The gap between richest and poorest region is around 150%. For wealth per household, the North-South divide is also large, with a gap between richest and poorest of 130%. These are striking differences. But are they unusual compared either with the past or other countries? 6  All speeches are available online at www.bankofengland.co.uk/speeches  6  Chart 2: Cartogram of UK income per head  Sources: Eurostat and Bank calculations. Notes: Purchasing power standard (PPS) per inhabitant for NUTS 1 regions. 7  All speeches are available online at www.bankofengland.co.uk/speeches  7  Chart 3: Cartogram of Great Britain wealth per household  Sources: ONS Wealth and Assets Survey and Bank calculations. Notes: Data refer to 2014-16 for NUTS 1 regions, re-sized and coloured by median household wealth. No equivalent data available for Northern Ireland. 8  All speeches are available online at www.bankofengland.co.uk/speeches  8  On the first of those, Chart 4 plots the distribution of income per head across UK regions on three dates: 1997, 2007 and 2016. All of the distributions are centred on mean levels of income in 2016. This suggests a modest increase in the degree of regional income dispersion over time. The 2016 distribution has somewhat fatter tails, lower and upper, than in earlier periods.12  Chart 4: Distribution of UK income per head over time (mean-aligned)  Sources: ONS and Bank calculations. Notes: Chart shows regional gross disposable income for different time periods at current basic prices, centred around the 2016 mean.
Importantly, it improves the decisions they make, nationally and locally, governments and citizens. Weather is by no means a unique example. Micro-level data, digital twins and massive-scale simulations are being used to better understand all manner of other systems at all manner of resolutions – from the sub-atomic scale when seeking the Higgs-Boson, to the global scale when modelling flows across oceans, the world wide web and galaxies. All have benefitted from drawing on mass micro-level data, crowd-  sourced, centrally-stitched, micro-to-macro. Until recently, fewer such high-resolution data existed when it came to tracking flows of goods and services, people and money through our economy. That is changing. These data increasingly exist in companies, whose management systems capture activity in close to real time. They exist through now-ubiquitous  sensor, camera and satellite technology. And they exist in governments, local and central, in the form of administrative data on people, goods and money flows. Increasingly, these data are being put to use to understand the economy.40 In the UK, the Office for National Statistics recently started publishing a range of high frequency economic indicators, based on such sources as administrative data on VAT returns and geospatial data on traffic flows. The Bank has made increasing use of these sorts of data in its own real-time assessment of the economy. Let me give a couple of examples. One topic attracting attention recently has been the economic consequences of a disruptive Brexit.