Category: Essential Economics for Business 7e and 6e

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Desperately seeking confidence, again

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.

Articles

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?
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Stop and smell the roses

Spring has already made its appearance here in Norfolk. Our garden is in full bloom and I am in a particularly spring-philosophical mood today – especially so as I should soon be hearing news from the editorial office of a coveted economics journal. This concerns a paper that I submitted for publication what feels like months ago.

And just as I was reflecting on this thought, a paper by Firmuc and Paphawasit (2018) landed on my desk, evaluating the impact of physical attractiveness on academic research productivity in the field of economics. More specifically, the authors pull together information about the research productivity of about 2000 published economics researchers. They then find photos of them and rate their attractiveness (yes, seriously!) using an online survey. In particular:

Besides collecting some basic information on the authors, we also rated their attractiveness. To this effect, we circulated a number of online survey links to potential participants at Brunel University and elsewhere, using direct communication, email and social networks. Each online survey collected basic background information on the assessor (gender, age, ethnicity, highest education, and whether they are currently enrolled as a student) followed by 30 randomly-chosen and randomly-ordered photos, with each picture placed on a separate page.

…Each rater was asked to rate the attractiveness of the person in the photo on an 11-point scale, from 0 (unattractive) to 10 (very attractive). No information on the photographed individuals was provided and the raters were told that the survey studies the formation of perceptions of beauty. The raters were also asked whether they recognised the person in the picture, or whether the picture did not load properly: in such instances, their scores were excluded from the analysis.

The average beauty score was 3.9, with the most attractive academic scoring 7.6

They even attach photographs of the three most attractive male authors in their sample in an appendix (thankfully the other end of the distribution was left out – I had to check to make sure, as I was worried for a few minutes I would find my photo posted there!).

Their results show that there is a link between authors’ attractiveness and quality of journals where their papers are published, as well as number of citations that they receive. According to their findings, this association matters most for more productive authors (‘of intermediate and high productivity’), whereas there seems to be very small or no effect for less productive authors. Some of these effects disappear once controlling for journal quality:

…attractive authors tend to publish their research in better journals, but once their work is published, it does not attract more citations than other papers published in the same journal by less good-looking authors.

Although there are many methodological parts of this paper that I do not quite understand (probably because it is not my area of specialisation), it does remind us that looks do matter in labour markets. There is a well-established literature in labour economics discussing the association between appearance/beauty and wages and the so-called ‘halo effect’ (referring to the physical attractiveness premium that more attractive workers are likely to command in labour markets – see also Langlois et al., 2000; Zebrowitz et al., 2002; Kanazawa and Kovar, 2004; for a detailed discussion on this).

I was also surprised to read that this beauty bias can be also gender specific. For instance, Cash et al (1977) and Johnson et al. (2010) find that the effect goes the other way (negative impact) when considering female candidates applying for jobs traditionally perceived as ‘masculine’ ones. By contrast, male candidates are more likely to experience a positive return on good looks, irrespective of the type of job that they do (see also Johnson et al., 2010).

No surprise then that ‘guyliners’, ‘make up for men’ and other male beauty products are becoming increasingly popular amongst younger workers – in Europe it is not as common yet as it is in parts of Asia (Japan comes to mind), but I imagine it is a matter of time, as more workers realise that there are positive returns to be made!

References

Article

Questions

  1. Read some of the papers posted above and explain the main argument about the link between physical attraction and wages. What does the empirical evidence show on this?
  2. Using examples and anecdotal evidence, do you agree with these findings?
  3. If these findings are representative of the real world, what do they suggest about the functioning of modern labour markets?
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London leads house price slowdown

The latest UK house price index continues to show an easing in the rate of house price inflation. In the year to January 2019 the average UK house price rose by 1.7 per cent, the lowest rate since June 2013 when it was 1.5 per cent. This is significantly below the recent peak in house price inflation when in May 2016 house prices were growing at 8.2 per cent year-on-year. In this blog we consider how recent patterns in UK house prices compare with those over the past 50 years and also how the growth of house prices compares to that in consumer prices.

The UK and its nations

The average UK house price in January 2019 was £228,000. As Chart 1 shows, this masks considerable differences across the UK. In England the average price was £245,000 (an annual increase of 1.5 per cent), while in Scotland it was £149,000 (an increase of 1.3 per cent), Wales £160,000 (an increase of 4.6 per cent) and £137,000 in Northern Ireland (an increase of 5.5 per cent). (Click here to download a PowerPoint copy of the chart.)

Within England there too are considerable differences in house prices, with London massively distorting the English average. In January 2019 the average house price in inner London was recorded at £568,000, a fall of 1.9 per cent on January 2018. In Outer London the average price was £426,000, a fall of 0.2 per cent. Across London as a whole the average price was £472,000, a fall of 1.6 per cent. House prices were lowest in the North East at £125,000, having experienced an annual increase of 0.9 per cent.

The Midlands can be used as a reference point for English house prices outside of the capital. In January 2019 the average house price in the West Midlands was £195,000 while in the East Midlands it was £193,000. While the annual rate of house price inflation in London is now negative, the annual rate of increase in the Midlands was the highest in England. In the West Midlands the annual increase was 4 per cent while in the East Midlands it was 4.4 per cent. These rates of increase are currently on par with those across Wales.

Long-term UK house price trends

Chart 2 shows the average house price for the UK since 1969 alongside the annual rate of house price inflation, i.e. the annual percentage change in the level of house prices. The average UK house price in January 1969 was £3,750. By January 2019, as we have seen, it had risen to around £228,000. This is an increase of nearly 6,000 per cent. Over this period, the average annual rate of house price inflation was 9 per cent. However, if we measure it to the end of 2007 it was 11 per cent. (Click here to download a PowerPoint copy of the chart.)

The significant effect of the financial crisis on UK house prices is evident from Charts 1 and 2. In February 2009 house prices nationally were 16 per cent lower than a year earlier. Furthermore, it was not until August 2014 that the average UK house rose above the level of September 2007. Indeed, some parts of the UK, such as Northern Ireland and the North East of England, remain below their pre-financial crisis level even today.

Nominal and real UK house prices

But how do house price patterns compare to those in consumer prices? In other words, what has happened to inflation-adjusted or real house prices? One index of general prices is the Retail Prices Index (RPI). This index measures the cost of a representative basket of consumer goods and services. Since January 1969 the RPI has increased by nearly 1,600 per cent. While substantial in its own right, it does mean that house prices have increased considerably more rapidly than consumer prices.

If we eliminate the increase in consumer prices from the actual (nominal) house price figures what is left is the increase in house prices relative to consumer prices. To do this we estimate house prices as if consumer prices had remained at their January 1987 level. This creates a series of average UK house prices at constant January 1987 consumer prices.

Chart 3 shows the average nominal and real UK house price since 1969. It shows that in real terms the average UK house price increased by around 266 per cent between January 1969 and January 2019. Therefore, the average real UK house price was 3.7 times more expensive in 2019 compared with 1969. This is important because it means that general price inflation cannot explain all the long-term growth seen in average house prices. (Click here to download a PowerPoint copy of the chart.)

Real UK house price cycles

Chart 4 shows that annual rates of nominal and real house price inflation. As we saw earlier, the average nominal house price inflation rate since 1969 has been 9 per cent. The average real rate of increase in house prices has been 3.1 per cent per annum. In other words, house prices have on average each each year increased by the annual rate of RPI inflation plus 3.1 percentage points. (Click here to download a PowerPoint copy of the chart.)

Chart 4 shows how, in addition to the long-term relative increase in house prices, there are also cycles in the relative price of houses. This is evidence of a volatility in house prices that cannot be explained by general prices. This volatility reflects frequent imbalances between the demand and supply of housing, i.e. between instructions to buy and sell property. Increasing levels of housing demand (instructions to buy) relative to housing supply (instructions to supply) will put upward pressure on house prices and vice versa.

In January 2019 the annual real house price inflation across the UK was -0.9 per cent. While the rate was slightly lower in Scotland at -1.2 per cent, the biggest drag on UK house price inflation was the London market where the real house price inflation rate was -4.0 per cent. In contrast, January saw annual real house price inflation rates of 2 per cent in Wales, 2.3 per cent in Northern Ireland and 1.8 per cent in the East Midlands.

Inflation-adjusted inflation rates in London have been negative consistently since June 2017. From their July 2016 peak, following the result of the referendum on UK membership of the EU, to January 2019 inflation-adjusted house prices fell by 7.6 per cent. This reflects, in part, the fact that the London housing market, like that of other European capitals, is a more international market than other parts of the country. Therefore, the current patterns in UK house prices are rather distinctive in that the easing is being led by London and southern England.

Articles

Questions

  1. What is meant by the annual rate of house price inflation?
  2. How is a rise in the rate of house price inflation different from a rise in the level of house prices?
  3. What factors are likely to determine housing demand (instructions to buy)?
  4. What factors are likely to affect housing supply (instructions to sell)?
  5. Explain the difference between nominal and real house prices.
  6. What does a decrease in real house prices mean? Can this occur even if actual house prices have risen?
  7. How might we explain the recent differences between house price inflation rates in London relative to other parts of the UK, like the Midlands and Wales?
  8. Why were house prices so affected by the financial crisis?
  9. Assume that you asked to measure the affordability of housing. What data might you collect?
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Riding the consumer credit cycle (again)

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.

Articles

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?
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The ECB loosens monetary policy – again

Growth in the eurozone has slowed. The European Central Bank (ECB) now expects it to be 1.1% this year; in December, it had forecast a rate of 1.7% for 2019. Mario Draghi, president of the ECB, in his press conference, said that ‘the weakening in economic data points to a sizeable moderation in the pace of the economic expansion that will extend into the current year’. Faced with a slowing eurozone economy, the ECB has announced further measures to stimulate economic growth.

First it has indicated that interest rates will not rise until next year at the earliest ‘and in any case for as long as necessary to ensure the continued sustained convergence of inflation to levels that are below, but close to, 2% over the medium term’. The ECB currently expects HIPC inflation to be 1.2% in 2019. It was expected to raise interest rates later this year – probably by the end of the summer. The ECB’s main refinancing interest rate, at which it provides liquidity to banks, has been zero since March 2016, and so there was no scope for lowering it.

Second, although quantitative easing (the asset purchase programme) is coming to an end, there will be no ‘quantitative tightening’. Instead, the ECB will purchase additional assets to replace any assets that mature, thereby leaving the stock of assets held the same. This would continue ‘for an extended period of time past the date when we start raising the key ECB interest rates, and in any case for as long as necessary to maintain favourable liquidity conditions and an ample degree of monetary accommodation’.

Third, the ECB is launching a new series of ‘quarterly targeted longer-term refinancing operations (TLTRO-III), starting in September 2019 and ending in March 2021, each with a maturity of two years’. These are low-interest loans to banks in the eurozone for use for specific lending to businesses and households (other than for mortgages) at below-market rates. Banks will be able to borrow up to 30% of their eligible assets (yet to be fully defined). These, as their acronym suggests, are the third round of such loans. The second round was relatively successful. As the Barron’s article linked below states:

Banks boosted their long-term borrowing from the ECB by 70% over the course of the program, although they did not manage to increase their holdings of business loans until after TLTRO II had finished disbursing funds in March 2017.

Whether these measures will be enough to raise growth rates in the eurozone depends on a range of external factors affecting aggregate demand. Draghi identified three factors which could have a negative effect.

  • Brexit. The forecasts assume an orderly Brexit in accordance with the withdrawal deal agreed between the European Commission and the UK government. With the House of Commons having rejected this deal twice, even though it has agreed that there should not be a ‘no-deal Brexit’, this might happen as it is the legal default position. This could have a negative effect on the eurozone economy (as well as a significant one on the UK economy). Even an extension of Article 50 could create uncertainty, which would also have a negative effect
  • Trade wars. If President Trump persists with his protectionist policy, this will have a negative effect on growth in the eurozone and elsewhere.
  • China. Chinese growth has slowed and this dampens global growth. What is more, China is a major trading partner of the eurozone countries and hence slowing Chinese growth impacts on the eurozone through the international trade multiplier. The ECB has taken this into account, but if Chinese growth slows more than anticipated, this will further push down eurozone growth.

Then there are internal uncertainties in the eurozone, such as the political and economic uncertainty in Italy, which in December 2018 entered a recession (2 quarters of negative economic growth). Its budget deficit is rising and this is creating conflict with the European Commission. Also, there are likely to be growing tensions within Italy as the government raises taxes.

Faced with these and other uncertainties, the measures announced by Mario Draghi may turn out not to be enough. Perhaps in a few months’ there may have to be a further round of quantitative easing.

Articles

Videos

ECB publications

Questions

    • Investigate the history of quantitative easing and its use by the Fed, the Bank of England and the ECB. What is the current position of the three central banks on ‘quantitative tightening’, whereby central banks sell some of the stock of assets they have purchased during the process of quantitative easing or not replace them when they mature?
    • What are TLTROs and what use of them has been made by the ECB? Do they involve the creation of new money?
    • What will determine the success of the proposed TLTRO III scheme?
    • If the remit of central banks is to keep inflation on target, which in the ECB’s case means below 2% HIPC inflation but close to it over the medium term, why do people talk about central banks using monetary policy to revive a flagging economy?
    • What is ‘forward guidance’ by central banks and what determines its affect on aggregate demand?