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Hedging Climate Change

Hedging Climate Change



A 2007 Allianz report calls for new approaches to risk diversification in the insurance industry to prepare for climate change-related damages.

A 2007 Allianz report calls for new approaches to risk diversification in the insurance industry to prepare for climate change-related damages.



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    Hedging Climate Change Hedging Climate Change Document Transcript

    • Risk reportHedging climate changeHow insurers can manage the risk of increasing natural catastrophes
    • Risk report Hedging climate changeContent page 3 page 5 page 10 1 2Natural catastrophes in the Natural catastrophes Future insurance potentialgrip of climate change on the march in natural catastrophes page 16 page 19 page 24 3 4 5Catastrophe risk in im- Are catastrophe risks Path to the futureportant markets is heavily capable of being efficiently 1. Extending the insurability of cat riskunder-insured insured? 2. Rethinking the role of the state 3. Private and public risk partnerships: the example of flood insurance Bibliography page 34ImprintRisk report: “Hedging climate change” | Publication: September 2007 | Author: Allianz Dresdner Economic Research, Dr. Helmut Kesting | Published by: Allianz SELayout: Volk:art 51 GmbH, Munich | Contact: Michael Anthony, Allianz SE, Group Communications/Corporate Affairs, Königinstrasse 28, D-80802 Munichemail: michael.anthony@allianz.com 2
    • Risk report Hedging climate change Natural catastrophes in the grip of climate change t the beginning of February 2007, the Intergovernmental Panel on Climate ChangeA (IPCC) published the first part of its Fourth Assessment Report on world climatechange.1On the origins of climate changes, the report finds that:• The main cause is the greenhouse effect which, in the first instance, can be attrib- uted to an increased level of carbon dioxide in the air. This rose by 30 percent between 1900 and 2005. Almost half of the increase has come in the past 25 years. Seventy-eight percent of the higher CO2 concentration has been caused by the use of fossil fuels. Another 22 percent is because of changes in land use (such as in- creases in arable land).• Further causes include rises in the amounts of other significant greenhouse gases such as methane and nitrous oxide. Their combined increase amounts to half the increase in CO2 levels.• By way of comparison, changes in solar radiation have exerted a minimal influ- ence.A broad consensus exists that the main cause of climate change is human activity(especially CO2 emissions). We have ourselves to blame for the rise in global tem-peratures. At the same time, however, this means that we are in a position to influence climatepositively. But this means quicker, more effective and globally coordinated efforts. 1 The IPCC was set up in 1998 by the World Mete-At the moment, the concentration of CO2 in the atmosphere is about 400 ppm (parts orological Organization (WMO) and the Unitedper million). The current rate of increase is at least 2 ppm a year. However, this rate Nations Environment Programme (UNEP).is rising because energy and transport needs are increasing worldwide. Even if CO2 As an institution independent of governments,emissions were immediately held to present levels, greenhouse-gas concentrations the organization has the task of assessing on awould still rise to 550 ppm by 2050. The rise in temperatures of the earth’s surface regular basis the state of knowledge of climatewould not stop but would, over the next decades, increase by at least half a degree. change and the effects of these changes on The transition to the post-fossil fuel age involves the largest program of renewal human society. More information can be foundand restructuring that the world economy has ever seen.2 Especially affected is elec- on the institution’s web site (www.ipcc.ch)tricity generation (power stations), which is responsible for 40 percent of CO2 emis- 2 See essay by Peter Hennicke in Handelsblattsions, transport (20 percent), industry (18 percent), plus housebuilding, service (20.03.07, 9) 3
    • Risk report Hedging climate changeindustries and agriculture (together about 13 percent). Clearly, this restructuringalso involves changes in consumer habits. Climate protection is not just a matter ofmoney. At the same time new markets and opportunities for growth are emerging.The markets for energy efficiency and renewable energy are alone showing a globalgrowth rate of between 10 and 20 percent. Allianz SE has for years been warning – as have other insurers – of the results ofunhindered climate change.3 In cooperation with the WWF (World Wide Fund forNature) over a number of years, Allianz SE has supported many projects and initia-tives to strengthen climate protection. It belongs to the Global Roundtable on ClimateChange (GROCC)4 and espouses a broad alliance of all societal forces to work towardsa sustainable energy systems capable of achieving economic growth. Other compa-nies within the Allianz Group are also committed to climate protection. DresdnerBank is the market leader in European Union (EU) Emissions Trading Scheme CO2certificates. But this is not merely a matter of supporting noble ideals such as thepreservation of life’s fundamentals for future generations. For both Allianz and Dres-dner Bank, earth warming has long become a matter of business. Regardless ofwhether it is insurance, emissions trading, asset management or project financing,many areas of activity need to take into consideration the effects of climate change.5 Further activity involves the effects of climate change on insurance markets. Atthe core of the issue is to what extent, or under which conditions, catastrophescaused by climate change will be insurable. This is crucial because questions of pros-perity are linked with insurance: entities such as institutions can protect themselvesfrom damage that threatens their existence. At the same time, positive influences onentire economies result when people can act with the backing of insurance – theyare more prepared to enter high-risk innovative projects than they would be withoutinsurance. The next part of the report documents the development of damage caused by nat-ural catastrophes. In view of the existing massive under insuring, it investigates whymarkets cannot function effectively when dealing with catastrophe damage. It con-cludes by discussing private and state initiatives.The study reaches the following main conclusions:• The number of catastrophes caused by natural forces, as well as the extent of the damage, indicates a significantly rising trend (Chapter 1) .• The insurance potential is enormous. Annual expected average total damage be- tween 2010 and 2020 is estimated at 80-120 billion US dollars (in today’s prices). But because of the high degree of variability, the real damage could significantly depart from this figure (Chapter 2).• These risks are greatly under-insured. As a whole, the markets for catastrophe risks do not functions optimally. They are linked with the specific characteristics of such large risks which, among other things, makes their diversification difficult (Chapter 3 and 4).• Innovative developments by insurers such as catastrophe bonds, (cat bonds) which enable risks to be transferred on capital markets, as well as private and public risk partnerships, can help improve the insurability of catastrophe risks (Chapter 5). 3 To examine the activities of the European Insurance and Reinsurance Federation on climate change, see www.cea.assur.org 4 See www.earth.columbia.edu/grocc 5 See www.allianz.com/Klima 4
    • Risk report Hedging climate change 1 Natural catastrophes on the march oth the frequency and extent of natural catastrophes have, over recent years,B increased notably. Before taking a closer look at this, some concepts need to beclarified. Where many separate cases of damage have a common cause, they are said to bein a close time and geographical context. If the total amount of damage reaches anextraordinarily high level measured against “normal” conditions, the reference is toa catastrophe.6 But catastrophes occur in different categories. A natural catastrophe is described as one being caused by natural forces. Theseinclude flooding, storms, earthquakes, tidal waves, drought/bushfire/heat, cold/frost,hail or avalanches. The extent of the damage depends not only on the strength of thenatural force. A role is played by preventive measures as well as technical or organi-zational factors that can help limit the consequences. The overall damage from a 6 What precisely “extraordinarily high” is is obvi-natural catastrophe always has a social dimension. ously an issue of convention. For the reporting Man-made catastrophes are events that are closely associated with human activity. year of 2006, Swiss Re used, among others, theMostly of the time these involves a large object in a confined space, such as a build- following definition: for insurance losses in ship-ing complex.7 Among such catastrophes are, for example, large fires, explosions, air ping, 16.1 million U.S. dollars; in civil aviation,crashes, or mine disasters. 32.2 million U.S. dollars; and in other areas, 40 Terrorist attacks are a special category of catastrophe risk. They are not due to million U.S. dollars. Smaller claims were there-chance but a result of premeditated human action. In contrast to natural or man- fore not included in the sigma catastrophe datamade catastrophes, the probability of occurrence cannot be assessed using the bank. As well as that, adjustments for inflationusual insurance processes. were made to ensure consistency of data The number of natural catastrophes since 1970 is shown in Chart 18. The trend is 7 Wars, including civil wars and events that resem-clearly upwards. The annual number of natural catastrophes has, over the period, ble wars, are excludedcontinually risen. The representation of the trend as straight (linear function) ac- 8 The sources are the catastrophe data banks ofcords with the overall picture of the data. The vast majority of natural catastrophes the two largest reinsurance companies, Swiss Reare weather-related (see Chart 3). This suggests that there is a connection between and Muenchener Rueck. See the equivalentthe increases in natural catastrophes and the likewise slow but constantly rising indices from sigma (www.swissre.com) and Top-increases in global temperatures as a consequence of climate change. ics Geo (www.munichre.com) 5
    • Risk report Hedging climate change Chart 1 Number of natural catastrophes 180 160 140 120 100 80 60 40 20 0 19 19 19 19 19 19 19 19 19 19 20 20 20 70 73 76 79 82 85 88 91 94 97 00 03 06 Source: sigma 2/07 In contrast, the annual level of claims resulting from natural catastrophes coveredby insurers shows from the outset a far higher variation because the total claims inany given year are heavily dependent on whether, in that year, there is one or morelarge catastrophes. Chart 2 confirms this. The year 1992 was the year of HurricaneAndrew, up until then the second largest natural catastrophe (see Table 1). In termsof claims, the record year was 2005, when Hurricanes Katrina, Wilma and Rita allstruck. They stand respectively in places 1, 6 and 7 on the table of the 40 most-expen-sive insurance claims ever. The year 2006, however, shows a relatively low level ofclaims amounting to just 12 billion US dollars. This is because, with ten storms de-clared, and five of them reaching hurricane strength, the level was merely averagebecause no built-up areas were hit and there was thus little damage9. Chart 2 Insured natural catastrophes ($ billion US) 100 80 60 40 20 0 19 19 19 19 19 19 19 19 19 19 20 20 20 70 73 76 79 82 85 88 91 94 97 00 03 06 Source: sigma 2/07 Chart 2 basically shows the rising trend of damage. The increases are dispropor-tionate. This is clear if the period covered is divided in two. Up until 1988 the totaldamage exceeded the 10 billion US dollar level only once. But from 1989, the totalannual damage is only four times below that level and has exceeded the 15 billion-dollar mark a total of ten times, sometimes considerably. That the differences ofclaims increases in absolute terms over two successive years suggests the trend issubject to a non-linear function. 9 See Topics Geo – Naturkatastrophen 2006 6
    • Risk report Hedging climate change Table 1 indicates the non-linear increase of expected claims levels. Thirty-four(85 percent) of the largest 40 catastrophes happened between 1988 and 2006, while15 (about 38 percent) happened after 2000. It is also clear that the majority of casesof large claims were, by a long way, related to natural catastrophes. The terror attackof September 11, 2001, is – at least so far – a rare exception.Table 1The 40 most expensive insurance claims 1970-2006Insured Losses10 Date Event CountryIn $ mn US, inflation (Beginning)indexed as of 200666,311 25.08.2005 Hurricane Katrina; floods, burst levees, USA, Gulf of Mexico, Bahamas, oil platform damage North Atlantic22,987 23.08.1992 Hurricane Andrew; floods USA, Bahamas21,379 11.09.2001 Terror attack on World Trade Center, USA Pentagon, other buildings19,040 17.01.1994 Northridge Earthquake, LA USA (6.6 on the Richter Scale)13,651 02.09.2004 Hurricane Ivan; Oil-platform damage USA, Caribbean, Barbados, elsewhere12,953 19.10.2005 Hurricane Wilma; rain, flooding USA, Mexico, Jamaica, elsewhere10,382 20.09.2005 Hurricane Rita; flooding, USA, Gulf of Mexico, Cuba Oil-platform damage8,590 11.08.2004 Hurricane Charley USA, Cuba, Jamaica, elsewhere8,357 27.09.1991 Typhoon Mireille/Nr. 19 Japan7,434 15.09.1989 Hurricane Hugo USA, Puerto Rico, elsewhere7,204 25.01.1990 Winter storm Daria France, UK, Belgium, elsewhere7,019 25.12.1999 Winter storm Lothar Switzerland, UK, France, elsewhere5,500 15.10.1987 Storms, Flooding in Europe France, UK, Netherlands, elsewhere5,485 26.08.2004 Hurricane Frances USA, Bahamas4,923 25.02.1990 Winter storm Vivian Europe4,889 22.09. 1999 Typhoon Bart/Nr. 18 Japan4,366 20.09.1998 Hurricane Georges; flooding USA, Caribbean4,100 05.06.2001 Tropical storm Alison; flooding USA4,022 13.09.2004 Hurricane Jeanne; flooding, landslides USA, Caribbean (incl. Haiti), elsewhere3,826 06.09.2004 Typhoon Songda/Nr. 18 Japan, South Korea3,512 02.05.2003 Thunder storms, tornados, hailstorms USA3,415 10.09.1999 Hurricane Floyd; flooding USA, Bahamas, Colombia3,409 06.07.1988 Explosion on platform Piper Alpha UK3,315 01.10.1995 Hurricane Opal; flooding USA, Mexico, Gulf of Mexico 7
    • Risk report Hedging climate changeInsured Losses10 Date Event CountryIn $ mn US, inflation (Beginning)indexed as of 20063,270 17.01.1995 Great Hanshin Earthquake in Kobe; Japan (7.2 on the Richter Scale)2,905 27.12.1999 Winter storm Martin Spain, France, Switzerland2,736 10.03.1993 Snowstorms, tornados, flooding USA, Canada,Mexico, Cuba2,587 06.08.2002 Serious flooding UK, Spain, Germany, elsewhere2,516 20.10.1991 Urban forest fires, drought, in California USA2,505 06.04.2001 Hailstorms, tornados, flooding USA2,364 18.09.2003 Hurricane Isabel USA, Canada2,331 05.09.1996 Hurricane Fran USA2,305 03.12.1999 Winter storm Anatol Denmark, Sweden, elsewhere2,299 11.09.1992 Hurricane Iniki USA, North Pacific2,217 29.08.1979 Hurricane Frederic USA2,155 23.10.1989 Petrochemical works explosion USA2,134 26.12.2004 Earthquake (9 on the Richter Scale), Indonesia, Thailand, elsewhere Tidal wave in Indian Ocean2,091 19.08.2005 Rain, landslides, flooding Switzerland, Germany, elsewhere2,044 18.09.1974 Tropical Cyclone Fifi Honduras2,009 04.07.1997 Flooding after heavy rain Poland, Czech Rep., Germany, elsewhereSource: sigma 2/07 Data analyzed by Muenchener Rueck arrives at similar conclusions11. About 16,000natural catastrophes from between 1980 and 2005 were examined. The catastropheswere divided into six loss categories: 1. Small Losses; 2. Medium Losses; 3. Medium-to-Serious Losses (totalling more than 60 million US dollars); 4. Serious Losses (morethan 200 million dollars); 5. Devastating Losses (more than 500 million dollars); and6. Huge Natural Catastrophes (extreme losses as defined by the United Nations). When the incidence of catastrophes was worked out, the dominating occurrencewith more than 85 percent was weather-related natural catastrophes. This empha-sizes again the central significance of climate change for catastrophe insurance12.The incidence of catastrophes however in percentage terms differ little from one ofthe three (consolidated) loss categories to another. Earthquake related losses are the 10 Property damage and production breakdownleast evenly divided. claims, but not life assurance or third-party liability 11 See www.munichre.com and the NatCatService page 12 However the greatest conceivable insurance losses are connected with earthquakes. A serious earthquake in California and a major earthquake in Tokyo with total losses running into trillions of US dollars would probably cause a world-wide depression. Astronomical events such as the ex- treme case of a collision with a black hole are not, for obvious reasons, taken into account 8
    • Risk report Hedging climate change Chart 3 Catastrophes according to category (1980-2005) 45% Temperature extremes, 40% mass motions such as landslides 35% Earthquakes, 30% tidal waves, 25% volcanic eruptions 20% Storms 15% 10% Flooding 5% 0% Category 1+2 Category 3+4 Category 5+6 Source: Muenchener Rueck A completely different picture emerges if the significance of individual categoriesin relation to total losses is considered. Here, major losses dominate, although theycomprise just three percent of all cases. Categories 5 + 6 are responsible for the bulkof all losses and deaths with respectively 80 percent and 86 percent.According to Muenchener Rueck, the geographical distribution of losses is:• With 4,500 disasters, most of the damage is in Asia, the most heavily populated continent with the most cities and conurbations. Although 70 percent of the disas- ters involved small losses, this region was also hit by the highest number of large- scale and devastating disasters (225).• Most of the fatalities were also in Asia, with more than 800,000. Almost 90 percent of these were victims of Category 5+6 occurrences.• By comparison, both Europe and North America (USA and Canada) were hit by an almost equal number of natural catastrophes. Most of those in Europe resulted in small losses while in North America there was a high proportion of major dam- age. Consistent with this is the fact that the total damage in North America was three times as high as in Europe. But in absolute terms, more people died in Europe, mainly because of the heat wave of 2003 which claimed the lives of more than 35,000.Overall, it is clear that over the past decades the insured damage caused by naturalcatastrophes in relation both to the number of linear occurrences and the non-linearextent of damage have increased. The annual total damage is far and away a conse-quence of large natural catastrophes, which are mainly the result of extremes ofweather (various storms, including hurricanes and typhoons, as well as flooding,drought and heat waves). 9
    • Risk report Hedging climate change 2 Future insurance potential in natural catastrophes s impressive as the losses are, they cannot be said to reflect the extent of the realA damage. There are various reasons. The report on insured losses put togetherby Swiss Re does not cover all actual insured losses. The central issues are propertydamage and production interruptions. Because of slow data accumulation, liabilityinsurance and life assurance were also not included. Non-insured losses are also part of the picture. Apart from private losses, this alsoincludes damage to public infrastructure, which is almost never insured. An important role is played by the way the term “damage” is defined13. Insurersmostly choose a relatively tight interpretation in the interests of topicality, precision,and commercially related reasons that in the first instance aim at defining immedi-ate losses. Broader economic analyses tend to take into greater consideration indirectlosses such as consequential damage. In this way, apart from the immediate costs ofa loss of production because of damaged manufacturing capacity, projected reduc-tions in growth are also considered. Definitions can, in fact, be so broad that even “non-monetary” damage such as lossof quality of life can be included. However, there are usually insuperable problems inestimating and assessing such losses. The difficulties of arriving at a “quantitativelymeasurable assessment” were especially clear in the case of the tidal wave that in2004 was unleashed by a submarine earthquake in the Indian Ocean. In Table 1, it islisted in fourth-to-last-place because, in the first instance, losses in the tourist indus-try were taken into account. The insured losses were estimated at only about two bil-lion US dollars. That is in no way commensurate with a human tragedy that resultedin the deaths of more than 280,000 people and the destruction of the means of exis-tence for innumerable families. 13 It has already bee pointed out that the term This is why the various estimates of total damage are only to some extent compa- “natural catastrophe” is defined differently byrable and need to be interpreted with reference to the methods used in compilation. Swiss Re and Muenchener Rueck. Typically,This means they should be used as a guide only rather than an exact estimate. In Muenchener Rueck’s numbers are smallerspite of these problems, the differences between insured and real losses is relevant because of a tighter definition 10
    • Risk report Hedging climate changebecause the latter can be many times bigger. One spectacular example is that of Hur-ricane Katrina, in August 2005, which is the biggest individual case of loss (see Table1). The insured losses amounted to 49 billion US dollars whereas the total lossesamounted to 144 billion dollars14. This disproportion between total losses and insured losses is greatest in develop-ing countries, where insurance markets are rudimentary. In 1996 flooding in Chinacaused losses of about 24 billion US dollars, of which less than 500 million dollarswere covered by insurance – a ratio of 48-to-one, high which ever way it is looked at.Two years later, more flooding in China caused an economic loss of 30 billion dollars.Insurance covered just one billion dollars – a ratio of 30 to one. But cases of extremely high imbalances between total losses and insured lossesare also known in industrialized countries. In the Kobe earthquake of 1995, the ratiowas 37 to one – 110 billion dollars to just three billion dollars. Normally, this ratio isbetween 1.5 and 5, depending on the tightness of damage definition. Improved insur-ance options, obligatory safeguards (such as in the case of mortgage credit) and bet-ter provisions against contingencies ensure that at least relatively closely definedtotal losses do not exceed insured losses by more than a low single figure15. Scientists and specialized companies develop complex catastrophe models to helpestimate future losses in natural catastrophes. These models use specific regionalinfluences to predict the consequences of climate change in terms of the respectiveloss categories. (See Chapter 5.1) Ideally, the accumulation of a wealth of individualfactors would then result in a global pattern. Because of the available information, such a bottoms-up approach is however,not really practicable. The catastrophe models are drawn up specifically with the rel-evant risks in mind with the result that an incalculable number of equivalent modelresults need to be processed. This more-or-less trips up on the fact that free accessto most model results is not available. Instead, the alternative here is to estimate pro-jected global losses over the next decade (2010-2019) with the aid of a simple statis-tical process. The trend of insured losses is first extrapolated; this result is then cal-culated into projected total losses. This process is, however, based on the assumption that over the following years,the fundamental cause-effect structure remains essentially the same. This makessense. At a global level, three main factors are responsible for climate-related natu-ral catastrophes. The first is climate change itself. The temperature rises caused byit have been noticeable in the past few years. According to the World MeteorologicalOrganization, 2006 will probably go down as the sixth warmest year on record. Thepast six years are now among the seven “record years.”16 Climate change marches on. That is not surprising, because the climate reactsto changed greenhouse-gas emissions very sluggishly and with considerable timedelays. In comparison with pre-industrial levels (1750-1850) the global average tem-perature has risen half a degree Celsius. And it is certain that the current greenhouse- 14 Sigma 2/07, 13. The proportion is smaller if thegas concentration in the atmosphere will lead to an increase of at least another half state’s own NFIP National Flood Insurance Pro-degree in the coming decades. gram is considered, because the insured losses The extent of global losses caused by natural catastrophes is influenced by two then rise to 66.3 billion dollars. On the otherother main factors: one is worldwide economic growth, and the other is urbanization, hand, the total losses from Katrina are estimateda process that goes hand in hand with flight from the land. In 1950, 2.5 billion people, at up to 170 billion dollars (Kunreuther/Michel-or 30 percent of the world’s population, lived in cities. According to United Nations’ Kerjn, 2007, 22), which increases the differenceestimates, by 2025, a total of 8.3 billion people, or 60 percent of the world’s popula- 15 See Kunreuther/Michel-Kerjn, 2007tion, will be in cities. The number of mega cities with more than 10 million people 16 For a description of the extreme weather condi-will increase from 12 in 1990 to 26 in 2015. Both these factors, growth and urbaniza- tions in 2006, and their position in a larger con-tion, are bringing about an increase in the concentration of assets in endangered text, see Topics Geo (2006), 42regions17. It is plausible to assume that in the next few years there will be no change 17 In addition, coastal regions such as Florida havein the basic trends – as with climate change. a magnet effect. The population of Florida is ris- This leads to an estimate of average losses for the period 2010-2019. On the basis ing from 6.8 million in 1950 to a projected 19.3of deducing an average from insured-losses data (see Chart 2) a potential trend func- million by 2010. See Kunreuther/Michel-Kerjan,tion emerges. The determining coefficient of 0.954 shows that the value of the trend 2007 11
    • Risk report Hedging climate changecurve broadly concurs with the data for the period 1970-2006 (see Chart 4). The right-hand column indicates that this trend will continue. The average annual insureddamage over the period 2010-2019 amounts therefore to a projected 41 billion USdollars (in constant prices of 2006). Chart 4 Average insured losses per period ($ billion US) $45 bn $40 bn $35 bn $30 bn $25 bn $20 bn $15 bn $10 bn $ 5 bn 0 1970-79 1980-89 1990-99 2000-06 2010-19 Source: own calculations This extrapolated trend suggests that the average losses in the period 2000-2006is roughly equivalent to the average losses for the entire period 2000-2010. In order tobe able to use the historical values to calculate projected actual losses, the assump-tion must be made that the relation between insured losses and total losses will notsignificantly change. The assumption over historical values is not as problematic as it might seem atfirst glance. To take an example, an increased awareness of risk leads to higher in-surance penetration. It is highly probable that this would mean a lower ratio ofinsured losses to total losses. The overall effect would be small. If such a change inratio were not lasting, it would not matter, because of the average reading. However,the quality of the prognosis does depend in the first instance on how stable the frame-work conditions remain. Otherwise, there would be no point in calculating a futuretrend.The following findings emerge:• With a conservative forecast (tight loss parameters) with a factor two it is to be expected that projected average annual total damage in the period 2010 to 2019 will be in the region of a good 80 billion US dollars18.• With a more progressive forecast (broader loss parameters) using a factor of three, the projected annual figure rises to a good 120 billion US dollars.Two things need to be noted about interpreting these figures. First, both estimatesare actually conservative inasmuch as a relatively tight loss parameter (low ratio oftotal to insured losses) is used. From an insurance/technical point of view – bearingin mind that the level of premiums to be calculated needs to be sufficient to coverrisks – the expected losses need to be expressed as unambiguous and quantifiablyas possible. Second is the fact that this deals with averages. Annual total losses can vary con-siderably up or down from this average. An initial indication of the dimensions ofthese annual departures from the trend is shown in Chart 2. Over the past 16 years(from 1990 to 2006) insured losses exceeded their trend values seven times. In three 18 In today’s prices. Nominal amounts for, as anof these years, the variations were considerable: in 2004 the insured losses were example 2010, are calculated with an inflation-more than 150 percent of the trend value. In 1992, they were twice as large, and in ary adjustment 12
    • Risk report Hedging climate change2005 more than three times as high. In line with the logic of the method used, itmeans that annual total losses of up to 400 billion US dollars (progressively calculat-ed) are not merely possible but probable, bearing in mind that the calculations donot even include any extremely rare occurrence. Muenchener Rueck data confirms this conclusion. It finds that between 1975 and2006, total losses exceeded the respective trend value eight times, and by largeamounts: three times well over 150 percent above, three times around 200 percentmore, once well over 200 percent greater, and once almost four times as much19. Another indication that extraordinarily high annual losses need to be reckonedwith can be seen in Table 2. It uses Swiss Re loss reference figures that in giving anidea of the dimensions of damage potential includes rarer and larger natural 19 Again, Muenchener Rueck and Swiss Re calculatethreats. Long recurrent periods have been intentionally chosen because the length using different data limits. But because theof the period under observation the amount of the maximum damage increases. amounts are percentages, the differences do notSuch mega damage occurs rarely, but it does occur. matter. See Topics Geo 2006, 47Table 2Major natural disasters in selected regionsCountry Occurrence Review period Total damage % of GDP Uninsured years (approx.) in $ bn US in %Japan Earthquakes 200 500 11.5 0-95USA Earthquakes in California 200 300 2.3 80-90USA Hurricanes 200 300 2.3 40-60Japan Typhoons 200 50 1.1 60-80Italy Earthquakes 500 50 2.7 70-80Turkey Earthquakes 500 50 12.6 70-80Mexico Earthquakes 500 50 5.9 80-90Portugal Earthquakes 1,000 50 25.9 80-90Britain Storms 200 30 1.3 10-30Canada Earthquakes 500 20 1.6 30-50Australia Earthquakes in Sydney 1,000 20 2.7 30-50France Storms 200 15 0.7 10-30Germany Storms 200 15 0.5 40-60Netherlands Storms 200 7 1.0 10-30Belgium Storms 200 5 1.3 30-50Source: sigma 2/07 13
    • Risk report Hedging climate change Table 2 shows these damage references in selected countries. It deals with esti-mates for isolated events. Often, these events are not independent of each other.As an example, winter storms in Europe can hit the entire continent and not justindividual countries. Swiss Re estimates the 200-year reference damage for Europeat 50 billion US dollars. The future loss potential from natural catastrophes is also notable. Sums of lowthree-digit billions for annual total losses must be regarded as a rule rather than asan exception. At any given time, a rogue occurrence could push the figures muchhigher. So the insurance markets are facing future challenges that demand validparallels from the past. This data also can be placed into another context. The effects of climate changeare not exhausted by large natural catastrophes. In October 2006, Sir Nicholas Stern,former chief economist at the World Bank, presented his report, The Stern Review onthe Economics of Climate Change, for the British government. It was the first econom-ic investigation to contain a comprehensive quantitative estimate of the long-termconsequences of climate change and the possible measures that might be taken20. According to the Stern Report, climate change threatens to become the greatestmarket failure ever seen . It “threatens the fundamentals of human life in the entireworld – access to water, food production, health, and the use of land and the envi- 20 www.hm-treasury.gov.uk/independent_ronment”. The most important consequences for humans and nature are outlined reviews/stern_review_economics_climate_in Box 1. change/sternreview_index.cfmBox 1Global warming has many serious consequences, often involving water:• Melting glaciers bring first an increased risk of flooding, and • Eco systems will be especially vulnerable to climate change, then sharply reduced reserves of water. This would threaten one and a global warming increase of just two degrees Celsius would sixth of the world’s population – mainly on the Indian subconti- be enough to threaten about 15 to 40 percent of species with nent, parts of China, and in the South American Andes. extinction In addition, acidification of the oceans, a direct result of increased carbon dioxide concentrations, would have serious• Declining crop yields, especially in Africa, could mean that repercussions for marine eco systems, with possibly serious con- hundreds of millions of people will be unable to produce or buy sequences for fish reserves. sufficient food. In the medium to high latitudes, crop yields might increase with moderate rises in temperature of between two • Higher temperatures increase the possibility of unleashing and three degrees Celsius, but then go into decline as tempera- abrupt large-scale changes. tures keep climbing. Increases of four degrees and more would probably seriously affect global food production. • Global warming could cause sudden changes in regional weather patterns, such as monsoon rains in south Asia or the• At higher latitudes, the incidence of death linked to the cold El Niño phenomenon. These changes would have serious conse- would increase. Climate change would mean higher death rates quences for the availability of drinking water as well as increas- worldwide because of inadequate nutrition and heat. Diseases ing the likelihood of flooding in tropical regions and threatening such as malaria and dengue fever would spread if no effective the lives of millions of people. preventative measures were taken. • A number of studies indicate that the Amazon rain forests• Rising sea levels would, at temperatures increases of three or four could be susceptible to climate change, and models point to degrees Celsius, mean flooding every year for dozens or even considerable dehydration in the region. One model, for example, hundreds of millions more people. Coastlines in South-East Asia comes to the conclusion that global warming of between two (Bangladesh and Vietnam), of small Caribbean and Pacific islands and three degrees Celsius would be enough to damage Amazon as well as of big coastal cities such as Tokyo, New York, Cairo, and rain forests, perhaps irreversibly. London, would be seriously threatened and pressure to protect them would increase. It is estimated that, by the middle of this • The melting or crumbling of ice layers would threaten land century, 200 million people will be permanently displaced because on which five percent of the human race lives. of rising sea levels, worse flooding, and more intensive drought.Source: Stern Report, Summary, Pages VI/VII 14
    • Risk report Hedging climate changeSome central findings of the report:• The annual losses by the middle of this century would amount to five percent of global GDP.• If non-monetary factors such as health, the extinction of many species, and other non-market effects, as well as the so-called “feedback mechanisms” (which may mean that as the stock of greenhouse gases increases there is a disproportionate rise in warming with each new increment in emissions) are taken into account, the annual damage could rise to as much as 20 percent of world GDP.• On the other hand, the cost of stabilizing global temperature increases at beneath the dangerous threshold of two-three degrees Celsius above the temperatures of the pre-industrial age would amount to “only” one percent of global GDP by 2050.• If stabilization of temperatures were not successful, costs would increase consid- erably.The report’s conclusions are clear: immediate action is easily the best option.Delayed action would from every perspective be much more expensive. To do noth-ing is not a realistic alternative, because the consequences would be incalculable21. The costs of climate change are geographically unevenly distributed. The threatto developing countries is especially serious: climates there are generally alreadywarmer than in other regions and precipitation levels are highly changeable. Devel-oping countries are heavily reliant on agriculture, which is the sector most vulnera-ble to climate. As well, the low level of economic performance makes it difficult toput through measures to adjust and adapt. 21 Such a complex prognosis over such a long period of time is naturally in many ways chal- lengeable. Some of the objections are certainly justifiable. Some evaluations are objectively not clearly resolvable (What, for example, is the monetary value of an extinct specie?) That as it may be, the merits of the Stern Report lie in the fact that, for the first time, the overall conse- quences of climate change have been scientifi- cally analyzed 15
    • Risk report Hedging climate change 3 Catastrophe risk in important markets is heavily under-insured isk-spreading, or general diversification of risk, is among the greatest socialR successes of modern society. In view of the damage potential of natural catas-trophes, efficient insurance markets are of especial importance so that both privatepeople and companies can be protected from ruinous damage. A second benefit is toprevent the consequences of such damage from spreading across entire economies. However, empirical surveys suggest that these markets do not function quiteas ideally. In cases where actual damage exceeds insured damage by a substantialamount, insurance penetration is small. In other words, risks related to naturalcatastrophes (cat risks) are highly under insured. There are considerable deficits incoverage, as data compiled by Swiss Re shows (Table 2).Various studies reveal a series of empirical abnormalities, which also indicate that theefficiency of catastrophe-risk markets is not high22:• A large proportion of catastrophe risks are not insured. Large industrial firms tend to insure themselves. Policies that offer cat-risk cover are often inadequately reinsured. In total, risk sharing functions much better with small/medium risks than with major risks. It can be said that the diversification of cat risk is not opti- mal.• Cat risk premiums for both insurance and reinsurance are very expensive in some markets. They can amount to as high as seven times as high as expected losses23. Pricing is sometimes inefficient.• Premium changes depend to a large extent on the appearance of natural catastro- 22 See Froot (2001), Cummins (2006) and phes. After Hurricane Andrew, in August 1992, premiums rose sharply. After the Jaffee/Russell (1997) Northridge (Los Angeles) earthquake in 1994 and when no further major events 23 See Froot (2001): 539. The level of expected occurred, they eased somewhat. (see Chart 5) Demand for cat-risk insurance is losses for each respective period are regarded as also occurrence dependent. a benchmark for a “fair” premium. HoweverThis occurrence dependence indicates that the market players do not act rationally there can be objective reasons for surcharges onand/or that mistakes are happening in the market. It is difficult to establish why the premiums. See text for more on this 16
    • Risk report Hedging climate changeabsence of a catastrophe during a relatively short period should result in either areassessment of projected losses (and thus premiums) or of demand. On the otherhand, the appearance of a catastrophe can cause a reassessment of risk providedthat new information (over, for example, the level of damage) emerges. But onlythen. There is no automatic actuarial context between the occurrence of a catastro-phe and changes in premiums. This all goes to show that the global market for cat insurance is decided by oc-currence-driven cycles. Chart 5 appears to confirm this. The Rate-on-Line-Index is ameasurement of the tone of the market. It is defined as the relation between insur-ance premiums on the basis of reinsurance policies to the maximum agreed cover-age in those policies. A higher index hints at a “harder” market phase. When big losses occur as a resultof a major occurrence, reinsurance capital becomes rarer and reinsurers are pre-pared only to offer a narrow range of coverage. At the same time, awareness of risk,and thus the demand for insurance cover normally rises to a high level. Because oftheir strong positioning on the market, reinsurers can achieve high premiums forrelatively low levels of cover (higher index). If no further catastrophes strike, then, over time, market relations change. Rein-surers have more capital because of profits. Then, lured by attractive conditions,new capital comes to the sector. Awareness of risk declines, and thus the demandfor insurance cover. Premiums begin to sink (on average to as low as 50 percent oftheir peak levels), and the market enters a “soft” phase with low premiums and rela-tively high amounts of cover in money terms (lower index). The ideal type of situation pretty well reflects reality, as is shown in Chart 5. Theindex rose sharply, principally because of Hurricane Andrew, but then, after 1993,went into a long decline. However, 11 September 2001 and a generally tougher mar-ket conditions at the turn of the century again ushered in a “hard” phase. Chart 5 World Rate-On-Line Index: catastrophe reinsurance 400 350 300 250 200 150 100 50 0 19 19 19 19 19 19 19 19 19 19 20 20 20 20 20 20 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 Source: Carpenter (2005) Similarly, the years 2004/2005 show that this development does not take placeautomatically and that record catastrophe years do not always lead to ever higherindexes. New insurance capital (Bermuda-registered reinsurers) and general factorssuch as advances in cat models (ascertaining premiums that are adequate to coverrisk) have a dampening effect on the Rate-on-Line Index. 17
    • Risk report Hedging climate change Business for primary insurers is even more cyclical. Chart 6 shows the underwrit-ing cycle of United States property insurers. The operational yields (in percent) pro-vide data about the profitability of pure insurance business (underwriting policy)that is determined by the relation of premium income to paid compensation claims.On the other hand, general yields also take into account results from the financialassets. Chart 6 Yields of US property insurers (%) 15 10 5 0 79 81 83 85 87 89 91 93 95 97 99 01 03 -5 19 19 19 19 19 19 19 19 19 19 19 20 20 -10 -15 -20 Source: A.M. Best General yields Operational yields Company, according to Cummins (2006) Here, the influence of major occurrences becomes especially clear. Followingon the heels of the big insurance crisis at the beginning of the eighties, a numberof losses as a consequence of catastrophes (Andrew in 1992, the Northridge Earth-quake in 1994, and the World Trade Center attack in 2001) ushered in “hard” marketphases24. The extent of under insuring as well as an inadequate level of functioning riskdiversification raise the entire issue of the insurability of catastrophe risks. Whichis dealt with in the next section. 24 For more on the indemnity insurance crisis see Lai and others (March 1997). For an outlines of major insured losses in the USA, see Litan (2006 b): 16 18
    • Risk report Hedging climate change 4 Are catastrophe risks capable of being efficiently insured? nsurers take on risks and then diversify by grouping similar risks in a collective.I This spreading of risks in a group works best when it deals with many individualrisks of limited extent and not connected with one another. One example of this ismotor vehicle insurance. In this case, the total losses vary relatively little from yearto year. This enables simple premium strategies. For example, premiums can beadjusted to the average losses of the past three years25. In such situations, the insurer can assume that, in any given period, premiumincome will essentially be sufficient to cover insured losses. Of course additionalcapital is required as a buffer just in case total losses in any given year are unexpect-edly high. But this demand for capital is relatively small and visible at a glance be-cause losses and premiums develop overwhelmingly constantly and in accord withone another.These examples allow various criteria that are relevant to the insurability of risks to be elabo-rated (in Box 2, insurability is dealt with using mathematical and statistical yardsticks):• A large number of people need to be exposed to a certain risk. They then form a group within which risk spreading can take place. The insured must be averse to risk. This implies a readiness to use financial means to transfer the risk to a third 25 Of course determining levels of premiums is party. subject to other factors such as the competitive• A private offer to insure these risks comes about when the insuring company is in situation. But on the issue of risk insurability this a position to levy an appropriate premium. The prerequisite is that the probability is a secondary matter of occurrence and the extent of damage can be reliably estimated. This applies 26 An ex-ante moral hazard emerges in the case of particularly in “high-frequency – low-severity” risks (as in the above example). catastrophe risk, for example, if, after an insur-• Occurrence and extent of damage must not be subject to influence by the insured ance policy has been signed, prevention meas- party. If that were the case, the moral-hazard situation might come into play. This ures are not taken. An ex-post moral hazard situ- might take the form, for example, where the insured party is more prepared to ation arises when the insured party desists, after take risks than he or she would be without insurance. The result of this would be the outbreak of a catastrophe, to act to limit the doubts about the calculability of risks26. extent of that catastrophe (Pfister 2003: 12) 19
    • Risk report Hedging climate changeBox 2Insurability and risk classification27In mathematical terms, insurability rests on two laws of statistics: requirements per policy strive towards zero. This lends weight tothe law of large numbers and the central limit theorem. Losses the conclusion that the insurer remains solvent if he determinesresulting from exposure to a risk can be interpreted as a random the premium approximately with the aid of the projected damage.variable. Damage occurring within a certain period forms a random Insurance markets with many identically spread , independent riskssample of this random variable. In accordance with the law of large with moderate variations are consequently locally insurable (=numbers, the middle value of this random sample tends “almost only through the primary insurer).certainly” to move against the expectancy value of the randomvariable, provided that the extent of the random sample equates With increasing capital requirements, reinsurance becomeswith a desired size. In an insurance context, this means that the important. This is the case with large variations and less identicallyexpected losses (= the fair premium) can be reliably approxi- spread but statistically independent risks. If the risks are correlatedmated with the help of a middle value of realizations from the pre- among each other, then the capital requirements per policy risevious period provided we are dealing with a high-frequency risk rapidly in line with the number of risks. Instead of risk spreadingunder which many cases of realizations (large random sample) are inside the group, the accumulation of risks becomes a threat.available. Alternatively, these many cases of realizations made by Under certain circumstances, reinsurance can even here step in.insurers (collective) inside a year can be equated with identically Locally dependent risks can be globally independent. Take thedistributed random variables (same risk). On the other hand, medi- examples of losses caused by tornados in the Mid West of the Unit-um levels of losses give a reliable approximation of the expected ed States and Australia. The reinsurer can also diversify in that hedamage (fair premium), provided the group and thus the number retains a global portfolio containing many risks that are independ-of realizations is high. ent of each other. Locally uninsurable risks that in this way, with the help of a reinsurer are globally diversifiable, are termed globallyThe insurer, however, needs to retain capital in case of unexpected insurable risks. With an increasing dimension of these risks, tradi-losses. These capital requirements can be calculated with the aid tional reinsurers however do push up against limits, so that newof this central limit theorem. Then the (standardized) spread of methods of risk diversification become crucial. (see Chapter 5.1)unexpected losses (= total of damage minus premium income)tends with increasing random surveys (large collective) against thenormal distribution. It transpires that in a large group, identical andindependently spread risks with relatively small variations of capital If all the above criteria are fulfilled, then conditions are ideal and the process ofrisk spreading functions optimally in the group. But for natural catastrophes, the cri-teria are either not or only partly fulfilled because with catastrophe risks (cat risks),it is a matter of “low-frequency – high severity” risks. From an actuarial viewpoint,this has weighty consequences.1. Problem: the predictability of occurrence likelihood and loss levels. In the case offrequently occurring damage, the insurer has possession of sufficient data to be ableto calculate, with the aid of statistical processes, a “fair premium.” However, naturalcatastrophes are a relatively rare occurrence. Which is why the amount of dataavailable to calculate the probability of losses in the future is low. This means theprojections are loaded with considerable uncertainty. Another difficulty is that in the case of extreme occurrences, the spectrum of pos-sible damage is extreme. This is because the damage caused by a hurricane doesnot entirely depend on storm strength but also on the route it takes. Between 1950and 2000, there were a total of 51 cases of major damage caused by natural forces28.The next table outlines the extraordinarily large spectrum of damage. 27 For a more formal account, see Cummins 2006: 342 28 Occurrences causing damage of at least one bil- lion US dollars and/or claiming at least fifty lives were included. See American Re (2002) 20
    • Risk report Hedging climate changeTable 3Historic damage in $ billion US Earthquakes Hurricanes Flooding (6 cases) (27 cases) (18 cases)Maximum 51.3 37.0 25.1Median 2.7 3.0 1.6Minimum 0.1 0.9 0.1Source: American Re (2002) Natural catastrophes might occur rarely, but the damage they cause varies enor-mously. Future incidence often varies considerably from past incidence. This is shownby the example of Katrina in 2005, where the total economic damage is estimated ashigh as 170 billion US dollars. This exceeds by a factor of four the next most devas-tating hurricane between 1950 and 2000. If the level of future projected damage does not allow itself to be adequately deter-mined, this has consequences for premium calculation. Security loadings are leviedon the presumed projected level of damage. Because the insurer himself is riskaverse and, in view of the scale of the possible damage, becomes worried about hisown solvency, these loadings can either be pretty high and/or the insurer reduceshis offer or even declines to offer cover at all.2. Problem: high capital requirements. With natural catastrophes, occurrence pat-terns of the damage is highly variable from year to year, and thus inconstant. Inmany years, damage is slight. In rare cases, mega damage is the threat. As a result,premiums and damage trends are to a high degree not synchronized. The followingtable illustrates the point using Californian earthquake insurance.Table 4Annual losses as a percent of premium income (1972-1994)72 73 74 75 76 77 78 79 80 81 82 83 84 850.0 0.6 3.4 0.0 0.0 0.7 1.5 2.2 9.2 0.9 0.0 2.9 5.0 1.386 87 88 89 90 91 92 93 949.3 22.8 11.5 129.8 47.0 17.2 12.8 3.2 2,272.7Source: Jaffee/Russell (1997) Where coverage involves small risks and many claims (such as motor vehicleinsurance), payments is made in the group within a certain period, usually a year.In the case of rare and high losses risk diversification takes on a time dimension(intertemporal diversification). The catastrophe insurer must at all times haveaccess to considerable amounts of liquid capital, apart from premium income, incase catastrophe losses exceed premium income by a hefty amount. 21
    • Risk report Hedging climate change As an illustration, if we assume a one percent occurrence probability per year,then annual premiums equate to one hundredth of the calculated loss29. This meansthat capital required in a case of catastrophe can be as much as one hundred timeslarger than the premium income in the year the catastrophe occurs. The risk thatthe catastrophe occurs before the insurer has collected a sufficiently large propor-tion of premium cash (including interest) is termed “timing risk.30” There are various ways of going ahead with intertemporal diversification. Themost common ways are self- and reinsurance31. With self insurance, the primaryinsurer backs the catastrophe risk with own capital. In view of the sums that arehere involved, this version has limits. The funds needs to be in the forms of liquidassets, and thus subject to low-interest rates. If an effort to cover the cost of owncapital through the equivalent loading on the insurance premium, the yield on capi-tal sinks. Expensive and rare capital thus limit the underwriting capacity of theinsurer. A high reserve of cash then makes the firm an ideal target for a takeover32. 3. Problem: sufficient reinsurance capacity? With catastrophe losses, the primaryinsurer cannot manage without risk transfer. The risk-transfer capacity then becomesthe limiting factor of cat-risk underwriting capacity. From 2000 to 2005 the annualaverage level of insured losses from natural catastrophes worldwide amounted toabout 30 billion US dollars (Chart 5). The narrowly defined annual total damagewas estimated at between 60 and 90 billion US dollars (factors two or three). By con-trast, reinsurers had available a worldwide average of about 300 billion US dollarsin capital33. At first glance it might seem that there was more than enough capital to insurenatural catastrophes. The truth is however that such a global comparison is more orless irrelevant. First, it deals with average losses. As was shown in 2005, actual totaldamage can be much higher. In addition, the estimate in Chapter 2 shows that in thefuture much higher levels of damage must be reckoned with. Second, reinsurers useonly part of their capital for natural catastrophe risks. Some reinsurers avoid thismarket altogether. Third, in the case of “low-frequency – high severity” risks, reinsurers face funda-mentally the same problems as primary insurers. For example, they are confrontedwith similar uncertainties with regard to projected damage. In such a situation,much depends on the building up of trust in insurance markets. Stable, persistingbusiness relations between primary insurers and reinsurers depend on a commonconsensus that losses long-term need to be spread between them. If such a relation-ship exists, then neither side need fear any short-term duplicity. A failure of the mar-ket through uncertainty in the event of catastrophe damage would be highly unlike-ly, if not eliminated. In this relationship between primary insurers and reinsurers, it seems as if theissue of a fair division of burden pales into insignificance. Business relations are be-coming less stable and clearly increasingly decided through short-term yield consid-erations. This is a trend that undermines the capability of the sector to cover extreme 29 It is assumed in the interest of simplicity that arisks. The reinsuring capacity in catastrophe risk depends not only on capital avail- (fair) annual premium works out as the equiva-ability but also on the nature of the business relationship between primary insurer lent of the projected value of an annual lossand reinsurer34. 30 See Litan (2006a, 2006b) The above three problem areas describe the specific difficulties involved with cat 31 In the next section, further possibilities (capitalrisk. By comparison, the moral risk of catastrophe insurance plays no major role. In- markets, state means) will be discussedsurers have learned to cope with such mistaken incentives. Fund retention, maximum 32 If an insurer possesses a degree of liquidity tocoverage levels and other contractual regulations such as adhering to regulations finance a catastrophe with an assumed ten-yearand safety standards can here, as in other insurance fields, be deployed to mitigate recurrence periodicity, then an investor couldagainst such erroneous courses of action. take over the insurer in the first year, not renew Another often mentioned reason for market failure is “adverse selection”, which the insurance policies in the second year, andis the choice of bad risks. In the case of asymmetrically distributed information, the use the capital elsewhereinsurer is unable to distinguish between “good” and “bad” risks. In such a situation, 33 See Cummins 2006: 347there is the danger that people exposed to an over-average risk can insure themselves 34 See sigma 4/05 22
    • Risk report Hedging climate changetoo cheaply. This comes at the expense of people exposed to below-average risk. As aconsequence the insurer is threatened with a concentration of bad risks. In connec-tion with natural catastrophes, any information advantage can, however, assumedto be on the side of the insurer. Adverse selection can be said to hardly play a role. Overall, this is the picture: The market error we’ve been dealing with here isdirectly related to the specific characteristics of natural catastrophes. The high levelof under insurance becomes comprehensible. On one side, many primary insurers,because of the existent uncertainty in relation to probability of occurrence and levelof damage, are right from the outset opposed to entering the market. On the other,premiums are high because of loadings (uncertainty, timing problem, and capitalcosts) . And, just as in every other market, high prices dampen demand. The event-driven cycle now makes sense. The intertemporal diversification of low-frequency –high severity risks is created only with certain difficulties. Serious catastrophes there-fore usually imply large unexpected losses. This forces the insurer to limit the offerand demand higher premiums, or to abandon the market altogether (harder market). 23
    • Risk report Hedging climate change 5 Path to the futureClimate change has long been a reality. Over the next decades, natural catastropheswill have an increasingly destructive effect, even if many details are still disputed35.There can be no doubt that catastrophe risk will increase for millions of people. Whichleads to the question of how the efficiency of markets can be improved to better copewith these risks.5.1 Extending the insurability of Cat Risk rivate insurers are working at extending insurability borders and thus openingP up new avenues for insuring weather-related catastrophes. Two developments inparticular should be mentioned: the construction of catastrophe models and the useof capital markets for risk diversification. As we have seen, weather-related natural catastrophes embody an extreme chal-lenge for the insurer. The potential damage is very high, and the nature of the eventitself unpredictable. Once, insurers relied mainly on figures derived from experienceto determine projected levels of losses. That changed with Hurricane Andrew. Thiscaused levels of damage (see Table 1) that, at the time, were not considered possible.Since then, work on so-called catastrophe models has been intensified. Apart fromthe large insurance companies, special firms such as Risk Management Solutions(Newark, Calif.), Applied Insurance Research (Boston, Mass.), and Eqecat (Oakland,Calif.) are also involved in this work. The aim is to improve the precision of project-ing the probability of and the damage caused by certain catastrophes to improve 35 See for example the summary of discussion overthe insurability of these risks. the causes of hurricanes in Kunreuther/Michel- A catastrophe mode is based on four fundamentals, as shown in Chart 7 36. Kerja (2007): 13 36 See Kunreuther/Michel-Kerja (2007) 24
    • Risk report Hedging climate change Chart 7 Structure of catastrophe models Risk factors Vulnerability Damage (= Physical effects) (= Monetary loss Portfolio To arrive at a precisely defined risk, parameters of all dimensions that exert asubstantial influence on damage are specified as exactly as possible and the rela-tionship between them assessed in line with model requirements. As an example,an insurer wants to know what levels of losses he faces if a hurricane hits a certainregion. Then factors that determine the character of the hurricane such as windstrength and storm path are entered in the risk factors module. After that, the port-folio is identified. This contains information such as insured property in geographi-cally localized regions, together with characteristics such as type of construction,number of floors, and age. Using this as a basis, the physical effects of the hurricaneare calculated. Then, the monetary loss is arrived at. A distinction is made betweendirect losses and indirect losses such as those through production interruptions,for example. Such a model can be used for simulation. For example, for a strength-5 hurricane,a large number (1,000 or if necessary, many more) of different potential routesthrough a certain region can be calculated using a computer. The result is a patternof theoretical distribution of damage that gives the insurer an idea of the spectrumof possible damage and its probability of occurrence. In an ideal case, the model issufficiently efficient (in the sense of being close to reality) for the insurer to use thecalculated fictional factors (probability of occurrence, damage) to calculate premi-ums. This leads to a large range of catastrophe-risk coverage offers with attractiveconditions (reduced security loadings). Catastrophe models serve in the first instance to reduce the inherent uncertaintiesover cat risks. But diversification also comes into the picture. As has been shown, it is 37 See Swiss Re (2002)not enough for reinsurance to provide for adequate intertemporal diversification of 38 Since December 1992, futures contracts (CATmajor risks caused by natural forces. futures) have been traded on the Chicago Board It is appropriate to proceed with diversification over capital markets, because the of Trade’s (CboT) catastrophe insurance indexes.potential damage in relation to market capitalization is relatively small. Alone the These also enable a transfer of CAT risks. Butvalue of average fluctuation of all the net assets traded daily in the USA amounts to these CAT futures or CAT options (introduced133 billion US dollars37. That figure is significantly larger than the greatest case of in- on CboT in 1995) have so far have not been ablesured loss and is round about the level of total damage caused by Hurricane Katrina. to establish themselves. Trading has been low, Larger insurers (and investment bankers) have therefore developed a number of for reasons principally to do with credit risks in-capital market instruments that enable intertemporal risk diversification. The most volved. Their utilization possibilities are investi-important instruments today are formed by cat bonds38. Chart 8 illustrates typical gated by Albrecht et al (1994) . For a brief over-trading patterns for this class of asset. view of other instruments of risk transfer, see for example, Krenn/Oschischnik (2003): 76 25
    • Risk report Hedging climate change If an insurer wants to transfer the catastrophe risks of his portfolio to the capitalmarkets, he sets up a so-called Special Purpose Vehicle to issue the bond. The incomeis invested as safely as possible in securities of the highest credit rating. At the sametime, the investment vehicle insures the insurer against a precisely defined catastro-phe, for which an annual premium is paid. Chart 8 Cat Bond payment system Insurance One-time capital premiums payment Investment Insurer Investors vehicle Cover Coupon payments Nominal Risk-free value interest Security with highest credit rating In most cases, cat bonds are subject to variable interest rates. The coupon paymentemerges from the relevant money market interest (LIBOR) level plus an interestloading . The investment vehicle finances these interest payments with earningsfrom safe bonds (risk-free interest) and insurers’ premiums. Embedded in the security is an option on the event. If an event does occur, then,in the simplest case, the bond plus interest simply expires39. The vehicle immediate-ly sells the safe bonds and pays the insurer the agreed coverage. If the event does notoccur, the investor gets back the nominal value of the catastrophe bonds at maturi-ty. This, in turn, is financed through the sale of safe funds. After payments have been completed, the investment vehicle is dissolved. Asidefrom the legal and taxation advantages of this system, there is another importantadvantage. Where the insurer himself is the issuer, investors would be affected byany possible insolvency of the insurer, and would therefore need to be paid an equiv-alent amount because of this additional credit risk. But this is here not the case be-cause the vehicle and the funds it holds are not part of the insurer’s body of assets.This is also an advantage for the investor because he is now offered the chance of 39 A great number of variations is possible. Thepure play in catastrophe risks40. coverage can be limited merely to future inter- est payments and/or part of the nominal value.The most important cat bond parameter is the trigger event that causes the option. There Basically what counts is: the smaller the cover-are various types. Among them41: age, the better the investment vehicle rating• Indemnity-based trigger. The trigger here is a certain loss by the insurer’s business. 40 Strictly speaking this is not quite right because In this case, there is no basic risk for the insurer. That means that the insurer is he is still exposed to other risks, although these completely safeguarded through the cat bonds because the loss equates precisely are of a subordinate role: a money market risk with the agreed level of coverage. From the investors’ point of view this approach (LIBOR), a risk of liquidation (either no or a tight has the disadvantage that the insurer under certain circumstances can influence secondary market) and possibly to a currency the trigger event to his own advantage. Equivalently large is the investors’ need for risk information in relation to the insurer’s business policies. 41 See Pensa (2004), 14 26
    • Risk report Hedging climate change• A market-damage based index. The trigger here is a decline in an index that reflects the exposure of a group of insurers. There is no chance of exercising any influence. The basic danger can be considerable if the risks or their weight in the portfolio vary greatly from those of the group.• Model losses as trigger. This is where a catastrophe model offered by one of the firms specializing in such models are used. In using the parameters of a real occurring catastrophe, the calculation is made to assess whether the “model damage” exceeds that of the contractually laid-down loss trigger or not. In such a case, the basic risk is small (provided, as pointed out above, the portfolio of the insurer is adequately taken into account). For investors, this trigger is usually the least transparent.• Physical trigger. The occurrence of a catastrophe is tied to certain objective parameter values. For example, a hurricane must reach speeds of at least 200 km/h to qualify as a catastrophe. The approach is interesting for both investors and rating agencies because it is extremely transparent. On the other hand, the basic risk can be high.• Parametric indexes. The majority of today’s cat bonds are based on this trigger type, which is a further development of the physical trigger (second generation). Objective measurable factors relating to the exposure of insurance in certain regions are summarized in an index . When a catastrophe occurs, the level of cov- erage is determined by a stipulated formula (Box 3). In an ideal case, the insurer’s loss is adequately approximated (small basis risk) while the investors need for transparency is taken into account.As can be seen, the various loss triggers are viewed differently by insurers and in-vestors. As a rule, there is a discord between, on the one hand, the basic risk of theinsurer and, on the other, the objectivity and transparence of the method. On top of that, the characteristic of a catastrophe bond is naturally determined bythe size of the spread. This depends largely on the price of the option. Further riskssuch as, for example, a minimal liquidity of a bond or the investment vehicle’s rat-ing likewise influence the size of the interest loading. Regrettably, no generally acceptable valuation formula exists for these catastro-phe options. Options prices are independent of the dynamic of the so-called under-lyings. In the case of share options, these are the movement of a relevant share.Because the dynamics of catastrophe damage is considerably different from assetstraded on the finance markets, proved options price formulas (for example, that ofBlack-Scholes) cannot be used. Instead, methods that are tailored to the relevant catbonds, such as simulation, are used.This is however not without problems if the level of information of the involved partiesis either different or not high. Problems can emerge if:• the insured damage is submitted only after a long delay• the assets of the catastrophe model are not clearly clarified• or the know how is concentrated one-sidedly with the insurerWhere is the attraction of cat bonds for the investor? A central role is played by port-folio aspects. Cat bonds are not regarded in isolation but in relation to the portfolioof a potential investor. As a rule, they have very advantageous correlation properties.And even if it cannot be entirely ruled out that the occurrence of a natural catastrophewill cause a price collapse on capital markets, this is fairly unlikely42. On the other 42 The S&P 500 lost more than 12 percent in fiveside, a crash of financial markets cannot cause a natural catastrophe. Cat bonds trading days after the reopening of the stockshow no (or an extremely small) correlation with financial issues already being exchange after the attack of September 11trade by the market. In the jargon of portfolio theory, the beta factor is zero (or very 43 In other words, they can drive their efficientsmall)43. Investors can successfully diversify their portfolio by acquiring cat bonds. frontier upwards and achieve a high portfolio A further argument in favor of buying these securities is their attractive yield. yield with the risk remaining the same. EmpiricalBetween 2003 and 2006 the spreads of various cat securities amounted to between examinations confirm this. See Pensa (2004): 19 27
    • Risk report Hedging climate change200 and 900 basic points44. This means that catastrophe securities yields are amongthe highest. However, in the case of long-term yields, much depends on whether alarge catastrophe occurs. The uncertainty of catastrophe predictions is reflected inprognoses relating to catastrophe securities. Box 3 contains a case study in which the first cat bond issued by Allianz SE is shown. 44 See sigma 2/7: 9Box 3Marc Hannebert, head of reinsurance strategy at Allianz Global Corporate & Specialty AGThe new Allianz Cat BondOn April 10, 2007, Allianz Global Corporate & Specialty announced in which the expectations of both the sponsor (insurer) and thethe successful offering of an innovative catastrophe security in an investor were fulfilled. A sponsor doesn’t want to concede theamount of 150 million US dollars. The cat bond provides protection investor a too-detailed insight into the state of assets, risk manage-against high severity losses incurred from earthquakes in Canada or ment, underwriting or claims settlements, as is necessary in thethe United States, not including California, and river floods in Great case of indemnity based trigger. This is why a parametric triggerBritain. The multi-peril issuance is part of a one billion dollar program was selected. The challenge here was to construct an index thatby Blue Wings Ltd, a special purpose vehicle launched by Allianz was robust and transparent enough to satisfy both investors andGlobal Corporate & Specialty. The emission was fronted by Swiss Re rating agencies and, at the same time, to keep within limits thewhich also acted as arranger and lead manager. The bonds offer a basic risk for the sponsor, Allianz.return of 3.15 percent over LIBOR and have a Standard & Poor’s The architects of the bond drew up what might be called a “vir-BB+ rating, and the insurance risk, modeled by Risk Management tual infrastructure”. This, administered by the Halcrow Group, aSolutions (MRS) is 0.54 percent per annum. This means that in- British firm of consulting engineers, enables the parties involved tovestors must reckon with an annual loss of 0.54 percent of their measure with a high degree of precision the flood levels in moreinvested capital. But in reality there is a high probability that inside than 50 places throughout Britain (the system is illustrated in thethe maturity period of six years no triggering event (catastrophe) chart). The measurements are fed into the index formula, whichoccurs, for which capital from the bond would have to be used. As determines if and to what extent the investors lose their investeda result, the chances of a worst-case scenario in which the invest- capital.ment is totally lost is small. The cover is fully collateralized with Likewise new was the readiness of investors to invest in a catminimal credit exposure. bond, although because of the new infrastructure it was not possi- Earthquakes in Canada and the United States – except California – ble to ascertain retroactively the performance of the trigger (highand severe river flooding in Britain were chosen because they water index) for any previous periods. Instead, the investors reliedrepresent high risks that are insufficiently covered by existing rein- on an estimated distributive curve within the index that was estab-surance. The trigger for earthquakes is based on modeled losses lished by Risk Management Solutions (RMS) from its still unsur-using data from the United States Geological Survey. The modeled passed flood model for Britain.insurance risk from earthquakes was 0.43 percent. The trigger for The bond found a large resonance in the market. Demand wassevere river flooding is based on a parametric index of the second heavy. It is the aim of Allianz Global Corporate & Specialty as wellgeneration. The modeled insurance risk by river flooding in this as the Allianz Group to strengthen their competence in this fieldregion was 0.11 percent (a total of 0.54 percent).The parametric and make available such products to customers both medium andindex trigger for river flooding is the most innovative part of the long term.project. It enabled for the first time an insurer to issue a cat bond Vertical distance – reference point flood depth Pre-event Post-event For each reference location specified in a measurement notice, the vertical dis- Reference point Reference point tance (v) is the vertical distance (measured by the measurement agent within the relevant measurement window) between each relevant reference point Flood watermark Ground elevation and the corresponding watermark. of reference location For each reference point satisfying the measurement conditions, the reference point flood depth (d) is calculated with the formula: d = r – v Where: r is the difference between the elevation of the reference point and the v r ground elevation of the corresponding reference location (as measured during } d (calculated) the establishment of the reference point and listed in a schedule), v is the vertical distance of the respective reference point Source: Swiss Re Capital Markets 28
    • Risk report Hedging climate change The next chart shows how the market of Cat Bonds developed until March 2005. Chart 9 Cat Bond issues (1997-2006) Volume of Cat Bonds Number of in $ bn US emissions 5 25 4.5 4 20 3.5 3 15 2.5 2 10 1.5 1 5 0.5 0 0 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 Source: Marsh & McLen- non Securities (2006): Cat Bonds in $ bn US Number of emissions The Catastrophe Bond Market at Yearend 2005 Annual issuing totals of a maximum of 4.7 billion US dollars and in total a volumeof about 15 billion US dollars of issued securities are fairly modest levels45. However,the trend of emitted cat bonds is showing in an upward direction. Yet, as of today, themarket for cat bonds could not meet all expectations. One reason might be the prob-lem of valuation. Expected advances in the modeling of catastrophe risks will bringwith them adjustments. Also, some insurers regard the bonds as somewhat expen-sive. It has been shown that, so far, cat bond spreads lie clearly above reinsurancepremiums. Another possible explanation is the high transaction costs, because most of thetime a large number of external experts such as investment bankers, lawyers, spe-cialist firms, and actuaries are needed. More explanations indicate a low level ofliquidity, a shortage of experience with these securities, and a lack of interest byinvestors. In the event, insurance companies in 1999 turned up on a large scale asbuyers of cat bonds (primary insurers with a market share of 30 percent, and rein-surers with one of 25 percent). So insurers dominated both side of the market, sup-ply and demand. But by 2004 this had fundamentally changed. Only seven percentof bond underwriters were now from the insurance industry. The interest amonghedge funds, specialist cat bonds, and other institutional investors had also in-creased significantly. A major part of the problem seemed to be traceable back to typical teethingtroubles. The potential of the financial markets in relation to the intertemporal 45 The first large wave of issues was in 1997. Thediversification of cat risks is in any case enormous. Now, it is a matter of improving current annual volume of issues is a good threeon this potential. Insurers can also contribute to this by , for example, make cat billion US dollarsbonds contractually more attractive46. The ability of insurance markets to function 46 Froot (1998) names the following elements thatis not least dependent on the efficiency of capital markets. positively influence the success chances of a cat-bond issue: a higher excess, a larger volume because of the high fixed costs, transparent triggers, and marginal incomes that are not too high. Implicit in the last is a low probability of loss and an equivalently low bond rating that does not justify the issuing price 29
    • Risk report Hedging climate change5.2 Rethinking the role of the state nadequately functioning insurance markets in relation to natural catastrophesI serves to put politics under heavy public pressure to become engaged in the field.When a catastrophe does strike and cause damage, as a rule the state steps in andmakes available a wide range of resources. This ex-post help, while understandable,is not without problems. For a start, it contains considerable fiscal/political risks. In the case of Katrina,assistance from the US federal government in the form of expenditure and tax reliefamounted to more than 100 billion US dollars. A major part went on compensationfor storm damage that was not covered by insurance, although that would have beenpossible47. Second, state assistance is unfair, inasmuch as it comes from general taxation andis thus financed by the entire population. It does not make sense for people who vol-untarily live in an endangered area to be supported by the rest of the population. Third, this form of aid is inefficient, because it creates a false set of incentives. Itleads to a variation of the “samaritan dilemma”: state support after a disaster under-mines the motivation of people who are potentially affected to carry out risk-reducingmeasures in advance of a possible catastrophe. This low level of insurance penetra-tion in expectation of assistance in turn simply increases the pressure on politics toextend assistance. This threatens to become an ever stronger self-propelling cycle. A higher level of penetration for cat risks is therefore lies in the state’s own inter-ests. This is hardly a new phenomenon. Many countries run programs to guaranteethe availability of cat insurance in cases where the private sector offers either inade-quate coverage or no coverage at all 48. Although these programs show significantlydiffering financing structures and means of operating, most do pursue similaraims49.• Extension of the insurance protection on offer, or even creating an equivalent market if no private coverage is available.• Limitation of household risks to natural catastrophes.Just as in the private sector, a state insurer can also function basically as either a pri-mary insurer or a reinsurer. A well-known example of a public primary insurer is the 47 Protection against flood damage was offeredFederal Flood Insurance Program (NFIP) in the USA50. Insurance protection against by the National Flood Insurance Program. Theflooding was for the first time offered by private firms in the late 18th century. But insurance penetration among house owners inheavy losses caused by floods in the Mississippi in 1927 prompted most insurers to Louisiana communities affected by Katrina var-pull out of this market. Over the next forty years, insurance coverage against flood- ied between 57.7 percent (St. Bernard Parish)ing was limited to a few private firms. The risks, because of the concentration in spe- and 7.3 percent (Tangipahoa Parish). In Orleanscific regions, and because of the sheer amount of potential damage, made this mar- Parish, 40 percent were insured. See Kunreutherket appear to be uninsurable. (2005): 3/4 In 1968, Congress approved the National Flood Insurance Program (NFIP) . At the 48 A special role played here in recent times is ter-moment, the federal government is the primary insurer of coverage against damage rorism. Since the September 11 attacks, theseto private houses and small business caused by floods. Private insurers market the risks also count among major cat risks. StateNFIP and administer claims settlements. Participating communities in endangered involvement appears both necessary and sensi-regions are under obligation to ensure that building plans and safety standards ble. First, these risks are not exclusively privatelyinclude factors to mitigate against flood damage. It is also envisaged that the NFIP insurable. Second, there is here a general overallwill finance itself so that, in the long term, no taxation funds will be needed. interest by society that justifies the use of tax In August 2006, there were almost 4.6 million insurance policy holders in 20,000 resources. Coverage of terrorist risks often takescommunities in the USA. In the period from 1968 until August 2006, the NFIP paid place in the form of partnerships between privateout 14.6 billion US dollars in compensation for insured damage. At first glance, it enterprise and public authorities. See attachmentseems that the NFIP has been a success. It has meant that the range of insurance on in sigma 4/2005offer has been significantly extended. 49 For an overview, see OECD (2005) 50 See Cummins (2006): 357 30
    • Risk report Hedging climate change But the truth is that reforms are urgently needed. Premiums are not appropriateto the risks and coverage is as low as 35-40 percent of expected damage. After theyear of record damage in 2004/5 (Table 1) the NFIP is practically insolvent. About 25-30 percent of the compensated damage claims fall into the category of “repetitive-loss properties”, properties for which compensation claims have been settled sever-al times over. This leads to the conclusion that the incentive to take damage-preven-tion measures that is meant to be in place simply does not exist. Finally, insurancepenetration is inadequate. Even in the most endangered regions, only 50 percent ofhouse owners, at best, are insured. The faults of the NFIP are not isolated. State primary insurance programs areoften trapped in various forms of inefficiency. Subsidized policies can “crowd out”private insurers or inhibit their market penetration. Public programs are exposed tomassive lobby interests. Subsidized premiums create “moral hazard” problems.High administration costs (public servants placed in privileged positions), lack ofknow how, and the lax handling of tax money can cause further problems. The deficits associated with state-run primary insurance programs can generallyavoided if the following principles are observed51.1. Private insurers should as far as possible be involved in the state program. State insurance programs should back the private market or supplement it, but not replace it.2. If state programs are needed, their design should, as far as possible, imitate the proven structure of private markets.But this results in a paradoxical situation: if an efficient state primary insuranceprogram against catastrophe risks should imitate as far as possible private marketstructures, why have a public program at all? Clearly it would make more sense ifthe state in the first place took the trouble to create the basic conditions to enable afree-market coverage of catastrophe risks. What is needed therefore is not so muchstate primary insurance but, instead, appropriate cooperation between private in-surers and public authorities. The example of Britain shows that flood risks are infact insurable on the free market. 51 See Jaffee/Russell (2006) 31
    • Risk report Hedging climate change5.3 Private and public risk partnerships:the example of flood insurance lthough it cannot be expected that every risk is insurable at any given time, aA risk partnership between the private insurance business and public authoritiescan decisively improve the insurability of these risks. Here, two approaches are rele-vant to the issue of large risks. The first approach involving cooperation between private insurers and publicauthorities is based on the obvious fact that public policies can exert considerableinfluence over the effects of natural catastrophes. A prime example is the case offlood risks in Britain52. More than two million houses, or 10 percent of the total, are presently exposedto the risk of flooding. Of those, 400,000 are in highly endangered regions where theannual occurrence risk of flood damage is 1.3 percent. Long-term, if suitable countermeasures are not taken, the situation could significantly worsen because of the effectsof climate change. This means that the number of buildings vulnerable to risk threat-ens to rise to 3.5 million. After widespread floods in the autumn of 2000 caused by record levels of rainfall,doubts arose about whether this sort of damage would even be insurable on privateinsurance market53. All parties agreed that public infrastructure needed to be funda-mentally modernized to minimize flood damage. After constructive dialogue be-tween the government and the Association of British Insurers (ABI)54 it was agreed inJanuary 2003 that private insurers would continue to offer insurance protectionagainst flood damage while the government would make available more funds toimprove mitigation efforts in endangered areas and improve its flood risk informa-tion practices55. In November 2005, the partnership was extended. Insurance cover would contin-ue to be offered to private house owners and small businesses for whom the proba-bility of flood damage was no higher than 1.3 percent. Premiums were to be calculat-ed on the basis of the extent of the risk. On top of that, insurance cover remainedavailable for another 100,000 buildings that within the next five years would be, withstate assistance, brought into the 1.3 percent category. Existing policyholders inhighly endangered regions for whom no risk-mitigation program exists, were to bedealt with on a case-by-case basis.Private insurers agreed to take on these obligations on the condition that the governmentmade progress in five key areas:• reducing risks over the next three years for 100,000 buildings in endangered areas.• Establishing adequate investment programs against flood damage, taking into account climate change.• Improving land-use planning to restrict construction of new buildings in risky regions. 52 See the web site of the Association of British• Making available more accurate state information to the public about flood risks Insurers (ABI): www.abi.org.uk/flooding and state programs to mitigate these risks. 53 The insured damage amounted to more than• Taking steps to minimize risks posed by drain flooding and flash floods. one billion pounds sterling 54 More than 400 insurance companies, or 97The British example shows that, even under difficult conditions, the insurability of percent of the British insurance industry, iscat risks can be warranted. But this is only one, individual, example. The range of organized under the ABI umbrellapossible cooperation is large and full of possibilities. Areas of cooperation include 55 The funds were initially increased to 394 millionsafety standards, construction regulations, area planning, public infrastructure pounds sterling (2002/3) and then, in stages,(such as dams and other protective installations), deciding on appropriate tax con- to 564 million pounds by 2005/6ditions, and catastrophe protection measures. Public and private risk partnerships 56 Of course policyholders can also contribute bycan help make those effects of climate change that cannot be avoided at least man- not taking unnecessary risks and by makingageable from a social point of view56. available information that is relevant for insur- ance purposes 32
    • Risk report Hedging climate change An important condition for the insurability of major risks is the possibility ofdiversification. But in many markets, as we have seen, the opportunities for risktransfer using reinsurance are limited and the relevant capital-market instrumentsunder-developed. This is where the second approach comes into play. The insurabil-ity of risks to natural catastrophes can be improved if state reinsurance exists57. Such programs can be arranged in many ways. Of course, the previously men-tioned construction principles should be used. Specifically these involve observingthe following principles.First: State reinsurance should only be available for cases of major damage that ex-ceed a certain level. Where this level is set depends on the relevant market conditions.Out of this emerges a system of multi-layered liability, as is typical in insurancemarkets. The insured damage is spread between policy holder (through an excessrequirement) primary insurers, private reinsurers and capital markets, and, finally,public authorities.Second: the private insurance business should always remain involved in cases ofmajor damage. This, inasmuch as state coverage, by remaining flexible and adjustedto the relevant market, is limited. Alternatively, a proportional division of coverage –above that “certain level” – between insurers and state can be agreed on. In this way,there is an overview of household risks. At the same time, private primary insurersand reinsurers remain interested in using their own wherewithal to improve theinsurability of risks to natural forces.Third: Such a program needs to be financed by premiums that are set at levelsappropriate to risk. This is to avoid false incentives being inferred from public rein-surance. If premiums are too low, the danger is that private insurers will be crowdedout of the market. In addition, the opportunity increases for moral-hazard behaviorby both primary insurers and policy holders. If premiums are too high, there will beno demand for state reinsurance and they will the program will thus not fulfill itsaim.If, because of public pressure and political pressure, setting an appropriate premiumlevel becomes either difficult or impossible, a price can be set at more-or-less mar-ket conditions with the help of regular auctions. This means that the state auctionsoff a limited number of reinsurance contracts at annual auctions where a reserveprice is set at a level that reflects the risk58. Buyers would, in the main, be primaryinsurers but, in certain circumstances, other investors as well. Such speculative pur-chases would be welcome because they would increase liquidity and make it easierto set prices more efficiently. Such a system of state reinsurance has several attractive facets. For a start, it givesthe impression of extending the market without actually entering the private insur-ance market. It also reduces the timing risk and provides for a commercial environ-ment which allows the primary insurer to insure cat risks at more attractive condi-tions. At the same time, it allows policies to remain in force that were completedwith private insurers under conditions containing incentives for policyholders to actappropriately to the risks. Policyholder would need to continue to accept excess pro-visions if they are to obtain coverage from a primary insurer. The state benefits fromsuch a program as its fiscal risks are reduced. But all of society also gains. Having amore efficient way of dealing with the risks of natural catastrophes is to the advan- 57 Such programs already exist in one form ortage of everyone. another. Prominent examples include the Japan- ese Earthquake Reinsurance Company and the French Programm Caisse Centrale de Reassur- ance (CCR). See Cummins (2006) 58 The Clinton administration intended introducing such a system. See Litan (2006b) 33
    • Risk report Hedging climate changeBibliographyP. Albrecht, A. König, H.R. Schradin: Katastrophenversicherungs-Termingeschäfte, Mannheimer Manuskriptezu Versicherungsbetriebslehre Nr. 72American Re (2002): Topics – Annual Review of North American Natural Catastrophes 2001Guy Carpenter (2005):The World Reinsurance Market. New YorkK.A. Froot (1998): The Evolving Market for Catastrophic Event Risk, White paper, Guy Carpenter & Company, IncK.A. Froot (2001): The Market for Catastrophic Risk, Journal of Financial Economics, 60 (2001) 529-571H.C. Kunreuther (2005): Has the Time Come for Comprehensive natural Disaster Insurance? in: On Risk andDisaster: Lessons from Hurrican Katrina, R.J. Daniels u.a. (eds.), University of Pennsylvania Press 2006H. C. Kunreuther, E. O. Michel-Kerjan (2007): Climate Change, Insurability of large-scale Disasters and theemerging Liability Challenge, NBER WP 12821D.M. Jaffee (2006): Commentary, Federal Reserve Bank of St. Louis Review, July/August 2006D. M. Jaffee, Th. Russell (1997): Catastrophe Insurance, Capital Markets and Uninsurable Risks, in: journal ofRisk and Insurance, Vol 64, Nr. 2, 205-30D. M. Jaffee, Th. Russell (2006): Should Governments Provide Catastrophe Insurance?G. Krenn, U. Oschischnig(2003): Systemrelevante Risikofaktoren der Versicherungswirtschaft und Methoden zurRisikoeinschätzung, in: Stabilitätsbericht 6 (OeNB)G.C. Lai, R.C. Witt, H-G. Fung, R.D. MacMim (March 1997): On Liability Insurance Crisis(www.aria.org/rts/proceedings/1997/crisis.pdf)R.E. Litan (2006a): What is the Appropriate Role of Federal Government in the private Markets for Credit andInsurance?, Federal Reserve Bank of St. Louis Review, July/August 2006R.E. Litan (2006b): Sharing and Reducing the Financial Risks of Future “Mega-Catastrophes”, Issues in EconomicPolicy, Nr. 4, March 2006Münchener Rück: Topics Geo – Naturkatastrophen 2006OECD (2005): Catastrophic Risks and Insurance, Policy Issues in Insurance Nr. 8P. Pensa (2004): Cat-Bonds (www.wwz.unibas.ch/cofi/publications/papers/2004/06-04.pdf)G. Pfister (2003): Zur Versicherungsfähigkeit von Katastrophenrisiken, Arbeitsbericht Nr.232(www.ta-akademie.de)Swiss Re (2007): sigma 2/07, Natur- und Man-made-Katastrophen im Jahr 2006Swiss Re (2005): sigma 4/05, Innovationen zur Versicherung unversicherbarer RisikenSwiss Re (2002): Terrorismus – Umgang mit der neuen Bedrohung. Focus Report 34