Over the past three months oil prices have been falling. From the beginning of September to the end of November Brent Crude has fallen by 30.8%: from $101.2 to a four-year low of $70.0 per barrel (see chart below: click here for a PowerPoint). The fall in price has been the result of changes in demand and supply.
As the eurozone, Japan, South America and other parts of the world have struggled to recover, so the demand for oil has been depressed. But supply has continued to expand as the USA and Canada have increased shale oil production through fracking. As far as OPEC is concerned, rather than cutting production, it decided at a meeting on 27 November to maintain the current target of 30 million barrels a day.
The videos and articles linked below look at these demand and supply factors and what is likely to happen to oil prices over the coming months.
They also look at the winners and losers. Although falling prices are likely in general to benefit oil importing countries and harm oil exporting ones, it is not as simple as that. The lower prices could help boost recovery and that could help to halt the oil price fall and be of benefit to the oil exporting countries. But if prices stay low for long enough, this could lower inflation and even cause deflation (in the sense of falling prices) in many countries. This, in turn, could dampen demand (see the blog post, Deflation danger). This is a particular problem in Japan and the eurozone. Major oil importing developing countries, such as China and India, however, should see a boost to growth from the lower oil prices.
Some oil exporting countries will be harder hit than others. Russia, in particular, has been badly affected, especially as it is also suffering from the economic sanctions imposed by Western governments in response to the situation in Ukraine. The rouble has fallen by some 32% this year against the US dollar and nearly 23% in the past three months alone.
Then there are the environmental effects. Cheaper oil puts less pressure on companies and governments to invest in renewable sources of energy. And then there are the direct effects on the environment of fracking itself – something increasingly being debated in the UK as well as in the USA and Canada.
Use a diagram to illustrate the effects of changes in the demand and supply of oil on oil prices.
How does the price elasticity of demand and supply of oil affect the magnitude of these price changes?
Explain whether (a) the demand for and (b) the supply of oil are likely to be relatively elastic or relatively inelastic? How are these elasticities likely to change over time?
Distinguish between the spot price and forward prices of oil? If the three-month forward price is below the spot price, what are the implications of this?
Analyse who gains and who loses from the recent price falls.
What are the effects of a falling rouble on the Russian economy?
What are likely to be the effects of further falls in oil prices on the eurozone economy?
Much of the east coast of England is subject to tidal flooding. One such area is the coastline around the Wash, the huge bay between Norfolk and Lincolnshire. Most of the vulnerable shorelines are protected by sea defences, usually in the form of concrete walls or earth embankments, traditionally paid for by the government. But part of the Norfolk shoreline is protected by shingle banks, which require annual maintenance.
Full government funding for maintaining these banks ended in 2013. According to new government rules, only projects that provide at least £8 of benefits for each £1 spent would qualify for such funding to continue. The area under question on the Norfolk cost of the Wash does not qualify.
Between 2013 and 2015 the work on the shingle banks is being paid for by the local council charging levies. After that, the plan is for a partnership-funding approach, where the government will make a (small) contribution as long as the bulk of the funding comes from the local community. This will involve setting up a ‘community interest company’, which will seek voluntary contributions from local residents, landowners and businesses.
Sea defences are a public good, in that it is difficult to exclude people benefiting who choose not to pay. In other words, there is a ‘free rider’ problem. However, in the case of the Wash shoreline in question, one borough councillor, Brian Long, argues that it might be possible to maintain the flood defences to protect those who do contribute while ignoring those who do not.
Not surprisingly, many residents and businesses argue that the government ought to fund the defences and, if it does have to be financed locally, then everyone should be required to pay their fair share.
Managing our coastlineBorough Council of King’s Lynn and West Norfolk, Environment Agency
Questions
What are the two main features of a public good? Are sea defences a pure public good?
Is there a moral hazard if people choose to live in a coastal area that would be subject to flooding without sea defences?
Who is the ‘public’ in the case of sea defences? Is it the whole country, or the local authority or just all those being protected by the defences?
What are the problems with relying on voluntary contributions to fund, or partly fund, sea defences? How could the free-rider problem be minimised in such a funding model?
Discuss the possible interpretations of ‘equity’ when funding sea defences.
If ‘flood defences could be built or maintained to protect those who do contribute while ignoring those who do not’, does this mean that such defences are not a public good?
Find out how sea defences are funded in The Netherlands. Should such a funding model be adopted in the UK?
How much does the UK spend on welfare? This is a highly charged political question, with some arguing that benefit claimants are putting great demands on ‘hard-working tax payers’. According to information being sent by the government to all 24 million income tax payers in the UK, the figure of £168bn being spent on welfare is around 24.5% of public spending. But what is included in the total? Before you read on, try writing down the categories of government expenditure included under the heading ‘welfare’.
The heading does not include spending on certain parts of the ‘welfare state’, such as health and education. These are services, the production of which contributes to GDP. The category ‘welfare’ does not include expenditure on produced services, but rather transfer payments. The way the government is using the term, it does not include state pensions either, which account for 11.6% of public expenditure. So does the 24.5% largely consist of payments to the unemployed? The answer is no.
The category ‘welfare’ as used by the government includes the following elements. The percentages are of total managed expenditure (i.e. government spending).
•
Public service pensions, paid to retired public-sector employees, such as teachers, police officers, doctors and nurses
(2.6%)
•
Other support for the elderly, including pension credit, winter fuel allowance, bus passes, etc.
(1.5%)
•
Sickness and disability benefits, including long-term care for the elderly, sick and disabled
(6.6%)
•
Support for families and children, such as child benefit and child tax credits
(3.4%)
•
Social exclusion, including income support and housing benefit
(7.8%)
•
Unemployment benefits, including Job Seekers Allowance
(0.7%)
•
Other
(1.9%)
Lumping all these together under a single heading ‘welfare’ can be highly misleading, as many people have strongly held preconceptions about who gets welfare. In fact the term is used pejoratively by many who resent their taxes being given to those who do not work.
But, as you can see from the figures, only a small proportion goes to the unemployed, the majority of whom (around 65%) are unemployed for less than a year as they move between jobs (see). The bulk of benefits goes to children, the retired and the working poor.
Another preconception is that much of welfare spending goes to fraudulent claimants. But, as the article by Professor Hills states:
Just 0.7% of all benefits was over-paid as the result of fraud, less than the amount underpaid as a result of official error. For the main benefit for unemployed people, Jobseeker’s Allowance, estimated fraud was 2.9%, or an annual total of £150million.
It is also important to consider people’s life cycle. The same people receive benefits (via their parents or guardians) as children, pay taxes when they work and receive benefits when they retire or fall sick. Thus you might be a net contributor to public finances at one time and a net beneficiary at another. For example, the majority of pensioners were net contributors when they were younger and are now mainly net beneficiaries. Many unemployed people who rely on benefits now were net contributors when they had a job.
The message is that you should be careful when interpreting statistics, even if these statistics are factually accurate. How figures are grouped together and the labels put on them can give a totally misleading impression. And politicians are always keen to ‘spin’ statistics to their advantage – whether in government or opposition.
What benefits do you receive? How would you expect this to change over your lifetime?
What are the arguments for (a) reducing and (b) increasing welfare payments. In each case, under which categories of welfare would you decrease or increase the level of benefits?
Referring to Table 5.2 in the PESA data below (the table used for the government’s calculations), which of the categories would be classified as expenditure on goods and services and which as transfer payments?
Assess the arguments of the IFS for the reclassification of the categories of ‘welfare’ payments.
Referring to the pie chart above, also in the BBC video and articles and Table 5.2 in the PESA data, assess the arguments about the size of the UK’s contributions to the EU budget.
In his 1971 book, Income Distribution, Jan Pen, a Dutch economist, gave a graphic illustration of inequality in the UK. He described a parade of people marching by. They represent the whole population and the parade takes exactly one hour to pass by. The height of each person represents his or her income. People of average height are the people with average incomes – the observer is of average height. The parade starts with the people on the lowest incomes (the dwarfs), and finishes with those on the highest incomes (the giants).
Because income distribution is unequal, there are many tiny people. Indeed, for the first few minutes of the parade, the marchers are so small they can barely be seen. Even after half an hour, when people on median income pass by, they are barely waist high to the observer.
The height is growing with tantalising slowness, and forty-five minutes have gone by before we see people of our own size arriving. To be somewhat more exact: about twelve minutes before the end the average income recipients pass by.
In the final minutes, giants march past and then in the final seconds:
the scene is dominated by colossal figures: people like tower flats. Most of them prove to be businessmen, managers of large firms and holders of many directorships and also film stars and a few members of the Royal Family.
The rear of the parade is brought up by a few participants who are measured in miles. Indeed they are figures whose height we cannot even estimate: their heads disappear into the clouds and probably they themselves do not even know how tall they are.
Pen’s description could be applied to most countries – some with even more dwarfs and even fewer but taller giants. Generally, over the 43 years since the book was published, countries have become less equal: the giants have become taller and the dwarfs have become smaller.
The 2011 Economist article, linked below, uses changes in Gini coefficients to illustrate the rise in income inequality. A Gini coefficient shows the area between the Lorenz curve and the 45° line. The figure will be between 0 and 1 (or 0% and 100%). a figure of 0 shows total equality; a figure of 1 shows a situation of total inequality, where one person earns all the nation’s income. The higher the figure, the greater the inequality.
The chart opposite shows changes in the Gini coefficient in the UK (see Table 27 in the ONS link below for an Excel file of the chart). As this chart and the blog post Rich and poor in the UK show, inequality rose rapidly during the years of the 1979–91 Thatcher government, and especially in the years 1982–90. This was associated with cuts in the top rate of income tax and business deregulation. It fell in the recession of the early 1990s as the rich were affected more than the poor, but rose with the recovery of the mid- to late 1990s. It fell again in the early 2000s as tax credits helped the poor. It fell again following the financial crisis as, once more, the rich were affected proportionately more than the poor.
The most up-to-date international data for OECD countries can be found on the OECD’s StatExtracts site (see chart opposite: click here for a PowerPoint). The most unequal developed county is the USA, with a Gini coefficient of 0.389 in 2012 (see The end of the American dream?), and US inequality is rising. Today, the top 1% of the US population earns some 24% of national income. This compares with just 9% of national income in 1976.
Many developing countries are even less equal. Turkey has a Gini coefficient of 0.412 and Mexico of 0.482. The figure for South Africa is over 0.6.
When it comes to wealth, distribution is even less equal. The infographic, linked below, illustrates the position today in the USA. It divides the country into 100 equal-sized groups and shows that the top 1% of the population has over 40% of the nation’s wealth, whereas the bottom 80% has only 7%.
So is this inequality of income and wealth desirable? Differences in wages and salaries provide an incentive for people to work harder or more effectively and to gain better qualifications. The possibility of increased wealth provides an incentive for people to invest.
But are the extreme differences in wealth and income found in many countries today necessary to incentivise people to work, train and invest? Could sufficient incentives exist in more equal societies? Are inequalities in part, or even largely, the result of market imperfections and especially of economic power, where those with power and influence are able to use it to increase their own incomes and wealth?
Could it even be the case that excessive inequality actually reduces growth? Are the huge giants that exist today accumulating too much financial wealth and creating too little productive potential? Are they spending too little and thus dampening aggregate demand? These arguments are considered in some of the articles below. Perhaps, by paying a living wage to the ‘tiny’ people on low incomes, productivity could be improved and demand could be stimulated.
Distinguish between income and wealth. Is each one a stock or a flow?
Explain how (a) a Lorenz curve and (b) a Gini coefficient are derived.
What other means are there of measuring inequality of income and wealth other than using Gini coefficients (and giants and dwarfs!)?
Why has inequality been rising in many countries over the years?
How do (a) periods of rapid economic growth and (b) recessions affect income distribution?
Define ‘efficiency wages’. How might an increase in wages to people on low incomes result in increased productivity?
What is the relationship between the degree of inequality and household debt? What implications might this have for long-term economic growth and future financial crises? Is inequality the ‘enemy of growth’?
An investigation by the International Consortium of Investigative Journalists has revealed how more than 1000 businesses from 340 major companies from around the world have used Luxembourg as a base for avoiding huge amounts of tax. Many of the companies are household names, such as Ikea, FedEx, Apple, Pepsi, Coca Cola, Dyson, Amazon, Fiat, Google, Accenture, Burberry, Procter & Gamble, Heinz, JP Morgan, Caterpillar, Deutsche Bank and Starbucks. Through complicated systems of ‘advanced tax agreements’ (ATAs), negotiated with the Luxembourg authorities via accountants PricewaterhouseCoopers (PwC), companies have used various methods of avoiding tax.
Although such measures are legal, they have denied other countries vast amounts of tax revenues on sales generated in their own countries. Instead, the much reduced tax bills have been paid to Luxembourg. The result is that this tiny country, with a population of just 550,000, has, according to the IMF, the highest (nominal) GDP per head in the world (estimated to be $116,752 in 2014).
So what methods do Luxembourg and these multinational companies use to reduce the companies’ tax bills? There are three main methods. All involve having a subsidiary based in Luxembourg: often little more than a small office with one employee, a telephone and a bank account. All involve varieties of transfer pricing: setting prices that the company charges itself in transactions between a subsidiary in Luxembourg and divisions in other countrries.
The first method is the use of internal loans. Companies lend money to themselves, say in the UK, from Luxembourg at high interest rates. The loan interest can be offset against profit in the UK, reducing tax liability to the UK tax authorities. But the interest earned by the Luxembourg subsidiary incurs very low taxes. Profits are thus effectively transferred from the UK to Luxembourg and a much lower tax bill is incurred.
The second involves royalty payments for the use of the company’s brands. These are owned by the Luxembourg subsidiary and the overseas divisions pay the Luxembourg subsidiary large sums for using the logos, designs and brand names. Thus, again, profits are transferred to Luxembourg, where there is a generous tax exemption.
The third involves generous allowances in Luxembourg for losses in the value of investments, even without the company having first to sell the investments. These losses can be offset against future profits, again reducing tax liability. By transferring losses made elsewhere to Luxembourg, again usually by some form of transfer pricing, these can be used to reduce the already small tax bill in Luxembourg even further.
Tax loopholes offered by tax havens, such as Luxembourg, the Cayman Islands and the Channel Islands, are denying exchequers around the world vast sums. Not surprisingly, countries, especially those with large deficits, are concerned to address the issue of tax avoidance by multinationals. This is one item on the agenda of the G20 meeting in Brisbane from the 12 to 16 November 2014.
The problem, however, is that, with countries seeking to attract multinational investment and to gain tax revenues from them, there is an incentive to reduce corporate tax rates. Getting any binding agreement on tax harmonisation, and creating an essentially global single market, is likely, therefore, to prove virtually impossible.
Over the past three months oil prices have been falling. From the beginning of September to the end of November Brent Crude has fallen by 30.8%: from $101.2 to a four-year low of $70.0 per barrel (see chart below: click here for a PowerPoint). The fall in price has been the result of changes in demand and supply. 
As far as OPEC is concerned, rather than cutting production, it decided at a meeting on 27 November to maintain the current target of 30 million barrels a day.
Major oil importing developing countries, such as China and India, however, should see a boost to growth from the lower oil prices.
Oil price at four-year low as Opec meets BBC News, Mark Lobel (27/11/14)
