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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?

The IFS has launched a major five-year review into all aspects of inequality. The review is led by Sir Angus Deaton, the Scottish-born Professor of Economics and International Affairs at Princeton University. In 2015, he was awarded the Nobel Prize in Economic Sciences for his analysis of consumption, poverty, and welfare. The review will cover all aspects of inequality, including inequality of income, wealth, health, life-span, education, social mobility, housing, opportunity and political access, and by gender, age, ethnicity, family and geography. It will look at trends in and causes of inequality, the impacts of globalisation and political change, barriers to tackling inequality and poverty, and at various policy measures.

Although the published Gini coefficient in England and Wales has not changed much over the past 15 years, largely because of support given to the poor by tax credits, it did rise from 31.7 to 33.2 from 2015/16 to 2017/18 (the latest year for which figures are available). Other measures of inequality, however, have changed more dramatically. There is huge geographical inequality in income in the UK, reflected in inequality in health. Average weekly earnings in London are 66% higher than in the north east of England. And, according to the IFS, ‘Men in the most affluent areas can expect to live nearly 10 years longer than those in the most deprived areas, and this gap is widening’.

The UK has the greatest inequality of income of developed countries, with the exception of the USA. The IFS warns that the UK could follow the USA:

…where wages for non-college-educated men have not risen for five decades, and where rising mortality for less-educated white men and women in middle age has caused average life expectancy in America to fall for the last three years – something that has not happened for a century. We have not experienced anything similar in the UK but we have now had a decade of stagnant wages and there is recent evidence that ‘deaths of despair’ – deaths from suicide and drug and alcohol abuse – are now rising among middle-aged Britons. Sir Angus will go on to say:
 
‘I think that people getting rich is a good thing, especially when it brings prosperity to others. But the other kind of getting rich, “taking” rather than “making”, rent-seeking rather than creating, enriching the few at the expense of the many, taking the free out of free markets, is making a mockery of democracy. In that world, inequality and misery are intimate companions.’

The initial report, which introduces the IFS Deaton Review, points to some possible causes of growing inequality, including the dramatic decline in union membership, which now stands at just 13% of private-sector employees, with more flexible labour markets with growing numbers of workers on temporary or zero-hour contracts. Other causes include growing globalisation, rapid technological change making some skills redundant, the power of large companies and their shareholders, large pay rises given to senior executives, growing inequality of access to education and changing family environments with more single parents.

About one in six children in the UK are born to single parents – a phenomenon that is heavily concentrated in low-income and low-educated families, and is significantly less prevalent in continental Europe.

Then there is the huge growth in housing inequality as house prices and rents have risen faster than incomes. Home ownership has increasingly become beyond the reach of many young people, while many older people live in relative housing wealth. Generational inequality is another major factor that the Deaton Review will consider.

Inequalities in different dimensions – income, work, mental and physical health, families and relationships – are likely to reinforce one another. They may result in, and stem from, other inequalities in wealth, cultural capital, social networks and political voice. Inequality cannot be reduced to any one dimension: it is the culmination of myriad forms of privilege and disadvantage.

The review will consider policy alternatives to tackle the various aspects of inequality, from changes to the tax and benefit system, to legislation on corporate behaviour, to investment in various structural resources, such as health and education. As the summary to the initial report states:

The Deaton Review will identify policy responses to the inequalities we face today. It will assess the relative merits of available policy options – taxes and benefits, labour market policies, education, competition policy, ownership structures and regulations – and consider how policies in different spheres can be designed to complement each other and minimise adverse effects. We aim not just to further our understanding of inequalities in the twenty-first century, but to equip policymakers with the knowledge and tools to tackle those inequalities.

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IFS Deaton Review

Questions

  1. Identify different aspects of inequality. Choose two or three aspects and examine how they are related.
  2. Why has inequality widened in most developed countries over the past 20 years?
  3. What is meant by ‘rent seeking’? Why may it be seen as undesirable? Can it be justified and, if so, on what grounds?
  4. What policies could be adopted to tackle poverty?
  5. What trade-offs might there be between greater equality and faster economic growth?
  6. What policies could be adopted that would both reduce inequality and boost long-term economic growth?

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?

The latest consumer confidence figures from the European Commission point to consumer confidence in the UK remaining at around its long-term average. Despite this, confidence is markedly weaker than before the outcome of the EU referendum. Yet, the saving ratio, which captures the proportion of disposable income saved by the household sector, is close to its historic low. We consider this apparent puzzle and whether we can expect the saving ratio to rise.

The European Commission’s consumer confidence measure is a composite indicator based on the balance of responses to 4 forward-looking questions relating to the financial situation of households, the general economic situation, unemployment expectations and savings.

Chart 1 shows the consumer confidence indicator for the UK. The long-term average (median) of –6.25 shows that negative responses across the four questions typically outweigh positive responses. In October 2018 the confidence balance stood at –5.2, essentially unchanged from its September value of –5.8. While above the long-term average, recent values mark a weakening in confidence from levels before the EU referendum. At the beginning of 2016 the aggregate confidence score was running at around +4. (Click here to download a PowerPoint of the chart.)

Chart 1 shows two periods where consumer confidence fell markedly. The first was in the early 1990s. In 1990 the UK joined the Exchange Rate Mechanism (ERM). This was a semi-fixed exchange rate system whereby participating EU countries allowed fluctuations against each other’s currencies, but only within agreed bands, while being able to collectively float freely against all other currencies. In attempting to staying in the ERM, the UK was obliged to raise interest rates in order to protect the pound. The hikes to rates contributed to a significant dampening of aggregate demand and the economy slid into recession. Britain crashed out of the ERM in September 1992.

The second period of declining confidence was during the global financial crisis in the late 2000s. The retrenchment among financial institutions meant a significant tightening of credit conditions. This too contributed to a significant dampening of aggregate demand and the economy slid into recession. Whereas the 1992 recession saw the UK national output contract by 2.0 percent, this time national output fell by 6.3 per cent.

The collapses in confidence from 1992 and from 2007/08 are likely to have helped propagate the effects of the fall in aggregate demand that were already underway. The weakening of confidence in 2016 is perhaps a better example of a ‘confidence shock’, i.e. a change in aggregate demand originating from a change in confidence. Nonetheless, a fall in confidence, whether it amplifies existing shocks or is the source of the shock, is often taken as a signal of greater economic uncertainty. If we take this greater uncertainty to reflect a greater range of future income outcomes, including potential income losses, then households may look to insure themselves by increasing current saving.

It is usual to assume that people suffer from diminishing marginal utility of total consumption. This means that while total satisfaction increases as we consume more, the additional utility from consuming more (marginal utility) decreases. An implication of this is that a given loss of consumption reduces utility by more than an equivalent increase in consumption increases utility. This explains why people prefer more consistent consumption levels over time and so engage in consumption smoothing. The utility, for example, from an ‘average’ consumption level across two time periods, is higher, than the expected utility from a ‘low’ level of consumption in period 1 and a ‘high’ level of consumption in period 2. This is because the loss of utility from a ‘low’ level of consumption relative to the ‘average’ level is greater than the additional utility from the ‘high’ level relative to the ‘average’ level.

If greater uncertainty, such as that following the EU referendum, increases the range of possible ‘lower’ consumption values in the future even when matched by an increase in the equivalent range of possible ‘higher’ consumption values, then expected future utility falls. The incentive therefore is for people to build up a larger buffer stock of saving to minimise utility losses if the ‘bad state’ occurs. Hence, saving which acts as a from of self-insurance in the presence of uncertainty is known as buffer-stock saving or precautionary saving.

Chart 2 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 more 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 that of this. The early 1990s and late 2000s certainly coincided with both waning confidence and a rising saving ratio. The saving ratio rose to as high as 15.2 per cent in 1993 and 12.0 per cent in 2009. Meanwhile the rising confidence seen in the late 1990s coincided with a fall in the saving ratio to 4.7 per cent in 1999.

As Chart 2 shows, the easing of confidence since 2016 has coincided with a period where the saving ratio has been historically low. Across 2017 the saving ratio stood at just 4.5 per cent. In the first half of 2018 the ratio averaged just 4.2 per cent. While the release of the official figures for the saving ratio are less timely than those for confidence, the recent very low saving ratio may be seen to raise concerns. Can softer confidence data continue to co-exist with such a low saving ratio?

There are a series of possible explanations for the recent lows in the saving ratio. On one hand, the rate of price inflation has frequently exceeded wage inflation in recent years so eroding the real value of earnings. This has stretched household budgets and limited the amount of discretionary income available for saving. On the other hand, unemployment rates have fallen to historic lows. The rate of unemployment in the three months to August stood at 4 per cent, the lowest since 1975. Unemployment expectations are important in determining levels of buffer stock saving because of the impact of unemployment on household budgets.

Another factor that has fuelled the growth of spending relative to income, has been the growth of consumer credit. In the period since July 2016, the annual rate of growth of consumer credit, net of repayments, has averaged 9.7 per cent. Behavioural economists argue that foregoing spending can be emotionally painful. Hence, spending has the potential to exhibit more stickiness than might otherwise be predicted in a more uncertain environment or in the anticipation of income losses. Therefore, the reluctance or inability to wean ourselves off credit and spending might be a reason for the continuing low saving ratio.

We wait to see whether the saving ratio increases over the coming months. However, for now, the UK household sector appears to be characterised by low saving and fragile confidence. Whether or not this is a puzzle, is open to question. Nonetheless, it does appear to carry obvious risks should weaker income growth materialise.

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Questions

  1. Draw up a series of factors that you think might affect consumer confidence.
  2. Which of the following statements is likely to be more accurate: (a) Consumer confidence drives economic activity or (b) Economic activity drives consumer confidence?
  3. What macroeconomic indicators would those compiling the consumer confidence indicator expect the indicator to predict?
  4. How does the diminishing marginal utility of consumption (or income) help explain why people engage in buffer stock saving (precautionary saving)?
  5. How might uncertainty affect consumer confidence?
  6. How does greater income uncertainty affect expected utility? What affect might this have on buffer stock saving?