GINI: Income Disparity

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.

5 Responses to GINI: Income Disparity

  1. Excuse the sarcasm, but the CIA and leading researchers world wide left and right use the more sophisticated GINI index, and you put together one graph and try to interpret the problem away. That’s very weak. Deal with reality, pino! There are a lot of single poor, but the issue is the economic structure of society — to pretend that those who can’t find jobs or are the working poor are that way just because they aren’t a “family” doesn’t make sense. No, Pino, we do have a real issue, and the gap has been growing tremendously. Moreover the top 1% has grown 279% in 30 years, the top 10% “only” 95. The wealthier you are the more your income has grown. They do look at per capita average too, they consider the difference between someone living alone and a family.

    No, you’re doing what I warn students about — it’s back from “how to lie with statistics.” You can organize the data in different ways and then “interpet” a problem a way, with no real reason. That’s why you don’t believe pundits with quick stats who try to say that everyone else is wrong. You go with what scholars who are experts and who have fought over the methodological issues have agreed is best. The CIA is one organization that is very careful about what it accepts, and it uses the GINI index. To try to define away the large income inequality (which has been growing much worse) and class immobility by saying it’s family structure is fallacious and unsupported. Poverty is a cause of family structure problems. I don’t mean to sound overly sarcastic but as a social scientist this kind of thing irritates me, and people on the left and right both misuse/falsely interpret statistics to try to make reality go away.

    • CIA and leading researchers world wide left and right use the more sophisticated GINI index

      The GINI is simply a tool that measures the distribution of inequality. It doesn’t have to be income. It could be seed distribution or any other topic that’s being discussed.

      you put together one graph and try to interpret the problem away.

      Yes. I think it’s important to look at the composition of “households” when you make a blanket statement that income is not being fairly distributed. Do you seriously mean to tell me that a household with 4 wage earners isn’t going to have the same income pattern as a “household” with zero or even one wage earner?

      If anything is weak, it’s THAT.

      o pretend that those who can’t find jobs or are the working poor are that way just because they aren’t a “family” doesn’t make sense.

      I think study after study after study proves that a married household with the father present is a recipe for a more successful lifestyle. More than that, if a household has the opportunity to have more wage earners, that family is more likely to have more wages.

      You can NOT tell me with a straight face that comparing a bunch of houses with ZERO wage earners to a bunch of houses with FOUR wage earners is proof that income is unfairly distributed. You simply can not make that claim. You may make the claim that wage earners are somehow unfairly distributed–which would be silly–and maybe you could claim that jobs are unfairly distributed, but you aren’t. You’re claiming INCOME is unfairly distributed. I’m saying that when you account for the number of workers in a household, the picture becomes clearer.

      No, you’re doing what I warn students about — it’s back from “how to lie with statistics.

      Sorry teach. This time it’s you that are guilty of that. You are using the statistic to make your point. And it’s not valid.

      You go with what scholars who are experts and who have fought over the methodological issues have agreed is best.

      They are using GINI. A simple well known tool.

      The CIA is one organization that is very careful about what it accepts, and it uses the GINI index.

      I have come to doubt the CIA data several times. Another topic that they use poor data is on world heath. They use infant mortality as a measure and yet can’t manage to measure it correctly either.

      To try to define away the large income inequality

      You [and CIA] aren’t measuring income inequality. You are measuring household income inequality. Which is WAY different.

      class immobility

      The GINI doesn’t measure mobility.

      aying it’s family structure is fallacious and unsupported

      Really?

      2 households. 2 kids.

      1: A married family with both parents home and working with a 17 year old wage earner.
      2: A single mother with 2 children under 5.

      Which one do YOU think is going to earn more? And how, exactly, is that “unfair”? And IF it’s unfair, it’s not due to compensation norms and changes. It MAY be due to how poorly we teach our kids to raise kids. But that’s a different thing to fix than somehow addressing how much we pay people.

      • where did you get your data? can you please provide a link? there should be the same number of households in each quintile, the fact that the top quintile has more than twice as many households as the bottom quintile doesn’t make much sense.

      • where did you get your data?

        Hi John. It’s my main complaint of this theme from wordpress; the links don’t show up.

        I linked to it above the data. But here it is again:

        http://www.census.gov/hhes/www/cpstables/032011/hhinc/new05_000.htm

        If you follow the link you’ll see the chart. The very top line, the one labeled “Number” shows the Total # first and then the Fifths. They come in at 23,736 each. My graph shows households that are “families”.

        For the most part, the top quintile isn’t more wealthy because they have higher wage earners, it’s because they have MORE wage earners.

        Now, to be fair, I’m sure there is the phenomenon of the Doctor mom and the dad that works at the library part time, but still. The number of wage earners in a household drives income.

  2. The World Bank and other experts take things like household size, equivalent number of adults, etc., into account in their weighting of the data. It’s not like they’d treat a one person household with $40,000 the same as a four person household with the same income. There are different ways that one can weigh these, and statisticians argue about which gives the most accurate result, but they don’t blindly treat all households as the same.

    And it’s not just the GINI index. From: http://en.wikipedia.org/wiki/Income_inequality_in_the_United_States:

    “The distribution of income in the United States is becoming increasingly unequal. In 2010, the top 20% of Americans earned 49.4% of the nation’s income, compared with the 3.4% earned by Americans living below the poverty line (roughly 15% of the population). This earnings ratio of 14.5 to 1 was an increase from the 13.6 to 1 ratio in 2008 and a significant rise from the historic low of 7.69 to 1 in 1968.[14] Looking back even further to 1915, an era in which the Rockefellers and Carnegies dominated American industry, the richest 1% of Americans earned roughly 18% of all income. Today, the top 1% account for 24% of all income.”

    The article goes on from there — yes, it’s Wikipedia, but it cites its sources. Nothing in your data counters the other data out there. It does show that poverty tends to make it harder to have functional families — another negative effect of poverty — and that there are a lot of poor single people heading households. But that even makes it more difficult to get ahead! I read: income maldistribution destroys families, which hurts children. That is just as valid a way your data could be interpreted.

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