Category: Economics 10e: Ch 17

With many countries experiencing low growth some 12 years after the financial crisis and with new worries about the effects of the coronavirus on output in China and other countries, some are turning to a Keynesian fiscal stimulus (see Case Study 16.6 on the student website). This may be in the form of tax cuts, or increased government expenditure or a combination of the two. The stimulus would be financed by increased government borrowing (or a reduced surplus).

The hope is that there will also be a longer-term supply-side effect which will boost potential national income. This could be through tax reductions creating incentives to invest or work more efficiently; or it could be through increased capacity from infrastructure spending, whether on transport, energy, telecommunications, health or education.

In the UK, the former Chancellor, Sajid Javid, had adopted a fiscal rule similar to the Golden Rule adopted by the Labour government from 1997 to 2008. This stated that, over the course of the business cycle, the government should borrow only to invest and not to fund current expenditure. Javid’s rule was that the government would balance its current budget by the middle of this Parliament (i.e. in 2 to 3 years) but that it could borrow to invest, provided that this did not exceed 3% of GDP. Previously this limit had been set at 2% of GDP by the former Chancellor, Philip Hammond. Using his new rule, it was expected that Sajid Javid would increase infrastructure spending by some £20 billion per year. This would still be well below the extra promised by the Labour Party if they had won the election and below what many believe Boris Johnson Would like.

Sajid Javid resigned at the time of the recent Cabinet reshuffle, citing the reason that he would have been required to sack all his advisors and use the advisors from the Prime Minister’s office. His successor, the former Chief Secretary to the Treasury, Rishi Sunak, is expected to adopt a looser fiscal rule in his Budget on March 11. This would result in bigger infrastructure spending and possibly some significant tax cuts, such as a large increase in the threshold for the 40% income tax rate.

A Keynesian stimulus would almost certainly increase the short-term economic growth rate as inflation is low. However, unemployment is also low, meaning that there is little slack in the labour market, and also the output gap is estimated to be positive (albeit only around 0.2%), meaning that national income is already slightly above the potential level.

Whether a fiscal stimulus can increase long-term growth depends on whether it can increase capacity. The government hopes that infrastructure expenditure will do just that. However, there is a long time lag between committing the expenditure and the extra capacity coming on stream. For example, planning for HS2 began in 2009. Phase 1 from London to Birmingham is currently expected to be operation not until 2033 and Phase 2, to Leeds and Manchester, not until 2040, assuming no further delays.

Crossrail (the new Elizabeth line in London) has been delayed several times. Approved in 2007, with construction beginning in 2009, it was originally scheduled to open in December 2018. It is now expected to be towards the end of 2021 before it does finally open. Its cost has increased from £14.8 billion to £18.25 billion.

Of course, some infrastructure projects are much quicker, such as opening new bus routes, but most do take several years.

The first five articles look at UK policy. The rest look at Keynesian fiscal policies in other countries, including the EU, Russia, Malaysia, Singapore and the USA. Governments seem to be looking for a short-term boost to aggregate demand that will increase short-term GDP, but also have longer-term supply-side effects that will increase the growth in potential GDP.

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Questions

  1. Illustrate the effect of an expansionary fiscal policy with a Keynesian Cross (income and expenditure) diagram or an injections and withdrawals diagram.
  2. What is meant by the term ‘output gap’? What are the implications of a positive output gap for expansionary Keynesian policy?
  3. Assess the benefits of having a fiscal rule that requires governments to balance the current budget but allows borrowing to invest.
  4. Would there be a problem following such a rule if there is currently quite a large positive output gap?
  5. To what extent are the policies being proposed in Russia, the EU, Malaysia and Singapore short-term demand management policies or long-term supply-side policies?

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?

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.

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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.

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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?