Tag Archives: Income Disparity

Wealth and Distribution

Posted on November 11, 2011 | 3 comments

Occupy Wall Street is having an impact.  There’s little doubt that they have generated much conversation and debate.  Some think that the impact they’ve had is positive; others negative.  For me, it’s focused the debate on income distribution, income mobility and wealth distribution.

We’ve talked about the GINI.  That’s the tool, in general, that measures distribution.  It could be World Series Titles or brown hair.  It could be the letter “W” in license plates or it could be income.  And I’ve come to the conclusion that the GINI, as reported by the major players, isn’t reporting anything useful.  The GINI measures income per family.  And all families aren’t created equal.

So, next up is wealth.  This time I built a thought experiment.  A simple and crude one to be sure, but, based on feedback, could be refined.  In fact, it’s my goal to refine it as I go.  The idea is to create a world that is as equal as possible.  I’ve built a population that is the same in every regard.  They make the same, save the same and spend the same.  And they advance the same.  Given such a world, what does income and wealth distribution look like?

Let’s look at wealth.

I assume a number of things.  All in the name of equality:

  1. 1000 people per year
  2. A starting salary of $30,000
  3. A raise of 3% a year.
  4. Progressive living: roommate-own apartment-saving for home
  5. Progressive retirement savings – none to 401k
  6. Rent and food don’t increase in real terms
  7. People only have living and food expenses.  And save ALL other money.

If we start at year 1 and continue to build our population, it looks like this for the first 15 years:

The graphics are tough to see without clicking through.  Lemme give ya the money shot:

Total
Worth
$20,150.00
$41,065.00
$62,768.00
$85,282.81
$108,633.07
$132,996.30
$155,049.73
$178,141.44
$202,303.53
$227,569.27
$253,973.07
$281,551.59
$310,340.71
$340,378.62
$371,702.83

Using the gross assumptions above, I have identified the “Total Worth” of the individuals year over year.

Each row above represents another cohort advancing and the previous year taking it’s place.  That is, this year’s “Year Ones” becomes next year’s “Year Twos”, And this year’s “Year Twos” become next year’s “Year Threes”.

We like to break down distributions by quintiles.  Let’s do that.  Let’s break it down by quintile.

If you sum all the wealth of the 15 represented years, you get $2,771,905.  If you divide $2,771,905 by 5 you get $554,381.  The first SIX years of cohort classes don’t equal one single quintile.  On the other end of the spectrum, just 2 cohort classes are at $712,081.  Nearly 40% more than the top quintile.  In other words, more than the poorest third of people control less than 20% of the net wealth while the richest 14% control more than 20% of the net wealth.

6/15th’s of the poorest control less money than the top 2/15ths.

And this in a world controlled by exact equality and accounting for no good/bad decisions.

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Posted in Economics, GINI, Middle Class, Politics: National

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GINI: Further Clarification on Wage Earners

Posted on October 31, 2011 | 4 comments

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
No Earners 62.4% 29.6% 14.0% 6.3% 3.0%
One Earner 33.0% 52.6% 48.4% 33.1% 22.2%
Two Earners 4.3% 16.0% 32.4% 49.3% 55.9%
Three Earners 0.2% 1.6% 4.4% 8.9% 13.1%
Four Earners 0.0% 0.2% 0.8% 2.4% 5.8%

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?

No.

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.

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Posted in Economics, GINI, Liberty, Life, Politics: National

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GINI: Income Disparity

Posted on October 31, 2011 | 5 comments

Thursday I posted my thoughts on the GINI rating and how it pertains to income here in America.  In that post, my main thrust was the fact that GINI, as reported when comparing national income disparity rankings, was comparing household incomes.  Not the incomes of individuals, but of households.

And I think that’s important.  As I demonstrated in that post, taking these two families:

  • Family A making $60,000 a year
  • Family B making $70,000 a year

Looks to be fairly equitable.  But now let’s consider that family A and family B get divorced, created 4 households out of two.  Then the breakdown looks like this:

  • Family A making $0 a year
  • Family B making $28,000 a year
  • Family C making $32,000 a year
  • Family D making $70,000 a year

THIS looks to be dramatically different.  However, the same four families in the second picture are the individual household represented in the first picture.  Remarkable, yes?

So, how do things look in real life?  Let’s take a look at the US Census Bureau’s Current Population Survey for 2010:

Descriptor Lowest Fifth Second Fifth Third Fifth Fourth Fifth Highest Fifth
Family Households 9,411 13,969 16,162 18,543 20,528
% 12 17.8 20.6 23.6 26.1
Married Couples 4,037 8,521 11,587 15,270 18,621
% 7 14.7 20 26.3 32.1
No Earners 14,805 7,037 3,327 1,496 722
% 54.1 25.7 12.1 5.5 2.6
One Earner 7,845 12,474 11,488 7,853 5,263
% 17.5 27.8 25.6 17.5 11.7
Two Earners 1,020 3,790 7,702 11,700 13,258
% 2.7 10.1 20.6 31.2 35.4
Three Earners 55 379 1,040 2,112 3,119
% 0.8 5.6 15.5 31.5 46.5
Four Earners 5 58 180 577 1,377
% 0.2 2.6 8.2 26.2 62.7
Aggregate Earners 10,240 21,940 31,595 41,125 48,338

The data is remarkable.  Let’s go through it bit by bit.

First, the “Fifths” listed at the top is earnings by quintile.  That is, the poorest 20% is the “Lowest Fifth” while the richest 20% is the “Highest Fifth”.

Now then, the data:

Households that are “families” is a massive indicator of income.As the percentage of families in each fifth increases, so does the wealth.  The same goes for married couples.  The top fifth has nearly 5x the number of married couples as the bottom fifth.  Seems that family is important in wealth creation.

Family aside, the powerful statistic that I took away was the number of earners in a household.  And what I found matches exactly with the phenomenon I described in my earlier post.

Of the households in the bottom fifth, more than HALF don’t have a single wage earner in the household.  More than half.  While the top 20% has only 2.6% of households that don’t qualify as a wage earner.

Further, if you look at the “Lowest Fifth” as a column and march down, you’ll see that fewer and fewer of those households have the described number of earners.  Starting at the top, this segment of the population has 54% of households with 0 wage earners.  While at the bottom, it has but .2% of the households with 4 wage earners.  The exact opposite is true of the “Highest Fifth”.

In short, it would seem that as a household has more wage earners, that household moves from one of the fifths to another.  And to the extent that this is true, look at the last line; aggregate earners.

The “Lowest Fifth” has 10,240 members.  The fifth that earns twice as much money as the lowest fifth has twice as many wage earners.  The fifth that makes three times as much as the lowest fifth has three times as many wage earners.  The fourth has four times as many wage earners.  And the highest has five times the number of wage earners.

This is true almost to the exact number.

The data presented above tells me that we don’t have an income disparity issue.  We have a family structure issue.  If you take a single wage earner in a household and compare that household to one with 4 wage earners, it should be no surprise which of the two households makes more money.

And lest there be any doubt.  The “Highest Fifth”?  They are some working sums -o- beetches.  Fully 62.7% of those households have FOUR wage earners.  This is not the lazy rich that the OWS and the ((% make them out to be.

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Posted in Economics, Economy, GINI, Liberty, Life, Politics: National, Rocket Surgery

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GINI: Income Mobility and Disparity

Posted on October 27, 2011 | 5 comments

Much has been said during the last few years about income disparity.  And not just the disparity, but the mobility of people from one income group to another.

I’ve done some reading last night and this morning a thought struck me:

GINI measures the disparity in household income.  Consider Dick and Jane and their neighbors John and Mary.

Dick works in retail and is making $28,000 a year.  Jane works in service and makes $32,000 a year.

John works as a manager in a factory making $70,000.  Mary stays home and cares for their family.

The disparity between Dick and Jane vs. John and Mary is low.  Dick and Jane earn $60,000 a year while John and Mary earn $70,000.

Now, consider Dick and Jane get divorced.

The disparity between two households earning $28k and $32k compared to the one earning $70k is much higher, and the GINI goes up.  But nothing changed as far as economic earnings are concerned.  In fact, if you take this one step further, consider John and Mary also suffer divorce.  Now the incomes for FOUR households is:

  • $0
  • $28,000
  • $32,000
  • $70,000

A very disparate view when compared to the initial comparison of $60,000 and $70,000.

In the same way that the demographics of America impact life expectancy statistics [Japanese Americans live as long as native Japanese] I suspect that demographics impact the GINI.  I also suspect that this isn’t calculated into the analysis when people discuss the GINI.

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Posted in Economics, Technology

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Income Disparity

Posted on September 5, 2011 | 1 comment

Income disparity.

Wikipedia describes it like this:

Income inequality in the United States of America is the extent to which income, most commonly measured by household or individual, is distributed in an uneven manner.

Pretty fair I think.  It hits what I think are the important aspects of the topic:

  1. Income
  2. How measured
  3. Distributed
  4. Uneven

I think that most reasonable people wanna help out the folks who need the help.  Further, I think that most reasonable people wouldn’t personally help those folks, who-while down on their luck, aren’t down due to luck.

Anyway, very often when solutions are discussed, or when examples of success are presented, I am faced with the argument that the Income Disparity, the Income Inequality of America is very very poor.  So poor, perhaps, that we rank near, tied for or dead, last.  A common tool to measure the disparity in incomes is the GINI Coefficient.  Or the GINI Index.

The Gini coefficient is a measure of statistical dispersion developed by the Italian statistician and sociologist Corrado Gini and published in his 1912 paper “Variability and Mutability”

The Gini coefficient is a measure of the inequality of a distribution, a value of 0 expressing total equality and a value of 1 maximal inequality. It has found application in the study of inequalities in disciplines as diverse as sociology, economics, health science, ecology, chemistry, engineering and agriculture.

It is commonly used as a measure of inequality of income or wealth.  Worldwide, Gini coefficients for income range from approximately 0.23 (Sweden) to 0.70 (Namibia) although not every country has been assessed.

Most uses of the GINI Coefficient that I have ever heard of deal with Income Disparity.  Though from reading wiki, it seems that the GINI Coefficient is simply a tool to measure dispersion.  So, it’s nice to learn that the GINI is simply a statistical tool that has been applied to measure income disparity.

As I am generally ignorant of many things the measuring of income between the people of a nation, I think it’s important to learn more.  As I enter into this investigations, I’m struck by two aspects of the inquiry:

  1. Does it matter?
  2. What is being measured?

The second first.  Because the GINI can be used to measure seemingly anything at all;  fish in a body of water, water in a body of land or pine cones in a body of grass.  It’s important to know what the subject of the measurement is.  And I think that most discussions surrounding the GINI are clear on what they are measuring.

For example, we are having a discussion concerning taxation on my post concerning Denmark and the United States.  One of my friends  points out that:

The US pre-tax and transfer GINI index is at .46, while Sweden is at .43, and Denmark and Norway are at .42. That means pre-tax they are slightly more even in income distribution, but not much. German has a bigger pre-tax gap between the rich and the poor than the US at .51.

After tax the US GINI index moves to .38 — a modest improvement. But it is the most income disparity of the entire industrialized world. Taxes and transfers move the wealth distribution from .46 to .38.

After taxes and transfers Denmark is at .23.

Clearly the GINI is being used to measure two different things.  Income pre-tax and then income post-tax.  Which is valid as long as the measurements are clearly labelled.  And again, I think in most cases they are honestly so represented.

Now the first.  Does it matter?

This is trickier.  Does the fact that the richest among us make more than the poorest among us matter?  Perhaps.  It sounds like there is a body of evidence that suggests it does matter AND that when that disparity is high, society suffers.  I don’t know, I haven’t looked at it.  First blush, I think my take is that I don’t care as long as I have a reasonable shot at getting pretty close to the top.  And reasonable can mean many things.  When I buy a lottery ticket I have as reasonable a shot as anyone else.  I certainly would resent the rich having a better shot at winning numbers than me JUST because they were rich.

So, where are we.

I wanna look at Income Disparity.  Perhaps as it’s measured by the GINI.  And I wanna know, at the end, several things.  The first of which is: DOES IT MATTER?

And if it does, which of the following matters the most:

  1. Straight income.  The MONEY paid from employer to employee.
  2. Total compensation.  The total compensation from employer to employee.
  3. This measurement BEFORE taxes.
  4. This measurement AFTER taxes.
  5. Finally, this measurement AFTER social entitlement programs.

Let’s see how this goes.

Thoughts?

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Posted in Economics, Economy, Liberty, Politics: National

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Shrinking The Income Disparity Gap: What Would It Mean?

Posted on June 22, 2011 | 4 comments

So, I had an interesting discussion with reflectionephemeral over at Poison Your Mind.  We were discussing the meaning of income disparity here in America and then around the world.

I acknowledge that such disparity is increasing; the gap between the rich and the poor seems to be getting wider and wider all the time.  And America is much less income level mobile.  That is, it is more difficult here in America to move from one income bracket to another than it is in say, Europe.

However, I make my point that while the gap may be larger, the rich may indeed be getting a larger slice of the pie, that the slice the poor DO get is much bigger than they otherwise would.

In my conversation, I envisioned two scenarios:

A. On a scale of 1 to 10, with 1 being poor and 10 being rich, the poorest averaged a 2 while the rich averaged a 3.

B. On a scale of 1 to 10, with 1 being poor and 10 being rich, the poorest averaged a 4 while the rich averaged a 9.

In world B, the poor earn MORE than the rich in world A. However, in world B, the rich are wealthier in relation to the poor in world A.

Which would you pick?

Continue reading →

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Posted in Economics, Liberty, Politics: International, Politics: National

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