Tag: productivity

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Why is UK productivity growth so low?

Since the financial crisis of 2008–9, the UK has experienced the lowest growth in productivity for the past 250 years. This is the conclusion of a recent paper published in the National Institute Economics Review. Titled, Is the UK Productivity Slowdown Unprecedented, the authors, Nicholas Crafts of the University of Sussex and Terence C Mills of Loughborough University, argue that ‘the current productivity slowdown has resulted in productivity being 19.7 per cent below the pre-2008 trend path in 2018. This is nearly double the previous worst productivity shortfall ten years after the start of a downturn.’

According to ONS figures, productivity (output per hour worked) peaked in 2007 Q4. It did not regain this level until 2011 Q1 and by 2019 Q3 was still only 2.4% above the 2007 Q4 level. This represents an average annual growth rate over the period of just 0.28%. By contrast, the average annual growth rate of productivity for the 35 years prior to 2007 was 2.30%.

The chart illustrates this and shows the productivity gap, which is the amount by which output per hour is below trend output per hour from 1971 to 2007. By 2019 Q3 this gap was 27.5%. (Click here for a PowerPoint of the chart.) Clearly, this lack of growth in productivity over the past 12 years has severe implications for living standards. Labour productivity is a key determinant of potential GDP, which, in turn, is the major limiter of actual GDP.

Crafts and Mills explore the reasons for this dramatic slowdown in productivity. They identify three primary reasons.

The first is a slowdown in the impact of developments in ICT on productivity. The office and production revolutions that developments in computing and its uses had brought about have now become universal. New developments in ICT are now largely in terms of greater speed of computing and greater sophistication of software. Perhaps with an acceleration in the development of artificial intelligence and robotics, productivity growth may well increase in the relatively near future (see third article below).

The second cause is the prolonged impact of the banking crisis, with banks more cautious about lending and firms more cautious about borrowing for investment. What is more, the decline in investment directly impacts on potential output, and layoffs or restructuring can leave people with redundant skills. There is a hysteresis effect.

The third cause identified by Crafts and Mills is Brexit. Brexit and the uncertainty surrounding it has resulted in a decline in investment and ‘a diversion of top-management time towards Brexit planning and a relative shrinking of highly-productive exporters compared with less productive domestically orientated firms’.

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Questions

  1. How suitable is output (GDP) per hour as a measure of labour productivity?
  2. Compare this measure of productivity with other measures.
  3. According to Crafts and Mills, what is the size of the impact of each of their three explanations of the productivity slowdown?
  4. Would you expect the growth in productivity to return to pre-2007 levels over the coming years? Explain.
  5. Explain the underlying model for obtaining trend productivity growth rates used by Crafts and Mills.
  6. Explain and comment on each of the six figures in the Crafts and Mills paper.
  7. What policies should the government adopt to increase productivity growth?
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A gift for the new decade: working less for more!

A lack of productivity growth has been a major problem for the UK economy over the past decade (click here for a PowerPoint of the chart). Is it possible that the new decade may see a pick-up in the growth in output per hour worked?

One possible solution to low productivity growth is to reduce working hours and even to move to a four-day week, but not to reduce total pay. If people work fewer hours, they may well be more productive in the hours they do work. In fact, not only may output per hour increase, but so too may output per worker, despite fewer hours being worked. What is more, the quality of output may increase with people being less tired and more motivated.

Several companies have experimented with a four-day week, including Microsoft in Japan, which employees 2300 workers. It found that, despite a 20% reduction in hours worked, output per hour worked increased by 40%, with total output thereby increasing. Workers were generally happier and more motivated and asked for fewer days off.

And it is not just a question of output: fewer hours can result in lower costs. The effect on costs will depend on the nature of new work patterns, including whether everyone has the same extra day off.

But a four-day week is only one way of cutting working hours for full-time employees. Another is to reduce the length of the working day. The argument is that people may work more efficiently if the standard working day is cut from eight to, say, five hours. As the first Thrive Global article article (linked below) states:

Just because you’re at your desk for eight hours doesn’t mean you’re being productive. Even the best employees probably only accomplish two to three hours of actual work. The five-hour day is about managing human energy more efficiently by working in bursts over a shorter period.

If people have more leisure time, this could provide a boost to the leisure and other industries. According to a Henley Business School study:

An extra day off could have a knock-on effect for the wider society. We found 54% of employees said they would spend their day shopping, meaning a potential boost for the high street, 43% would go to the cinema or theatre and 39% would eat out at restaurants.

What is more, many people would be likely to use the extra time productively, undertaking training, volunteering or other socially useful activities. Also family life is likely to improve, with people spending less time at work and commuting and having more time for their partners, children, other relatives and friends. In addition, people’s physical and mental health is likely to improve as they achieve a better work-life balance.

So, should firms be encouraged to reduce hours for full-time workers with no loss of pay? Many firms may need no encouragement at all if they can see from the example of others that it is in their interests. But many firms may find it difficult, especially if their suppliers and/or customers are sticking with ‘normal’ working hours and want to do business during those hours. But, over time, as more firms move in this direction, so it will become increasingly in the interests of others to follow suit.

In the meantime, should the government introduce incentives (such as tax breaks) or regulations to limit the working week? Indeed, it was part of the Labour manifesto for the December 2019 election that the country should, over time, move to a four-day week. Although this was a long-term goal, it would probably have involved the use of some incentives to encourage employers to move in that direction or the gradual introduction of limits on the number of hours or days per week that people could work in a particular job. It is unlikely that the new Conservative government will introduce any specific measures, but would probably not want to discourage firms from reducing working hours, especially if it is accompanied by increased output per worker.

But despite the gains, there are some problems with reduced working hours. Many small businesses, such as shops, restaurants and firms offering technical support, may not have the flexibility to offer reduced hours, or may find it hard to increase productivity when there is a specific amount of work that needs doing, such as serving customers.

Another problem concerns businesses where the output of individuals is not easy to measure because they are part of a team. Reducing hours or the working week may not make such people work harder if they can ‘get way with it’. Not everyone is likely to be motivated by fewer hours to work harder.

Then there is the problem if reduced hours don’t work in boosting productivity. It may then be very difficult to reintroduce longer hours.

But, despite these problems, there are many firms where substantial gains in productivity could be made by restructuring work in a way that reduces hours worked. We may see more and more examples as the decade progresses.

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Questions

  1. Distinguish between different ways of measuring labour productivity.
  2. Give some examples (from the linked references) of employers which have tried introducing a four-day week or reduced hours for full-time workers. What has been the outcome in each case?
  3. In what ways may reducing working hours reduce a firm’s total costs?
  4. What are the advantages and disadvantages of the government imposing (at some point in the future) a maximum working week or a four-day week?
  5. What types of firm might struggle in introducing a four-day week or a substantially reduced number of hours for full-time employees?
  6. What external benefits and costs might arise from a shorter working week?
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The costs of alternative Brexit scenarios

A general election has been called in the UK for 12 December. Central to the debates between the parties will be their policy on Brexit.

They range from the Liberal Democrats’, Plaid Cymru’s and Sinn Féin’s policy of cancelling Brexit and remaining in the EU, to the Scottish Nationalists’ and Greens’ policy of halting Brexit while a People’s Vote (another referendum) is held, with the parties campaigning to stay in the EU, to the Conservative Party’s policy of supporting the Withdrawal Agreement and Political Declaration negotiated between the Boris Johnson government and the EU, to the DUP which supports Brexit but not a version which creates a border between Great Britain and Northern Ireland, to the Brexit Party and UKIP which support leaving the EU with no deal (what they call a ‘clean break’) and then negotiating individual trade deals on a country-by-country basis.

The Labour Party also supports a People’s Vote, but only after renegotiating the Withdrawal Agreement and Political Declaration, so that if Brexit took place, the UK would have a close relationship with the single market and remain in a customs union. Also, various laws and regulations on environmental protection and workers’ rights would be retained. The referendum would take place within six months of the election and would be a choice between this new deal and remain.

But what are the economic costs and benefits of these various alternatives? Prior to the June 2016 referendum, the Treasury costed various scenarios. After 15 years, a deal would make UK GDP between 3.4% and 7.8% lower than if it remained in the EU, depending on the nature of the deal. No deal would make GDP between 5.4% and 9.5% lower.

Then in November 2018, the Treasury published analysis of the original deal negotiated by Theresa May in July 2018 (the ‘Chequers deal’). It estimated that GDP would be up to 3.9% lower after 15 years than it would have been if the UK had remained in the EU. In the case of a no-deal Brexit, GDP would be up to 9.3% lower after 15 years.

When asked for Treasury forecasts of the effects of Boris Johnson’s deal, the Chancellor, Sajid Javid, said that the Treasury had not been asked to provide forecasts as the deal was “self-evidently in our economic interest“.

Other forecasters, however, have analysed the effects of the Johnson deal. The National Institute for Economic and Social Research (NIESR), the UK’s longest established independent economic research institute, has estimated the costs of various scenarios, including the Johnson deal, the May deal, a no-deal scenario and also a scenario of continuing uncertainty with no agreement over Brexit. The NIESR estimates that, under the Johnson deal, with a successful free-trade agreement with the EU, in 10 years’ time UK GDP will be 3.5% lower than it would be by remaining in the EU. This represents a cost of £70 billion. The costs would arise from less trade with the EU, lower inward investment, slower growth in productivity and labour shortages from lower migration. These would be offset somewhat by savings on budget contributions to the EU.

Under Theresa May’s deal UK GDP would be 3.0% lower (and thus slightly less costly than Boris Johnson’s deal). Continuing in the current situation with chronic uncertainty about whether the UK would leave or remain would leave the UK 2% worse off after 10 years. In other words, uncertainty would be less damaging than leaving. The costs from the various scenarios would be in addition to the costs that have already occurred – the NIESR estimates that GDP is already 2.5% smaller than it would have been as a result of the 2016 Brexit vote.

Another report also costs the various scenarios. In ‘The economic impact of Boris Johnson’s Brexit proposals’, Professors Anand Menon and Jonathan Portes and a team at The UK in a Changing Europe estimate the effects of a decline in trade, migration and productivity from the various scenarios – again, 10 years after new trading arrangements are in place. According to their analysis, UK GDP would be 4.9%, 6.4% and 8.1% lower with the May deal, the Johnson deal and no deal respectively than it would have been from remaining in the EU.

But how much reliance should we put on such forecasts? How realistic are their assumptions? What other factors could they have taken into account? Look at the two reports and at the articles discussing them and then consider the questions below which are concerned with the nature of economic forecasting.

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Questions

  1. What are the arguments in favour of the assumptions and analysis of the two recent reports considered in this blog?
  2. What are the arguments against the assumptions and analysis of the two reports?
  3. How useful are forecasts like these, given the inevitable uncertainty surrounding (a) the outcome of negotiations post Brexit and (b) the strength of the global economy?
  4. If it could be demonstrated beyond doubt to everyone that each of the Brexit scenarios meant that UK GDP would be lower than if it remained in the EU, would this prove that the UK should remain in the EU? Explain.
  5. If economic forecasts turn out to be inaccurate, does this mean that economists should abandon forecasting?
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Automation revisited

It’s been a while since I last blogged about labour markets and, in particular, about the effect of automation on wages and employment. My most recent post on this topic was on the 14th of April 2018 and it was mostly a reflection on some interesting findings that had been reported by Acemoglu et al (2017). More specifically, Acemoglu and Restrepo (2017) developed a theoretical framework to evaluate the effect of AI on employment and wages. They concluded that the effect was negative and potentially sizeable (for a more detailed discussion see my blog).

Using a model in which robots compete against human labor in the production of different tasks, we show that robots may reduce employment and wages … According to our estimates, one more robot per thousand workers reduces the employment to population ratio by about 0.18–0.34 percentage points and wages by 0.25–0.5 percent.

Since then, I have seen a constant stream of news on my news feed about the development of ever more advanced industrial robots and artificial intelligence. And this was not because of some spooky coincidence (or worse). It has been merely a reflection of the speed at which technology has been progressing in this field.

There are now robots that can run, jump, hold conversations with humans, do gymnastics (and even sweat for it!) and more. It is really impressive how fast change has been happening recently in this field – and, unsurprisingly, it has stimulated the interest of labour economists!

A paper that has recently come to my attention on this subject is by Graetz and Michaels (2018). The authors put together a panel dataset on robot adoption within seventeen countries from 1993 to 2007 and use advanced econometric techniques to evaluate the effect of these technologies on employment and productivity growth. Their analysis focuses exclusively on developed economies (due to data limitations, as they explain) – but their results are nevertheless intriguing:

We study here for the first time the relationship between industrial robots and economic outcomes across much of the developed world. Using a panel of industries in seventeen countries from 1993 to 2007, we find that increased use of industrial robots is associated with increases in labor productivity. We find that the contribution of increased use of robots to productivity growth is substantial and calculate using conservative estimates that it comes to 0.36 percentage points, accounting for 15% of the aggregate economy-wide productivity growth.
 
The pattern that we document is robust to including various controls for country trends and changes in the composition of labor and other capital inputs. We also find that robot densification is associated with increases in both total factor productivity and wages, and reductions in output prices. We find no significant relationship between the increased use of industrial robots and overall employment, although we find that robots may be reducing the employment of low-skilled workers.

This is very positive news for most – except, of course, for low-skilled workers. Indeed, like Acemoglu and Restrepo (2017) and many others, this study shows that the effect of automation on employment and labour market outcomes is unlikely to be uniform across all types of workers. Low-skilled workers are found again to be likely to lose out and be significantly displaced by these technologies.

And if you are wondering which sectors are likely to be disrupted most/first by automation, the rankings developed by McKinsey and Company (see chart below) would give you an idea of where the disruption is likely to start. Unsurprisingly, the sectors that seem to be the most vulnerable, are the ones that use the highest share of low-skilled labour.

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Questions

  1. “The effect of automation on wages and employment is likely to be positive overall”. Discuss.
  2. Using examples and anecdotal evidence, do you agree with these findings?
  3. Using Google Scholar, put together a list of 5 recent (i.e. 2015 or later) articles and working papers on labour markets and automation. Compare and discuss their findings.
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Mind the productivity gap

Latest resesarch from the independent American think tank The Conference Board paints a worrying picture about the growth of UK labour productivity. While global growth in labour productivity has weakened following the financial crisis, its weakness in the UK is singled out in the Board’s 2019 Productivity Brief. It finds that amongst large mature economies the decline in labour productivity growth rates has been greatest in the UK. This has important implications for the country’s longer-term well-being and, specifically, it peoples’ living standards.

The UK saw the growth in real GDP (national output) fall from 1.8 per cent in 2017 to 1.4 per cent in 2018. The Conference Board predicts that this will fall further to 0.8 per cent in 2019. In the context of living standards, the growth in real GDP per capita is particularly important. An increase in the population will, other things being equal, lower living standards because more people will be sharing a given amount of real national income. The growth in real GDP per capita fell from 1.1 per cent in 2017 to 0.7 per cent in 2018 and is predicted to fall to just 0.1 per cent in 2019.

Chart 1 shows the annual rates of growth in real GDP and real GDP per capita from the 1950s. The average growth rates are 2.4 and 1.9 per cent respectively. The other series shown is the annual growth in real GDP per person employed. This is a measure of the growth in labour productivity. Its average annual growth rate is also 1.9 per cent. This illustrates the intrinsic long-run relationship between labour productivity growth and the growth rate of GDP per capita and hence in general living stanadards. (Click here to download a PowerPoint copy of the chart.)

In the short term, rates of growth in output per worker (labour productivity) and GDP per capita (general living standards) can be less similar. For example, when unemployment rates rise labour productivity rates may be little affected despite GDP per capita falling. Nonetheless, the important point here is the close long-run relationship between the growth in labour productivity and GDP per capita. This then raises an important question: what factors contribute to the growth in output and labour productivity?

An approach known as growth accounting helps to identify four key contributors to the growth of total output. The first is the quantity of labour, commonly measured in labour hours. The second is the quality of labour, also known as labour composition. Third is capital services which are physical inputs into production and include machinery, structures and IT capital. Capital services are affected by quantity and quality, but, unlike labour, it is practically more difficult to separate out these dimensions. Fourth, is Total Factor Productivity (TFP).

TFP it is essentially the residual contribution to output growth that cannot be explained by changes in the quantity and quality of the individual inputs. Hence, in principle, it is capturing changes in how effectively the labour and capital inputs are being employed and combined in production. The Conference Board’s Productivity Brief describes the growth in TFP as providing ‘a more accurate picture of the overall efficiency by which capital, labour and skills are combined in the production process’.

Chart 2 shows Conference Board estimates of the percentage point contribution of these four sources of growth since 1990. Over this period, output growth averaged 2 per cent per year. The contribution of capital services and, hence, what is known as capital accumulation is particularly significant at 1.5 percentage points per year. This has been significantly larger than the contribution of labour hours which averaged only 0.3 percentage points per year since 1990. This evidences the importance played by capital deepening for output growth in the UK. (Click here to download a PowerPoint copy of the chart.)

Capital deepening captures the growth in capital services relative to the growth in the labour input. It takes on even greater significance when we think about the growth in labour productivity since, after all, this is the growth in output relative to the quantity of labour. It is significant though that since 2015 the growth of capital services has contributed only 1 percentage point to output growth while the growth of labour hours has contributed an average of 0.7 percentage points. This points to a slowdown in capital deepening and hence in the growth of labour productivity.

Chart 2 also illustrates the importance of TFP growth to overall output growth. It is also important (along with capital deepening and the growth in labour quality) for the growth in labour productivity. Interestingly, we observe significant fluctuations in the growth of TFP. This is thought to reflect fluctuations in the utilisation of inputs. For example, if the utilisation of inputs falls (rises) when output falls (increases) this will be mirrored by a disproportionately large fall (increase) in TFP. In the longer-term, however, changes in TFP capture aspects of technological progress and advancement that enable more effective production methods and techniques to be deployed. In other words, the growth of TFP captures the ability of production to benefit from the advancement in ideas, products, processes and know-how.

A decline in the growth in TFP growth following the financial crisis is found quite widely in mature economies. The annual rate of growth of TFP across mature economies fell from 0.5 per cent year in 2000-2007 to 0.2 per cent in 2010-2017. In the UK this fall was from 0.5 per cent to -0.1 per cent. Hence, the decline in TFP growth of 0.6 percentage points between 2010 and 2017 was double the 0.3 percentage point fall across all mature economies. In 2018 the Conference Board estimate that TFP in the UK fell by 0.1 percent further exacerbating the downward pressure on labour productivity.

As our final chart shows, it is the magnitude to which labour productivity has eased following the financial crisis that sets the UK apart. While across all mature economies the growth of output per labour hour (another measure of labour productivity growth) fell from an average of 2.3 per cent per year in 2000-2007 to 1.2 per cent in 2010-2017, in the UK the fall was from 2.2 per cent to 0.5 per cent per year. (Click here to download a PowerPoint copy of the chart.)

While the productivity problem facing the UK is not new, the latest figures comes as a very timely reminder of the extent of the problem. To some extent the uncertainty around Brexit and the negative impact on capital accumulation has only helped to exacerbate the problem. But, this may mask a more systemic problem facing the UK. Getting to the root of this problem matters. It matters most significantly for our long-term wellbeing and prosperity. The productivity gap with our major industrial competitors is a gap that policymakers need not only to be mindful of but one that needs closing.

Articles

Questions

  1. What do you understand by the term labour productivity. How could we measure it?
  2. Why is it important to look at the growth of output per capita when assessing the benefits of long-term growth?
  3. Why is labour productivity important for the long-term well-being of a country?
  4. What do you understand by the method of growth accounting?
  5. What is the distinction between capital accumulation and capital deepening?
  6. What might explain why the growth of labour productivity has been lower in the years following the post-financial crisis?
  7. What do you understand by Total Factor Productivity (TFP)?
  8. What does the long-term growth of TFP attempt to capture?
  9. If you were an economic advisor to the government, what types of policy initiatives might you recommend for a government concerned about low rates of growth of labour productivity?