WEBVTT NOTE 8.09. Risk, Uncertainty, and Insurance 1 00:00:00.000 --> 00:00:06.000 9. Risk, Uncertainty and Insurance 2 00:00:06.000 --> 00:00:11.000 Entrepreneurship deals with the inevitable uncertainty of the future. 3 00:00:11.000 --> 00:00:17.000 Some forms of uncertainty, however, can be converted into actuarial risk. 4 00:00:17.000 --> 00:00:24.000 The distinction between risk and uncertainty has been developed by Professor Knight. 5 00:00:24.000 --> 00:00:31.240 Risk occurs when an event is a member of a class of a large number of homogeneous events, 6 00:00:31.240 --> 00:00:37.360 and there is fairly certain knowledge of the frequency of occurrence of this class of events. 7 00:00:37.360 --> 00:00:44.660 Thus, a firm may produce bolts, and know from long experience that a certain almost fixed 8 00:00:44.660 --> 00:00:50.320 proportion of these bolts will be defective, say 1%. 9 00:00:50.320 --> 00:00:56.460 It will not know whether any given bolt will be defective, but it will know the proportion 10 00:00:56.460 --> 00:00:59.460 of the total number defective. 11 00:00:59.460 --> 00:01:05.760 This knowledge can convert the percentage of defects into a definite cost of the firm's 12 00:01:05.760 --> 00:01:11.140 operations, especially where enough cases occur within a firm. 13 00:01:11.140 --> 00:01:17.760 In other situations, a given loss or hazard may be large and infrequent in relation to 14 00:01:17.760 --> 00:01:24.200 to a firm's operations, such as the risk of fire, but over a large number of firms, 15 00:01:24.200 --> 00:01:29.480 it could be considered as a measurable or actuarial risk. 16 00:01:29.480 --> 00:01:36.440 In such situations, the firms themselves could pool their risks, or a specialized firm, an 17 00:01:36.440 --> 00:01:41.200 insurance company, could organize the pooling for them. 18 00:01:41.200 --> 00:01:47.400 The principle of insurance is that firms or individuals are subject to risks which, in 19 00:01:47.400 --> 00:01:51.600 and the aggregate form a class of homogeneous cases. 20 00:01:51.600 --> 00:01:58.760 Thus, out of a class of a thousand firms, no one firm has any idea whether it will suffer 21 00:01:58.760 --> 00:02:01.560 a fire next year or not. 22 00:02:01.560 --> 00:02:05.560 But it is fairly well known that ten of them will. 23 00:02:05.560 --> 00:02:12.080 In that case, it may be advantageous for each of the firms to take out insurance, to pool 24 00:02:12.080 --> 00:02:14.400 their risks of loss. 25 00:02:14.400 --> 00:02:20.440 Each firm will pay a certain premium which will go into a pool to compensate those firms 26 00:02:20.440 --> 00:02:23.360 which suffer the fires. 27 00:02:23.360 --> 00:02:29.200 As a result of competition, the firm organizing the insurance service will tend to obtain 28 00:02:29.200 --> 00:02:35.920 the usual interest income on its investment, no more and no less. 29 00:02:35.920 --> 00:02:41.600 The contrast between risk and uncertainty has been brilliantly analyzed by Ludwig von 30 00:02:41.600 --> 00:02:42.600 Mises. 31 00:02:42.600 --> 00:02:52.100 Mises has shown that they can be subsumed under the more general categories of class probability and case probability. 32 00:02:52.100 --> 00:02:58.100 Class probability is the only scientific use of the term probability, 33 00:02:58.100 --> 00:03:03.600 and is the only form of probability subject to numerical expression. 34 00:03:03.600 --> 00:03:12.500 In the tangled literature on probability, no one has defined class probability as cogently as Ludwig von Mises. 35 00:03:12.500 --> 00:03:20.000 Class probability means, we know or assume to know, with regard to the problem concerned, 36 00:03:20.000 --> 00:03:25.700 everything about the behavior of a whole class of events or phenomena. 37 00:03:25.700 --> 00:03:35.200 But about the actual singular events or phenomena, we know nothing but that they are elements of this class. 38 00:03:35.200 --> 00:03:39.900 Insurable risk is an example of class probability. 39 00:03:39.900 --> 00:03:46.300 The businessman knew how many bolts would be defective out of a total number of bolts, 40 00:03:46.300 --> 00:03:51.660 but had no knowledge as to which particular bolts would be defective. 41 00:03:51.660 --> 00:03:59.100 In life insurance, the mortality tables reveal the proportion of mortality of each age group in the 42 00:03:59.100 --> 00:04:05.740 population, but they tell nothing about the particular life expectancy of any given individual. 43 00:04:05.740 --> 00:04:31.740 Insurance firms have their problems. As soon as something specific is known about individual cases, firms break down the cases into sub-aggregates in an effort to maintain homogeneity of classes, that is, the similarity, as far as is known, of all individual members in the class with respect to the attribute in question. 44 00:04:31.740 --> 00:04:38.820 Thus, certain subgroups within one age group may have a higher mortality rate because of 45 00:04:38.820 --> 00:04:40.700 their occupation. 46 00:04:40.700 --> 00:04:46.040 These will be segregated, and different premiums applied to the two cases. 47 00:04:46.040 --> 00:04:51.540 If there were knowledge about differences between subgroups and insurance firms charged 48 00:04:51.540 --> 00:04:58.340 the same premium rate to all, then this would mean that the healthy or less risky groups 49 00:04:58.340 --> 00:05:01.380 would be subsidizing the riskier. 50 00:05:01.380 --> 00:05:07.560 Unless they specifically desire to grant such subsidies, this result will never be maintained 51 00:05:07.560 --> 00:05:10.060 in the competitive free market. 52 00:05:10.060 --> 00:05:16.220 In the free market, each homogeneous group will tend to pay premium rates in proportion 53 00:05:16.220 --> 00:05:24.260 to its actuarial risk, plus a sum for interest income and for necessary costs for the insurance 54 00:05:24.260 --> 00:05:26.180 firms. 55 00:05:26.180 --> 00:05:32.900 Most uncertainties are uninsurable, because they are unique, single cases, and not members 56 00:05:32.900 --> 00:05:34.240 of a class. 57 00:05:34.240 --> 00:05:38.980 They are unique cases facing each individual or business. 58 00:05:38.980 --> 00:05:45.540 They may bear resemblances to other cases, but are not homogeneous with them. 59 00:05:45.540 --> 00:05:51.140 Individuals or entrepreneurs know something about the outcome of the particular case, 60 00:05:51.140 --> 00:05:52.760 but not everything. 61 00:05:52.760 --> 00:05:59.920 As Mises defines it, case probability means we know with regard to a particular event 62 00:05:59.920 --> 00:06:06.200 some of the factors which determine its outcome, but there are other determining factors about 63 00:06:06.200 --> 00:06:08.780 which we know nothing. 64 00:06:08.780 --> 00:06:15.940 Estimates of future costs, demands, etc. on the part of entrepreneurs are all unique cases 65 00:06:15.940 --> 00:06:22.380 Methods of Uncertainty, where methods of specific understanding and individual judgment of the 66 00:06:22.380 --> 00:06:30.860 situation must apply, rather than objectively measurable or insurable risk. 67 00:06:30.860 --> 00:06:38.460 It is not accurate to apply terms like gambling or betting to situations either of risk or 68 00:06:38.460 --> 00:06:40.300 of uncertainty. 69 00:06:40.300 --> 00:06:47.220 These terms have unfavorable emotional implications and for this reason, they refer to situations 70 00:06:47.220 --> 00:06:56.700 where new risks or uncertainties are created for the enjoyment of the uncertainties themselves. 71 00:06:56.700 --> 00:07:02.420 Gambling on the throw of the dice and betting on horse races are examples of the deliberate 72 00:07:02.420 --> 00:07:10.280 creation by the bettor or gambler of new uncertainties which otherwise would not have existed. 73 00:07:10.280 --> 00:07:14.380 There is a distinction between gambling and betting. 74 00:07:14.380 --> 00:07:20.940 Gambling refers to wagering on events of class probability, such as throws of dice, where 75 00:07:20.940 --> 00:07:24.700 there is no knowledge of the unique event. 76 00:07:24.700 --> 00:07:32.700 Betting refers to wagering on a unique event about which both parties to the bet know something, 77 00:07:32.700 --> 00:07:36.220 such as a horse race or a presidential election. 78 00:07:36.220 --> 00:07:43.240 In either case, however, the wagerer is creating a new risk or uncertainty. 79 00:07:43.240 --> 00:07:49.000 The entrepreneur, on the other hand, is not creating uncertainties for the fun of it. 80 00:07:49.000 --> 00:07:53.420 On the contrary, he tries to reduce them as much as possible. 81 00:07:53.420 --> 00:07:58.780 The uncertainties he confronts are already inherent in the market situation. 82 00:07:58.780 --> 00:08:05.580 Indeed, in the nature of human action, someone must deal with them, and he is the most skilled 83 00:08:05.580 --> 00:08:33.100 Profit and Loss Are the Results of Entrepreneurial Uncertainty, Actuarial Risk Is Converted Into 84 00:08:33.100 --> 00:08:45.100 to a cost of business operation and is not responsible for profits or losses except insofar as the actuarial estimates are erroneous.