Abstract
This chapter investigates the economic and behavioural reasons underlying the reactions of extreme event insurance markets such as the aviation war risk insurance market following the occurrence of an extreme insured event. Two broad areas of legal scholarship are conscripted to provide a theoretical basis for this investigation: the traditional law and economics movement on the one hand; and, the behavioural law and economics movement on the other. Both schools of thought involve economic analysis of law, a concept which has been used both in an effort to explain the legal system as it is (i.e., positive or descriptive analysis) and also to recommend changes that might improve it (i.e., normative or prescriptive analysis). The difference between the two schools lies only in the nature and scope of the underlying assumptions which drive their respective analyses and conclusions.
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- 1.
The discipline of law and economics deals with the economic analysis of legal rules through verbal, mathematical and/or graphical models in order to distill the essence of the relationships being studied. The traditional law and economics approach posits that legal rules are best analyzed and understood in the light of standard economic principles. See generally: Polinsky (2003) pp. xv–xvii; 3. Central to the use of models in the analytical process is the introduction of various assumptions. Economists make assumptions for the obvious reason that the world, viewed economically, is too complicated to understand without some abstraction. A typical account of the assumptions usually made in such analysis is as follows: “all human behavior can be viewed as involving participants who [1] maximize their utility [2] from a stable set of preferences and [3] accumulate an optimal amount of information and other inputs in a variety of markets”. See Jolls et al. (1998) p. 1476.
- 2.
As a discipline, behavioral law and economics builds upon and sometimes challenges some of the central concepts of traditional law and economics mainly by exploring the implications of actual human behavior (as opposed to hypothesized behavior) on the economic analysis of law. It involves both the development and incorporation within traditional law and economics of behavioral insights drawn from various fields of psychology. According to proponents, some of the foundational assumptions of traditional law and economics (e.g.: utility maximization; stable preferences; rational expectations; and, optimal processing of information) reflect an unrealistic picture of human behavior, and models built on those assumptions sometimes yield erroneous predictions. Behavioral law and economics therefore attempts to improve the predictive power of traditional law and economics by building in more realistic accounts of actors’ behavior. See Jolls (2007). See also Jolls et al. (1998) p. 1476.
- 3.
Polinsky (2003) p. xvii.
- 4.
A fundamental assumption within the law and economics movement is that individuals are rational maximizers of their satisfactions in their non-market as well as their market behavior. This assumption of perfect rationality is drawn from neoclassical microeconomic theory and is refutable as an empirical matter because empirical studies often find participants whose behavior systematically deviates from economic definitions of rationality. Proponents of law and economics acknowledge this descriptive inaccuracy but retain the assumption for a lack of a better alternative for prediction and policy analysis. In contrast, a fundamental assumption of the behavioral law and economics movement is that individuals systematically fall prey to a host of cognitive illusions that lead to predictable non-rational behaviors both inside and outside traditional markets. This assumption is drawn from behavioral studies of judgment and decision-making which suggest that human judgment and decision-making necessarily rely on imperfect psychological mechanisms that cause departures from rationality. Because these irrational tendencies are supposedly uniform, pervasive and predictable, they can be incorporated into behavioral models and used in policy analysis. Thus, whereas law and economics treats all legal actors in all situations as if they were perfectly rational, behavioral law and economics treats all legal actors in all situations as if they were equally predisposed to commit errors of judgment and choice. See Mitchell (2002–2003) pp. 68–71.
- 5.
Posner (1987). The author, a long time Judge of the United States Court of Appeals for the Seventh Circuit and a Senior Lecturer at the University of Chicago Law School, wrote this article in reaction to the opposition raised by some economists to the extension of economics from the study of market to non-market behavior. In refuting the claims made by these economists, he noted inter alia that: “The economics of law is the set of economic studies that build on a detailed knowledge of some area of law; whether the study is done by a ‘lawyer’, an ‘economist’ or someone with both degrees, or a lawyer-economist team has little significance”. See idem., p. 4. As evidenced by the title of this article, Judge Richard Posner has been given credit as helping start the traditional law and economics movement.
- 6.
Idem., p. 1.
- 7.
See e.g., Wolf (1979).
- 8.
Microeconomic efficiency, also referred to as Pareto optimality, is the degree to which an economic system meets the material wants, as measured by quantity and quality, of its members. It is achieved when it is impossible to make one person better off without making someone else worse off. See Winston (2006) p. 2.
- 9.
The argument that free markets lead to efficient outcomes “as if by an invisible hand” was first made by Adam Smith in 1776. See Smith (1977, first published in 1776).
- 10.
Stiglitz (2003) p. 580.
- 11.
Chiappori and Gollier (2006) p. 2.
- 12.
Idem., p. 3 where the authors state:
… it is assumed that all agents [market participants] share the same information about the likelihood of the various states. This allows for heterogeneous populations as long as the characteristics of the risk borne by each participant is [sic] common knowledge. For example, the fact that young women are safer drivers than young men is compatible with full insurance of every driver at the competitive equilibrium with a risk neutral insurance industry. The premium rate for every category of risk will be fair (hence gender specific), thereby inducing every individual to purchase full insurance at the optimum.
- 13.
Idem., p. 2.
- 14.
Idem.
- 15.
Idem.
- 16.
Idem.
- 17.
See footnote 20 below for a distinction between “private” and “public” goods.
- 18.
See Bator (1958) where the author states that market failure refers to the failure of a more or less idealized system of price-market institutions to sustain “desirable” activities and estop “undesirable” activities.
- 19.
See footnote 8 above for a definition of Pareto optimality (also known as microeconomic efficiency).
- 20.
A public good involves two elements: non-excludability and non-rivalrous consumption. Non-excludability refers to the impossibility of preventing non-paying individuals from enjoying the benefits of a good or service, whereas non-rivalrous consumption refers to cases where an individual’s ability to consume a good or service is not diminished by allowing additional individuals to consume it. All other goods are private goods. See Cowen (1988). See also Cowen and Crampton (2003a) pp. 3–4.
- 21.
An externality exists whenever an individual’s actions affect the utility of another individual. Positive externalities are those that benefit others; negative externalities are those that make others worse off. See Cowen (1988) p. 2.
- 22.
Cowen and Crampton (2003a) p. 3.
- 23.
Cowen (1988) p. 3.
- 24.
Idem.
- 25.
Samuelson (1954).
- 26.
Bator (1958).
- 27.
Cowen and Crampton (2003a) p. 3.
- 28.
Cowen (1988) p. 4.
- 29.
These two leading economists were awarded the 2001 Nobel Prize in Economics for their groundbreaking work on the economics of information.
- 30.
Stiglitz (2003) pp. 579–580.
- 31.
Booth (2008).
- 32.
Idem., p. 1.
- 33.
Stiglitz (2003) p. 581.
- 34.
Cowen and Crampton (2003a) p. 6.
- 35.
Stiglitz (2003) pp. 584–585.
- 36.
Cowen and Crampton (2003a) p. 5.
- 37.
Idem., p. 4. See also Stiglitz (2003) p. 582 where the author notes: “Perhaps most importantly, under the standard paradigm, markets are Pareto efficient, except when one of a limited number of market failures occurs. Under the imperfect information paradigm, markets are almost never Pareto efficient”.
- 38.
In a number of his writings on the subject, Joseph Stiglitz presented credit rationing and efficiency wages—both based on imperfect information—as two clear examples of how markets may misfire. See Cowen and Crampton (2003a) p. 6.
- 39.
- 40.
See Jaffee and Russell (2003).
- 41.
See Chiappori and Gollier (2006) p. 3. The authors claim that asymmetric information is a central reason why competition in insurance markets may fail to guarantee that all mutually advantageous risk exchanges are realized in our economies. They specifically identify moral hazard and adverse selection as two phenomena derived from asymmetric information that can explain why competitive insurance markets fail to provide an efficient level of insurance, and why public interventions are required to cure the problem. See also Jaffee and Russell (2003) p. 36.
- 42.
Shavell (1992).
- 43.
Winter (1992).
- 44.
Idem., pp. 61–62.
- 45.
Idem., p. 62.
- 46.
Chiappori and Gollier (2006) pp. 4-5.
- 47.
Winter (1992) p. 62.
- 48.
Idem. It is also referred to as “effort” in the economics literature.
- 49.
Jaffee and Russell (2003) p. 36.
- 50.
Winter (1992) p. 62.
- 51.
Jaffee and Russell (2003) p. 36.
- 52.
Winter (1992) p. 62.
- 53.
Arnott (1992) p. 327.
- 54.
Idem., p. 326.
- 55.
Winter (1992) p. 62.
- 56.
Arnott (1992) p. 326.
- 57.
Idem.
- 58.
Idem.
- 59.
Shavell (1992) p. 280.
- 60.
Idem., [emphasis added].
- 61.
Arnott (1992) p. 326.
- 62.
Idem.
- 63.
Idem., [emphasis added].
- 64.
Idem., at 327 [emphasis added].
- 65.
Idem. [emphasis added]. The issue of governmental intervention in private insurance markets is discussed in detail below.
- 66.
Idem. See also Winter (1992) p. 65 where the author notes that the contractual implications of adverse selection and moral hazard are identical. He cites the following example in support: “under both moral hazard and adverse selection, partial coverage for at least some individuals is optimal”.
- 67.
- 68.
Outreville (1998) p. 152.
- 69.
Chiappori and Gollier (2006) p. 3.
- 70.
Outreville (1998) p. 152.
- 71.
Cowen and Crampton (2003a) p. 7.
- 72.
Akerlof (1970).
- 73.
“Lemons” is a term used in America to refer to bad quality new or used cars. See idem., p. 489.
- 74.
Cowen and Crampton (2003a) p. 7.
- 75.
Idem., p. 6.
- 76.
Idem., pp. 6–7.
- 77.
Idem., p. 8.
- 78.
Idem.
- 79.
Idem.
- 80.
Idem.
- 81.
Kunreuther and Pauly (1985).
- 82.
Cowen and Crampton (2003a) p. 7. See also Chiappori and Gollier (2006) pp. 3–4 where the authors note that:
The adverse selection problem … originates from the observation that if insurance companies calculate the premium rate on the basis of the average probability distribution in the population, the less risky agents will purchase less insurance than riskier agents. In the extreme case, the low-risk agents will find the premium rate too large with respect to their actual probability of loss. They will prefer not to insure their risk. Insurers will anticipate this reaction, and they will increase the premium rate to break even only on the population of high-risk policyholders. In summary, the presence of high risk agents generates a negative externality to lower risk agents who are unable to find an insurance premium at an acceptable premium rate.
- 83.
Cowen and Crampton (2003a) p. 3.
- 84.
Idem., p. 8.
- 85.
Idem.
- 86.
- 87.
Extreme event insurance markets consist of those insurers who provide cover for events characterized by low probability and high losses or consequences. They include natural disaster insurance markets (e.g., earthquakes and hurricanes), insurance markets for catastrophic nuclear accidents, and terrorist insurance markets (e.g., the aviation war risk insurance market).
- 88.
Their joint essay on the subject is published as a part of a collection of essays in honour of Joseph E. Stiglitz. Despite very careful research, this is the only essay that the present author came across that specifically addresses the issue of extreme event insurance market failure following a major event. See Jaffee and Russell (2003).
- 89.
Idem., p. 38.
- 90.
Idem.
- 91.
With respect to extreme events, they specify the differences between the relevant parameter values as follows:
-
1.
The size of the risks are larger;
-
2.
The correlation coefficients between individual risks may be higher; and,
-
3.
The performance guarantee costs may be higher as a result of (1) and (2).
See idem., p. 38.
-
1.
- 92.
Idem., [emphasis added].
- 93.
Idem., p. 39.
- 94.
“In forming an insurance syndicate, there is always the possibility that some members will have more information about the risks at issue than others. This problem is distinct from the insured/insurer adverse selection problem … [b]ut this source of asymmetric information can also lead to market failure”. See idem.
- 95.
“If the losses created by an extreme event threaten an insurance firm with bankruptcy, then there is a potential for deadweight bankruptcy costs and related agency costs. In particular, it is clear that the probability that an insurance firm would be made bankrupt by a particularly bad extreme loss during 1 year is substantially higher than the probability that the same firm would be made bankrupt by a particularly bad run of, say, auto insurance losses during a year. It could thus be quite sensible for the insurance firm’s managers to refuse to take on extreme risks for fear that the big one will cause the loss of their jobs due to the bankruptcy of their firm”. See idem., pp. 38–39.
- 96.
“Extreme losses tend to be large, often exceeding the annual premiums collected for the coverage by a factor of 10 and possibly by as much as 100. In particular, if the event occurs early in the life of a syndicate, the premiums accumulated to that date will fall far short of the loss, leaving the syndicate responsible for the shortfall. Even with the risk spreading associated with reinsurance [and retrocession], any one risk bearing entity, and certainly the industry as a whole must have access to substantial capital if it is to pay these losses… This compares with routine lines such as auto insurance or dental insurance, where one year’s premiums will almost always cover one year’s losses, thus requiring the insurance firm to place little of its own capital at risk.” See idem., p. 40. Three fundamental problems with insurance companies retaining earnings or raising capital in anticipation of possible future losses have been identified by the same authors in a previous publication:
-
U.S. accounting rules preclude “ear-marking” retained profits or other capital funds as “reserves” against future losses, if the actual events have not yet occurred. Insurance firms, of course, are always free to retain their earnings, but the accounting rules preclude pre-committing these funds to pay only catastrophic losses.
-
U.S. tax rules require full taxation of profits that are retained as reserves against future losses. This makes retained earnings an expensive way to accumulate funds against possible future losses.
-
A firm that accumulates liquidity to cover future large losses could become a takeover target due to its large cash assets. Since the liquidity cannot be pre-committed to catastrophic losses, a third party could take over the firm, allow the policies to mature, and then use the liquidity for another purpose.
See generally: Jaffee and Russell (1997).
-
- 97.
Jaffee and Russell (2003) p. 41.
- 98.
Idem., p. 36.
- 99.
Idem.
- 100.
The insurance of Chicago airports offers a practical illustration of the foregoing. Prior to September 11, 2001, Chicago carried $750 million of terrorist insurance for an annual premium of $125,000. Post-September 11, their insurers would only offer $150 million of coverage for the new premium of $6.9 million. Not only had premiums been significantly increased; the upper limit of coverage had also been severely reduced. See idem.The incidence of very steep increases in the rates of premium charged coupled with severe rationing or restriction of the quantity of insurance cover previously available provides the basis for economists to conclude that a market failure has occurred in the war risk insurance market.
- 101.
Idem.
- 102.
Idem.
- 103.
Idem., p. 43.
- 104.
Idem., pp. 41–42. Two major factors that may account for this situation were identified by the same authors in a previous publication. They are:
-
The fact that potential investors in the new securities may be concerned that their funds will be used to pay off past losses and not to support new profitable initiatives; and,
-
The possibility that asymmetric information may lead potential investors to evaluate future risks at a higher level than does the issuing firm, causing the new investors to require a lower price for the new securities than the firm is willing to accept.
See generally: Jaffee and Russell (1997).
-
- 105.
Doherty et al. (2003) p. 186.
- 106.
“Catastrophe bonds are a class of securities issued by insurance or reinsurance firms. The issuer places the proceeds from the bond sale in Treasury securities. If the cat [catastrophic] event does not occur, the Treasury securities are sold to repay the principal to the bondholders. If the cat event does occur, then the insurance firm receives the proceeds from the Treasury bond sale, and the firm is also relieved of its obligation to repay the principal and any further interest on the bonds”. See Jaffee and Russell (2003) p. 42, fn. 4. Catastrophe bonds have been used extensively in the natural disaster insurance markets (earthquakes, hurricanes, etc.), but not in the terrorism insurance market (e.g., the aviation war risk insurance market). The present author therefore highly recommends that the aviation war risk insurance market could explore the feasibility of adapting such derivatives as a means of raising the much needed capital for the industry.
- 107.
Idem., p. 42.
- 108.
Idem. Also, see generally: Jaffee and Russell (1997).
- 109.
Jaffee and Russell (2003). This suggestion rekindles the debate as to who should bear the cost of aerial terrorism (i.e., as between operators: airlines, airports, air navigation service providers, ground handling service providers and their insurers on the one hand; victims on the ground; and, governments on the other hand). This issue will be revisited in subsequent sections of this book.
- 110.
For a collection of key articles challenging the claims of the new market failure arguments in the more recent debates on market failure, See generally: Cowen and Crampton (2003b).
- 111.
Cowen and Crampton (2003a) pp. 5, 8–9.
- 112.
Idem., p. 9. Critics refer to the fact that Joseph Stiglitz has never presented empirical work on his basic mechanisms as an added basis for skepticism about the relevance of his research.
- 113.
Idem., p. 10.
- 114.
- 115.
- 116.
Cowen and Crampton (2003a) p. 4.
- 117.
Idem.
- 118.
Idem., p. 12.
- 119.
See idem., citing Klein (2002).
- 120.
Cowen and Crampton (2003a) p. 12.
- 121.
Idem.
- 122.
Idem.
- 123.
Idem., pp. 12–13.
- 124.
Idem., p. 10.
- 125.
Hemenway (1990).
- 126.
Idem., pp. 1063–1064.
- 127.
Idem., pp. 1065–1066. The author demonstrates this phenomenon empirically with statistics from the Boston General Hospital and the Brackenridge Hospital in Austin Texas. Although the empirical evidence relied upon by the author is not very rigorous, it is at least suggestive. See Cowen and Crampton (2003a).
- 128.
Hemenway (1990) p. 1066.
- 129.
Idem., pp. 1066–1067.
- 130.
Cowen and Crampton (2003a)
- 131.
See Doherty and Posey (1997).
- 132.
Idem., pp. 58 ff.
- 133.
See Doherty et al. (2003) p. 181.
- 134.
These goals are as follows: “First, undiversifiable risk is passed back to the policyholders. Second insurers can cover their additional costs by raising prices, but do not disassemble since this would involve greater rationing at the post-loss prices. Thirdly, and prospectively, insurers are more willing to offer coverage for such severe events because they know they can raise prices for such coverage and by rationing they need not stretch their depleted capital”. See Doherty and Posey (1997) p. 189.
- 135.
Idem., pp. 181–182.
- 136.
See Jaffee and Russell (2003).
- 137.
Idem., p. 43.
- 138.
Cognitive theories of choice (also referred to as consequentialist theories) posit that risk-related decisions (and choices) made by human beings are always the result of some conscious intellectual or cognitive activity of the human mind. They assume that people assess the desirability and likelihood of possible outcomes of risky choice alternatives, albeit subjectively and possibly with bias or error, and integrate this information through some type of expectation-based calculus to arrive at a decision. Under these theories, feelings triggered by the decision situation and imminent risky choice are seen as epiphenomenal, i.e., not integral to the decision making process. See Loewenstein et al. (2001). Non-cognitive theories of choice, on the other hand, are premised on the fact that additional psychological factors (such as emotional reactions to risky situations) play a role in decision making processes.
- 139.
Hogarth (2002) (emphasis added).
- 140.
Kunreuther and Hogarth (1992) p. 308. The authors demonstrate ambiguous probability with the example of political risks: the reluctance of insurers to provide coverage for industrial firms investing in developing countries with unstable political systems stems from the difficulty in estimating the probabilities associated with losses of different magnitudes. With respect to ambiguous losses, the historic reluctance of insurers to provide coverage to manufacturers of the pertussis vaccine against possible brain damage caused by the use of the vaccine is offered as an example. Although the probability of such serious side effects of the vaccine were well known, the size of court awards from product liability suits against the manufacturer made the costs of insurance prohibitive to the manufacturers.
- 141.
Idem. See also Kunreuther et al. (1993). The findings made by these authors were based on the results of empirical surveys of actuaries, underwriters and reinsurers.
- 142.
- 143.
Kunreuther and Hogarth (1992) p. 318.
- 144.
Idem.
- 145.
Idem. The example offered is the case of insurance coverage for environmental pollution damage which, at some point in time, was avoided by practically all major insurance firms. Not only was the probability of a claim against the insurer uncertain, but should a suit be filed against the insured party, there was no guarantee that the costs to the insurer would be bounded by the stated limits of coverage. Coverage for aviation war risks and other extreme events fall within this category.
- 146.
Jaffee and Russell (2003) p. 43.
- 147.
The various empirical studies referred to above suggest that actuaries and underwriters will add an ambiguity premium in pricing a given risk whenever there is heightened uncertainty regarding either the probability or the magnitude of losses. For a discussion of the various reasons underlying the ambiguity aversion patterns of insurers, see Kunreuther et al. (1995) pp. 346–349.
- 148.
Jaffee and Russell (2003).
- 149.
Kahneman et al. (1986) p. 729.
- 150.
Jaffee and Russell (2003) p. 44.
- 151.
Idem.
- 152.
Idem., pp. 44–45.
- 153.
Idem. See also Loewenstein et al. (2001) p. 270, where the authors note as follows: “The risk-as-feelings hypothesis … postulates that responses to risky situations (including decision making) result in part from direct … emotional influences, including feelings such as worry, fear, dread, or anxiety. People are assumed to evaluate risky alternatives at a cognitive level … based largely on the probability and desirability of associated consequences. Such cognitive evaluations have affective consequences, and feeling states also exert a reciprocal influence on cognitive evaluations. At the same time, however, feeling states are postulated to respond to factors such as the immediacy of a risk, that do not enter into cognitive evaluations of the risk and also respond to probabilities and outcome values in a fashion that is different from the way in which these variables enter into cognitive evaluations”.
- 154.
Loewenstein et al. (2001) p. 281.
- 155.
Idem., p. 280. The authors note further that although the two types of reactions are interrelated, they have different determinants. Whereas cognitive evaluations are sensitive to variables such as probabilities and outcome valences, emotional reactions are sensitive to the vividness of associated imagery, proximity in time, and a variety of other variables that play a minimal role in cognitive evaluations. As a result of these differences, people often experience a discrepancy between the fear they experience in connection with a particular risk and their cognitive evaluation of the threat posed by that risk.
- 156.
Idem., pp. 270–271.
- 157.
Jaffee and Russell (2003) p. 45 where the authors note that “noncognitive factors lead to inaction rather than wrong action in the face of some risks”. See also Loewenstein et al. (2001) p. 269, where the authors elaborate further with the following examples: “Fear causes us to slam on the brakes instead of steering into the skid, immobilizes us when we have greatest need for strength, causes sexual dysfunction, insomnia, ulcers and gives us dry mouth and jitters at the very moment when there is the greatest premium on clarity and eloquence”.
- 158.
Peters and Slovic (1996).
- 159.
Loewenstein et al. (2001) p. 269 [emphasis added].
- 160.
Idem.
- 161.
Idem. [emphasis added].
- 162.
Idem., pp. 272–273. See also Jaffee and Russell (2003) p. 45. This observation is based on the findings of a series of studies conducted by a group of psychologists. In those studies, subjects were told that they could earn hypothetical money by turning over cards from one of four decks. Two of the decks contained high payouts ($100) and two contained low payouts ($50). The high paying decks however also contained a catastrophe card marked with a very high loss. On average, subjects sampled from all four decks until they drew the catastrophe card, at which point they thereafter avoided the catastrophe deck. For a report on the studies, See Bechara et al. (1997).
- 163.
Jaffee and Russell (2003) p. 45.
- 164.
Jolls (2007) pp. 14–15; 21 (hindsight bias).
- 165.
Tversky and Kahneman (1974).
- 166.
Idem., p. 1127.
- 167.
Jolls (2007) pp. 14–15.
- 168.
Idem. Other commentators have explained this difference in attitudes by noting that insurance company managers who are rewarded with a share of the profits but suffer a large penalty in case the firm suffers insolvency will behave as if they are risk averse. They provide the following example: “suppose an insurance underwriter is concerned with his future employment opportunities should his firm be declared insolvent. He may then limit the amount of coverage for a particular risk or charge higher premiums than otherwise if he perceives the risks in his portfolio to be highly correlated”. See Kunreuther et al. (2004).
- 169.
Bianco (2002).
- 170.
Idem.
- 171.
Idem.
- 172.
Schwarcz (2008) pp. 196–197.
- 173.
Baur and Enz (2003) p. 7.
- 174.
- 175.
- 176.
Schwarcz (2008)
- 177.
Property and Casualty Insurers Association of America (2009).
- 178.
Mundy (2004) p. 30 [emphasis added].
- 179.
Idem., p. 29.
- 180.
Kaufman and Scott (2003) pp. 372–373 [emphasis added].
- 181.
Acharya et al. (2009) p. 283.
- 182.
OECD (2003) p. 9 [emphasis added].
- 183.
Idem.
- 184.
Kaufman and Scott (2003) p. 371.
- 185.
Schwarcz (2008) p. 198.
- 186.
Idem.
- 187.
Fitzsimmons (2004).
- 188.
According to Fitzsimmons, “[c]lassical insurance works on the basis of pooling of money (the premium) so that when someone suffers an insured loss, their loss is indirectly paid by the many (including reinsurers), out of the premiums received from those who have not suffered loss. There is an additional buffer, for bad times, of the insurer’s capital, but even taking account of contingent capital available through reinsurance, this is distinctly finite”. See idem., p. 73.
- 189.
Kendall (2002).
- 190.
These criteria of insurability include: randomness of the loss occurrence; the size of the maximum probable loss; the average expected loss amount upon occurrence; the average frequency of loss occurrences; the insurance premium; and, the absence of moral hazard. See Fitzsimmons (2004) p. 74.
- 191.
Mahul (2002) p. 2.
- 192.
There is another important requirement that the risks in an insurer’s pool should not be correlated. This typically means that the realization of one risk within the portfolio must not simultaneously cause the realization of other insured risks in the portfolio. By virtue of their inherently systemic nature, most catastrophic risks are correlated. This affects the availability of commercial insurance for such risks by limiting the potential for insurers to pool individual risks. See Faure and Hartlief (2003) pp. 109–110.
- 193.
In this regard, Fitzsimmons notes that the most serious factor in the aviation war risk insurance market following September 11, 2001, was “the absence of an identifiable maximum possible loss from the broad causative factor of terrorism”. He notes further that “[e]ven now, aggregate loss estimates are in many cases little more than educated guesses at the outturn. … there is no way which an insurer insuring terrorism in the traditional manner can now quantify his maximum exposure to terrorism risks across his portfolio in general. That alone was sufficient to make terrorism uninsurable in the traditional manner”. See Fitzsimmons (2004) p. 74.
- 194.
Idem.
- 195.
According to Fitzsimmons: “It is essential to conventional insurance that history is a reasonable guide to the future as regards loss size and frequency, and this is more important the larger the potential loss. The insurer needs to know that it has enough capital to withstand even unlikely losses with a sufficient degree of confidence. 11 September meant that history ceased to be a predictor of the future, and the big picture of terrorism ceased to be random”. See idem.
- 196.
Mahul (2001). Unlike other businesses, a special quality of the conventional insurance industry is that its financial capacity is determined by the amount of reserves and capital at its disposal. “When large firms such as Daimler or Wal-Mart suffer financial losses, they may defer capital expenditures, but their capacity will be little affected. By contrast, if insurers experience large underwriting or investment losses, the industry’s capacity will be depleted”. In such situations, given the costs of raising new capital quickly and a reluctance to underwrite risks that might weaken their balance sheets, insurers would typically scale back their underwriting activities. See Laster and Schmidt (2005) p. 10.
- 197.
- 198.
Faure and Hartlief (2003).
- 199.
The study stresses that precise information on the probability that a certain loss will occur (i.e., its predictability) and the possibility of making a more or less accurate estimate of the potential magnitude of damage (i.e., magnitude) is necessary not only for the purpose of making an accurate calculation of the premium to be charged, but also for purposes of setting aside a reserve in case the accident for which insurance coverage was taken out does occur. With respect to predictability, the study notes that although insurers may, in theory, charge an additional risk premium (known as an ambiguity premium) in situations where there is uncertainty as to the predictability of occurrence of a risk, in practice, there are a number of reasons that strongly militate against charging such premiums. Problems associated with uncertainty about the magnitude of potential losses could also be addressed through the use of insurance techniques such as co-insurance, reinsurance and retrocession. Yet systemic risks may still be of such a large magnitude that even with the use of all the aforementioned techniques, capacity may not be sufficient to cover the risk once it materializes. See idem., pp. 82–89.
- 200.
Property and Casualty Insurers Association of America (2009).
- 201.
Idem.
- 202.
Idem.
- 203.
Idem.
- 204.
Krenn and Oschischnig (2003).
- 205.
Mahul (2002) p. 2. Diversification of risks is discussed in detail in the next chapter under securitization of risks.
- 206.
Acharya et al. (2009) pp. 283 et seq. The authors observe further that, existing financial regulations [including deposit requirements] are usually directed at limiting each individual’s risk in isolation; they are not sufficiently focused on systemic risk.
- 207.
Mahul (2002) p. 2.
- 208.
According to the literature, the best known examples of such “availability crises” occurred in the mid 1980s when several lines of commercial liability insurance were subject to massive price increases and coverage reductions primarily as a result of increases in the number and cost of tort awards. During the early 1970s, a similar phenomenon occurred in the medical malpractice insurance market and the satellite insurance market witnessed price and availability problems in the early 1980s. See Doherty and Posey (1997) p. 56.
- 209.
De Mey (2003) p. 66.
- 210.
Mundy (2004) p. 30.
- 211.
Idem., [emphasis added].
- 212.
De Mey (2003) p. 68 [emphasis added]. Although there is general consensus regarding the existence of systemic risk in the aviation insurance industry, opinions differ as to what impact increasing globalization, consolidation and integration within the financial services sector has on systemic risk in the insurance sector. According to De Mey, “the integration of the financial services industry will increase its ability to absorb shocks and spread risks … integration reduces the probability that the first domino falls down, and therefore reduces systemic risk”. On the other hand, Chris Mundy is of the view that “the rate of consolidation and globalization in the primary insurance sector, combined with the insidiousness of insurance into every aspect of our lives is bringing primary insurance ever closer to systemic risk”. See Mundy (2004) p. 30.
- 213.
- 214.
See footnote 213 above and accompanying text.
- 215.
Mahul (2002) p. 2.
- 216.
See Rhee (2005) p. 461 where the author notes that “exogenous shocks create short term ‘psychological’ distortions in the [insurance] industry as perceptions of the risk are changed by new information”. In the footnote accompanying this text, Robert Rhee notes further that “[s]hocks actually have been more psychological than financial due to the benefits of diversification”.
- 217.
Idem., p. 440 [emphasis added].
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Nyampong, Y.O.M. (2013). Catastrophic Risks and Reflexes: Some Theoretical Perspectives on the Use of Insurance as a Risk Management Tool for Large Catastrophic Risks. In: Insuring the Air Transport Industry Against Aviation War and Terrorism Risks and Allied Perils. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32433-8_4
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