Even more dwarfs and fewer but larger giants

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.


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


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)


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


  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’?