Such a chart does speak to the whole distribution, and it facilitates easy comparison with the previous forecast round [Slide 17]. But it still has the problem that it assigns a precise probability to a given outcome. A solitary Bayesian policymaker may be comfortable with that. But in reality there is no unique answer that encapsulates the collective judgement of the MPC. In the Bank’s experience, MPC members find it more important to focus on distinguishing between the different broad orders of magnitude of future events, and are less interested in debating whether something will happen 49 times out of 100 or 52 times. One answer to this tension is to describe the problem in words. But that carries its own difficulties. An alternative is to design a graphical device which prevents the illusion of spurious precision. Simple graphical changes to the chart such as [Slide 18] emphasise that the MPC’s view is not best expressed by a precise numerical for the probability. But a downside of this sort of representation is that it does not readily permit comparisons between successive forecasts. Instead, a further alternative that the MPC is considering is to present this as a “probability ribbon” [Slide 19]. This shows a range estimate of the probability that inflation will exceed target, defined by the edges of the relevant band of the fan chart. In doing so it preserves the broad impression of the Committee’s overall view, yet filters out the artificial accuracy.
BIS Review 36/2010  5  risk failure by pursuing strategies that are different from the norm. The penalty of failure may be less if others fail in the same way – as Keynes pointed out was true of banks. (iv)  People have excessive faith in their own judgements and are subject to confirmation bias and wishful thinking. An experiment, well known in the literature, asked respondents to report 90% confidence intervals around our estimates of a set of unknown quantities (e.g. the diameter of the moon). 13 But the true answer lay outside the reported confidence intervals half of the time. This reflects a general result that people are overly confident in their own judgements. This effect suggests that there may be a tendency to understate uncertainty and could explain why the “severe” stress testing scenarios used by banks before the crisis were so mild. 5. Policy implications  These observations about decision making under uncertainty in economics have implications for policy along three dimensions. First, decision making under uncertainty affects the dynamics of the economy. Some of the psychological biases discussed above can offer an explanation for “herding” behaviour and “risk illusion” (a tendency to over/underestimate likelihoods of different type of events). Taken together, these biases could offer an explanation for periodic bouts of exuberance in the economy and the financial system in particular. 14 As such they should bear on our assessment of the likelihood of the range of possible outcomes.