Category: Essentials of Economics: 8e Ch 12

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.

Podcast

Articles

Report

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?

Consumer credit is borrowing by individuals to finance current expenditure on goods and services. Consumer credit is distinct from lending secured on dwellings (referred to more simply as ‘secured lending’). Consumer credit comprises lending on credit cards, lending through overdraft facilities and other loans and advances, for example those financing the purchase of cars. We consider here recent trends in the flows of consumer credit in the UK and discuss their implications.

Analysing consumer credit data is important because the growth of consumer credit has implications for the financial wellbeing or financial health of individuals and, of course, for financial institutions. As we shall see shortly, the data on consumer credit is consistent with the existence of credit cycles. Cycles in consumer credit have the potential to be not only financially harmful but economically destabilising. After all, consumer credit is lending to finance spending and therefore the amount of lending can have significant effects on aggregate demand and economic activity.

Data on consumer credit are available monthly and so provide an early indication of movements in economic activity. Furthermore, because lending flows are likely to be sensitive to changes in the confidence of both borrowers and lenders, changes in the growth of consumer credit can indicate turning points in the economy and, hence, in the macroeconomic environment.

Chart 1 shows the annual flows of net consumer credit since 2000 – the figures are in £ billions. Net flows are gross flows less repayments. (Click here to download a PowerPoint copy of the chart.) In January 2005 the annual flow of net consumer credit peaked at £23 billion, the equivalent of just over 2.5 per cent of annual disposable income. This helped to fuel spending and by the final quarter of the year, the economy’s annual growth rate had reached 4.8 per cent, significantly about its long-run average of 2.5 per cent.

By 2009 net consumer credit flows had become negative. This meant that repayments were greater than additional flows of credit. It was not until 2012 that the annual flow of net consumer credit was again positive. Yet by November 2016, the annual flow of net consumer credit had rebounded to over £19 billion, the equivalent of just shy of 1.5 per cent of annual disposable income. This was the largest annual flow of consumer credit since September 2005.

Although the strength of consumer credit in 2016 was providing the economy with a timely boost to growth in the immediate aftermath of the referendum on the UK’s membership of the EU, it nonetheless raised concerns about its sustainability. Specifically, given the short amount of time that had elapsed since the financial crisis and the extreme levels of financial distress that had been experienced by many sectors of the economy, how susceptible would people and organisations be to a future economic slowdown and/or rise in interest rates?

The extent to which the economy experiences consumer credit cycles can be seen even more readily by looking at the 12-month growth rate in the net consumer credit. In essence, this mirrors the growth rate in the stock of consumer credit. Chart 2 evidences the double-digit growth rates in net consumer credit lending experienced during the first half of the 2000s. Growth rates then eased but, as the financial crisis unfolded, they plunged sharply. (Click here to download a PowerPoint copy of the chart.)

Yet, as Chart 2 shows, consumer credit growth began to recover quickly from 2013 so that by 2016 the annual growth rate of net consumer credit was again in double figures. In November 2016 the 12-month growth rate of net consumer credit peaked at 10.9 per cent. Thereafter, the growth rate has continually eased. In January 2019 the annual growth rate of net consumer credit had fallen back to 6.5 per cent, the lowest rate since October 2014.

The easing of consumer credit is likely to have been influenced, in part, by the resumption in the growth of real earnings from 2018 (see Getting real with pay). Yet, it is hard to look past the economic uncertainties around Brexit.

Uncertainty tends to cause people to be more cautious. With the heightened uncertainty that has has characterised recent times, it is likely that for many people and businesses prudence has dominated impatience. Therefore, in summary, it appears that prudence is helping to steer borrowing along a downswing in the credit cycle. As it does, it helps to put a further brake on spending and economic growth.

Articles

Questions

  1. What is the difference between gross and net lending?
  2. Consider the argument that we should be worried more by excessive growth in consumer credit than on lending secured on dwellings?
  3. How could we measure whether different sectors of the economy had become financially distressed?
  4. What might explain why an economy experiences credit cycles?
  5. Explain how the growth in net consumer credit can affect economic activity?
  6. If people are consumption smoothers, how can credit cycles arise?
  7. What are the potential policy implications of credit cycles?
  8. It is said that when making financial decisions people face an inter-temporal choice. Explain what you understand this by this concept.
  9. If economic uncertainty is perceived to have increased how could this affect the consumption, saving and borrowing decisions of people?

One of the most enduring characteristics of the macroeconomic environment since the financial crisis of the late 2000s has been its impact on people’s pay. We apply the distinction between nominal and real values to evidence the adverse impact on the typical purchasing power of workers. While we do not consider here the distributional impact on pay, the aggregate picture nonetheless paints a very stark picture of recent patterns in pay and, in turn, the consequences for living standards and wellbeing.

While the distinction between nominal and real values is perhaps best know in relation to GDP and economic growth (see the need to get real with GDP), the distinction is also applied frequently to analyse the movement of one price relative to prices in general. One example is that of movements in pay (earnings) relative to consumer prices.

Pay reflects the price of labour. The value of our actual pay is our nominal pay. If our pay rises more quickly than consumer prices, then our real pay increases. This means that our purchasing power rises and so the volume of goods and services we can afford increases. On the other hand, if our actual pay rises less quickly than consumer prices then our real pay falls. When real pay falls, purchasing power falls and the volume of goods and services we can afford falls.

Figures from the Office for National Statistics show that in January 2000 regular weekly pay (excluding bonuses and before taxes and other deductions from pay) was £293. By December 2018 this had risen to £495. This is an increase of 69 per cent. Over the same period the consumer prices index known as the CPIH, which, unlike the better-known CPI, includes owner-occupied housing costs and Council Tax, rose by 49 per cent. Therefore, the figures are consistent with a rise both in nominal and real pay between January 2000 to December 2018. However, this masks the fact that in recent times real earnings have fallen.

Chart 1 shows the annual percentage changes in actual (nominal) regular weekly pay and the CPIH since January 2001. Each value is simply the percentage change from 12 months earlier. The period up to June 2008 saw the annual growth of weekly pay outstrip the growth of consumer prices – the blue line in the chart is above the red line. Therefore, the real value of pay rose. However, from June 2008 to August 2014 pay growth consistently fell short of the rate of consumer price inflation – the blue line is below the red line. The result was that average real weekly pay fell. (Click here to download a PowerPoint copy of the chart.)

Chart 2 show the average levels of nominal and real weekly pay. The real series is adjusted for inflation. It is calculated by deflating the nominal pay values by the CPIH. Since the CPIH is a price index whose value averages 100 across 2015, the real pay values are at constant 2015 prices. From the chart, we can see that the real value of weekly pay peaked in March 2008 at £482.01 at 2015 prices. The subsequent period saw rates of pay inflation that were lower than rates of consumer price inflation. This meant that by March 2014 the real value of weekly pay had fallen by 8.8 per cent to £439.56 at 2015 prices. (Click here to download a PowerPoint copy of the chart.)

Although real (inflation-adjusted) pay recovered a little during 2015 and 2016, 2017 again saw consumer price inflation rates greater than those of pay inflation (see Chart 1). Consequently, the average level of real weekly pay fell by 1 per cent between January and November 2017. Since then, real regular pay has again increased. In December 2018, average real pay weekly pay was £462.18 at 2015 prices: an increase of 1.1 per cent from November 2017. Nonetheless, inflation-adjusted average weekly pay in December 2018 remained 4.1 per cent below its March 2008 level.

Chart 3 shows very clearly the importance of the distinction between real and nominal when analysing the growth of earnings. The sustained period of real pay deflation (negative rates of pay inflation) that followed the financial crisis can be seen much more clearly by plotting growth rates rather than their levels. Since June 2008 the average annual growth of real regular weekly pay has been −0.2 per cent, despite nominal pay increasing at an annual rate of 2 per cent. In the period from January 2001 to May 2008 real regular weekly pay had grown at an annual rate of 2.1 per cent with nominal pay growing at an annual rate of 4.0 per cent. (Click here to download a PowerPoint copy of the chart.)

The distinction between nominal and real helps us to understand better why some argue that patterns in pay, living standards and well-being have been fundamental in characterising the macroeconomic environment since the financial crisis. Indeed, it is not unreasonable to suggest that these patterns have helped to shape macroeconomic debates and broader conversations around the role of government and of public policy and its priorities.

Articles

Questions

  1. Using the example of GDP and earnings, explain how the distinction between nominal and real relates to the distinction between values and volumes.
  2. In what circumstances would an increase in actual pay translate into a reduction in real pay?
  3. In what circumstances would a decrease in actual pay translate into an increase in real pay?
  4. What factors might explain the reduction in real rates of pay seen in the UK following the financial crisis?
  5. Of what importance might the growth in real rates of pay be for consumption and aggregate demand?
  6. Why is the growth of real pay an indicator of financial well-being? What other indicators might be included in measuring financial well-being?
  7. Assume that you have been asked to undertake a distributional analysis of real earnings since the financial crisis. What might be the focus of your analysis? What information would you therefore need to collect?

It is impossible to make both precise and accurate forecasts of a country’s rate of economic growth, even a year ahead. And the same goes for other macroeconomic variables, such as the rate of unemployment or the balance of trade. The reason is that there are so many determinants of these variables, such as political decisions or events, which themselves are unpredictable. Economics examines the effects of human interactions – it is a social science, not a natural science. And human behaviour is hard to forecast.

Leading indicators

Nevertheless, economists do make forecasts. These are best estimates, taking into account a number of determinants that can be currently measured, such as tax or interest rate changes. These determinants, or ‘leading indicators’, have been found to be related to future outcomes. For example, surveys of consumer and business confidence give a good indication of future consumer expenditure and investment – key components of GDP.

Leading indicators do not have to be directly causal. They could, instead, be a symptom of underlying changes that are themselves likely to affect the economy in the future. For example, changes in stock market prices may reflect changes in confidence or changes in liquidity. It is these changes that are likely to have a direct or indirect causal effect on future output, employment, prices, etc.

Macroeconomic models show the relationships between variables. They show how changes in one variable (e.g. increased investment) affect other variables (e.g. real GDP or productivity). So when an indicator changes, such as a rise in interest rates, economists use these models to estimate the likely effect, assuming other things remain constant (ceteris paribus). The problem is that other things don’t remain constant. The economy is buffeted around by a huge range of events that can affect the outcome of the change in the indicator or the variable(s) it reflects.

Forecasting can never therefore be 100% accurate (except by chance). Nevertheless, by carefully studying leading indicators, economists can get a good idea of the likely course of the economy.

Leading indicators of the US economy

At the start of 2019, several leading indicators are suggesting the US economy is likely to slow and might even go into recession. The following are some of the main examples.

Political events. This is the most obvious leading indicator. If decisions are made that are likely to have an adverse effect on growth, a recession may follow. For example, decisions in the UK Parliament over Brexit will directly impact on UK growth.

As far as the USA is concerned, President Trump’s decision to put tariffs on steel and aluminium imports from a range of countries, including China, the EU and Canada, led these countries to retaliate with tariffs on US imports. A tariff war has a negative effect on growth. It is a negative sum game. Of course, there may be a settlement, with countries agreeing to reduce or eliminate these new tariffs, but the danger is that the trade war may continue long enough to do serious damage to global economic growth.

But just how damaging it is likely to be is impossible to predict. That depends on future political decisions, not just those of the recent past. Will there be a global rise in protectionism or will countries pull back from such a destructive scenario? On 29 December, President Trump tweeted, ‘Just had a long and very good call with President Xi of China. Deal is moving along very well. If made, it will be very comprehensive, covering all subjects, areas and points of dispute. Big progress being made!’ China said that it was willing to work with the USA over reaching a consensus on trade.

Rises in interest rates. If these are in response to a situation of excess demand, they can be seen as a means of bringing inflation down to the target level or of closing a positive output gap, where real national income is above its potential level. They would not signify an impending recession. But many commentators have interpreted rises in interest rates in the USA as being different from this.

The Fed is keen to raise interest rates above the historic low rates that were seen as an ’emergency’ response to the financial crisis of 2007–8. It is also keen to reverse the policy of quantitative easing and has begun what might be described as ‘quantitative tightening’: not buying new bonds when existing ones that it purchased during rounds of QE mature. It refers to this interest rate and money supply policy as ‘policy normalization‘. The Fed maintains that such policy is ‘consistent with sustained expansion of economic activity, strong labor market conditions, and inflation near the Committee’s symmetric 2 percent objective over the medium term’.

However, many commentators, including President Trump, have accused the Fed of going too fast in this process and of excessively dampening the economy. It has already raised the Federal Funds Rate nine times by 0.25 percentage points each time since December 2015 (click here for a PowerPoint file of the chart). What is more, announcing that the policy will continue makes such announcements themselves a leading indicator of future rises in interest rates, which are a leading indicator of subsequent effects on aggregate demand. The Fed has stated that it expects to make two more 0.25 percentage point rises during 2019.

Surveys of consumer and business confidence. These are some of the most significant leading indicators as consumer confidence affects consumer spending and business confidence affects investment. According to the Duke CFO Global Business Outlook, an influential survey of Chief Financial Officers, ‘Nearly half (48.6 per cent) of US CFOs believe that the US will be in recession by the end of 2019, and 82 per cent believe that a recession will have begun by the end of 2020’. Such surveys can become self-fulfilling, as a reported decline in confidence can itself undermine confidence as both firms and consumers ‘catch’ the mood of pessimism.

Stock market volatility. When stock markets exhibit large falls and rises, this is often a symptom of uncertainty; and uncertainty can undermine investment. Stock market volatility can thus be a leading indicator of an impending recession. One indicator of such volatility is the VIX index. This is a measure of ’30-day expected volatility of the US stock market, derived from real-time, mid-quote prices of S&P 500® Index (SPXSM) call and put options. On a global basis, it is one of the most recognized measures of volatility – widely reported by financial media and closely followed by a variety of market participants as a daily market indicator.’ The higher the index, the greater the volatility. Since 2004, it has averaged 18.4; from 17 to 28 December 2018, it averaged 28.8. From 13 to 24 December, the DOW Jones Industrial Average share index fell by 11.4 per cent, only to rise by 6.2 per cent by 27 December. On 26 December, the S&P 500 index rallied 5 per cent, its best gain since March 2009.

Not all cases of market volatility, however, signify an impending recession, but high levels of volatility are one more sign of investor nervousness.

Oil prices. When oil prices fall, this can be explained by changes on the demand and/or supply side of the oil market. Oil prices have fallen significantly over the past two months. Until October 2018, oil prices had been rising, with Brent Crude reaching $86 per barrel by early October. By the end of the year the price had fallen to just over $50 per barrel – a fall of 41 per cent. (Click here for a PowerPoint file of the chart.) Part of the explanation is a rise in supply, with shale oil production increasing and also increased output from Russia and Saudi Arabia, despite a commitment by the two countries to reduce supply. But the main reason is a fall in demand. This reflects both a fall in current demand and in anticipated future demand, with fears of oversupply causing oil companies to run down stocks.

Falling oil prices resulting from falling demand are thus an indicator of lack of confidence in the growth of future demand – a leading indicator of a slowing economy.

The yield curve. This depicts the yields on government debt with different lengths to maturity at a given point in time. Generally, the curve slopes upwards, showing higher rates of return on bonds with longer to maturity. This is illustrated by the blue line in the chart. (Click here for a PowerPoint file of the chart.) This is as you would expect, with people requiring a higher rate of return on long-term lending, where there is normally greater uncertainty. But, as the Bloomberg article, ‘Don’t take your eyes off the yield curve‘ states:

Occasionally, the curve flips, with yields on short-term debt exceeding those on longer bonds. That’s normally a sign investors believe economic growth will slow and interest rates will eventually fall. Research by the Federal Reserve Bank of San Francisco has shown that an inversion has preceded every US recession for the past 60 years.
 
The US economy is 37 quarters into what may prove to be its longest expansion on record. Analysts surveyed by Bloomberg expect gross domestic product growth to come in at 2.9 percent this year, up from 2.2 percent last year. Wages are rising as unfilled vacancies hover near all-time highs.
 
With times this good, the biggest betting game on Wall Street is when they’ll go bad. Barclays Plc, Goldman Sachs Group Inc., and other banks are predicting inversion will happen sometime in 2019. The conventional wisdom: Afterward it’s only a matter of time – anywhere from 6 to 24 months – before a recession starts.

As you can see from the chart, the yield curve on 24 December 2018 was still slightly upward sloping (expect between 6-month and 1-year bonds) – but possibly ready to ‘flip’.

However, despite the power of an ‘inverted’ yield in predicting previous recessions, it may be less reliable now. The Fed, as we saw above, has already signalled that it expects to increase short-term rates in 2019, probably at least twice. That alone could make the yield curve flatter or even downward sloping. Nevertheless, it is still generally thought that a downward sloping yield curve would signal belief in a likely slowdown, if not outright recession.

So, is the USA heading for recession?

The trouble with indicators is that they suggest what is likely – not what will definitely happen. Governments and central banks are powerful agents. If they believed that a recession was likely, then fiscal and monetary policy could be adjusted. For example, the Fed could halt its interest rate rises and quantitative tightening, or even reverse them. Also, worries about protectionism may subside if the USA strikes new trade deals with various countries, as it did with Canada and Mexico in USMCA.

Articles

Surveys and Data

Questions

  1. Define the term ‘recession’.
  2. Are periods of above-trend expansion necessarily followed by a recession?
  3. Give some examples of leading indicators other than those given above and discuss their likely reliability in predicting a recession.
  4. Find out what has been happening to confidence levels in the EU over the past 12 months. Does this provide evidence of an impending recession in the EU?
  5. For what reasons may there be lags between a change in an indicator and a change in the variables for which it is an indicator?
  6. Why has the shape of the yield curve previously been a good predictor of the future course of the economy? Is it likely to be at present?
  7. What is the relationship between interest rates, government bond prices (‘Treasuries’ in the USA) and the yield on such bonds?

Would you like to be a millionaire? Of course you would – who wouldn’t, right? Actually the answer to this question may be more complicated than you might think (see for instance Sgroi et al (2017) on the economics of happiness: see linked article below), but, generally speaking, most people would answer positively to this question.

What if I told you, however, that you could become a millionaire (actually, scratch that – think big – make that “trillionaire”) overnight and be deeply unhappy about it? If you don’t believe me see what happened to Zimbabwe 10 years ago, when irresponsible money printing and fiscal easing drove the country’s economy to staggering hyperinflation (see the blogs A remnant of hyperinflation in Zimbabwe and Fancy a hundred trillion dollar note?. At the peak of the crisis, prices were increasing by a factor of 130 each year. I have in my office a 100 trillion Zimbabwean dollar note (see below) which I show in my lectures when I talk about hyperinflation to my first year Economics for Business students (if you are one of them, make sure not to miss it next February at UEA!). How much is this 100 trillion note worth? Nothing (except, may be, for collectors). It has been withdrawn from circulation as it ended up not even being worth the cost of the paper on which it was printed.

The Zimbabwean economy managed to pull itself out of this spiral of economic death, partly by informally replacing its hyperinflationary currency with the US greenback, and partly by keeping its fiscal spending under control and reverting to more sane economic policy making. That lasted until 2013, after which the government launched a Zimbabwean digital currency (known as “Zollar”) that had a nominal value set equal to a US dollar; and forced its exporters to exchange their greenbacks for Zollars. It then started spending these USD to finance a very ambitious and unsustainable programme of fiscal expansion.

The Economist published yesterday a story that shows the results of this policy – wild price increases and empty supermarket shelves are both back. According to the newspaper’s report:

At a supermarket in Harare, Zimbabwe’s capital, the finance minister is staring aghast at a pack of nappies. ‘This is absolutely ridiculous!’, exclaims Mthuli Ncube. ‘$49!’ A manager says it cost $23 two weeks ago, before pointing out other eye-watering items such as $20 Coco Pops. […] Over the past two weeks zollars have been trading at as little as 17 cents to the dollar. The devaluation has led to a surge in prices—and not just in imported goods like nappies. Football fans attending the Zimbabwe v Democratic Republic of Congo game on October 16th were shocked to learn that ticket prices had doubled on match day.

How long will it take for the 100 trillion Zollar to make its appearance again? We shall find out. I am sure Zimbabweans will be less than thrilled!

Articles and Report

Videos

Questions

  1. Using an AS/AD diagram, explain the concept of hyperinflation. How can irresponsible fiscal policy-making lead to hyperinflation?
  2. What are the effects of hyperinflation on the people who live in the affected countries? Search the web for examples and case studies, and use them to support your answer.
  3. Once it has started, what policies can be used to fight hyperinflation? Use examples to support your answer.
  4. How does speculation affect hyperinflation?