Following a recent lecture in my MBA program on distribution of wealth in the U.S. and around the world, I thought I'd do a little research on the topic. Although I'm usually a skeptic and think the press likes to knock the U.S. in general while taking shots at big business and the upper class, the empirical data actually supports the notion that distribution of wealth in the U.S. is not exactly on par with the rest of the developed world and the disparity is increasing rapidly.

How do you measure distribution of wealth or lack thereof?

There are some key statistical measures which are utilized elsewhere in academia, but in the context cited here, they are primarily utilized for just this topic:

Lorenze Curve: Starting with this measure, you can measure what percentage of households possess a certain percentage of total income. Have you ever heard politicians invoke, "The tax cuts benefited the rich because the top earners realized the majority of the tax benefit..." while conveniently leaving out they they pay more than their fair share of taxes. It's tough to reduce taxes for people who don't pay taxes!...at the bottom of the continuum. Anyway, without getting sidetracked, this same principle applies to who's holding the income in this country. Obviously, there is no Utopian society whereby income is perfectly distributed amongst the full populace, even in Communist countries, where the leaders generally enrich themselves while the populace starves...but as you'll see in the graphical representation below, some countries come pretty close.

To close the book on the Lorenze curve and move on, here's a visual of how it articulates a cumulative distribution function and then we'll get into our next measure derived from this curve. The green line would represent perfect distribution, whereas the red line below reflects the reality that say, the bottom 80% of the households only hold 60% of the wealth (so the lucky top 20% hold more than an equivalent amount per capita).

If you try to quantify the area between the green and the red line, you get what is called the Gini Coefficient. This measure is effectively the "area under the curve" if you inverted the green axis to represent the x-axis on your conventional graph for anyone out there who's been through calculus bliss (5 semesters for me was more than enough!). By measuring this shaded area, you can build a comparison model to rank countries by the size of the shaded area.

How does the U.S. compare?

Interestingly, the U.S. is actually one of the bad actors in western countries as evidenced by the following graph. The higher the measure, the more disparate the income distribution. In this graph, green is good, through red being bad. Note the Nordic countries are tops. They do a nice job in distributing those oil revenues, Norway especially.

Not only is the U.S. at the upper end of the comparable country population, but over time, the U.S. Gini index has increased to the point where it's now at an all time high!

Gini coefficients for the United States at various times, according to the US Census Bureau:
1967: 0.397 (first year reported)
1968: 0.386 (lowest coefficient reported)
1970: 0.394
1980: 0.403
1990: 0.428
2000: 0.462
2005: 0.469 (most recent year reported; highest coefficient reported

So, what do you think. Do the economists and pundits have a point? Are we greedy Americans or is this just a function of the most entreprenurial/free market economy on the planet?

*Much of this was derived from wiki, but I consolidated, researched/added other sources and my own commentary. Wiki Commons is freely licensed media. Fully referenced below.

Sources:

U.S. Census Bureau: http://www.census.gov/


Wikipedia: http://en.wikipedia.org/wiki/Main_Page

New York Times