That is for the Pensions Commission next year, and the Government in its turn. But I do want to show that risk is at the heart of the issue. 2. The nature of risk  “In this world nothing can be said to be certain, except death and taxes” wrote Benjamin Franklin in 1789. Great man though Franklin was, it is clear that there is indeed substantial uncertainty both about death, or at least its timing, and the contributions or taxes required to pay for our pensions. When thinking of how much to save for retirement, there are three main risks to consider. First, how much will we be earning in the future? Second, what will be the rate of return on our savings? Third, how long are we likely to live? Tonight I shall focus exclusively on longevity risk - the uncertainty about how long we shall live - in order to focus on my two propositions about probabilistic thinking and public policy.4 None of us know how long we shall live. But we can assess our chances by looking at the experience of others. A key distinction is between individual and collective risk. Chart 1 plots the observed mortality rates at different ages for women in England and Wales in 2002, the most recent year for which detailed data are available. (A similar story can be told for men). The most common age of death for women was 87, but many died at very different ages. Mortality among individuals varies greatly - individual risk.
On the Bank of England’s Monetary Policy Committee the nine members debate among themselves our current state of knowledge of the  7  The data in Chart 5 are for occupational pension holders of Actuarial Profession member institutions. These individuals are typically wealthier than the rest of the population, and for that reason tend to live longer. 8  Peterman et. al. (1988) found that the probability of infecting a partner was unrelated to the number of sexual acts with that partner. 9  The large models made the further simplifying assumption that the rate took one of only two values. In fact, it varies widely among the population. Robert May, and his colleague Roy Anderson, showed that a key driver of the proportion of the population eventually infected was the “variance of the rate of acquisition of new sexual partners”. Simulations of the proportion of the population ultimately infected with AIDS are sensitive to that variance, and plausible differences in the number of their partners among different people changed the estimate of the proportion likely to be infected from 25% to 90%. 10  Many non-economists believe that economists use a single “model” to explain all economic phenomena. Hence the interest of many commentators in “the model” that is alleged to generate the forecasts of inflation and economic growth published by the Bank of England. But, as we never cease pointing out, the Bank uses not one but many models to help us understand particular aspects of economic behaviour.