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With inequality now a front-page issue, the stats that measure inequality have taken on a new importance. And no inequality stat has a longer pedigree — or more confusion surrounding it — than the ‘Gini coefficient.’
By Salvatore Babones
Levels of income inequality in America today are running at record levels. Activists from the Occupy movement have placed rising inequality firmly on the national agenda, and inequality looks to figure prominently in the 2012 election campaigns.[pullquote]The Gini coefficient was first defined in a 1912 paper by an Italian economist.[/pullquote]
All this makes inequality statistics suddenly newsworthy, but how do statisticians measure something as slippery as inequality? Some people obviously have more than others, but how does that difference translate into numbers that represent the level of inequality for an entire society?
Anyone following the inequality debate so far has probably heard of the Gini coefficient. America’s Gini coefficient is 46.9. Or 37.0. Or maybe as high as 57.4. Really, it depends who you ask.
The Gini coefficient was first defined in a 1912 paper by the Italian economist Corrado Gini (1884-1965). The coefficient measures the degree the degree of concentration in a country’s income distribution. Social statisticians today use many different inequality measures, but none more than the Gini coefficient.
The Gini coefficient amounts to a kind of percentage and can run from 0 to 100. A Gini of 0 represents 0 percent concentration in a country’s income distribution. In a country with a Gini coefficient of 0, everyone receives exactly the same income.
A Gini coefficient of 100 represents 100 percent concentration in a country’s income distribution. In a country with a Gini of 100, one person receives all of the country’s income. Everyone else gets nothing.[pullquote]The official Gini coefficient for the United States has shot way up from the all-time low set in 1968.[/pullquote]
In between 0 and 100, Gini coefficients are harder to interpret. A Gini coefficient of 50 represents 50 percent concentration in a country’s income distribution. What does it mean to have 50 percent concentration in a country’s income?
A Gini of 50 could mean that half the people share all of the income while the other half get nothing. In other words, a country that literally consisted of haves and have-nots in a 50-50 split would have a Gini coefficient of 50.
This scenario, of course, isn’t very realistic. Everyone, no matter how poor, has to have some income to live. There are no literal have-nots.
We could also have a Gini coefficient of 50 with the top 10 percent of a country’s population very well-off, the next 50 percent more or less equal, and the bottom 40 percent very poor.
With some fiddling around the edges, that’s more or less the situation in America today.
According to the Census Bureau, the official Gini coefficient for the United States was 46.9 in 2010, the most recent year with data available. This is way up from the all-time low of 38.6 set in 1968.[pullquote]Income inequality statistics can differ depending on how income is defined.[/pullquote]
Gini coefficients can be used to measure the concentration of any distribution, not just the distributions of income. Higher concentrations translate into higher inequality. Lower concentrations mean lower inequality.
For example, wealth inequality in America runs much higher than income inequality. New York University economist Edward Wolff estimates the Gini coefficient for household wealth — net worth — in the United States to be 86.5, based on 2009 data. That’s much higher than any income inequality estimate.
Leaving aside wealth and other forms of inequality, even income inequality statistics can differ depending on how income is defined.
The most common definition of income used by the Census Bureau and other statistical agencies is total money income of a household, excluding capital gains. All of the members of a household are assumed to share in the household’s combined income.
Household income includes wages, salaries, interest, dividends, alimony payments, child support, Social Security payments, and any other cash transfers. It doesn’t include food stamps, Medicare, or other non-cash benefits.
A major gap in the measurement of income inequality is the exclusion of capital gains, profits made on increases in the value of investments. Capital gains are excluded for purely practical reasons. The Census doesn’t ask about them, so they can’t be included in inequality statistics. [pullquote]Real levels of income inequality in America run much higher than the official Census Bureau figures would suggest.[/pullquote]
Obviously, the rich earn much more from investments than the poor. As a result, real levels of income inequality in America are much higher than the official Census Bureau figures would suggest.
Edward Wolff, working with Federal Reserve Board data that included capital gains, but not government transfer payments, put the figure at 57.4 for 2006.
How does America’s Gini coefficient compare to those of other countries? Comparative data on income inequality are reported by the Organisation for Economic Cooperation and Development.
The OECD reports three different Gini coefficients for the United States and other countries (see accompanying table). The first covers the Gini coefficient for wages earned from work. The second traces overall income inequality. The third measures inequality in total living standards, including government-provided health and education benefits.
According to the OECD, the Gini coefficient for income inequality in the United States is just 37.0. The OECD is highly secretive about its methodologies, so it’s impossible to know why this is so different from the official figure of 46.9 reported by the U.S. Census Bureau.
Whatever exact procedures the OECD uses, it claims to use the same procedures for all countries. According to the OECD, the Gini coefficient for wages is highest in Italy (46.5) and the United Kingdom (45.6). The United States comes in third-highest out of the 18 developed countries for which data are available.[pullquote]Including the value of government-provided health and education benefits makes the United States look even more unequal compared to other developed countries. [/pullquote]
After other sources of income are included, however, the United States is by far the most unequal of all 18 countries. The United States (37.0) is well ahead of number two Portugal (34.7) and number three United Kingdom (34.5).
The United States scores worse mainly because Social Security, unemployment insurance, and other cash benefits in the United States contribute much less to income than comparable programs in other countries.
Including the value of government-provided health and education benefits makes the United States look even more unequal compared to other developed countries. In this final comparison the U.S. Gini coefficient (30.3) is still worse than number two Portugal (29.1) and far worse than number three Italy (26.2) and all other developed countries.
By this last measure, the most equal countries in the world are the usual suspects: Denmark (19.4), Norway (19.3), and Sweden (18.1).
So is America’s Gini coefficient 46.9 (Census Bureau), 37.0 (OECD), or 57.4 (Edward Wolff based on Federal Reserve data)? It depends what you mean by income. If by income you mean all the money that households get from all sources, including both government transfers and capital gains, then it’s probably around 50, give or take a point.
So we’re right back to the haves and have-nots. That we’re a society of haves and have-nots may not be literally true, but it’s more than just a metaphor. America is suspended roughly half-way between full equality and a situation in which all of the country’s income is concentrated in one person’s hands.
In other words, we’re half-way between a socialist utopia and an absolute monarchy. America in 1968 was hardly a socialist country, but it was much closer to the utopia. Maybe it’s time to turn back the clock on income inequality. Utopia doesn’t sound so bad.
Salvatore Babones is a senior lecturer in sociology and social policy at the University of Sydney and an associate fellow at the Institute for Policy Studies.