Category: Economics 10e: Ch 17

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.

Articles

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?

In his Budget on 29 October, the UK Chancellor, Philip Hammond, announced a new type of tax. This is a ‘digital services tax’, which, after consultation, he is planning to introduce in April 2020. The target of the tax is the profits made by major companies providing social media platforms (e.g. Facebook and Twitter), internet marketplaces (e.g. Amazon and eBay) or search engines (such as Alphabet’s Google).

Up to now, their profits have been very hard to tax because the companies operate in many countries and use accounting techniques, such as transfer pricing (see the blogs Disappearing tax revenues: how Luxembourg saves companies billions and Starbucks pays not a bean in corporation tax, thanks to transfer pricing), to declare most of their profits in low-tax countries, such as Luxembourg. One way of doing this is for a company’s branches in different countries to pay the head office (located in a tax haven) a ‘royalty’ for using the brand.

The proposed digital services tax is a 2% tax on the revenues earned by such companies in the UK. It would only apply to large companies, defined as those whose global revenue is at least £500m a year. It is expected to raise around £400m per year.

The EU is considering a similar tax at a rate of 3%. India, Pakistan, South Korea and several other countries are considering introducing digital taxes. Indeed, many countries are arguing for a worldwide agreement on such a tax. The OECD is studying the implications of the possible use of such a tax by its 36 members. If an international agreement on such a tax can be reached, a separate UK tax may not go ahead. As the Chancellor stated in his Budget speech:

In the meantime we will continue to work at the OECD and G20 to seek a globally agreed solution. And if one emerges, we will consider adopting it in place of the UK Digital Services Tax.

The proposed UK tax is a hybrid between direct and indirect taxes. Like corporation tax, a direct tax, its aim is to tax companies’ profits. But, unlike corporation tax, it would be harder for such companies to avoid. Like VAT, an indirect tax, it would be a tax on revenue, but, unlike VAT, it would be an ‘end-stage’ tax rather than a tax on value added at each stage of production. Also, it would not be a simple sales tax on companies as it would be confined to revenue (such as advertising revenue) earned from the use in the UK of search engines, social media platforms and online marketplaces. As the Chancellor said in his speech.

It is important that I emphasise that this is not an online-sales tax on goods ordered over the internet: such a tax would fall on consumers of those goods – and that is not our intention.

There is, however, a political problem for the UK in introducing such a tax. The main companies it would affect are American. It is likely that President Trump would see such taxes as a direct assault on the USA and could well threaten retaliation. As the Accountancy Age article states, ‘Dragging the UK into an acrimonious quarrel with one of its largest trading partners is perhaps not what the Chancellor intends.’ This will be especially so as the UK seeks to build new trading relationships with the USA after Brexit. As the BBC article states, ‘The chancellor will be hoping that an international agreement rides to his rescue before the UK tax has to be imposed.’

Articles

Government documents

Questions

  1. How do multinational digital companies avoid profit taxes (corporation tax in the UK)?
  2. Explain how a digital services tax would work.
  3. Why is a digital services tax likely to be set at a much lower rate than a profit tax?
  4. Explain the difference between tax avoidance and tax evasion.
  5. Would it be possible for digital companies to avoid or evade such taxes?
  6. Is there a possibility of a prisoners’ dilemma game in terms of seeking international agreement on such taxes
  7. How does a digital services tax differ from a sales revenue tax

The IMF has just published its six-monthly World Economic Outlook. This provides an assessment of trends in the global economy and gives forecasts for a range of macroeconomic indicators by country, by groups of countries and for the whole world.

This latest report is upbeat for the short term. Global economic growth is expected to be around 3.9% this year and next. This represents 2.3% this year and 2.5% next for advanced countries and 4.8% this year and 4.9% next for emerging and developing countries. For large advanced countries such rates are above potential economic growth rates of around 1.6% and thus represent a rise in the positive output gap or fall in the negative one.

But while the near future for economic growth seems positive, the IMF is less optimistic beyond that for advanced countries, where growth rates are forecast to decline to 2.2% in 2019, 1.7% in 2020 and 1.5% by 2023. Emerging and developing countries, however, are expected to see growth rates of around 5% being maintained.

For most countries, current favorable growth rates will not last. Policymakers should seize this opportunity to bolster growth, make it more durable, and equip their governments better to counter the next downturn.

By comparison with other countries, the UK’s growth prospects look poor. The IMF forecasts that its growth rate will slow from 1.8% in 2017 to 1.6% in 2018 and 1.5% in 2019, eventually rising to around 1.6% by 2023. The short-term figures are lower than in the USA, France and Germany and reflect ‘the anticipated higher barriers to trade and lower foreign direct investment following Brexit’.

The report sounds some alarm bells for the global economy.
The first is a possible growth in trade barriers as a trade war looms between the USA and China and as Russia faces growing trade sanctions. As Christine Lagarde, managing director of the IMF told an audience in Hong Kong:

Governments need to steer clear of protectionism in all its forms. …Remember: the multilateral trade system has transformed our world over the past generation. It helped reduce by half the proportion of the global population living in extreme poverty. It has reduced the cost of living, and has created millions of new jobs with higher wages. …But that system of rules and shared responsibility is now in danger of being torn apart. This would be an inexcusable, collective policy failure. So let us redouble our efforts to reduce trade barriers and resolve disagreements without using exceptional measures.

The second danger is a growth in world government and private debt levels, which at 225% of global GDP are now higher than before the financial crisis of 2007–9. With Trump’s policies of tax cuts and increased government expenditure, the resulting rise in US government debt levels could see some fiscal tightening ahead, which could act as a brake on the world economy. As Maurice Obstfeld , Economic Counsellor and Director of the Research Department, said at the Press Conference launching the latest World Economic Outlook:

Debts throughout the world are very high, and a lot of debts are denominated in dollars. And if dollar funding costs rise, this could be a strain on countries’ sovereign financial institutions.

In China, there has been a massive rise in corporate debt, which may become unsustainable if the Chinese economy slows. Other countries too have seen a surge in private-sector debt. If optimism is replaced by pessimism, there could be a ‘Minsky moment’, where people start to claw down on debt and banks become less generous in lending. This could lead to another crisis and a global recession. A trigger could be rising interest rates, with people finding it hard to service their debts and so cut down on spending.

The third danger is the slow growth in labour productivity combined with aging populations in developed countries. This acts as a brake on growth. The rise in AI and robotics (see the post Rage against the machine) could help to increase potential growth rates, but this could cost jobs in the short term and the benefits could be very unevenly distributed.

This brings us to a final issue and this is the long-term trend to greater inequality, especially in developed economies. Growth has been skewed to the top end of the income distribution. As the April 2017 WEO reported, “technological advances have contributed the most to the recent rise in inequality, but increased financial globalization – and foreign direct investment in particular – has also played a role.”

And the policy of quantitative easing has also tended to benefit the rich, as its main effect has been to push up asset prices, such as share and house prices. Although this has indirectly stimulated the economy, it has mainly benefited asset owners, many of whom have seen their wealth soar. People further down the income scale have seen little or no growth in their real incomes since the financial crisis.

Articles

Report

Data

Questions

  1. For what reasons may the IMF forecasts turn out to be incorrect?
  2. Why are emerging and developing countries likely to experience faster rates of economic growth than advanced countries?
  3. What are meant by a ‘positive output gap’ and a ‘negative output gap’? What are the consequences of each for various macroeconomic indicators?
  4. Explain what is meant by a ‘Minsky moment’. When are such moments likely to occur? Explain why or why not such a moment is likely to occur in the next two or three years?
  5. For every debt owed, someone is owed that debt. So does it matter if global public and/or private debts rise? Explain.
  6. What have been the positive and negative effects of the policy of quantitative easing?
  7. What are the arguments for and against using tariffs and other forms of trade restrictions as a means of boosting a country’s domestic economy?

Would you start a family if you were pessimistic about the future of the economy? Buckles et al (2017) (see link below) believe that fewer of us would do so and, therefore, fertility rates could be used by investors and central banks as an early signal to pick up subtle changes in consumer confidence and overall economic climate.

Their study titled ‘Fertility is a leading economic indicator’ uses ‘live births’ data, sourced from US birth certificates, to explore if there is any association between fertility changes (measured as the rate of change in number of births) and GDP growth. Their results suggest that, in the case of the USA, there is: dips in fertility rates tend to precede by several quarters slowdown in economic activity. As the authors state:

The growth rate of conceptions declines prior to economic downturns and the decline occurs several quarters before recessions begin. Our measure of conceptions is constructed using live births; we present evidence suggesting that our results are indeed driven by changes in conceptions and not by changes in abortion or miscarriage. Conceptions compare well with or even outperform other economic indicators in anticipating recessions.

Conception and GDP Growth Rates (source Buckles et al p33: see below)

Although this is not the first piece of academic writing to claim that fertility has pro-cyclical qualities (see for instance, Adsera (2004, 2011), Adsera and Menendez (2011), Currie and Schwandt (2014) and Chatterjee and Vogle (2016) linked below), it is, to the best of our knowledge, the most recent paper (in terms of data used) to depict this relationship and to explore the suitability of fertility as a macroeconomic indicator to predict recessions.

Economies, after all, are groups of people who participate actively in day-to-day production and consumption activities – as consumers, workers and business leaders. Changes in their environment should affect their expectations about the future.

Are people, however, forward-looking enough to guide their current behaviours by their expectations of future economic outcomes? They may be, according to the findings of this study.

Did you know, for instance, that sales of ties tend to increase in economic downturns, as men buy more ties to show that they are working harder, in fear of losing their job[1]? But this is probably a topic for another blog.

Articles

Academic papers

Questions

  1. Give two reasons why fertility rates may be a good indicator of economic activity.
  2. Give two reasons why fertility rates may NOT be a good indicator of economic activity.
  3. Do a literature search to identify and explain an ‘unorthodox’ macroeconomic indicator of your choice, and how it has been used to track economic activity.

[1] A brief description of other ‘unorthodox’ trackers of economic activity can be found in this Business Insider article: “54 bizarre ways to track the economy”

The Winter Olympics are full on as athletes from all over the world compete against each other, hoping to set new world records, win medals and be known as Olympians. Pyeongchang, the South Korean county that hosts the 2018 Winter games, enjoys a large influx of tourists – estimated at 80,000 people a day. This is certainly an unusually large number of tourists for a region that has a regular winter-time population of no more than 45,000 people.

Having such a high number of visitors to the Winter Olympics, and even more to the larger Summer Olympics, is not an unusual occurrence, however, and it is often mentioned as one of the benefits of being a host to the Olympic Games.

Baade and Matheson (see link below) distinguish between three key benefits of hosting the Olympic Games: “the short-run benefits of tourist spending during the Games; the long-run benefits or the ‘Olympic legacy’, which might include improvements in infrastructure and increased trade, foreign investment, or tourism after the Games; and intangible benefits such as the ‘feel-good effect’ or civic pride”.

On these grounds, a number of studies have been authored, attempting to analyse some or all of these benefits, distinguishing between short-term and long-term effects. Müller (see link below), uses data from the 2014 Oympic Games in Sochi, Russia, to assess the net economic outcome for the host region. He concludes that any short-term economic benefits caused by the investment influx (before and during the games) could not offset the long-term costs, leading to an estimated net loss of $1.2 billion per year.

Zimbalist (2015) and Szymanski (2011) report similar results when analysing data from the London Games (2012) and past major sporting events (Games and FIFA World Cup). Kasimati (2003) points out the significant economic benefits that host regions tend to enjoy for years after hosting the games, but argues that the overall effect depends on a number of factors (including pre-existing infrastructure and location).

The jury is, therefore, still out on what is the overall economic effect of being host to this ancient institution. But I must now dash as women’s hockey is soon to start. “Let everyone shine”.

Articles

For the sake of the games, South Korea needs to show hosting an Olympics can be economically viable CNBC, Yen Nee Lee (15/2/18)
South Korea’s Olympic bet is unlikely to pay off, economics professor says CNBC, Andrew Wong and Andrew Zimbalist (12/2/18)
Going for the Gold: The Economics of the Olympics Journal of Economic Perspectives, Robert A. Baade and Victor A. Matheson (Spring 2016)
After Sochi 2014: Costs and Impacts of Russia’s Olympic Games Eurasian Geography and Economics, Martin Müller (9/4/15)
Circus Maximus: The Economic Gamble Behind Hosting the Olympics and the World Cup The Brookings Institution, Andrew Zimbalist (14/1/15)
About Winning: The Political Economy of Awarding the World Cup and the Olympic Games SAIS Review of International Affairs, Stefan Szymanski (Winter/Spring 2011)
Economic aspects and the Summer Olympics: a review of related research International Journal of Tourism Research, Evangelia Kasimati (4/11/03)
“Let Everyone Shine”: the song for the PyeongChang 2018 Torch Relay unveiled with 200 days to go Olympic Committee (24/7/17)

Video

The Olympic Winter Games PyeongChang 2018 Torch Relay Official Song PyeongChang 2018

Questions

  1. Using supply and demand diagrams, explain whether you would expect hotel room prices to change during the hosting of a major sports event, such as the Winter Olympics.
  2. List three economic (or economics-related) arguments in favour of and against the hosting of the Olympic games. Relate your answer to the empirical evidence presented in the literature.
  3. Why is it so difficult to estimate with accuracy the net economic effect of the Olympic Games?