Category: Economics: Ch 20

Three international agencies, the IMF, the European Commission and the OECD, all publish six-monthly forecasts for a range of countries. As each agency’s forecasts have been published this year, so the forecasts for economic growth and other macroeconomic indicators, such as unemployment, have got more dire.

The IMF was the first to report. Its World Economic Outlook, published on 14 April, forecast that in the UK real GDP would fall by 6.5% in 2020 and rise by 4% in 2021 (not enough to restore GDP to 2019 levels); in the USA it would fall by 5.9% this year and rise by 4.7% next year; in the eurozone it would fall by 7.5% this year and rise by 4.7% next.

The European Commission was next to report. Its AMECO database was published on 6 May. This forecast that UK real GDP would fall by 8.3% this year and rise by 6% next; in the USA it would fall by 6.5% this year and rise by 4.9% next; in the eurozone it would fall by 7.7% this year and rise by 6.3% next.

The latest to report was the OECD on 10 June. The OECD Economic Outlook was the most gloomy. In fact, it produced two sets of forecasts.

The first, more optimistic one (but still more gloomy than the forecasts of the other two agencies) was based on the assumption that lockdowns would continue to be lifted and that there would be no second outbreak later in the year. This ‘single-hit scenario’ forecast that UK real GDP would fall by 11.5% this year and rise by 9% next (a similar picture to France and Italy); in the USA it would fall by 7.3% this year and rise by 4.1% next; in the eurozone it would fall by 9.1% this year and rise by 6.5% next.

The second set of OECD forecasts was based on the assumption that there would be a second wave of the virus and that lockdowns would have to be reinstated. Under this ‘double-hit scenario’, the UK’s GDP is forecast to fall by 14.0% this year and rise by 5.0 per cent next; in the USA it would fall by 8.5% this year and rise by 1.9% next; in the eurozone it would fall by 11.5% this year and rise by 3.5% next.


The first chart shows the four sets of forecasts (including two from the OECD) for a range of countries. The first four bars for each country are the forecasts for 2020; the other four bars for each country are for 2021. (Click here for a PowerPoint of the chart.)


The second chart shows unemployment rates from 2006. The figures for 2020 and 2021 are OECD forecasts based on the double-hit assumption. You can clearly see the dramatic rise in unemployment in all the countries in 2020. In some cases it is forecast that there will be a further rise in 2021. (Click here for a PowerPoint of the chart.)

As the OECD states:

In both scenarios, the recovery, after an initial, rapid resumption of activity, will take a long time to bring output back to pre-pandemic levels, and the crisis will leave long-lasting scars – a fall in living standards, high unemployment and weak investment. Job losses in the most affected sectors, such as tourism, hospitality and entertainment, will particularly hit low-skilled, young, and informal workers.

But why have the forecasts got gloomier? There are both demand- and supply-side reasons.

Aggregate demand has fallen more dramatically than originally anticipated. Lockdowns have lasted longer in many countries than governments had initially thought, with partial lockdowns, which replace them, taking a long time to lift. With less opportunity for people to go out and spend, consumption has fallen and saving has risen. Businesses that have shut, some permanently, have laid off workers or they have been furloughed on reduced incomes. This too has reduced spending. Even when travel restrictions are lifted, many people are reluctant to take holidays at home and abroad and to use public transport for fear of catching the virus. This reluctance has been higher than originally anticipated. Again, spending is lower than before. Even when restaurants, bars and other public venues are reopened, most operate at less than full capacity to allow for social distancing. Uncertainty about the future has discouraged firms from investing, adding to the fall in demand.


On the supply side, there has been considerable damage to capacity, with firms closing and both new and replacement investment being put on hold. Confidence in many sectors has plummeted as shown in the third chart which looks at business and consumer confidence in the EU. (Click here for a PowerPoint of the above chart.) Lack of confidence directly affects investment with both supply- and demand-side consequences.

Achieving a sustained recovery will require deft political and economic judgements by policymakers. What is more, people are increasingly calling for a different type of economy – one where growth is sustainable with less pollution and degradation of the environment and one where growth is more inclusive, where the benefits are shared more equally. As Angel Gurría, OECD Secretary-General, states in his speech launching the latest OECD Economic Outlook:

The aim should not be to go back to normal – normal was what got us where we are now.

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Questions

  1. Why has the UK economy been particularly badly it by the Covid-19 pandemic?
  2. What will determine the size and timing of the ‘bounce back’?
  3. Why will the pandemic have “dire and long-lasting consequences for people, firms and governments”?
  4. Why have many people on low incomes faced harsher consequences than those on higher incomes?
  5. What are the likely environmental impacts of the pandemic and government measures to mitigate the effects?

The global economic impact of the coronavirus outbreak is uncertain but potentially very large. There has already been a massive effect on China, with large parts of the Chinese economy shut down. As the disease spreads to other countries, they too will experience supply shocks as schools and workplaces close down and travel restrictions are imposed. This has already happened in South Korea, Japan and Italy. The size of these effects is still unknown and will depend on the effectiveness of the containment measures that countries are putting in place and on the behaviour of people in self isolating if they have any symptoms or even possible exposure.

The OECD in its March 2020 interim Economic Assessment: Coronavirus: The world economy at risk estimates that global economic growth will be around half a percentage point lower than previously forecast – down from 2.9% to 2.4%. But this is based on the assumption that ‘the epidemic peaks in China in the first quarter of 2020 and outbreaks in other countries prove mild and contained.’ If the disease develops into a pandemic, as many health officials are predicting, the global economic effect could be much larger. In such cases, the OECD predicts a halving of global economic growth to 1.5%. But even this may be overoptimistic, with growing talk of a global recession.

Governments and central banks around the world are already planning measures to boost aggregate demand. The Federal Reserve, as an emergency measure on 3 March, reduced the Federal Funds rate by half a percentage point from the range of 1.5–1.75% to 1.0–1.25%. This was the first emergency rate cut since 2008.

Economic uncertainty

With considerable uncertainty about the spread of the disease and how effective containment measures will be, stock markets have fallen dramatically. The FTSE 100 fell by nearly 14% in the second half of February, before recovering slightly at the beginning of March. It then fell by a further 7.7% on 9 March – the biggest one-day fall since the 2008 financial crisis. This was specifically in response to a plunge in oil prices as Russia and Saudi Arabia engaged in a price war. But it also reflected growing pessimism about the economic impact of the coronavirus as the global spread of the epidemic accelerated and countries were contemplating more draconian lock-down measures.

Firms have been drawing up contingency plans to respond to panic buying of essential items and falling demand for other goods. Supply-chain managers are working out how to respond to these changes and to disruptions to supplies from China and other affected countries.

Firms are also having to plan for disruptions to labour supply. Large numbers of employees may fall sick or be advised/required to stay at home. Or they may have to stay at home to look after children whose schools are closed. For some firms, having their staff working from home will be easy; for others it will be impossible.

Some industries will be particularly badly hit, such as airlines, cruise lines and travel companies. Budget airlines have cancelled several flights and travel companies are beginning to offer substantial discounts. Manufacturing firms which are dependent on supplies from affected countries have also been badly hit. This is reflected in their share prices, which have seen large falls.

Longer-term effects

Uncertainty could have longer-term impacts on aggregate supply if firms decide to put investment on hold. This would also impact on the capital goods industries which supply machinery and equipment to investing firms. For the UK, already having suffered from Brexit uncertainty, this further uncertainty could prove very damaging for economic growth.

While aggregate supply is likely to fall, or at least to grow less quickly, what will happen to the balance of aggregate demand and supply is less clear. A temporary rise in demand, as people stock up, could see a surge in prices, unless supermarkets and other firms are keen to demonstrate that they are not profiting from the disease. In the longer term, if aggregate demand continues to grow at past rates, it will probably outstrip the growth in aggregate supply and result in rising inflation. If, however, demand is subdued, as uncertainty about their own economic situation leads people to cut back on spending, inflation and even the price level may fall.

How quickly the global economy will ‘bounce back’ depends on how long the outbreak lasts and whether it becomes a serious pandemic and on how much investment has been affected. At the current time, it is impossible to predict with any accuracy the timing and scale of any such bounce back.

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Questions

  1. Using a supply and demand diagram, illustrate the fall in stock market prices caused by concerns over the effects of the coronavirus.
  2. Using either (i) an aggregate demand and supply diagram or (ii) a DAD/DAS diagram, illustrate how a fall in aggregate supply as a result of the economic effects of the coronavirus would lead to (a) a fall in real income and (i) a fall in the price level or (ii) a fall in inflation; (b) a fall in real income and (i) a rise in the price level or (ii) a rise in inflation.
  3. What would be the likely effects of central banks (a) cutting interest rates; (b) engaging in further quantitative easing?
  4. What would be the likely effects of governments running a larger budget deficit as a means of boosting the economy?
  5. Distinguish between stabilising and destabilising speculation. How would you characterise the speculation that has taken place on stock markets in response to the coronavirus?
  6. What are the implications of people being paid on zero-hour contracts of the government requiring workplaces to close?
  7. What long-term changes to working practices and government policy could result from short-term adjustments to the epidemic?
  8. Is the long-term macroeconomic impact of the coronavirus likely to be zero, as economies bounce back? Explain.

Confidence figures suggest that sentiment weakened across several sectors in June with significant falls recorded in retail and construction. This is consistent with the monthly GDP estimates from the ONS which suggest that output declined in March and April by 0.1 per cent and 0.4 per cent respectively. The confidence data point to further weakness in growth down the line. Furthermore, it poses the risk of fuelling a snowball effect with low growth being amplified and sustained by low confidence.

Chart 1 shows the confidence balances reported by the European Commission each month since 2007. It highlights the collapse in confidence across all sectors around the time of the financial crisis before a strong and sustained recovery in the 2010s. However, in recent months confidence indicators have eased significantly, undoubtedly reflecting the heightened uncertainty around Brexit. (Click here to download a PowerPoint copy of the chart.)

Between June 2016 and June 2019, the confidence balances have fallen by at least 8 percentage points. In the case of the construction the fall is 14 points while in the important service sector, which contributes about 80 per cent of the economy’s national income, the fall is as much as 15 points.

Changes in confidence are thought, in part, to reflect levels of economic uncertainty. In particular, they may reflect the confidence around future income streams with greater uncertainty pulling confidence down. This is pertinent because of the uncertainty around the UK’s future trading relationships following the 2016 referendum which saw the UK vote to leave the EU. In simple terms, uncertainty reduces the confidence people and businesses have when forming expectations of what they can expect to earn in the future.

Greater uncertainty and, hence, lower confidence tend to make people and businesses more prudent. The caution that comes from prudence counteracts the inherent tendency of many of us to be impatient. This impatience generates an impulse to spend now. On the other hand, prudence encourages us to take actions to increase net worth, i.e. wealth. This may be through reducing our exposure to debt, perhaps by looking to repay debts or choosing to borrow smaller sums than we may have otherwise done. Another option may be to increase levels of saving. In either case, the effect of greater prudence is the postponement of spending. Therefore, in times of high uncertainty, like those of present, people and businesses would be expected to want to have greater financial resilience because they are less confident about what the future holds.

To this point, the saving ratio – the proportion of disposable income saved by households – has remained historically low. In Q1 2019 the saving ratio was 4.4 per cent, well below its 60-year average of 8.5 per cent. This appears to contradict the idea that households respond to uncertainty by increasing saving. However, at least in part, the squeeze seen over many years following the financial crisis on real earnings, i.e. inflation-adjusted earnings, restricted the ability of many to increase saving. With real earnings having risen again over the past year or so, though still below pre-crisis levels, households may have taken this opportunity to use earnings growth to support spending levels rather than, as we shall see shortly, looking to borrow.

Another way in which the desire for greater financial resilience can affect behaviour is through the appetite to borrow. In the case of consumers, it could reduce borrowing for consumption, while in the case of firms it could reduce borrowing for investment, i.e. spending on capital, such as that on buildings and machinery. The reduced appetite for borrowing may also be mirrored by a tightening of credit conditions by financial institutions if they perceive lending to be riskier or want to increase their own financial capacity to absorb future shocks.

Chart 2 shows consumer confidence alongside the annual rate of growth of consumer credit (net of repayments) to individuals by banks and building societies. Consumer credit is borrowing by individuals to finance current expenditure on goods and services and it comprises borrowing through credit cards, overdraft facilities and other loans and advances, for example those financing the purchase of cars or other large ticket items. (Click here to download a PowerPoint copy of the chart.)

The chart allows us to view the confidence-borrowing relationship for the past 25 years or so. It suggests a fairly close association between consumer confidence and consumer credit growth. Whether changes in confidence occur ahead of changes in borrowing is debatable. However, the easing of confidence following the outcome of the EU referendum vote in June 2016 does appear to have led subsequently to an easing in the annual growth of consumer credit. From its peak of 10.9 per cent in the autumn of 2016, the annual growth rate of consumer credit dropped to 5.6 per cent in May 2019.

The easing of credit growth helps put something of a brake on consumer spending. It is, however, unlikely to affect all categories of spending equally. Indeed, the ONS figures for May on retail sales shows a mixed picture for the retail sector. Across the sector as a whole, the 3 month-on-3 month growth rate for the volume of purchases stood at 1.6 per cent, having fallen as low as 0.1 percent in December of last year. However, the 3 month-on-3 month growth rate for spending volumes in department stores, which might be especially vulnerable to a slowdown in credit, fell for the ninth consecutive month.

Going forward, the falls in confidence might be expected to lead to further efforts by the household sector, as well as by businesses, to ensure their financial resilience. The vulnerability of households, despite the slowdown in credit growth, so soon after the financial crisis poses a risk for a hard landing for the sector. After falls in national output in March and April, the next monthly GDP figures to be released on 10 July will be eagerly anticipated.

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Questions

  1. Which of the following statements is likely to be more accurate: (a) Confidence drives economic activity or (b) Economic activity drives confidence?
  2. Explain the difference between confidence as a source of economic volatility as compared to an amplifier of volatility?
  3. Discuss the links between confidence, economic uncertainty and financial resilience.
  4. Discuss the ways in which people and businesses could improve their financial resilience to adverse shocks.
  5. What are the potential dangers to the economy of various sectors being financially distressed or exposed?

It is perhaps timely given the ongoing uncertainty around Brexit to revisit and update our blog Desperately seeking confidence written back in January. Consumer and business confidence reflects the sentiment, emotion, or anxiety of consumers and businesses. Confidence surveys therefore try to capture these feelings of optimism or pessimism. They may then provide us with timely information for the short-term prospects for private-sector spending. For example, declining levels of confidence might be expected to play a part in weakening the growth of consumption and investment spending.

Attempts are made to measure confidence through the use of surveys. One long-standing survey is that conducted for the European Commission. Each month consumers and firms across the European Union are asked a series of questions, the answers to which are used to compile indicators of consumer and business confidence. For instance, consumers are asked about how they expect their financial position to change. They are offered various options such as ‘get a lot better, ‘get a lot worse’ and balances are then calculated on the basis of positive and negative replies.

The chart plots confidence in the UK for consumers and different sectors of business since the mid 1990s. The chart captures the volatility of confidence. This volatility is generally greater amongst businesses than consumers, and especially so in the construction sector. (Click here to download a PowerPoint copy of the chart.)

Confidence measures rebounded across all sectors during the 2010s, with positive balances being recorded consistently from 2013 to 2016 in services, retail and industry. Subsequently, confidence indicators became more erratic though often remaining at above-average levels. However, confidence indicators have eased across the board in recent months. In some cases the easing has been stark. For example, the confidence balance in the service sector, which contributes about 80 per cent of the economy’s national income, fell from +10.9 in February 2018 to -16.2 in February 2019, though recovering slightly to -9.2 in March 2019.

Chart 2 shows how the recent easing of consumer confidence has seen the confidence balance fall below its long-term (median) average of -7. In March 2019 the balance stood at -11.7 the lowest figure since November 2013. To put the easing into further perspective, the consumer confidence balance had been as high as +8.2 in September 2015. (Click here to download a PowerPoint copy of the chart.)

Changes in confidence are used frequently as an example of a demand shock. In reality changes in consumer confidence are often likely to be an amplifier of shocks rather than the source. For example, the collapse in aggregate demand in 2007/8 that followed the ‘credit crunch’, the severe tightening of credit conditions and financial distress of many sectors of the economy is likely to have been amplified by the collapse in consumer confidence. The weakening of confidence since 2016 is perhaps a purer example of a ‘confidence shock’. Nonetheless, falls in confidence, whether they amplify existing shocks or are the source of shocks, are often a signal of greater economic uncertainty.

Greater uncertainty is likely to go and hand in hand with lower confidence and is likely to reflect greater uncertainty about future income streams. The result is that people and businesses become more prudent. In the context of households this implies a greater willingness to engage in self-insurance through increased saving. This is known as buffer stock or precautionary saving. Alternatively, people may reducing levels of borrowing. In uncertain times prudence can dominate our impatience that encourages us to spend.

Chart 3 plots the paths of the UK household-sector saving ratio and consumer confidence. The saving ratio approximates the proportion of disposable income saved by the household sector. What we might expect to see, if greater uncertainty induces buffer-stock saving, is for falls in confidence to lead to a rise in the saving ratio. Conversely, less uncertainty as proxied by a rise in confidence would lead to a fall in the saving ratio. (Click here to download a PowerPoint of the chart.)

The chart provides some evidence of this. The early 1990s and late 2000s coincided with both waning confidence and a rising saving ratio, whilst the rising confidence seen in the late 1990s coincided with a fall in the saving ratio. However, the easing of confidence since 2016 has coincided with a period where the saving ratio has been historically low. In the first quarter of 2017 the saving ratio was just 3.3 per cent. Although the saving ratio has ticked up a little, in the final quarter of 2018 it remained historically low at just 4.9 per cent. Hence, the available data on the saving ratio does not provide clear evidence of the more cautious behaviour we might expect with waning confidence.

Consider now patterns in the consumer confidence balance alongside the annual rate of growth of consumer credit (net of repayments) to individuals by banks and building societies. Consumer credit is borrowing by individuals to finance current expenditure on goods and services.

Data on consumer credit is more timely than that for the saving ratio. Therefore, Chart 4 shows the relationship between consumer confidence and consumer credit into 2019. We observe a reasonably close association consumer credit growth and consumer confidence. Certainty, the recent easing in confidence is mirrored by an easing in the annual growth of net consumer credit. (Click here to download a PowerPoint of the chart.)

The year-to-year growth in net consumer credit has eased considerably since the peak of 10.9 per cent in November 2016. In February 2019 the annual growth rate of net consumer credit had fallen back to 6.3 per cent, its lowest rate since September 2014. As we noted in our recent blog Riding the consumer credit cycle (again) it is hard to look much past the effect of Brexit in acting as a lid on the growth in consumer credit. Therefore, while the recent falls in consumer confidence have yet to markedly affect the saving ratio they may instead be driving the slowdown in consumer credit. The effect will be to weaken the growth of consumer spending.

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Questions

  1. Draw up a series of factors that you think might affect both consumer and business confidence. How similar are both these lists?
  2. Which of the following statements is likely to be more accurate: (a) Confidence drives economic activity or (b) Economic activity drives confidence?
  3. What macroeconomic indicators would those compiling the consumer and business confidence indicators expect each indicator to predict?
  4. What is meant by the concept of ‘prudence’ in the context of spending? What factors might determine the level of prudence
  5. How might prudence be expected to affect spending behaviour?
  6. How might we distinguish between confidence ‘shocks’ and confidence as a ‘propagator’ of shocks?
  7. What is meant by buffer stock or precautionary saving? Draw up a list of factors that are likely to affect levels of buffer stock saving.
  8. 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.

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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?