This morning I posted on the flaw of using the popular measure of income disparity across nations. Many organizations use the GINI coefficient to measure this disparity. However, what these organizations fail to mention is that they are measuring household disparity, not individual disparity. And when they compare nation to nation, they don’t normalize those numbers so that we’re comparing apples to apples.
For example, in the United States, a massive amount of “households” is comprised of single parents. That is, the home will find a single eligible wage earner. And many of those parents opt not to work. Now, some will say that’s because there is no work to be had. Others, me included, will say that the incentives are all wrong. The entitlement programs offer enough aid that the prospect of going to work doesn’t make sense.
So, no income.
Is this sad? Most certainly.
Does this promote poverty generation to generation? With out a doubt.
Is this a serious problem that requires serious thought? Yes.
Does this implicate the job market, compensation structure or some inherent bias towards “the wealthy”? Under no circumstance.
This morning I showed the “horizontal” version of the data. Let’s look at the vertical:
|Descriptor||Lowest Fifth||Second Fifth||Third Fifth||Fourth Fifth||Highest Fifth|
The data continues to reveal reality. The quintile that represents the poorest among us, the “Lowest Fifth” has 62.4% of it’s members with ZERO wage earners. That is, more than half, WAY more than half of the poorest quintile has no one in it making any amount of money. NONE. There is no way that this can be counted towards any measure of income disparity. For that to happen, there must be an income!
I have lived in North Carolina for 12 years [damn! 12 years] and I have never won the North Carolina lottery. Never mind that we have had a lottery for only 7 years and that I’ve never bought a ticket. Is it realistic that I be counted among lottery players that haven’t won?
Back to the data. The “Lowest Fifth” has 62.4% of its members with no income. 62.4%. Compare this to the “Highest Fifth”. That quintile has 3% with no wage earners. Three. Further, the “Lowest Fifth” has only 4.5% of its membership with 2 or more earners. Compare that with the “Highest Fifth” who have 5.8% with FOUR wage earners.
It turns out that a predictor of income is, shockingly, the number of wage earners.
As I note in the other post, the GINI index weighs the data taking into account things like this. You are taking an obvious truth — that if you have more wage earners you’re likely to have more wealth (especially when broken up into large 20% groups)– and pretending that somehow means we don’t have an income distribution problem. Of course the poorest are the ones with a harder time finding jobs, and often are single people heading households. But any statistician who measures income distribution takes those things into account. No one would be dumb enough to treat a household of one earning $50,000 the same as a household of seven with the same income! Again, they argue on the best ways to weigh data, but you can’t jump from an obvious statement: “households with more earners have more money” to a conclusion that does not support “there is no problem with income distribution.”
Why is the Gini coefficient based upon net income rather than net worth? It seems to me that BOTH should be used in the calculation. I suspect that if net worth was added into the mix, the disparity between rich and poor would be even greater. Aren’t most folks with high annual income already sitting on a pot of gold left over from previous years?
If the GINI was based upon the amount that each family spent each year, the results might be more useful. It would show the amount that people were willing to use to support their lifestyle. Does it really matter how much we earn? In my mind, the real question is how much are we able to spend.
Actually GINI can be based on anything, it depends on what variable you are choosing to measure. This is old data, but it’s an example of a national comparison based on net worth: http://assets.aarp.org/rgcenter/econ/dd100_inequality.pdf
On page 5 they discuss the GINI coefficient which is much higher (.7 rather than .38) than in income. That means that if you look at net worth there is a lot more inequality than if you just look at income. They also make the point that net worth inequality is rising, though again that study is only through 2001.
Thanks for the information Scott.