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’.
- How suitable is output (GDP) per hour as a measure of labour productivity?
- Compare this measure of productivity with other measures.
- According to Crafts and Mills, what is the size of the impact of each of their three explanations of the productivity slowdown?
- Would you expect the growth in productivity to return to pre-2007 levels over the coming years? Explain.
- Explain the underlying model for obtaining trend productivity growth rates used by Crafts and Mills.
- Explain and comment on each of the six figures in the Crafts and Mills paper.
- What policies should the government adopt to increase productivity growth?
How would your life be without the internet? For many of you, this is a question that may be difficult to answer – as the internet has probably been an integral part of your life, probably since a very young age. We use internet infrastructure (broadband, 4G, 5G) to communicate, to shop, to educate ourselves, to keep in touch with each other, to buy and sell goods and services. We use it to seek and find new information, to learn how to cook, to download music, to watch movies. We also use the internet to make fast payments, transfer money between accounts, manage our ISA or our pension fund, set up direct debits and pay our credit-card bills.
I could spend hours writing about all the things that we do over the internet these days, and I would probably never manage to come up with a complete list. Just think about how many hours you spend online every day. Most likely, much of your waking time is spent using internet-based services one way or another (including apps on your phone, streaming on your phone, tablet or your smart TV and similar). If your access to the internet was disrupted, you would certainly feel the difference. What if you just couldn’t afford to have computer or internet access? What effect would that have on your education, your ability to find a job, and your income?
Martin Jenkins, a former homeless man, now entrepreneur, thinks that the magnitude of this effect is rather significant. In fact, he is so convinced about the importance of bringing the internet to poorer households, that he recently founded a company, Neptune, offering low-income households in the Bronx district of New York free access to online education, healthcare and finance portals. His venture was mentioned in a recent (and very interesting) BBC article – a link to which can be found at the end of this blog. But is internet connectivity really that important when it comes to economic and labour market outcomes? And is there a systematic link between economic growth and internet penetration rates?
These are all questions that have been the subject of intensive debate over the last few years, in the context of both developed and developing economies. Indeed, the ‘digital divide’ as it is known (the economic gap between the internet haves and have nots) is not something that concerns only developing countries. According to a recent policy brief published by the New York City Comptroller:
More than one-third (34 percent) of households in the Bronx lack broadband at home, compared to 30 percent in Brooklyn, 26 percent in Queens, 22 percent in Staten Island, and 21 percent in Manhattan.
The report goes on to present data on the percentage of households with internet connection at home by NYC district, and it does not take advanced econometric skills for one to notice that there is a clear link between median district income and broadband access. Wealthier districts (e.g. Manhattan Community District 1 & 2 – Battery Park City, Greenwich Village & Soho PUMA), tend to have a significantly higher share of households with broadband access, than less affluent ones (e.g. NYC-Brooklyn Community District 13 – Brighton Beach & Coney Island PUMA) – 88% of total households compared with 58%.
But, do these large variations in internet connectivity matter? The evidence is mixed. On the one hand, there are several studies that find a clear, strong link between internet penetration and economic growth. Czernich et al (2011), for instance, using data on OECD countries over the period 1996–2007, find that “a 10 percentage point increase in broadband penetration raised annual per capita growth by 0.9–1.5 percentage points”.
Another study by Koutroumpis (2018) examined the effect of rolling out broadband in the UK.
For the UK, the speed increase contributed 1.71% to GDP in total and 0.12% annually. Combining the effect of the adoption and speed changes increased UK GDP by 6.99% cumulatively and 0.49% annually on average”. (pp.10–11)
The evidence is less clear, however, when one tries to estimate the benefits between different types of workers – low and high skilled. In a recent paper, Atasoy (2013) finds that:
gaining access to broadband services in a county is associated with approximately a 1.8 percentage point increase in the employment rate, with larger effects in rural and isolated areas.
But then he adds:
most of the employment gains result from existing firms increasing the scale of their labor demand and from growth in the labor force. These results are consistent with a theoretical model in which broadband technology is complementary to skilled workers, with larger effects among college-educated workers and in industries and occupations that employ more college-educated workers.
Similarly, Forman et al (2009) analyse the effect of business use of advanced internet technology and local variation in US wage growth, over the period 1995–2000. Their findings show that:
Advanced internet technology is associated with larger wage growth in places that were already well off. These are places with highly educated and large urban populations, and concentration of IT-intensive industry. Overall, advanced internet explains over half of the difference in wage growth between these counties and all others.
How important then is internet access as a determinant of growth and economic activity and what role does it have in bridging economic disparities between communities? The answer to this question is most likely ‘very important’ – but less straightforward than one might have assumed.
- Comptroller, New York City, Internet Inequality
- Czernich, N., Falck, O., Kretschmer, T. and Woessmann, L., 2011, Broadband infrastructure and economic growth, The Economic Journal, 121(552), pp.505–32
- Koutroumpis, P., 2018, The economic impact of broadband: evidence from OECD countries, Ofcom
- Atasoy, H., 2013, The effects of broadband internet expansion on labor market outcomes, ILR Review, 66(2), pp.315–45
- Forman, C., Goldfarb, A. and Greenstein, S., 2009, The Internet and Local Wages: Convergence or Divergence? (No. w14750), National Bureau of Economic Research
- Is there a link between economic growth and internet access? Discuss, using examples.
- Explain the arguments for and against government intervention to subsidise internet access of poorer households.
- How important is the internet to you and your day to day life? Take a day offline (yes, really – a whole day). Then come back and write about it.
Cloud computing is growing rapidly and has started to dominate many parts of the IT market. Cloud revenues are rising at around 25% per year and, according to Jeremy Duke of Synergy Research Group:
“Major barriers to cloud adoption are now almost a thing of the past, especially on the public-cloud side. Cloud technologies are now generating massive revenues for technology vendors and cloud service providers, and yet there are still many years of strong growth ahead.”
The market leader in cloud services (as opposed to cloud hardware) is Amazon Web Services (AWS), a subsidiary of Amazon. At the end of 2016, it had a market share of around 40%, larger than the next three competitors (Microsoft, Google and IBM), combined. AWS originated cloud computing some 10 years ago. It is set to have generated revenue of $13 billion in 2016.
The cloud computing services market is an oligopoly, with a significant market leader, AWS. But is the competition from other players in the market, including IT giants, such as Google, Microsoft, IBM and Oracle, enough to guarantee that the market stays competitive and that prices will fall as technology improves and costs fall?
Certainly all the major players are investing heavily in new services, better infrastructure and marketing. And they are already established suppliers in other sectors of the IT market. Microsoft and Google, in particular, are strong contenders to AWS. Nevertheless, as the first article states:
Neither Google nor Microsoft have an easy task since AWS will continue to be an innovation machine with a widely recognized brand among the all-important developer community. Both Amazon’s major competitors have an opportunity to solidify themselves as strong alternatives in what is turning into a public cloud oligopoly.
While Amazon dominates cloud infrastructure, an oligopoly is emerging. Which will buyers bet on? diginomica, Kurt Marko (16/2/17)
Study: AWS has 45% share of public cloud infrastructure market — more than Microsoft, Google, IBM combined GeekWire, Dan Richman (31/10/16)
Cloud computing revenues jumped 25% in 2016, with strong growth ahead, researcher says GeekWire, Dan Richman (4/1/17)
Press releases Synergy Research Group
- Distinguish the different segments of the cloud computing market.
- What competitive advantages does AWS have over its major rivals?
- What specific advantages does Microsoft have in the cloud computing market?
- Is the amount of competition in the cloud computing market enough to prevent the firms from charging excessive prices to their customers? How might you assess what is ‘excessive’?
- What barriers to entry are there in the cloud computing market? Should they be a worry for competition authorities?
- Are the any network economies in cloud computing? What might they be?
- Cloud computing is a rapidly developing industry (for example, the relatively recent development of cloud containers). How does the speed of development impact on competition?
- How would market saturation affect competition and the behaviour of the major players?
The articles below examine the rise of the sharing economy and how technology might allow it to develop. A sharing economy is where owners of property, equipment, vehicles, tools, etc. rent them out for periods of time, perhaps very short periods. The point about such a system is that the renter deals directly with the property owner – although sometimes initially through an agency. Airbnb and Uber are two examples.
So far the sharing economy has not developed very far. But the development of smart technology will soon make a whole range of short-term renting contracts possible. It will allow the contracts to be enforced without the need for administrators, lawyers, accountants, bankers or the police. Payments will be made electronically and automatically, and penalties, too, could be applied automatically for not abiding by the contract.
One development that will aid this process is a secure electronic way of keeping records and processing payments without the need for a central authority, such as a government, a bank or a company. It involves the use of ‘blockchains‘ (see also). The technology, used in Bitcoin, involves storing data widely across networks, which allows the data to be shared. The data are secure and access is via individuals having a ‘private key’ to parts of the database relevant to them. The database builds in blocks, where each block records a set of transactions. The blocks build over time and are linked to each other in a logical order (i.e. in ‘chains’) to allow tracking back to previous blocks.
Blockchain technology could help the sharing economy to grow substantially. It could significantly cut down the cost of sharing information about possible rental opportunities and demands, and allow minimal-cost secure transactions between owner and renter. As the IBM developerWorks article states:
Rather than use Uber, Airbnb or eBay to connect with other people, blockchain services allow individuals to connect, share, and transact directly, ushering in the real sharing economy. Blockchain is the platform that enables real peer-to-peer transactions and a true ‘sharing economy’.
New technology may soon resurrect the sharing economy in a very radical form The Guardian, Ben Tarnoff (17/10/16)
Blockchain and the sharing economy 2.0 IBM developerWorks, Lawrence Lundy (12/5/16)
2016 is set to become the most interesting year yet in the life story of the sharing economy Nesta, Helen Goulden (Dec 2015)
Blockchain Explained Business Insider, Tina Wadhwa and Dan Bobkoff (16/10/16)
A parliament without a parliamentarian Interfluidity, Steve Randy Waldman (19/6/16)
Blockchain and open innovation: What does the future hold Tech City News, Jamie QIU (17/10/16)
Banks will not adopt blockchain fast Financial Times, Oliver Bussmann (14/10/16)
Blockchain-based IoT project does drone deliveries using Ethereum International Business Times, Ian Allison (14/10/16)
- What do you understand by the ‘sharing economy’?
- Give some current examples of the sharing economy? What other goods or services might be suitable for sharing if the technology allowed?
- How could blockchain technology be used to cut out the co-ordinating role carried out by companies such as Uber, eBay and Airbnb and make their respective services a pure sharing economy?
- Where could blockchain technology be used other than in the sharing economy?
- How can blockchain technology not only record property rights but also enforce them?
- What are the implications of blockchain technology for employment and unemployment? Explain.
- How might attitudes towards using the sharing economy develop over time and why?
- Referring to the first article above, what do you think of Toyota’s use of blockchain to punish people who fall behind on their car payments? Explain your thinking.
- Would the use of blockchain technology in the sharing economy make markets more competitive? Could it make them perfectly competitive? Explain.
What will production look like in 20 years time? Will familiar jobs in both manufacturing and the services be taken over by robots? And if so, which ones? What will be the effect on wages and on unemployment? Will most people be better off, or will just a few gain while others get by with minimum-wage jobs or no jobs at all?
The BBC has been running a series looking at new uses for robots and whether they will take people’s jobs? This complements three reports: one by Boston Consulting one by Deloitte and an earlier one by Deloitte and Michael Osborne and Carl Frey from Oxford University’s Martin School. As Jane Wakefield, the BBC’s technology reporter states:
Boston Consulting Group predicts that by 2025, up to a quarter of jobs will be replaced by either smart software or robots, while a study from Oxford University has suggested that 35% of existing UK jobs are at risk of automation in the next 20 years.
Jobs at threat from machines include factory work, office work, work in the leisure sector, work in medicine, law, education and other professions, train drivers and even taxi and lorry drivers. At present, in many of these jobs machines work alongside humans. For example, robots on production lines are common, and robots help doctors perform surgery and provide other back-up services in medicine.
A robot may not yet have a good bedside manner but it is pretty good at wading through huge reams of data to find possible treatments for diseases.
Even if robots don’t take over all jobs in these fields, they are likely to replace an increasing proportion of many of these jobs, leaving humans to concentrate on the areas that require judgement, creativity, human empathy and finesse.
These developments raise a number of questions. If robots have a higher marginal revenue product/marginal cost ratio than humans, will employers choose to replace humans by robots, wholly or in part? How are investment costs factored into the decision? And what about industrial relations? Will employers risk disputes with employees? Will they simply be concerned with maximising profit or will they take wider social concerns into account?
Then there is the question of what new jobs would be created for those who lose their jobs to machines. According to the earlier Deloitte study, which focused on London, over 80% of companies in London say that over the next 10 years they will be most likely to take on people with skills in ‘digital know-how’, ‘management’ and ‘creativity’.
But even if new jobs are created through the extra spending power generated by the extra production – and this has been the pattern since the start of the industrial revolution some 250 years ago – will these new jobs be open largely to those with high levels of transferable skills? Will the result be an ever widening of the income gap between rich and poor? Or will there be plenty of new jobs throughout the economy in a wide variety of areas where humans are valued for the special qualities they bring? As the authors of the later Deloitte paper state:
The dominant trend is of contracting employment in agriculture and manufacturing being more than offset by rapid growth in the caring, creative, technology and business services sectors.
The issues of job replacement and job creation, and of the effects on income distribution and the balance between work and leisure, are considered in the following videos and articles, and in the three reports.
What is artificial intelligence? BBC News, Valery Eremenko (13/9/15)
What jobs will robots take over? BBC News, David Botti (15/8/14)
Could a robot do your job? BBC News, Rory Cellan-Jones (14/9/15)
Intelligent machines: The robots that work alongside humans BBC News, Rory Cellan-Jones (14/9/15)
Intelligent machines: Will you be replaced by a robot? BBC News, John Maguire (14/9/15)
Will our emotions change the way adverts work? BBC News, Dan Simmons (24/7/15)
Could A Robot Do My Job? BBC Panorama, Rohan Silva (14/9/15)
Technology has created more jobs in the last 144 years than it has destroyed, Deloitte study finds Independent, Doug Bolton (18/8/15)
Technology has created more jobs than it has destroyed, says 140 years of data The Guardian, Katie Allen (18/8/15)
Will a robot take your job? BBC News (11/9/15)
Intelligent Machines: The jobs robots will steal first BBC News, Jane Wakefield (14/9/15)
Robots Could Take 35 Per Cent Of UK Jobs In The Next 20 Years Says New Study Huffington Post, Thomas Tamblyn (14/9/15)
The new white-collar fear: will robots take your job? The Telegraph, Rohan Silva (12/9/15)
Does technology destroy jobs? Data from 140 years says no Catch news, Sourjya Bhowmick (11/9/15)
Takeoff in Robotics Will Power the Next Productivity Surge in Manufacturing Boston Consulting Group (10/2/15)
Agiletown: the relentless march of technology and London’s response Deloitte (November 2014)
Technology and people: The great job-creating machine Deloitte, Ian Stewart, Debapratim De and Alex Cole (August 2015)
- Which are the fastest growing and fastest declining occupations? To what extent can these changes be explained by changes in technology?
- What type of unemployment is caused by rapid technological change?
- Why, if automation replaces jobs, have jobs increased over the past 250 years?
- In what occupations is artificial intelligence (AI) most likely to replace humans?
- To what extent are robots and humans complementary rather than substitute inputs into production?
- “Our analysis of more recent employment data also reveals a clear pattern to the way in which technology has affected work.” What is this pattern? Explain.
- Why might AI make work more interesting for workers?
- Using a diagram, show how an increase in workers’ marginal productivity from working alongside robots can result in an increase in employment. Is this necessarily the case? Explain.