The Christmas and new year period often draws attention to the financial well-being of households. An important determinant of this is the extent of their indebtedness. Rising levels of debt mean that increasing amounts of households’ incomes becomes prey to servicing debt through repayments and interest charges. They can also result in more people becoming credit constrained, unable to access further credit. Rising debt levels can therefore lead to a deterioration of financial well-being and to financial distress. This was illustrated starkly by events at the end of the 2000s.
The total amount of lending by monetary financial institutions to individuals outstanding at the end of October 2018 was estimated at £1.61 trillion. As Chart 1 shows, this has grown from £408 billion in 1994. Hence, indivduals in the UK have experience a four-fold increase in the levels of debt. (Click here to download a PowerPoint of the chart.)
The debt of individuals is either secured or unsecured. Secured debt is debt secured by property, which for individuals is more commonly referred to as mortgage debt. Unsecured debt, which is also known as consumer credit, includes outstanding debt on credit cards, overdrafts on current accounts and loans for luxury items such as cars and electrical goods. The composition of debt in 2018 is unchanged from that in 1994: 87 per cent is secured debt and 13 per cent unsecured debt.
The fourfold increase in debt is taken by some economists as evidence of financialisation. While this term is frequently defined in distinctive ways depending upon the content in which it is applied, when viewed in very general terms it describes a process by which financial institutions and markets become increasingly important in everyday lives and so in the production and consumption choices that economists study. An implication of this is that in understanding economic decisions, behaviour and outcomes it becomes increasingly important to think about the potential impact of the financial system. The financial crisis is testimony to this.
In thinking about financial well-being, at least at an aggregate level, we can look at the relative size of indebtedness. One way of doing this is to measure the stock of individual debt relative to the annual flow of GDP (national income). This is illustrated in Chart 2. (Click hereto download a PowerPoint of the chart.)
The growth in debt among individuals owed to financial institutions during the 2000s was significant. By the end of 2007, the debt-to-GDP ratio had reached 88 per cent. Decomposing this, the secured debt-to-GDP ratio had reached 75 per cent and the unsecured debt-to-GDP ratio 13 per cent. Compare this with the end of 1994 when secured debt was 46 per cent of GDP, unsecured debt 7 per cent and total debt 53 per cent. In other words, the period between 1994 and 2007 the UK saw a 25 percentage point increase in the debt-to-GDP ratio of individuals.
The early 2010s saw a consolidation in the size of the debt (see Chart 1) which meant that it was not until 2014 that debt levels rose above those of 2008. This led to the size of debt relative to GDP falling back by close to 10 percentage points (see Chart 2). Between 2014 and 2018 the stock of debt has increased from around £1.4 trillion to the current level of £1.61 trillion. This increase has been matched by a similar increase in (nominal) GDP so that the relative stock of debt remains little changed at present at around 76 per cent of GDP.
Chart 3 shows the annual growth rate of net lending (lending net of repayments) by monetary financial institutions to individuals. This essentially captures the growth rate in the stocks of debt, though changes in the actual stock of debt are also be affected by the writing-off of debts. (Click here to download a PowerPoint of the chart.)
We can see quite readily the pick up in lending from 2014. The average annual rate of growth in total net lending since 2014 has been just a little under 3½ per cent. This has been driven by unsecured lending whose growth rate has been close to 8½ per cent per annum, compared to just 2.7 per cent for secured lending. In 2016 the annual growth rate of unsecured lending was just shy of 11 per cent. This helped to fuel concerns about possible future financial distress. These concerns remain despite the annual rate of growth in unsecured debt having eased slightly to 7.5 per cent.
Despite the aggregate debt-to-GDP ratio having been relatively stable of late, the recent growth in debt levels is clearly not without concern. It has to be viewed in the context of two important developments. First, there remains a ‘debt hangover’ from the financial distress experienced by the private sector at the end of the 2000s, which itself contributed to a significant decline in economic activity (real GDP fell by 4 per cent in 2009). This subequently affected the financial well-being of the public sector following its interventions to cushion the economy from the full effects of the economic downturn as well as to help stabilise the financial system. Second, there is considerable uncertainty surrounding the UK’s exit from the European Union.
The financial resilience of all sectors of the economy is therefore of acute concern given the unprecedented uncertainty we are currently facing while, at the same time, we are still feeling the effects of the financial distress from the financial crisis of the late 2000s. It therefore seems timely indeed for individuals to take stock of their stocks of debt.
- How might we measure the financial distress of individuals?
- If individuals are financially distressed how might this affect their consumption behaviour?
- How might credit constraints affect the relationship between consumption and income?
- What do you understand by the concept of ‘cash flow effects’ that arise from interest rate changes?
- How might the accumulation of secured and unsecured debt have different effects on consumer spending?
- What factors might explain the rate of accumulation of debt by individuals?
- What is meant by ‘financial resilience’ and why might this currently be of particular concern?
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 201 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.
- Draw up a series of factors that you think might affect consumer confidence.
- Which of the following statements is likely to be more accurate: (a) Consumer confidence drives economic activity or (b) Economic activity drives consumer confidence?
- What macroeconomic indicators would those compiling the consumer confidence indicator expect the indicator to predict?
- How does the diminishing marginal utility of consumption (or income) help explain why people engage in buffer stock saving (precautionary saving)?
- How might uncertainty affect consumer confidence?
- How does greater income uncertainty affect expected utility? What affect might this have on buffer stock saving?
Would you like to be a millionaire? Of course you would – who wouldn’t, right? Actually the answer to this question may be more complicated than you might think (see for instance Sgroi et al (2017) on the economics of happiness: see linked article below), but, generally speaking, most people would answer positively to this question.
What if I told you, however, that you could become a millionaire (actually, scratch that – think big – make that “trillionaire”) overnight and be deeply unhappy about it? If you don’t believe me see what happened to Zimbabwe 10 years ago, when irresponsible money printing and fiscal easing drove the country’s economy to staggering hyperinflation (see the blogs A remnant of hyperinflation in Zimbabwe and Fancy a hundred trillion dollar note?. At the peak of the crisis, prices were increasing by a factor of 130 each year. I have in my office a 100 trillion Zimbabwean dollar note (see below) which I show in my lectures when I talk about hyperinflation to my first year Economics for Business students (if you are one of them, make sure not to miss it next February at UEA!). How much is this 100 trillion note worth? Nothing (except, may be, for collectors). It has been withdrawn from circulation as it ended up not even being worth the cost of the paper on which it was printed.
The Zimbabwean economy managed to pull itself out of this spiral of economic death, partly by informally replacing its hyperinflationary currency with the US greenback, and partly by keeping its fiscal spending under control and reverting to more sane economic policy making. That lasted until 2013, after which the government launched a Zimbabwean digital currency (known as “Zollar”) that had a nominal value set equal to a US dollar; and forced its exporters to exchange their greenbacks for Zollars. It then started spending these USD to finance a very ambitious and unsustainable programme of fiscal expansion.
The Economist published yesterday a story that shows the results of this policy – wild price increases and empty supermarket shelves are both back. According to the newspaper’s report:
At a supermarket in Harare, Zimbabwe’s capital, the finance minister is staring aghast at a pack of nappies. ‘This is absolutely ridiculous!’, exclaims Mthuli Ncube. ‘$49!’ A manager says it cost $23 two weeks ago, before pointing out other eye-watering items such as $20 Coco Pops. […] Over the past two weeks zollars have been trading at as little as 17 cents to the dollar. The devaluation has led to a surge in prices—and not just in imported goods like nappies. Football fans attending the Zimbabwe v Democratic Republic of Congo game on October 16th were shocked to learn that ticket prices had doubled on match day.
How long will it take for the 100 trillion Zollar to make its appearance again? We shall find out. I am sure Zimbabweans will be less than thrilled!
Articles and Report
- A fist full of zollars: Zimbabwe’s shops are empty and prices are soaring
The Economist (28/10/18)
- Shelves Empty as Specter of Hyperinflation Stalks Zimbabwe
Bloomberg, Paul Wallace, Godfrey Marawanyika and Desmond Kumbuka (12/10/18)
- imbabwe currency crisis: No cash, no bread, no KFC
BBC News, Andrew Harding (12/10/18)
- Hyperinflation in Zimbabwe: money demand, seigniorage and aid shocks
Journal of Applied Economics, Tara McIndoe-Calder (Volume 50, Issue 15, 18/9/17)
- Understanding Happiness
A CAGE Policy Report: Social Market Foundation, Daniel Sgroi, Thomas Hills, Gus O’Donnell, Andrew Oswald and Eugenio Proto (January 2017)
- Using an AS/AD diagram, explain the concept of hyperinflation. How can irresponsible fiscal policy-making lead to hyperinflation?
- What are the effects of hyperinflation on the people who live in the affected countries? Search the web for examples and case studies, and use them to support your answer.
- Once it has started, what policies can be used to fight hyperinflation? Use examples to support your answer.
- How does speculation affect hyperinflation?
Policymakers around the world have used Gross Domestic Product as the main gauge of economic performance – and have often adopted policies that aim to maximise its rate of growth. Generation after generation of economists have committed significant time and effort to thinking about the factors that influence GDP growth, on the premise that an expanding and healthy economy is one that sees its GDP increasing every year at a sufficient rate.
But is economic output a good enough indicator of national economic wellbeing? Costanza et al (2014) (see link below) argue that, despite its merits, GDP can be a ‘misleading measure of national success’:
GDP measures mainly market transactions. It ignores social costs, environmental impacts and income inequality. If a business used GDP-style accounting, it would aim to maximize gross revenue — even at the expense of profitability, efficiency, sustainability or flexibility. That is hardly smart or sustainable (think Enron). Yet since the end of the Second World War, promoting GDP growth has remained the primary national policy goal in almost every country. Meanwhile, researchers have become much better at measuring what actually does make life worthwhile. The environmental and social effects of GDP growth is a misleading measure of national success. Countries should act now to embrace new metrics.
The limitations of GDP growth as a measure of economic wellbeing and national strength are becoming increasingly clear in today’s world. Some of the world’s wealthiest countries are plagued by discontent, with a growth in populism and social discontent – attitudes which are often fuelled by high rates of poverty and economic hardship. In a recent report titled ‘The Living Standards Audit 2018’ published by the Resolution Foundation, a UK economic thinktank (see link below), the authors found that child poverty rose in 2016–17 as a result of declining incomes of the poorest third of UK households:
While the economic profile of UK households has changed, living standards – with the exception of pensioner households – have mostly stagnated since the mid-2000s. Typical household incomes are not much higher than they were in 2003–04. This stagnation in living standards for many has brought with it a rise in poverty rates for low to middle income families. Over a third of low to middle income families with children are in poverty, up from a quarter in the mid-2000s, and nearly two-fifths say that they can’t afford a holiday away for their children once a year. On the other hand, the share of non-working families in poverty has fallen, though not by enough to prevent an overall rise in poverty since 2010.
Their projections also show that this rise in poverty was likely to have continued in 2017–18:
Although the increase in broad measures of inequality were relatively muted last year, our nowcast suggests that there was a pronounced rise in poverty (measured after housing costs[…]. The increase in overall poverty (from 22.1 to 23.2 per cent) was the largest since 1988. But this was dwarfed by the increase in child poverty, which rose from 30.3 per cent to 33.4 per cent. […]The fortunes of middle-income households diverged from those towards the bottom of the distribution and so a greater share of households, and children, found themselves below the poverty threshold.
A simple literature search on Scope (or even Google Scholar) shows that there has been a significant increase in the number of journal articles and reports in the last 10 years on this topic. We do talk more about the limitations of GDP, but we are still using it as the main measure of national economic performance.
Is it then time to stop focusing our attention on GDP growth exclusively and start considering broader metrics of social development? And what would such metrics look like? Both interesting questions that we will try to address in coming blogs.
- What are the main strengths and weakness of using GDP as measure of economic performance?
- Is high GDP growth alone enough to foster economic and social wellbeing? Explain your answer using examples.
- Write a list of alternative measures that could be used alongside GDP-based metrics to measure economic and social progress. Explain your answer.
I admit it, the title of my blog today is a little bit misleading – but at the same time very appropriate for today’s topic. Nancy Sinatra certainly wasn’t thinking about emigration when she was singing this song – it had nothing to do with it, after all. It is, however, very relevant to economists: Indeed, there are many economics papers discussing the effects of skilled immigration on host and source economies and regions.
Economists often use the term ‘brain drain’ to describe the migration of highly skilled workers from poor/developing to rich/developed economies. Such flows are anything but unusual. As The Economist points out in a recent article, ‘[I]n the decade to 2010–11 the number of university-educated migrants in the G20, a group of large economies that hosts two-thirds of the world’s migrants, grew by 60% to 32m according to the OECD, a club of mostly rich countries.’.
The effects of international migration are found to be overwhelmingly positive for both skilled migrant workers and their hosts. This is particularly true for highly skilled workers (such as academics, physicians and other professionals), who, through emigration, get the opportunity to earn a significantly higher return on their skills that what they might have had in their home country. Very often their home country is saturated and oversupplied with skilled workers competing for a very limited number of jobs. Also, they get the opportunity to practise their profession – which they might not have had otherwise.
But what about their home countries? Are they worse off for such emigration?
There are different views when it comes to answering this question. One argument is that the prospect of international migration incentivises people in developing countries to accumulate skills (brain gain) – which they might not choose to do otherwise, if the expected return to skills was not high enough to warrant the effort and opportunity cost that comes with it. Beine et al (2011) find that:
Our empirical analysis predicts conditional convergence of human capital indicators. Our findings also reveal that skilled migration prospects foster human capital accumulation in low-income countries. In these countries, a net brain gain can be obtained if the skilled emigration rate is not too large (i.e. it does not exceed 20–30% depending on other country characteristics). In contrast, we find no evidence of a significant incentive mechanism in middle-income, and not surprisingly, high-income countries.
Other researchers find that emigration can have a significant negative effect on source economies (countries or regions) – especially if it affects a large share of the local workforce within a short time period. Ha et al (2016), analyse the effect of emigration on human capital formation and economic growth of Chinese provinces:
First, we find that permanent emigration is conducive to the improvement of both middle and high school enrollment. In contrast, while temporary emigration has a significantly positive effect on middle school enrollment it does not affect high school enrollment. Moreover, the different educational attainments of temporary emigrants have different effects on school enrollment. Specifically, the proportion of temporary emigrants with high school education positively affects middle school enrollment, while the proportion of temporary emigrants with middle school education negatively affects high school enrollment. Finally, we find that both permanent and temporary emigration has a detrimental effect on the economic growth of source regions.
So yes or no? Good or bad? As everything else in economics, the answer quite often is ‘it depends’.
- Open future: What educated people from poor countries make of the “brain drain” argument
The Economist, R.S. (27/8/18)
- Brain drain, brain gain, and economic growth in China
China Economic Review, Wei Ha, Junjian Yi and Junsen Zhang (April 2016)
- A Panel Data Analysis of the Brain Gain
World Development, Michel Beine, Ric Docquier and Cecily Oden-Defoort (Vol 39, No 4, pp 523–532, 2011)
- ‘The brain drain makes a bad situation worse, by stripping developing economies of their most valuable assets: skilled workers’. Discuss.
- Using Google, find data on the inflows and outflows of skilled labour for a developing country of your choice. Explain your results.
- ‘Brain drain’ or ‘brain gain’? What is your personal view on this debate? Explain your opinion by using anecdotal evidence, personal experience and examples.
- Referring to the previous question, write a critique of your answer.