The dispersion of services sector productivity is more than 50% higher in the UK than in other advanced economies (Chart 20a). It has also widened by materially more in the UK. Even in a world of long and lengthening tails of low-productivity companies, the UK is a striking outlier. One potential explanation for this longer tail of UK companies than elsewhere is poor management practices. Using the database developed by Bloom and Van Reenen (2007), we can plot a normalised distribution of management skills for a subset of UK firms. 51  This suggests (a lack of) management quality is a plausible  candidate explanation for the UK’s long tail of companies, as Bloom and Van Reenen find (Chart 21). Looked at quantitatively, there is a statistically significant link between the quality of firms’ management processes and practices and their productivity. And the effect is large. A one standard deviation improvement in the quality of management raises productivity by, on average, around 10%. This suggests potentially high returns to policies which improve the quality of management within companies. Decomposing the Distribution  We can go further in uncovering some of the characteristics of the companies in the upper and lower tails. Might they simply reflect sharp regional differences in productivity, with frontier companies clustered in some regions and laggards in others? Might it simply reflect some sectors, such as manufacturing, generating higher levels of productivity and sitting in the frontier while others, such as services, occupy the lower tail?
The latter episodes have typically been associated with periods of rapid technological th  th  th  change, as after the three industrial revolutions of the mid-18 , mid-19 and mid-20 centuries. In each case, there was a significant lag between the arrival of new technologies and their impact on productivity. Rates of technological diffusion were relatively slow and sedate. This is typically felt to have reflected the time it takes for new technologies to find widespread use and become General Purpose Technologies (GPTs). 34  After the first Industrial Revolution, it took around 70-100 years for technological  diffusion to occur, GPTs to emerge and TFP and living standards to rise. 35  Subsequent industrial revolutions have also seen a lag between the emergence of new technologies and their impact on productivity. But there is evidence this diffusion lag may have shortened. Comin and th  th  Mestieri (2014) estimate the diffusion lag during the industrial revolutions of the late 19 and 20 centuries to have been 20-30 years, roughly a third of that during the first industrial revolution. This may have reflected increased flows of labour, capital, ideas and information between firms, regions, sectors and countries. Table 1 looks at average rates of UK TFP growth over the past 2000 years. It tells a tale of long waves of productivity stagnation and innovation. The historical data do not reject either hypothesis. Table 1 also puts into historical perspective the UK’s recent productivity slowdown.