Tag: productivity

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 Growth accounting 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?

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.

Article

References

Questions

  1. Is there a link between economic growth and internet access? Discuss, using examples.
  2. Explain the arguments for and against government intervention to subsidise internet access of poorer households.
  3. 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.

Workers in the UK and USA work much longer hours per year than those in France and Germany. This has partly to do with the number of days paid holiday per year, partly with the number of hours worked per day and partly with the number of days worked per week.

According to the latest OECD figures, in 2017 average hours worked per year ranged from 2257 in Mexico (the OECD’s highest) to 1780 in the USA, 1710 in Japan, 1681 in the UK, 1514 in France, 1408 in Denmark and 1356 in Germany (the OECD’s lowest). Annual working hours have been falling in most countries across the decades, as the chart shows. However, in most countries the process has slowed in recent years and in the UK, the USA and France working hours have begun to rise. (Click here for a PowerPoint of the chart.)

But why do working hours differ so much from country to country? How do they relate to productivity? How do they relate to human happiness and welfare more generally?

Causes of the differences

There are various reasons for the differences in hours worked between countries.

In a situation where individual workers can choose how many hours to work, they have to decide the best trade off for them between income and leisure. As wages rise over time, there will be substitution and income effects of these extra hourly wages. Higher wages make work more valuable in terms of what people can buy from an extra hour’s work. There is thus an incentive to substitute work for leisure and hence work longer. This is the substitution effect. On the other hand, higher wages allow people to work fewer hours for a given income. This is the income effect.

As incomes rise, generally the substitution effect will tend to decline relative to the income effect. This is because of the diminishing marginal utility of income. Richer people will tend to value a given rise in income less than poorer people and therefore will value the income from extra work less than poorer people. Richer people will prefer to work fewer hours than poorer people. Generally workers in richer OECD countries work fewer hours than those in poorer OECD countries.

But this does not explain why people in the USA, Canada, Japan and the UK work longer hours than people in Germany, Denmark, Norway, The Netherlands and France.

One possible explanation for these differences is the role of trade unions. These tend to be stronger in countries with lower working hours. Reducing the working week or obtaining longer holidays is one of the key objectives of unions.

Another is income distribution. The USA, despite its high average (mean) income, has a relatively unequal distribution of income compared with Germany or France. The post-tax-and-benefits Gini coefficient in the USA is around 0.39, whereas in Germany it is 0.29, meaning that Germany has a more equal distribution of disposable income than the USA. In fact, rises in real incomes in the USA over the past 10 years have gone almost exclusively to the top 10 per cent of earners, leaving the median income little changed. In fact median household income only rose above its 2007 (pre-recession) level in 2016.

Social and cultural explanations may also be important. People in countries with higher working hours relative to hourly wages may put a greater store on consumption relative to leisure. The desire to shop may be very strong. The ‘Anglo-Saxon’ economic model pursued by right-of-centre governments in English-speaking countries, such as the USA, Canada, Australia and the UK puts emphasis on low taxes, low regulation, low public expenditure and self-advancement. Such a model encourages a more individualistic approach to work, with more emphasis on earning money.

Then there is the attitude to hours worked generally. There is a saying that in the UK the last one to leave the office is seen as the hardest working, whereas in Germany the last one to leave is seen as the least efficient. Social pressures, from colleagues, family, friends and society more generally can have a major effect on people’s choices between work and leisure.

Productivity

Productivity, in terms of output per hour worked, tends to decline as workers work longer hours. People get tired and possibly bored and demotivated towards the end of a long day or week. If workers are paid by the output they produce and if productivity declines towards the end of the day, then the hourly wage would fall as the day progresses. This would act as a disincentive to work long hours. In practice, most workers are normally paid a constant rate per hour for normal-time working. For overtime, they may even be paid a higher rate, despite their likely lower productivity. This encourages them to work longer hours than if they were paid according to their marginal productivity.

Linking pay more closely to productivity could encourage people to opt for fewer hours (if they had the choice). Indeed some companies are now encouraging workers to choose their hours – which may mean fewer hours as people seek a better work–life balance. (See the BBC article below about PwC’s employment strategy.) Alternatively, some other employers adopt the system of giving workers a set amount of work to do and then they can leave work when it is finished. This acts as an incentive to work more efficiently.

It is interesting that countries where workers work more hours per year tend to have a lower output per hour worked relative to output per worker than countries where workers work fewer hours. This is illustrated in the chart opposite. The USA, with its longer working hours, has higher output per person employed than France and Germany but very similar output per hour worked.

Hours and happiness

So are people who choose to work longer hours and take home more money likely to be happier than those who choose to work fewer hours and take home less money? If people were rational and had perfect knowledge, then they would choose the balance between work and leisure that best suited them.

In practice, labour markets are highly imperfect. People often do not have choices about the amount they work; they work the hours they are told. Even if they do have a choice, they are unlikely to have perfect knowledge about the impact of long hours on their health and happiness over their lifetime. They may not even be good judges of the shorter-term effects of more work and more pay. They may believe that more money will buy them more happiness only to find soon afterwards that they are wrong.

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Data

Questions

  1. What factors are likely to encourage workers to work longer hours?
  2. Give some examples of jobs where workers have flexibility in the amount of hours they work per week and jobs where the working week is of a fixed length.
  3. For what reasons are annual working hours longer in the USA than in Germany?
  4. Would it be in employers’ interests if the government legislated so as to reduce the maximum permitted working week? Explain.
  5. What is meant by ‘efficiency wages’? How relevant is the concept to the issue of the average number of hours worked per year from country to country?
  6. Explain why people in poorer countries tend to work more hours per year than people in richer countries.
  7. If workers’ wages equalled their marginal revenue product, why might some workers choose to work more and others choose to work less (assuming they had a choice)?
  8. Are jobs in the gig economy and zero-hour contract jobs in the interests of workers?
  9. Is South Korea wise to cut its work limit from 68 hours a week to 52?

The UK’s Low Pay Commission has just published its annual report. This shows that the lowest-paid 20% of workers aged 25 and over benefited from last April’s 4.4% rise in the ‘National Living Wage (NLW)’, the name the government gives to the statutory minimum wage for people in this age group. Although only around 6.5% of such workers are paid at the NLW, when it rises this tends to push up wage rates which are just above the NLW as employers seek to maintain the differential.

If the new NLW is above the equilibrium rate for those receiving it, it would be expected that firms would respond by employing fewer workers. However, the Low Pay Commission found no evidence that rises in the NLW caused unemployment. Instead, employers responded by combinations of increasing prices, accepting lower profit margins, restructuring their workforce and reducing the gaps between pay bands.

Over the longer term, employers often seek to increase labour productivity to offset the higher cost per worker of paying increased minimum wage rates. This, however, could lead to a reduction in employment if it involves substituting capital for labour or if greater labour efficiency does not result in a sufficient increase in total output to compensate for an increase in output per worker.

Articles

Report and data

Questions

  1. Demonstrate on a supply and demand diagram for a perfectly competitive labour market the impact of a rise in the minimum wage on employment and unemployment in that market. Assume that the market is initially in equilibrium at the previous minimum wage rate.
  2. For what reasons in such markets may a rise in the minimum wage not lead to a rise in unemployment?
  3. Now demonstrate the effect of a rise in the minimum wage in a monopsonistic market. Assume that the previous minimum wage was previously being paid by the employer.
  4. For what reasons may the employer in the previous question choose to retain employment at the current level?
  5. For what reasons may the effect of a rise in the minimum wage be different in the long run from the short run?
  6. How can employers avoid paying the minimum wage (a) when workers work in the ‘gig’ economy; (b) when workers have to travel as part of their job: e.g. care workers moving from house to house; (c) workers working from home producing items for an employer, such as clothing or jewelry, or providing a service such as telesales?

The IMF has just published its six-monthly World Economic Outlook. This provides an assessment of trends in the global economy and gives forecasts for a range of macroeconomic indicators by country, by groups of countries and for the whole world.

This latest report is upbeat for the short term. Global economic growth is expected to be around 3.9% this year and next. This represents 2.3% this year and 2.5% next for advanced countries and 4.8% this year and 4.9% next for emerging and developing countries. For large advanced countries such rates are above potential economic growth rates of around 1.6% and thus represent a rise in the positive output gap or fall in the negative one.

But while the near future for economic growth seems positive, the IMF is less optimistic beyond that for advanced countries, where growth rates are forecast to decline to 2.2% in 2019, 1.7% in 2020 and 1.5% by 2023. Emerging and developing countries, however, are expected to see growth rates of around 5% being maintained.

For most countries, current favorable growth rates will not last. Policymakers should seize this opportunity to bolster growth, make it more durable, and equip their governments better to counter the next downturn.

By comparison with other countries, the UK’s growth prospects look poor. The IMF forecasts that its growth rate will slow from 1.8% in 2017 to 1.6% in 2018 and 1.5% in 2019, eventually rising to around 1.6% by 2023. The short-term figures are lower than in the USA, France and Germany and reflect ‘the anticipated higher barriers to trade and lower foreign direct investment following Brexit’.

The report sounds some alarm bells for the global economy.
The first is a possible growth in trade barriers as a trade war looms between the USA and China and as Russia faces growing trade sanctions. As Christine Lagarde, managing director of the IMF told an audience in Hong Kong:

Governments need to steer clear of protectionism in all its forms. …Remember: the multilateral trade system has transformed our world over the past generation. It helped reduce by half the proportion of the global population living in extreme poverty. It has reduced the cost of living, and has created millions of new jobs with higher wages. …But that system of rules and shared responsibility is now in danger of being torn apart. This would be an inexcusable, collective policy failure. So let us redouble our efforts to reduce trade barriers and resolve disagreements without using exceptional measures.

The second danger is a growth in world government and private debt levels, which at 225% of global GDP are now higher than before the financial crisis of 2007–9. With Trump’s policies of tax cuts and increased government expenditure, the resulting rise in US government debt levels could see some fiscal tightening ahead, which could act as a brake on the world economy. As Maurice Obstfeld , Economic Counsellor and Director of the Research Department, said at the Press Conference launching the latest World Economic Outlook:

Debts throughout the world are very high, and a lot of debts are denominated in dollars. And if dollar funding costs rise, this could be a strain on countries’ sovereign financial institutions.

In China, there has been a massive rise in corporate debt, which may become unsustainable if the Chinese economy slows. Other countries too have seen a surge in private-sector debt. If optimism is replaced by pessimism, there could be a ‘Minsky moment’, where people start to claw down on debt and banks become less generous in lending. This could lead to another crisis and a global recession. A trigger could be rising interest rates, with people finding it hard to service their debts and so cut down on spending.

The third danger is the slow growth in labour productivity combined with aging populations in developed countries. This acts as a brake on growth. The rise in AI and robotics (see the post Rage against the machine) could help to increase potential growth rates, but this could cost jobs in the short term and the benefits could be very unevenly distributed.

This brings us to a final issue and this is the long-term trend to greater inequality, especially in developed economies. Growth has been skewed to the top end of the income distribution. As the April 2017 WEO reported, “technological advances have contributed the most to the recent rise in inequality, but increased financial globalization – and foreign direct investment in particular – has also played a role.”

And the policy of quantitative easing has also tended to benefit the rich, as its main effect has been to push up asset prices, such as share and house prices. Although this has indirectly stimulated the economy, it has mainly benefited asset owners, many of whom have seen their wealth soar. People further down the income scale have seen little or no growth in their real incomes since the financial crisis.

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Report

Data

Questions

  1. For what reasons may the IMF forecasts turn out to be incorrect?
  2. Why are emerging and developing countries likely to experience faster rates of economic growth than advanced countries?
  3. What are meant by a ‘positive output gap’ and a ‘negative output gap’? What are the consequences of each for various macroeconomic indicators?
  4. Explain what is meant by a ‘Minsky moment’. When are such moments likely to occur? Explain why or why not such a moment is likely to occur in the next two or three years?
  5. For every debt owed, someone is owed that debt. So does it matter if global public and/or private debts rise? Explain.
  6. What have been the positive and negative effects of the policy of quantitative easing?
  7. What are the arguments for and against using tariffs and other forms of trade restrictions as a means of boosting a country’s domestic economy?