In particular, economic outcomes are sensitive to the way people behave under uncertainty, and to their beliefs about the past, present and future. Perceptions of uncertainty affect behaviour. If enough people are uncertain about their future job prospects and save more as a precaution, that may lead firms to cut employment, so increasing the chance that jobs are indeed lost. But uncertainty about whether it will rain today does not change the weather. Beliefs adapt over time in response to changes in the environment; and this in turn affect show economic systems behave. Because the surrounding environment can affect economic decision-making, there are probably few genuinely “deep” (and, therefore, stable) parameters  3  This particular example is fortuitous for earth science and biology, since it helps us date rocks and the fossils they contain and chart continental drift, based on the history of changes in the magnetic field of the earth. BIS Review 36/2010  3  or relationships in economics. In contrast, in many settings in the physical sciences there are stable “rules of the game” (e.g. the laws of gravity are as good an approximation one day as the next). The study of decision making under uncertainty has a distinguished ancestry in economics. Frank Knight (1921) wrote about the difference between risk (where frequencies could be used to calculate probabilities) and uncertainty (where there was no objective basis on which to derive probabilities).
Thereafter, the MPC expected that inflation was more likely than not to fall back and be below target for a period [Slide 5]. You can see that the most likely outcome, shown in the darkest band, was for inflation to stay below the target at the end of the forecast period. But the MPC also saw upside risks to that projection, stemming from the possibility that the current high level of inflation might become embedded in inflation expectations, so making inflation itself more persistent. To make these risks easier to discern, the MPC also makes available charts of the cross section of the probability distribution at particular points on the forecast horizon, like the one shown in [Slide 6]. The upside risks mean that at the end of the forecast horizon, the MPC judged that inflation was as likely to be above the target as below it. We can see this in the chart, because the narrower bands towards the left hand side mean that the mass below the vertical line marking 2% is about the same as the mass above it. But why do we show our projections like this? Many other economic forecasters publish their forecast as a single, most likely outcome. In our view, this sort of forecast is not very informative, as the actual probability of it being correct is very close to zero. In contrast, the whole distribution contains much more information. What matters for policy is the entire distribution of outcomes.