How would your life be without the internet? For many of you, this is a question that may be difficult to answer – as the internet has probably been an integral part of your life, probably since a very young age. We use internet infrastructure (broadband, 4G, 5G) to communicate, to shop, to educate ourselves, to keep in touch with each other, to buy and sell goods and services. We use it to seek and find new information, to learn how to cook, to download music, to watch movies. We also use the internet to make fast payments, transfer money between accounts, manage our ISA or our pension fund, set up direct debits and pay our credit-card bills.
I could spend hours writing about all the things that we do over the internet these days, and I would probably never manage to come up with a complete list. Just think about how many hours you spend online every day. Most likely, much of your waking time is spent using internet-based services one way or another (including apps on your phone, streaming on your phone, tablet or your smart TV and similar). If your access to the internet was disrupted, you would certainly feel the difference. What if you just couldn’t afford to have computer or internet access? What effect would that have on your education, your ability to find a job, and your income?
Martin Jenkins, a former homeless man, now entrepreneur, thinks that the magnitude of this effect is rather significant. In fact, he is so convinced about the importance of bringing the internet to poorer households, that he recently founded a company, Neptune, offering low-income households in the Bronx district of New York free access to online education, healthcare and finance portals. His venture was mentioned in a recent (and very interesting) BBC article – a link to which can be found at the end of this blog. But is internet connectivity really that important when it comes to economic and labour market outcomes? And is there a systematic link between economic growth and internet penetration rates?
These are all questions that have been the subject of intensive debate over the last few years, in the context of both developed and developing economies. Indeed, the ‘digital divide’ as it is known (the economic gap between the internet haves and have nots) is not something that concerns only developing countries. According to a recent policy brief published by the New York City Comptroller:
More than one-third (34 percent) of households in the Bronx lack broadband at home, compared to 30 percent in Brooklyn, 26 percent in Queens, 22 percent in Staten Island, and 21 percent in Manhattan.
The report goes on to present data on the percentage of households with internet connection at home by NYC district, and it does not take advanced econometric skills for one to notice that there is a clear link between median district income and broadband access. Wealthier districts (e.g. Manhattan Community District 1 & 2 – Battery Park City, Greenwich Village & Soho PUMA), tend to have a significantly higher share of households with broadband access, than less affluent ones (e.g. NYC-Brooklyn Community District 13 – Brighton Beach & Coney Island PUMA) – 88% of total households compared with 58%.
But, do these large variations in internet connectivity matter? The evidence is mixed. On the one hand, there are several studies that find a clear, strong link between internet penetration and economic growth. Czernich et al (2011), for instance, using data on OECD countries over the period 1996–2007, find that “a 10 percentage point increase in broadband penetration raised annual per capita growth by 0.9–1.5 percentage points”.
Another study by Koutroumpis (2018) examined the effect of rolling out broadband in the UK.
For the UK, the speed increase contributed 1.71% to GDP in total and 0.12% annually. Combining the effect of the adoption and speed changes increased UK GDP by 6.99% cumulatively and 0.49% annually on average”. (pp.10–11)
The evidence is less clear, however, when one tries to estimate the benefits between different types of workers – low and high skilled. In a recent paper, Atasoy (2013) finds that:
gaining access to broadband services in a county is associated with approximately a 1.8 percentage point increase in the employment rate, with larger effects in rural and isolated areas.
But then he adds:
most of the employment gains result from existing firms increasing the scale of their labor demand and from growth in the labor force. These results are consistent with a theoretical model in which broadband technology is complementary to skilled workers, with larger effects among college-educated workers and in industries and occupations that employ more college-educated workers.
Similarly, Forman et al (2009) analyse the effect of business use of advanced internet technology and local variation in US wage growth, over the period 1995–2000. Their findings show that:
Advanced internet technology is associated with larger wage growth in places that were already well off. These are places with highly educated and large urban populations, and concentration of IT-intensive industry. Overall, advanced internet explains over half of the difference in wage growth between these counties and all others.
How important then is internet access as a determinant of growth and economic activity and what role does it have in bridging economic disparities between communities? The answer to this question is most likely ‘very important’ – but less straightforward than one might have assumed.
- Comptroller, New York City, Internet Inequality
- Czernich, N., Falck, O., Kretschmer, T. and Woessmann, L., 2011, Broadband infrastructure and economic growth, The Economic Journal, 121(552), pp.505–32
- Koutroumpis, P., 2018, The economic impact of broadband: evidence from OECD countries, Ofcom
- Atasoy, H., 2013, The effects of broadband internet expansion on labor market outcomes, ILR Review, 66(2), pp.315–45
- Forman, C., Goldfarb, A. and Greenstein, S., 2009, The Internet and Local Wages: Convergence or Divergence? (No. w14750), National Bureau of Economic Research
- Is there a link between economic growth and internet access? Discuss, using examples.
- Explain the arguments for and against government intervention to subsidise internet access of poorer households.
- How important is the internet to you and your day to day life? Take a day offline (yes, really – a whole day). Then come back and write about it.
Consumer and business confidence reflect the sentiment, emotion, or anxiety of consumers and businesses. Confidence surveys therefore try to capture these feelings of optimism or pessimism. They aim to shed light on spending intentions and hence the short-term prospects for private-sector spending. For example, a fall in confidence would be expected to lead to a fall in consumption and investment spending. This is particularly relevant in the UK with the ongoing uncertainty around Brexit. We briefly summarise here current patterns in confidence.
Through the use of surveys attempts are made to measure confidence. 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.)
The chart nicely captures the collapse in confidence during the global financial crisis in the late 2000s. The significant tightening of credit conditions contributed to a significant dampening of aggregate demand which was further propagated (amplified) by the collapse in confidence. Consequently, the economy slid in to recession with national output contracting by 6.3 per cent during the 5 consecutive quarters during which output fell.
To this point, the current weakening of confidence is not of the same magnitude as that of the late 2000s. In January 2009 consumer confidence had fallen to an historic low of -35. Nonetheless, the December 2018 figure for consumer confidence was -9, the lowest figure since July 2016 the month following the EU referendum, and markedly lower than the +8 seen as recently as 2014. The long-term (median) average for the consumer confidence balance is -6.
The weakening in consumer confidence is mirrored by a weakening in confidence in the retail and service sectors. The confidence balances in December 2018 in these two sector both stood at -8 which compares to their longer-term averages of around +5. In contrast, confidence in industry and construction has so far held fairly steady with confidence levels in December 2018 at +8 in industry and at 0 in construction compared to their long-term averages of -4 and -10 respectively.
It will be interesting to see how confidence has been affected by recent events. The glut of stories suggesting that trading conditions were especially difficult for retailers over the Christmas and New Year period is consistent with the weakening confidence already observed amongst consumers and retailers. However, it is unlikely that recent events will have done anything other than to exacerbate the trend for a weakening of confidence of domestic consumers and retailers. Hence, the likelihood is an intensification of caution and prudence.
- Draw up a series of factors that you think might affect both consumer and business confidence. How similar are both these lists?
- Which of the following statements is likely to be more accurate: (a) Confidence drives economic activity or (b) Economic activity drives confidence?
- What macroeconomic indicators would those compiling the consumer and business confidence indicators expect each indicator to predict?
- What is meant by the concept of ‘prudence’ in the context of spending? What factors might determine the level of prudence
- How might prudence be expected to affect spending behaviour?
- How might we distinguish between confidence ‘shocks’ and confidence as a ‘propagator’ of shocks?
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 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.
- 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?