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 UK consumer and business confidence 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.

Articles

With the UK parliament in Brexit gridlock, the Labour opposition is calling for a general election. Although its policy over Brexit and a second referendum is causing splits in the party, the Labour party is generally agreed that pubic expenditure on health, education and transport infrastructure needs to increase – that there needs to be an end to fiscal austerity. However, to fund extra public expenditure would require an increase in taxes and/or an increase in government borrowing.

One of the arguments against increasing government borrowing is that it will increase public-sector debt. The desire to get public-sector debt down as a percentage of GDP has been central to both the Coalition and Conservative governments’ economic strategy. Austerity policies have been based on this desire.

But, in the annual presidential address to the American Economics Association, former chief economist at the IMF, Olivier Blanchard, criticised this position. He has argued for several years that cutting government deficits may weaken already weak economies and that this may significantly reduce tax revenues and potential national income, thereby harming recovery and doing long-term economic damage. Indeed, the IMF has criticised excessively tight fiscal policies for this reason.

In his presidential address, he expanded the argument to consider whether an increase in government borrowing will necessarily increase the cost of servicing government debt. When the (nominal) interest rate (r) on government borrowing is below the nominal rate of economic growth (gn), (r gn), then even if total debt is not reduced, it is likely that the growth in tax revenues will exceed the growth in the cost of servicing the debt. Debt as a proportion of GDP will fall. The forecast nominal growth rate exceeds the 10-year nominal rate on government bonds by 1.3% in the USA, 2.2% in the UK and 1.8% in the eurozone. In fact, with the exception of a short period in the 1980s, nominal growth (gn) has typically exceeded the nominal interest rate on government borrowing (r) for decades.

When r gn, this then gives scope for increasing government borrowing to fund additional government spending without increasing the debt/GDP ratio. Indeed, if that fiscal expansion increases both actual and potential income, then growth over time could increase, giving even more scope for public investment.

But, of course, that scope is not unlimited.

Articles

Presidential Address

Questions

  1. What do you understand by ‘fiscal illusion’?
  2. What is the justification for reducing government debt as a proportion of GDP?
  3. What are the arguments against reducing government debt as a proportion of GDP?
  4. Explain the significance of the relationship between r and gn for fiscal policy and the levels of government debt, government borrowing and the government debt/GDP ratio.
  5. Under what circumstances would a rise in the budget deficit not lead to a rise in government debt as a proportion of GDP?
  6. Does Blanchard’s analysis suggest that a combination of both loose monetary policy and loose fiscal policy is desirable?
  7. Under Blanchard’s analysis, what would limit the amount that governments should increase spending?

Back in October, we examined the rise in oil prices. We said that, ‘With Brent crude currently at around $85 per barrel, some commentators are predicting the price could reach $100. At the beginning of the year, the price was $67 per barrel; in June last year it was $44. In January 2016, it reached a low of $26.’ In that blog we looked at the causes on both the demand and supply sides of the oil market. On the demand side, the world economy had been growing relatively strongly. On the supply side there had been increasing constraints, such as sanctions on Iran, the turmoil in Venezuela and the failure of shale oil output to expand as much as had been anticipated.

But what a difference a few weeks can make!

Brent crude prices have fallen from $86 per barrel in early October to just over $50 by the end of the year – a fall of 41 per cent. (Click here for a PowerPoint of the chart.) Explanations can again be found on both the demand and supply sides.

On the demand side, global growth is falling and there is concern about a possible recession (see the blog: Is the USA heading for recession?). The Bloomberg article below reports that all three main agencies concerned with the oil market – the U.S. Energy Information Administration, the Paris-based International Energy Agency and OPEC – have trimmed their oil demand growth forecasts for 2019. With lower expected demand, oil companies are beginning to run down stocks and thus require to purchase less crude oil.

Fracking (Source: US Bureau of Land Management Environmental Assessment, public domain image)

On the supply side, US shale output has grown rapidly in recent weeks and US output has now reached a record level of 11.7 million barrels per day (mbpd), up from 10.0 mbpd in January 2018, 8.8 mbpd in January 2017 and 5.4 mbpd in January 2010. The USA is now the world’s biggest oil producer, with Russia producing around 11.4 mpbd and Saudi Arabia around 11.1 mpbd.

Total world supply by the end of 2018 of around 102 mbpd is some 2.5 mbpd higher than expected at the beginning of 2018 and around 0.5 mbpd greater than consumption at current prices (the remainder going into storage).

So will oil prices continue to fall? Most analysts expect them to rise somewhat in the near future. Markets may have overcorrected to the gloomy news about global growth. On the supply side, global oil production fell in December by 0.53 mbpd. In addition OPEC and Russia have signed an accord to reduce their joint production by 1.2 mbpd starting this month (January). What is more, US sanctions on Iran have continued to curb its oil exports.

But whatever happens to global growth and oil production, the future price will continue to reflect demand and supply. The difficulty for forecasters is in predicting just what the levels of demand and supply will be in these uncertain times.

Articles

Video

Data

Questions

  1. Identify the factors on both the demand and supply sides of the oil market that have affected prices recently.
  2. What determines the amount that changes in these factors affect the oil price?
  3. What determines (a) the price elasticity of demand for oil; (b) the income elasticity of demand for oil; (c) the price elasticity of supply of oil?
  4. Why might oil prices overshoot the equilibrium price that reflects changed demand and supply conditions?
  5. Use demand and supply diagrams to illustrate (a) the destabilising effects that speculation could have on oil prices; (b) a stabilising effect.
  6. Is the holding or large stocks of oil likely to stabilise or destabilise oil prices? Explain.
  7. What will determine the likely success of the joint OPEC/Russian policy to support oil prices by reducing supply?

Workers in the UK and USA work much longer hours per year than those in France and Germany. This has partly to do with the number of days paid holiday per year, partly with the number of hours worked per day and partly with the number of days worked per week.

According to the latest OECD figures, in 2017 average hours worked per year ranged from 2257 in Mexico (the OECD’s highest) to 1780 in the USA, 1710 in Japan, 1681 in the UK, 1514 in France, 1408 in Denmark and 1356 in Germany (the OECD’s lowest). Annual working hours have been falling in most countries across the decades, as the chart shows. However, in most countries the process has slowed in recent years and in the UK, the USA and France working hours have begun to rise. (Click here for a PowerPoint of the chart.)

But why do working hours differ so much from country to country? How do they relate to productivity? How do they relate to human happiness and welfare more generally?

Causes of the differences

There are various reasons for the differences in hours worked between countries.

In a situation where individual workers can choose how many hours to work, they have to decide the best trade off for them between income and leisure. As wages rise over time, there will be substitution and income effects of these extra hourly wages. Higher wages make work more valuable in terms of what people can buy from an extra hour’s work. There is thus an incentive to substitute work for leisure and hence work longer. This is the substitution effect. On the other hand, higher wages allow people to work fewer hours for a given income. This is the income effect.

As incomes rise, generally the substitution effect will tend to decline relative to the income effect. This is because of the diminishing marginal utility of income. Richer people will tend to value a given rise in income less than poorer people and therefore will value the income from extra work less than poorer people. Richer people will prefer to work fewer hours than poorer people. Generally workers in richer OECD countries work fewer hours than those in poorer OECD countries.

But this does not explain why people in the USA, Canada, Japan and the UK work longer hours than people in Germany, Denmark, Norway, The Netherlands and France.

One possible explanation for these differences is the role of trade unions. These tend to be stronger in countries with lower working hours. Reducing the working week or obtaining longer holidays is one of the key objectives of unions.

Another is income distribution. The USA, despite its high average (mean) income, has a relatively unequal distribution of income compared with Germany or France. The post-tax-and-benefits Gini coefficient in the USA is around 0.39, whereas in Germany it is 0.29, meaning that Germany has a more equal distribution of disposable income than the USA. In fact, rises in real incomes in the USA over the past 10 years have gone almost exclusively to the top 10 per cent of earners, leaving the median income little changed. In fact median household income only rose above its 2007 (pre-recession) level in 2016.

Social and cultural explanations may also be important. People in countries with higher working hours relative to hourly wages may put a greater store on consumption relative to leisure. The desire to shop may be very strong. The ‘Anglo-Saxon’ economic model pursued by right-of-centre governments in English-speaking countries, such as the USA, Canada, Australia and the UK puts emphasis on low taxes, low regulation, low public expenditure and self-advancement. Such a model encourages a more individualistic approach to work, with more emphasis on earning money.

Then there is the attitude to hours worked generally. There is a saying that in the UK the last one to leave the office is seen as the hardest working, whereas in Germany the last one to leave is seen as the least efficient. Social pressures, from colleagues, family, friends and society more generally can have a major effect on people’s choices between work and leisure.

Productivity

Productivity, in terms of output per hour worked, tends to decline as workers work longer hours. People get tired and possibly bored and demotivated towards the end of a long day or week. If workers are paid by the output they produce and if productivity declines towards the end of the day, then the hourly wage would fall as the day progresses. This would act as a disincentive to work long hours. In practice, most workers are normally paid a constant rate per hour for normal-time working. For overtime, they may even be paid a higher rate, despite their likely lower productivity. This encourages them to work longer hours than if they were paid according to their marginal productivity.

Linking pay more closely to productivity could encourage people to opt for fewer hours (if they had the choice). Indeed some companies are now encouraging workers to choose their hours – which may mean fewer hours as people seek a better work–life balance. (See the BBC article below about PwC’s employment strategy.) Alternatively, some other employers adopt the system of giving workers a set amount of work to do and then they can leave work when it is finished. This acts as an incentive to work more efficiently.

It is interesting that countries where workers work more hours per year tend to have a lower output per hour worked relative to output per worker than countries where workers work fewer hours. This is illustrated in the chart opposite. The USA, with its longer working hours, has higher output per person employed than France and Germany but very similar output per hour worked.

Hours and happiness

So are people who choose to work longer hours and take home more money likely to be happier than those who choose to work fewer hours and take home less money? If people were rational and had perfect knowledge, then they would choose the balance between work and leisure that best suited them.

In practice, labour markets are highly imperfect. People often do not have choices about the amount they work; they work the hours they are told. Even if they do have a choice, they are unlikely to have perfect knowledge about the impact of long hours on their health and happiness over their lifetime. They may not even be good judges of the shorter-term effects of more work and more pay. They may believe that more money will buy them more happiness only to find soon afterwards that they are wrong.

Articles

Data

Questions

  1. What factors are likely to encourage workers to work longer hours?
  2. Give some examples of jobs where workers have flexibility in the amount of hours they work per week and jobs where the working week is of a fixed length.
  3. For what reasons are annual working hours longer in the USA than in Germany?
  4. Would it be in employers’ interests if the government legislated so as to reduce the maximum permitted working week? Explain.
  5. What is meant by ‘efficiency wages’? How relevant is the concept to the issue of the average number of hours worked per year from country to country?
  6. Explain why people in poorer countries tend to work more hours per year than people in richer countries.
  7. If workers’ wages equalled their marginal revenue product, why might some workers choose to work more and others choose to work less (assuming they had a choice)?
  8. Are jobs in the gig economy and zero-hour contract jobs in the interests of workers?
  9. Is South Korea wise to cut its work limit from 68 hours a week to 52?

It is impossible to make both precise and accurate forecasts of a country’s rate of economic growth, even a year ahead. And the same goes for other macroeconomic variables, such as the rate of unemployment or the balance of trade. The reason is that there are so many determinants of these variables, such as political decisions or events, which themselves are unpredictable. Economics examines the effects of human interactions – it is a social science, not a natural science. And human behaviour is hard to forecast.

Leading indicators

Nevertheless, economists do make forecasts. These are best estimates, taking into account a number of determinants that can be currently measured, such as tax or interest rate changes. These determinants, or ‘leading indicators’, have been found to be related to future outcomes. For example, surveys of consumer and business confidence give a good indication of future consumer expenditure and investment – key components of GDP.

Leading indicators do not have to be directly causal. They could, instead, be a symptom of underlying changes that are themselves likely to affect the economy in the future. For example, changes in stock market prices may reflect changes in confidence or changes in liquidity. It is these changes that are likely to have a direct or indirect causal effect on future output, employment, prices, etc.

Macroeconomic models show the relationships between variables. They show how changes in one variable (e.g. increased investment) affect other variables (e.g. real GDP or productivity). So when an indicator changes, such as a rise in interest rates, economists use these models to estimate the likely effect, assuming other things remain constant (ceteris paribus). The problem is that other things don’t remain constant. The economy is buffeted around by a huge range of events that can affect the outcome of the change in the indicator or the variable(s) it reflects.

Forecasting can never therefore be 100% accurate (except by chance). Nevertheless, by carefully studying leading indicators, economists can get a good idea of the likely course of the economy.

Leading indicators of the US economy

At the start of 2019, several leading indicators are suggesting the US economy is likely to slow and might even go into recession. The following are some of the main examples.

Political events. This is the most obvious leading indicator. If decisions are made that are likely to have an adverse effect on growth, a recession may follow. For example, decisions in the UK Parliament over Brexit will directly impact on UK growth.

As far as the USA is concerned, President Trump’s decision to put tariffs on steel and aluminium imports from a range of countries, including China, the EU and Canada, led these countries to retaliate with tariffs on US imports. A tariff war has a negative effect on growth. It is a negative sum game. Of course, there may be a settlement, with countries agreeing to reduce or eliminate these new tariffs, but the danger is that the trade war may continue long enough to do serious damage to global economic growth.

But just how damaging it is likely to be is impossible to predict. That depends on future political decisions, not just those of the recent past. Will there be a global rise in protectionism or will countries pull back from such a destructive scenario? On 29 December, President Trump tweeted, ‘Just had a long and very good call with President Xi of China. Deal is moving along very well. If made, it will be very comprehensive, covering all subjects, areas and points of dispute. Big progress being made!’ China said that it was willing to work with the USA over reaching a consensus on trade.

Rises in interest rates. If these are in response to a situation of excess demand, they can be seen as a means of bringing inflation down to the target level or of closing a positive output gap, where real national income is above its potential level. They would not signify an impending recession. But many commentators have interpreted rises in interest rates in the USA as being different from this.

The Fed is keen to raise interest rates above the historic low rates that were seen as an ’emergency’ response to the financial crisis of 2007–8. It is also keen to reverse the policy of quantitative easing and has begun what might be described as ‘quantitative tightening’: not buying new bonds when existing ones that it purchased during rounds of QE mature. It refers to this interest rate and money supply policy as ‘policy normalization‘. The Fed maintains that such policy is ‘consistent with sustained expansion of economic activity, strong labor market conditions, and inflation near the Committee’s symmetric 2 percent objective over the medium term’.

However, many commentators, including President Trump, have accused the Fed of going too fast in this process and of excessively dampening the economy. It has already raised the Federal Funds Rate nine times by 0.25 percentage points each time since December 2015 (click here for a PowerPoint file of the chart). What is more, announcing that the policy will continue makes such announcements themselves a leading indicator of future rises in interest rates, which are a leading indicator of subsequent effects on aggregate demand. The Fed has stated that it expects to make two more 0.25 percentage point rises during 2019.

Surveys of consumer and business confidence. These are some of the most significant leading indicators as consumer confidence affects consumer spending and business confidence affects investment. According to the Duke CFO Global Business Outlook, an influential survey of Chief Financial Officers, ‘Nearly half (48.6 per cent) of US CFOs believe that the US will be in recession by the end of 2019, and 82 per cent believe that a recession will have begun by the end of 2020’. Such surveys can become self-fulfilling, as a reported decline in confidence can itself undermine confidence as both firms and consumers ‘catch’ the mood of pessimism.

Stock market volatility. When stock markets exhibit large falls and rises, this is often a symptom of uncertainty; and uncertainty can undermine investment. Stock market volatility can thus be a leading indicator of an impending recession. One indicator of such volatility is the VIX index. This is a measure of ’30-day expected volatility of the US stock market, derived from real-time, mid-quote prices of S&P 500® Index (SPXSM) call and put options. On a global basis, it is one of the most recognized measures of volatility – widely reported by financial media and closely followed by a variety of market participants as a daily market indicator.’ The higher the index, the greater the volatility. Since 2004, it has averaged 18.4; from 17 to 28 December 2018, it averaged 28.8. From 13 to 24 December, the DOW Jones Industrial Average share index fell by 11.4 per cent, only to rise by 6.2 per cent by 27 December. On 26 December, the S&P 500 index rallied 5 per cent, its best gain since March 2009.

Not all cases of market volatility, however, signify an impending recession, but high levels of volatility are one more sign of investor nervousness.

Oil prices. When oil prices fall, this can be explained by changes on the demand and/or supply side of the oil market. Oil prices have fallen significantly over the past two months. Until October 2018, oil prices had been rising, with Brent Crude reaching $86 per barrel by early October. By the end of the year the price had fallen to just over $50 per barrel – a fall of 41 per cent. (Click here for a PowerPoint file of the chart.) Part of the explanation is a rise in supply, with shale oil production increasing and also increased output from Russia and Saudi Arabia, despite a commitment by the two countries to reduce supply. But the main reason is a fall in demand. This reflects both a fall in current demand and in anticipated future demand, with fears of oversupply causing oil companies to run down stocks.

Falling oil prices resulting from falling demand are thus an indicator of lack of confidence in the growth of future demand – a leading indicator of a slowing economy.

The yield curve. This depicts the yields on government debt with different lengths to maturity at a given point in time. Generally, the curve slopes upwards, showing higher rates of return on bonds with longer to maturity. This is illustrated by the blue line in the chart. (Click here for a PowerPoint file of the chart.) This is as you would expect, with people requiring a higher rate of return on long-term lending, where there is normally greater uncertainty. But, as the Bloomberg article, ‘Don’t take your eyes off the yield curve‘ states:

Occasionally, the curve flips, with yields on short-term debt exceeding those on longer bonds. That’s normally a sign investors believe economic growth will slow and interest rates will eventually fall. Research by the Federal Reserve Bank of San Francisco has shown that an inversion has preceded every US recession for the past 60 years.
 
The US economy is 37 quarters into what may prove to be its longest expansion on record. Analysts surveyed by Bloomberg expect gross domestic product growth to come in at 2.9 percent this year, up from 2.2 percent last year. Wages are rising as unfilled vacancies hover near all-time highs.
 
With times this good, the biggest betting game on Wall Street is when they’ll go bad. Barclays Plc, Goldman Sachs Group Inc., and other banks are predicting inversion will happen sometime in 2019. The conventional wisdom: Afterward it’s only a matter of time – anywhere from 6 to 24 months – before a recession starts.

As you can see from the chart, the yield curve on 24 December 2018 was still slightly upward sloping (expect between 6-month and 1-year bonds) – but possibly ready to ‘flip’.

However, despite the power of an ‘inverted’ yield in predicting previous recessions, it may be less reliable now. The Fed, as we saw above, has already signalled that it expects to increase short-term rates in 2019, probably at least twice. That alone could make the yield curve flatter or even downward sloping. Nevertheless, it is still generally thought that a downward sloping yield curve would signal belief in a likely slowdown, if not outright recession.

So, is the USA heading for recession?

The trouble with indicators is that they suggest what is likely – not what will definitely happen. Governments and central banks are powerful agents. If they believed that a recession was likely, then fiscal and monetary policy could be adjusted. For example, the Fed could halt its interest rate rises and quantitative tightening, or even reverse them. Also, worries about protectionism may subside if the USA strikes new trade deals with various countries, as it did with Canada and Mexico in USMCA.

Articles

Surveys and Data

Questions

  1. Define the term ‘recession’.
  2. Are periods of above-trend expansion necessarily followed by a recession?
  3. Give some examples of leading indicators other than those given above and discuss their likely reliability in predicting a recession.
  4. Find out what has been happening to confidence levels in the EU over the past 12 months. Does this provide evidence of an impending recession in the EU?
  5. For what reasons may there be lags between a change in an indicator and a change in the variables for which it is an indicator?
  6. Why has the shape of the yield curve previously been a good predictor of the future course of the economy? Is it likely to be at present?
  7. What is the relationship between interest rates, government bond prices (‘Treasuries’ in the USA) and the yield on such bonds?