It is impossible for the Bank of England to set separate interest rates for Aberdeen and Aberystwyth, Belfast and Birmingham. A central bank, by definition, cannot be local. Or can it? I would argue that not only is this feasible but essential. I have spoken previously about the “twin deficit” problem facing central banks: the deficit in public understanding and the deficit in public trust.56 Boosting this understanding, and restoring trust, among the public is among the most pressing issues facing central banks. Reconnecting communities with institutions helps strengthen Rajan’s Third Pillar. But how is this best done? The public’s understanding of the economy and policy is enhanced when messages are relevant to their lives and locality. 57 A central bank’s understanding of the economy is enhanced if it can tap into the lived, local experiences of companies and citizens making up the economy. And a better mutual understanding between communities and central banks would, in turn, help build trust between them. Constructing a Third Pillar shrinks the twin deficits of public trust and understanding. This is not a new point. Despite being headquartered in London since 1694, the Bank of England has had a regional presence for much of its history. After the UK banking crisis of 1825, the Bank set up a network of 15 regional branches to provide commercial banking facilities.58 Though their purpose was operational, it quickly became clear that the intelligence gathered by the Bank’s branches could help in understanding the economy.
Two colleagues at the Bank, Fergus Cumming and Al Firrell, have recently used a database on all mortgages granted in the UK since 2005 to explore house-moving patterns.42 The results are preliminary, but let me share some of the early findings to demonstrate what might be feasible. Chart 19 plots the frequency of house moves at different distances in 2018. The modal distance of a house move is less than 10km. This is twice as likely as the second most popular distance – 10-20km. In other words, a gravity (distance) model of house moves fits the data, with around one-third of all house moves within 50km. Most house moves are local. Most, but by no means all. The median move is a little below 100km, the mean 130km. There is a longer tail of long-distance house moves than I would have predicted. 42  Although this may sound simple, it involves a complex matching algorithm to identify housing chains, similar to Chakraborty, Gimpelewicz and Uluc (2017). 31  All speeches are available online at www.bankofengland.co.uk/speeches  31  Chart 19: Distribution of house moves by distance (mortgage-to-mortgage movers in 2018)  Sources: Product Sales Database and Bank calculations. Part of the explanation lies in regional and demographic differences. People outside London and the  South-East – for example, in Scotland – are much more likely to move greater distances (Chart 20). Older people (over 46) are more likely to move larger distances than younger people (under 33) (Chart 21).