power Plant

27. May 2011: Joplin, MO Tornado Deadliest tornado since 1950 $1-3 billion in damage

28. Natural catastrophes worldwide 1980 – 2010 Overall and insured losses with trend (bn US$) © 2011 Münchener Rückversicherungs-Gesellschaft, Geo Risks Research, NatCatSERVICE – As at January 2011 Trend insured lossesTrend overall losses Overall losses (in 2010 values)Insured losses (in 2010 values) Worldwide Evolution of Catastrophes, 1980-2010

29. Twenty-Five Most Costly Insured Catastrophes Worldwide, 1970–2010 (15 here in the U.S., 11 of these since 2001) $ BILLIONEVENTVICTIMS ( DEAD OR MISSING ) YEARAREA OF PRIMARY DAMAGE 48.6Hurricane Katrina1,8362005USA, Gulf of Mexico, et al. 37.09/11 Attacks3,0252001USA 24.8Hurricane Andrew431992USA, Bahamas 20.6Northridge Earthquake611994USA 17.9Hurricane Ike3482008USA, Caribbean, et al. 14.8Hurricane Ivan1242004USA, Caribbean, et al. 14.0Hurricane Wilma352005USA, Gulf of Mexico, et al. 11.3Hurricane Rita342005USA, Gulf of Mexico, et al. 9.3Hurricane Charley242004USA, Caribbean, et al. 9.0Typhoon Mireille511991Japan 8.0Maule earthquake (M w : 8.8)5622010Chile 8.0Hurricane Hugo711989Puerto Rico, USA, et al. 7.8Winter Storm Daria951990France, UK, et al. 7.6Winter Storm Lothar1101999France, Switzerland, et al. 6.4Winter Storm Kyrill542007Germany, UK, NL, France 5.9Storms and floods221987France, UK, et al. 5.9Hurricane Frances382004USA, Bahamas 5.3Winter Storm Vivian641990Western/Central Europe 5.3Typhoon Bart261999Japan 4.7Hurricane Georges6001998USA, Caribbean 4.4Earthquake (M w : 7.0)02010New Zealand 4.4Tropical Storm Alison412001USA 4.4Hurricane Jeanne3,0342004USA, Caribbean, et al. 4.1Typhoon Songda452004Japan, South Korea 3.8Storms452003USA **********************

30. 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

31. 31 Insured Exposure on the Coasts (Texas to Maine as of Dec. 2007): $10 trillion US Exposure to Natural Catastrophes

32. 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 What’s Happening? The Question of Attribution 32

33. $160 billion loss $82 billion saving with Adaptation measures in place 2. Benefits of Adaptation Measures and Role of Insurance Data on Reduction in Losses from 500-Year Hurricanes in U.S. 33

34. Six Climate Scenarios Studied Model TypeDescription Model AStatistical Model 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 BDynamical Model Based on a dynamical-model based forecast of future hurricane activity from Bender et al. 2010 using the global climate model (GCM) GFDL- CM2.1. Model CDynamical ModelAs above, using MRI-CGAM (Bender et al. 2010) Model DDynamical ModelAs above, using MPI-ECHAM5 (Bender et al. 2010) Model EDynamical ModelAs above, using UKMO (Bender et al. 2010) Model FStatistical ModelA 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)

35. 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 hazard- prone areas (e.g., low-income uninsured or inadequately insured homeowners) should come from general public funding and not through insurance premium subsidies. 35

36. 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) Pricing of Hurricane Insurance for Residential Portfolio 36

37. Premium (P Δ ) for a specific layer of coverage (Δ) is given by the following formula: P Δ = E(L Δ )(1 +λ) + c·σ Δ - E(L Δ ) is the expected loss or AAL - λ is the loading factor - σ Δ 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) - L Δ is the loss distribution for layer Δ. Pricing of Hurricane Insurance for Residential Portfolio (cont.) 37

38. Exceedance Probability (EP) Curve for Different Layers of Insurance (1990): Current Adaptation 6

39. Some Insurance Pricing Results 39

40. 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

41. 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

42. 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

43. Some Insurance Coverage Results 43

44. Insurance Coverage with Current and Full Adaptation: High Risk Scenario Percentage of Insurance Coverage by Private Market with Reinsurance (High Estimate)

45. Insurance Coverage with Current and Full Adaptation: Low Risk Scenario Percentage of Insurance Coverage by Private Market with Reinsurance (Low Estimate)

46. 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

47. 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

48. 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

49. 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 Adaptation Strategy for Protection Against Natural Disasters Multi-Year Flood Insurance in the United States 49

50. 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

51. 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

52. 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 How MYFI would Encourage Adaptation: An Example 52

53. Upfront cost of mitigation Expected benefits over time 53

54. 54 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 Linking Multi-Year Home Improvement Loans with Multi-Year Flood Insurance

55. 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

56. 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

57. Insurance Prices in the Four Treatments 57 Prices Treatment 1 Treatment 2 Treatment 3 Treatment 4 2,000 Hurricane in period 1 2,500 Two-period contract 2,010 2,110 2,210 No Hurricane in period 1

58. Percentage of subjects purchasing no insurance, 1-period and 2-period contracts averaged across all 30 games

59. 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 multi-year insurance and how to price them 59

60. 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

61. 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

62. 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. Munich Re. 2010. Topics Geo. Natural Catastrophes 2009. Munich: Munich Re. http://www.munichre.com/publications/302-06295_en.pdfhttp://www.munichre.com/publications/302-06295_en.pdf Pielke, R., Jr., J. Gratz, C. Landsea, D. Collins, M. Saunders, and R. Musulin. 2008. Normalized hurricane damage in the United States: 1900–2005. Natural Hazards Review 9 (1): 29–42. Ranger, N. and F. Niehorster 2011. “Deep Uncertainty in Long-term Hurricane Risk: Scenario Generation and the Implications for Planning Adaptation.” Risk Management Solutions (RMS) 2010. Study of Florida’s Windstorm Mitigation Credits: Assessing the Impact on the Florida Insurance Market. http://www.rms.com/publications/RMS_Study_of_Floridas_Windstorm_Mitigation_Credits.pdf 62