40  All speeches are available online at www.bankofengland.co.uk/speeches  40  Chart 25: Cartogram of local-authority level ECIs  Sources: ONS Business Register and Employment Survey (BRES) and Bank calculations. Notes: UK NUTS 3 regions re-sized and coloured using estimates of economic complexity. 41  All speeches are available online at www.bankofengland.co.uk/speeches  41  Table 1 lists the top ten local authorities by ECI across the UK in 2017, while Table 2 shows the bottom ten. There is a high degree of inertia in both rankings. The ECI framework could be used to help assess which industrial strategy interventions might boost the degree of specialism and diversity, and hence the income benefits, both in already-successful and struggling regions. Table 2: Bottom 10 local authorities by ECI Dudley  Moray  South Derbyshire  Hartlepool  Wrexham  Carmarthenshire  Aberdeenshire  Breckland  North-East Lincolnshire  Telford and Wrekin  Sources: ONS Business Register and Employment Survey (BRES) and Bank calculations. Economic complexity can also be assessed across industries using a product complexity index (PCI). This proxies the embedded knowledge in an industry. Table 3 plots the top-20 UK industries by PCI against their sector shares. Financial services, the creative industries, and higher education exhibit the highest economic complexity and thus potentially generate the highest value-added. PCI metrics could be used to identify industries where “sector deals” could benefit most the economy, as part of an industrial strategy.
Germany has nothing like the same skew, with the cartogram and map little different.10 A key focus of work among economic geographers is the importance of agglomeration effects – that is, increasing returns to economic scale at the spatial level.11 If those effects are powerful, and if workers are one of their most important sources, we would expect cartograms to have similar properties when looked at by population, income (per head) and wealth (per household). More should not only be merrier but wealthier. 6  For example, Case and Deaton (2017). For example, Viscek, Shlesinger and Matsushita (1994). McCann (2016), Centre for Cities (2019), What Works Centre for Local Economic Growth (2018). 9 See Dougenik, Chrisman and Niemeyer (1985). 10 Put differently, the correlation between geographic area size and population in the UK is in fact slightly negative (-0.05) while it is relatively high and positive (0.7) in Germany. 11 Viladecans-Marsal (2004) and Rosenthal and Strange (2003), example. 7 8  4  All speeches are available online at www.bankofengland.co.uk/speeches  4  Chart 1a: Map (LHS) and cartogram (RHS) of population in the UK  5  All speeches are available online at www.bankofengland.co.uk/speeches  5  Chart 1b: Map (LHS) and cartogram (RHS) of population in Germany  Sources: Eurostat and Bank calculations. Notes: Charts show population in 2018 for NUTS 1 regions. Cartograms resized by population. As Charts 2 and 3 show, broadly-speaking that is the case. The income per head cartogram suggests a shrunken North and a swollen South.