chart with different sectors ’ contributions to the whole economy labour productivity growth ( slide 4 ). the manufacturing and finance & insurance sectors made no contribution to average annual productivity growth in 2010 - 16. pre - crisis, these sectors contributed around ¾pp to annual average productivity growth. so combined, they accounted for over half of the growth puzzle to 2016, despite employing only 11 % of the workforce. indeed the treasury ’ s 2009 budget forecast applied a downward adjustment to the trend level of output of around 5 % between mid2007 and mid - 2010, which was within the range of external estimates of the impact of the global credit shock on medium - term potential output. haldane see also tenreyro all speeches are available online at www. bankofengland. co. uk / speeches three other sectors – communications, professional & scientific services, and real estate – almost fully account for the remainder of the growth puzzle. of course there are limitations to pre - crisis comparisons. the finance sector is a good example. increased leverage and risk - taking with financial firms prior to the crisis is likely to have boosted measured productivity, beyond what was sustainable. third, both slow growth in capital per hour worked ( known as capital deepening ) and the efficiency with which companies put their labour and capital inputs to use ( known as total factor productivity ) have contributed to weak growth in roughly equal measure. while the weakness in total factor productivity growth has been concentrated in manufacturing and finance, the weakness in capital deepening has been more widespread across sectors. in other words, whatever is driving slower capital deepening is likely to be more widespread across the economy. general uncertainty is one likely candidate, and may have been more of a feature in the uk than elsewhere, particularly in the period since the euro area crisis. indeed, the most commonly used measure of policy uncertainty has generally been more elevated for the uk than the equivalent measures for europe and the us, although it has fallen back sharply from its post referendum peaks ( slide 5 ). in periods of elevated uncertainty, businesses may be reluctant to undertake investment and prefer to employ more labour, which is easier to reverse, as i suggested in a speech in november last year. and a range of survey results suggest that brexit related uncertainty is an important factor weighing on investment in the uk, despite otherwise favourable conditions for capital expenditure globally and domestically. fourth, the slowing in uk productivity growth since the crisis has primarily reflected slower growth of high - productivity companies. as discussed in the

to base ratings and capital on a borrower ’ s position at the top of an economic cycle. operational risk use of internal ratings will of course raise many of the sorts of difficulties for testing and validation that were identified for credit risk modelling. however, we are at least talking about a reasonably well - defined type of risk and one which is quantifiable in statistical terms. we are in much more difficult territory when it comes to operational risk. the term operational risk covers a wide range of types and sources of risk, and banks ’ data bases of loss are generally patchy. there are numerous questions not only about the appropriate design of the charge, but also about the appropriate level. it is clear that some types of operational risk, such as fraud, can result in huge spikes of loss, as we saw in the case of barings and morgan grenfell. even though we are concerned with protecting the system, i feel it would be inappropriate to expect most banks to hold an additional cushion of capital to cover these sorts of very rare events : it would either be grossly excessive for most of the time, or alternatively seriously inadequate if a major problem arose. so the focus here must be on systems and controls, and on using variable target capital ratios under pillar 2 to encourage improvements in these. moreover, the appropriate level of capital will depend in part on how far we think operational losses are correlated with other types of loss which are already covered by capital. probably there are some types of operational loss - processing errors, settlement delays - which do not exhibit a high correlation with either credit or market risk. but in practice, there is clear evidence that credit or market losses put pressure on the firm, which can push managers into fraud or result in operationally - risky cost cutting. there have certainly been occasions when operational losses have only been revealed because of a market downturn or similar event. as i heard it graphically expressed the other day : “ it is only when the tide goes out that you discover who is not wearing a bathing costume ”! i am optimistic that, over time, operational risk will become more measurable and that, as was the case for market risk models, a consensus on methods of quantifying it will emerge. the basel committee ’ s framework will certainly have to be flexible in the face of this evolution. however, we should also not lose sight of the fact that the committee ’ s announced aim is not just coverage of operational risks, but “ other ”