This means that, if we looked only at the boost to income and wealth from looser monetary policy, this would significantly understate the well-being benefits to households from the MPC’s monetary actions, by a factor of at least two. 34  For example, Jacoby (2002). Both are shown in Table 1. Log utility is the best fit for happiness across households, but it is also common to use this functional form at the individual level. We also experimented with a variety of other specifications, with higher order terms to capture greater curvature in the utility function, but these were generally not statistically significant. Note that our regressions are based on a pooled cross section of households and so are not pure estimates of the impact on happiness of changes in income and wealth over time. 36 For example, Winkelmann and Winkelmann (1998) and Di Tella et al (2003). 37 There are various ways to calculate the income-equivalence of the lower probability of unemployment, and these numbers would vary depending on the assumptions made. For simplicity, we exploit the results from our analysis, which show the effect on welfare from the lower probability of unemployment on the average household to be around six times larger than the welfare boost from higher labour income. 38 For example, Clark and Oswald (1994). 35  13  All speeches are available online at www.bankofengland.co.uk/speeches  13  Second, these gains from higher employment are felt particularly strongly by younger people who gain most from having a job.
My view is that there is a strong case for making, on a periodic basis, comprehensive and transparent assessments of the distributional impact of monetary policy. This would help people understand the purpose and impact of monetary policy, both on the economy in general and on them as individuals, on “their GDP”. I give some illustrative examples of a “Monetary Policy Scorecard” summarising the impact of monetary actions on particular cohorts. Greater transparency of this type would not, by itself, reduce any distributional effects of policy. But it could help in explaining the impact of these actions, in a localised and personalised way, as a means of improving understanding and trust in central banks. Both have been a casualty of the crisis. Why Distributions Matter  Let me start with a bald statement: all public policy is distributional, be it monetary, fiscal, structural or social. The reason I know this is because redistribution is the way public policy works; it is what policy does for a living. Some policies redistribute resources between agents at a point in time. Others redistribute resources between agents over time. If policy is not working through one of these channels, it is not working. If all policy is distributional, it does not take much of a leap of imagination to see that policymakers may wish to understand and explain its distributional impact. In some policy settings, that already happens – in fiscal policy, social policy, climate change policy, pension policy.