# GINI Coefficient

The latest report from the OECD should make those in favor of redistributive policies vindicated in their opinion that the income disparity is growing.  Data suggests that it is:

THE gap between rich and poor has grown ever wider in wealthy countries over the past three decades. A new report by the OECD has reams of data on this phenomenon and is well worth looking at. The Gini coefficient, a measure of inequality in which zero corresponds to everyone having the same income and one means the richest person has all the income, increased by almost 10% from 0.29 in 1985 to 0.32 in 2008, for working-age people in OECD countries. The trend is caused by earnings: the pay of the richest 10% of employees has increased at a far greater rate than that of the poorest 10% of employees. Within the upper echelons, the top 1% have reaped the greatest gains.

I have ideas about why this gap is growing.  I think that much of it is the way in which they measure the Gini.  For example, you could take 4 people with incomes described as:

1. \$24,000
2. \$30,000
3. \$50,000
4. \$75,000

The Gini coefficient for the above data is .24162

Now, marry two of those wage earners:

1. \$24,000
2. \$50,000
3. \$105,000

The Gini coefficient for THAT data is .301676.  Without ANY income changing at all, the Gini increases by 25%.  In other words, the same number of people are working the same number of jobs and earning the same number of dollars.  The only difference is the method by which they calculate the Gini.

But are there other reasons for the Gini to increase?  Why yes:

Technology has disproportionately benefited high-earning workers, who also spend far longer at work than do low-earners. High earners marry other high earners. And governments are doing less to redistribute wealth than they have done in the past. So far, so familiar. But the report also argues that globalisation is not a significant cause of inequality, and that one of the many reasons for the rise in income inequality is that more people are in work now (or at least they were before the financial crisis hit) compared with the 1970s.

So, we have factors such as:

1. Technology has helped the wealthy [did it create them?].
2. Productive people marry other productive people .
3. Governments are correctly not redistributing wealth.
4. More people are “in work” now.

In the end, I’m not sure that the use of the Gini is an appropriate measure of income disparity.  Further, I’m not sure it even matters.

### 2 responses to “GINI Coefficient”

1. You are taking a nation-wide economic statistic, applying it to a population of four, then three, and drawing conclusions as to its usefulness?

• You are taking a nation-wide economic statistic, applying it to a population of four, then three, and drawing conclusions as to its usefulness?

You make my point. The population doesn’t change. It’s still four.

I’m saying that a measurement that compares household income to household income without discriminating on number of earners, hours worked, age, years of experience and education isn’t the Holy Grail that many think it is.