Tag: income distribution

In 2014, 19% of jobs in London and 23% of jobs outside London paid less than the living wage. This is according to figures just published by the Office for National Statistics. The figures compare with 17% and 22% respectively in 2013. The problem is that while the living wage rises with the cost of living, median wages have not kept pace with prices: in other words, in real terms median wages have fallen.

The living wage has been calculated annually since 2003 for London by the London Mayor’s Office and since 2011 for the rest of the UK by the Centre for Research in Social Policy (CRSP) at Loughborough University for the Living Wage Foundation.

According to the London Mayor’s Office:

The London Living Wage is an hourly rate of pay, calculated according to a combination of the costs of living in London and 60% of the median wage. This gives the wage rate needed to give a worker in London enough to provide their family with the essentials of life, including a cushion against unforeseen events. Unlike the compulsory national minimum wage, the London Living Wage is a voluntary commitment made by employers, who can become accredited with the Living Wage Foundation.

As the Chart 1 illustrates, the living wage is above the National Minimum Wage. Since November 2014, the living wage in London has been £9.15 in London and £7.85 in the rest of the UK. It is due to be uprated at the beginning of November 2015. From 1 October 2014 to 30 September 2015, the National Minimum Wage (for people aged 21 and over) was £6.50. It rose to £6.70 on 1 October 2015.

Note that the (voluntary) living wage is different from the compulsory ‘National Living Wage’ announced by the Chancellor in his July 2015 Budget, which will come into effect in April 2016 as a top-up to the National Minimum Wage (NLW) for those aged 25 and over. This will be only 50p above the National Minimum Wage and thus considerably below the living wage, although the Chancellor has pledged to increase the NLW to 60% of median wage rates for those aged 25 and over by 2020. According to the Office for Budget Responsibility, “the NLW will rise from £7.20 in April 2016 (equivalent to around 55 per cent of estimated median hourly earnings for employees aged 25 and over) to around £9.35 in April 2020 (reaching 60 per cent of expected median hourly earnings for that group) in steps that imply the rise relative to median hourly earnings is a straight line.”

The percentage of people being paid below the living wage varies by occupation, location of jobs (see map in Chart 2 – click to enlarge), sex and age and whether the job is full or part time. For example, in accommodation and food services, in retail and in sales and customer services, more than half the jobs paid less than the living wage. A greater percentage of women than men were paid below the living wage (29% and 18% respectively outside London). As far as young people are concerned, 48% of 18–24 year olds were paid less than the living wage in London and 58% outside London (see Chart 3). In London 45% of part-time jobs paid less than the living wage; in the rest of the UK the figure was 43%.

As The Guardian article linked below reports:

A spokesman for the Living Wage Foundation, which sets the figure each year, said despite ‘significant progress’ in many sectors, more jobs than ever were below the voluntary rates.

“These figures demonstrate that while the economy may be recovering as a whole, there is a real problem with ensuring everyone benefits, and low pay is still prevalent in Britain today,” he said.

The following articles look at the evidence presented by the ONS and examine the incidence of low pay in the UK.

Articles

More jobs paying below living wage BBC News (12/10/15)
A fifth of UK jobs pay less than living wage – ONS Financial Times (12/10/15)
The proportion of workers not being paid the living wage is rising Independent, Jon Stone (12/10/15)
Almost 30 per cent of women are paid below the living wage Independent, Jon Stone (12/10/15)
More UK jobs fail to pay a living wage The Guardian, Hilary Osborne and Damien Gayle (12/10/15)
Six million jobs pay below the living wage Full Fact, Laura O’Brien (19/10/15)

Data and Reports

Estimates of employee jobs paid less than the living wage in London and other parts of the UK ONS (12/10/15)
Annual Survey of Hours and Earnings ONS
Living wage rates: the calculation Living Wage Foundation
National Minimum Wage rates GOV.UK

Questions

  1. By referring to the Living Wage Foundation site, explain how the living wage is calculated. If you were defining the living wage, would you define it in this way? Explain.
  2. Distinguish between low pay and poverty. Does pay give a good indication of poverty?
  3. For what reasons has the number of jobs paying below the living wage increased? Does marginal productivty theory provide an explanation?
  4. Is it best to base statutory minimum wages on median earnings, mean earnings or the cost of living? Explain.
  5. If 6 million jobs pay below the living wage, does this mean that 6 million people, more than 6 million people or fewer than 6 million people receive average hourly wages below the living wage? Explain.
  6. For what reasons might firms volunteer to pay the living wage to their employees? Is doing so consistent with the aim of profit maximisation?
  7. Why are more women than men paid wage rates below the living wage?
  8. Why does the proportion of people being paid the living wage vary from one part of the UK to another? Is this likely to be purely a reflection of differences in the cost of living?

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.

Infographic

Wealth Inequality in America YouTube, Politizane (20/11/12)

Articles

The rise and rise of the cognitive elite The Economist (20/1/11)
Inequality in America: Gini in the bottle The Economist (26/11/13)
Pen’s Parade: do you realize we’re mostly dwarves? LVTFan’s Blog (21/2/11)
Here Are The Most Unequal Countries In The World Business Insider, Andy Kiersz (8/11/14)
Inequality in the World Dollars & Sense, Arthur MacEwan (Nov/Dec 14)
Britain is scared to face the real issue – it’s all about inequality The Observer, Will Hutton (19/1/14)
The tame inequality debate FundWeb, Daniel Ben-Ami (Nov 14)
Is inequality the enemy of growth? BBC News, Robert Peston (6/10/14)

Data

GINI index World Bank data
List of countries by income equality Wikipedia
The Effects of Taxes and Benefits on Household Income, 2012/13 ONS (see table 27)
Income Distribution and Poverty: Gini (disposale income) OECD StatExtract

Questions

  1. Distinguish between income and wealth. Is each one a stock or a flow?
  2. Explain how (a) a Lorenz curve and (b) a Gini coefficient are derived.
  3. What other means are there of measuring inequality of income and wealth other than using Gini coefficients (and giants and dwarfs!)?
  4. Why has inequality been rising in many countries over the years?
  5. How do (a) periods of rapid economic growth and (b) recessions affect income distribution?
  6. Define ‘efficiency wages’. How might an increase in wages to people on low incomes result in increased productivity?
  7. 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’?

The typical UK high street is changing. Some analysts have been arguing for some time that high streets are dying, with shops unable to face the competition from large supermarkets and out-of-town malls. But it’s not all bad news for the high street: while some types of shop are disappearing, others are growing in number.

Part of the reason for this is the rise in online shopping; part is the longer-term effects of the recession. One consequence of this has been a shift in demand from large supermarkets (see the blog, Supermarket wars: a pricing race to the bottom). Many people are using local shops more, especially the deep discounters, but also the convenience stores of the big supermarket chains, such as Tesco Express and Sainsbury’s Local. Increasingly such stores are opening in shops and pubs that have closed down. As The Guardian article states:

The major supermarket chains are racing to open high street outlets as shoppers move away from the big weekly trek to out-of-town supermarkets to buying little, local and often.

Some types of shop are disappearing, such as video rental stores, photographic stores and travel agents. But other types of businesses are on the increase. In addition to convenience stores, these include cafés, coffee shops, bars, restaurants and takeaways; betting shops, gyms, hairdressers, phone shops and tattoo parlours. It seems that people are increasingly seeing their high streets as social places.

Then, reflecting the widening gap between rich and poor and the general desire of people to make their money go further, there has been a phenomenal rise in charity shops and discount stores, such as Poundland and Poundworld.

So what is the explanation? Part of it is a change in tastes and fashions, often reflecting changes in technology, such as the rise in the Internet, digital media, digital photography and smart phones. Part of it is a reflection of changes in incomes and income distribution. Part of it is a rise in highly competitive businesses, which challenge the previous incumbents.

But despite the health of some high streets, many others continue to struggle and the total number of high street stores across the UK is still declining.

What is clear is that the high street is likely to see many more changes. Some may die altogether, but others are likely to thrive if new businesses are sufficiently attracted to them or existing ones adapt to the changing market.

How the rise of tattoo parlours shows changing face of Britain’s high streets The Guardian, Zoe Wood and Sarah Butler (7/10/14)
The changing face of the British High Street: Tattoo parlours and convenience stores up, but video rental shops and travel agents down Mail Online, Dan Bloom (8/10/14)
High Street footfall struggles in August Fresh Business Thinking, Jonathan Davies (15/9/14)
Ghost town Britain: Internet shopping boom sees 16 high street stores close every day Mail Online, Sean Poulter (8/10/14)

Questions

  1. Which of the types of high street store are likely to have a high income elasticity of demand? How will this affect their future?
  2. What factors other than the types of shops and other businesses affect the viability of high streets?
  3. What advice would you give your local council if it was keen for high streets in its area to thrive?
  4. Why are many large superstores suffering a decline in sales? Are these causes likely to be temporary or long term?
  5. How are technological developments affecting high street sales?
  6. What significant changes in tastes/fashions are affecting the high street?
  7. Are you optimistic or pessimistic about the future of high streets? Explain.

At least once a year The Economist publishes its ‘hamburger standard’ exchange rates for currencies. It is a light-hearted attempt to see if currencies are exchanging at their purchasing-power parity rates. The test is the price at which a ‘Big Mac’ McDonald’s hamburger sells in different countries!

According to this simplified version of the purchasing-power parity theory, exchange rates should adjust so that a Big Mac costs the same in dollars everywhere (see Economics 8th edition Box 25.4).

These Big Mac exchange rates can be used to compare various prices and incomes between countries. The article linked below from The Guardian compares minimum wages between European countries in Big Mac terms.

There are 25 countries across Europe which have minimum wages. A clear pattern of minimum wage rates can be seen: although actual exchange rates understate the purchasing power of incomes in poorer European countries compared to richer ones, minimum wages, even in purchasing-power standard terms, are still higher in the richer countries.

Luxembourg’s minimum wage buys you just about three Big Macs in an hour, while most of northern Europe (and France) between 2–2.5 Big Macs. Moving south, the minimum wage nets about one Big Mac an hour. As we progress east, it begins to cost more than an hour of work on the minimum wage in order to afford a Big Mac.

Of course, there are other factors determining the dollar price of a Big Mac other than the failure of exchange rates to reflect purchasing-power parities. Nevertheless, using the Big Mac index in this way does give a useful preliminary snap shot of differences in what minimum wages can buy in different countries.

Articles

Comparing the minimum wage across Europe using the price of a Big Mac The Guardian datablog, Alberto Nardelli (25/9/14)
Minimum wage statistics Eurostat (Sept/14)

Data

Earnings Database Eurostat

Questions

  1. What is meant by ‘purchasing-power parity exchange rates’?
  2. Why may actual exchange rates not accurately reflect the purchasing power of currencies within countries?
  3. Using the link to Eurostat article above, compare Big Mac minimum wages with (a) actual minimum wages and (b) minimum wages expressed in purchasing-power standard terms.
  4. Using the links to the Eurostat article and Eurostat data, describe how the proportion of employees earning minimum wages varies across European countries. What factors determine this proportion?
  5. Using the same links, describe how the monthly minimum wage as a proportion of average monthly earnings varies across European countries. Explain these differences.

A key economic objective of governments around the world is economic growth, where economic growth is taken to mean growth in Gross Domestic Product (GDP). This can be refined as growth in GDP per head or growth in Net National Income (NNY or NNI) – this takes account of depreciation and net flows of income to and from abroad. But is GDP (or NNY) an appropriate measure? There continues to be much debate about this and there is a lot of support for adopting an alternative measure – the Genuine Progress Indicator (GPI) as a target for economic policy.

GDP measures the market value of production and is the value added at each stage of production. If the value of a nation’s production is what you want to measure or target, then GDP is quite a good indicator. Its main drawbacks are that it uses market prices, which may be distorted, and that much of production in the informal sector is not included.

But if GDP growth is taken to be a proxy for development or growth in wellbeing of the residents of a country, then it has serious shortcomings. This is not to say that GDP gives no indication of progress. Generally, countries with higher GDP per head have a better standard of living, but it is not necessarily the case that, if Country A has higher production in the formal sector than Country B, its residents will be happier, more fulfilled and have fewer economic or other problems.

GDP, by focusing on production, ignores many environmental and social costs of that production. Valuable but not tradable resources, such as clean air, rivers and oceans, may be sacrificed for the sake of extra production and this is recorded as a gain in GDP.

Similarly, unless GDP is specifically weighted by income groups, which virtually never happens, it does not take into account income distribution. Much of the growth in production in both rich and poor countries in recent decades has gone to the richest people. Take the case of the USA. In 1944 the share of income going to the top 1% share was 11.3%, while the bottom 90% were receiving 67.5%. Such levels remained roughly constant for the next three decades. But then things began to change.

Starting in the mid- to late 1970s, the uppermost tier’s income share began rising dramatically, while that of the bottom 90% started to fall. The top 1% took heavy hits from the dot-com crash and the Great Recession but recovered fairly quickly: [preliminary estimates for 2012 by Emmanuel Saez] have that group receiving nearly 22.5% of all pre-tax income, while the bottom 90%’s share is below 50% for the first time ever (49.6%, to be precise).

So what does GPI measure and why may it be a better target for policy-makers than GDP or NNY? The answer is that it includes a number of important items that affect the well-being of a country, such as resource depletion, social activity and income distribution, that are not measured in GDP. So what would cause GPI to rise? According to The Guardian article below, examples would include:

Getting more energy from renewables; increased energy efficiency; reducing the income gap; putting more reliable, durable products on the market (have you heard of planned obsolescence?); volunteering more for your community; preserving wetlands, forests, and farmland; shorter commutes and transport routes. In fact, there are 26 ways the GPI can go up, all measured in dollars that boil down to a single number.

GPI is being increasingly adopted as a measure of progress. In the USA, it is officially used in Vermont and Maryland and is being considered in other states, such as Hawaii, Washington and Oregon.

And there are other alternatives. For example, since 1990, the United Nations Development Programme (UNDP) has published an annual Human Development Index (HDI) As Box 27.1 in Economics, 8th edition states:

HDI is the average of three indices based on three sets of variables: (i) life expectancy at birth, (ii) education (a weighted average of (a) the mean years that a 25-year-old person or older has spent in school and (b) the number of years of schooling that a 5-year-old child is expected to have over their lifetime) and (iii) real GNY per capita, measured in US dollars at purchasing-power parity exchange rates.

The following articles look at the suitability of GDP and GPI and whether, by targeting growth in GDP, governments are guilty of downplaying the importance of other economic and social objectives.

Beyond GDP: US states have adopted genuine progress indicators The Guardian, Marta Ceroni (23/9/14)
Forget the GDP. Some States Have Found a Better Way to Measure Our Progress. New Republic, Lew Daly and Sean McElwee (3/2/14)
Gross domestic problem Aljazeera, Sean McElwee (6/6/14)
Creating the Circular Economy, Part II Environmental Leader, David Dornfeld (17/9/14)
Development: Time to leave GDP behind Nature, Robert Costanza, Ida Kubiszewski, Enrico Giovannini, Hunter Lovins, Jacqueline McGlade, Kate E. Pickett, Kristín Vala Ragnarsdóttir, Debra Roberts, Roberto De Vogli and Richard Wilkinson (15/1/14)
The Problems With Using GPI Rather Than GDP Forbes, Tim Worstall (5/6/14)

Questions

  1. What does GDP measure?
  2. Does GDP of a country equate to the turnover of a firm?
  3. If growth in NNY is superior to growth in GDP as a measure of economic growth, why are GDP figures more generally used than NNY figures when assessing a country’s economic performance?
  4. How suitable is using GDP as a measure of a nation’s production?
  5. What does GPI measure?
  6. Is GPI superior to GDP as a measure of a nation’s level of development? Explain why or why not.
  7. Give some examples of where a growth in GDP might correspond to a decline in economic well-being.
  8. For what reasons could GPI measures be described as subjective?
  9. Would it be a good idea for a country to target growth in GPI/GDP? Explain your answer.
  10. In addition to real GNY per capita, the Human Development Index includes measures of education and life expectancy. For what other social objectives might education and life expectancy be useful proxies?