Posts tagged with economic inequality

Chances of US Blacks, Hispanics, Poor, Women, Men, Whites, Rich to reach the middle class by middle age.

by Isabel Sawhill, Scott Winship, and Kerry Searle Grannis

SWG define the US middle class as 3 times the poverty level. That’s

• at least \$35 000 / year for a single person
• or at least \$71 000 / year for a family of four (multiple family members can work toward that).

Middle age they take to begin at 40.

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You can also see the 40% who do not make it to the middle class in Catherine Mulbrandon’s picture:

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SWG find “rungs” on the ladder to prosperity, such that within their dataset,

• achieving today’s rung increases the odds of achieving tomorrow’s rung,
• and failing to achieve today’s rung decreases the odds of achieving tomorrow’s rung.

(The weakest link is from basic reading & maths skills + social & emotional skills → to high school graduation + non-criminality. The strongest link is from acceptable pre-reading & pre-maths + school-appropriate behaviour → to basic reading & maths + social-emotional skills.)

That is a Markov or AR(1) at each step, but changing 2×2 matrices (pass-through probabilities) each time.

The poor outcomes for low-birthweight black poor youths are then understood, within the paper, as the composite effect of passing through the several gates.

For example low birth weight, poor parents of the wrong race starts the child off in the disadvantaged category. 40% of those are off track when school starts. Then 55% of (not just the `0-disadvantaged ∩ 1-disadvantaged`, but all of the) stage-1-disadvantaged continue to advance to the next stage on the losing track.

In this way the eventual low success-rate of the adults from poor families is seen as the product of a succession of gates.

In matrix terms each 2×2 matrix “shuffles beads from gate to gate”. For example the first matrix is

$\dpi{300} \bg_white \begin{bmatrix} 72\% & 28\% \\ 59 \% & 41\% \end{bmatrix}$

and the product (composite) of the first two is this matrix product:

$\dpi{200} \bg_white \large \begin{bmatrix} .72 & .28 \\ .59 & .41 \end{bmatrix} \cdot \begin{bmatrix} .82 & .18 \\ .45 & .55 \end{bmatrix}$

In the product matrix the red entry is the fraction of babies born disadvantaged (`0-loser`) who end up `2-disadvantaged` after 2 matrices `M₁bull;M₂` have been applied—entering middle childhood.

$\dpi{200} \bg_white \large \begin{bmatrix} .72 & .28 \\ .59 & .41 \end{bmatrix} \cdot \begin{bmatrix} .82 & .18 \\ .45 & .55 \end{bmatrix} = \begin{bmatrix} \colorbox{red}{\color{white}{71\%}} & 29\% \\ 67\% & 33\% \end{bmatrix}$

If you wanted to compute the overall numbers from the bar chart at the top you would need also a starting vector `X₀` saying how many babies start off already at a disadvantage. (The fraction who don’t start off disadvanaged is not a free parameter.)

(Source: brookings.edu)

hi-res

What jobs do the 1% have? by Bajika, Cole, and Heim

BCH and the US government did all the work here. My only contribution was to highlight

1. professions I didn’t expect to see like pilot, farmer, government, teacher
2. some “standard narratives”:
• the one about “lawyers and doctors”
• (I don’t know why these two get grouped together, since one works in abstractions and the other works in gore…but whatever, that is a narrative)
• the one about “study hard and you’ll get ahead” (scientists, professors, computer, maths)
• and “real estate developers”
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Obviously the top 1.5M earners aren’t important to the exclusion of the other 311M Estadounidenses, the 145M employed Estadounidenses, or everyone else.

Equally obvious is that

$\dpi{200} \bg_white \large \Pr\{ \texttt{lawyer} | \rm{you} \in {1 \over 100} \} \not= \Pr \{{1 \over 100} \ni \rm{you} | \texttt{lawyer} \}$

(some lawyerly deeds are more lucrative than others … same for doctors.)

Still, if you’re

• choosing a career
• trying to understand how the world works

then you might want to find out about rich people. It might be better to do so with, you know, actual facts, rather than for example listening to a bunch of programmers b*tch about how much money lawyers and doctors make.

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Back to Bajika Cole & Heim. Why is it that this basic information wasn’t known? BCH, Pikkety Saez, and a few others who have bothered to parse data to answer simple questions seem to get fairly good citations. Are economics researchers so bent on complicated research that they won’t “arb” citations by doing something a non-PhD could do?

It is well known that the share of US income going to the top percentiles has increased dramatically over 1986–2006.  Piketty and Saez found that the top ¹⁄1000’s share of pre-tax income (ex cap gains) in the United States that was received by the top ¹⁄1000 rose from 2.2% to 8.0%.

But we don’t know what these people typically do for a living. Kaplan and Rauh (2010) looked through publicly-available information on top executives of publicly-traded firms, financial professionals, law partners, and professional athletes and celebrities. Despite making various extrapolations beyond what is directly available in publicly-available data sources, they were only able to identify the occupations of 17% of the top ¹⁄1000 of income earners.

We tabulated individual income tax return data from the U.S.Treasury Department on what share of top income earners work in each type of occupation. Through this method we are able to account for the occupations of almost all top earners – for example, for over 99% of primary taxpayers in the top ¹⁄1000.

(I liberally edited without [] or ….)

They also looked at spouses of the well-paid, computed income shares, computed growth rates, and broke down the incomes into

• 1% ex ½% (rank 1,500,000–750,000)
• ½% ex 0.1% (rank 750,000–150,000)
• 0.1% (rank 150,000–1)

. All of this is at the end of the PDF, after the bibliography.

Anyway let’s give BCH a hand for providing us with useful information.

"Theory is easy. Data are hard."

(Source: web.williams.edu)

Incomes of the top .01%, 1915–2008 in France and United States

via @JWMason1

from the interactive The Top Incomes Database —

• you can select countries such as Argentina, China, Indonesia, Ireland
• and you can select upper quantiles like the lower half of the top percent; the .5%–.1%; top .1%; the top 10%–5%; and so on
• and you can get income controls, price level indices, number of tax units, number of adults — the things you need to divide by in order to make apples-to-apples comparisons

Wooo, data!

hi-res

by Rachel Johnson, Urban-Brookings Tax Policy Center Microsimulation Model

Reading about the early meanings of the phrase “middle class” it clearly refers to:

…someone with so much capital that they could rival nobles….. professionals, managers, and senior civil servants.

and not to “the broad shoulders" holding up society, which should properly be called "the working class".

In other words, not “normal” or “typical” people at all (typical being \$21k/year)—the “middle class” could accurately refer in the U.S. only to those making over \$100k/year. I.e., “possessing significant human capital” which allows them not to just have a job at a successful corporation and be a line-item on that corporation’s budget, but to extract significant wages from the economy.

(Source: The New York Times)

hi-res

Markets do not give things to the people who want them most.

The logic of Marshallian S&D curves are wonderful in several respects:

1. resolves the “diamonds and water paradox” (why does unnecessary jewelry cost more than necessary water?)
2. sounds reasonable across a variety of real-world scenarios (FCOJ futures, corporate bond issuance, grocery stores, machine parts, olive oil exports, Tyler Cowen’s umbrella term “markets in everything”)
3. actually works in experiments! The legend is that Vernon Smith used to say in class that Marshallian S&D was “just a theory” — and then was shocked that prices actually converged to the predicted `P*`

Here’s a great way to misapply the Marshallian logic and arouse my ire:

• Say "Markets make sure that people who want things more are the ones who get them."

That’s not what the theory says. We use the jargon willingness to pay or reserve price to talk theoretically about the maximum someone would counterfactually give up for something—and equate this (by rational consistency hypotheses) to how much utility they derive from obtaining it. (The experiments I mentioned above literally created a reserve price—a redeemable coupon for \$13 if you get the paper at `P*`, so we as non-omniscient lab-gods know that you actually assign a personal dollar value on the `good`—and know what it is. So the fact that those experiments worked doesn’t prove the extra assumptions about the way people’s consent, pleasure, engagement, and desires interface with an opportunity for economic exchange.) Laura’s measured willingness to pay does not say how badly she wants something relative to Gemma. Why? Because maybe Gemma is poor and Laura is rich.

In the real world, rich people engage in retail therapy at prices that would pay for a poor person’s housing and food for months.

Maybe it makes them feel good, or they do it as a way to socialise (if you don’t consider yourself rich but you’re reading this on a computer: do you socialise at bars or restaurants or just outside on the street? Why?), or maybe they’re bored. Whatever.

Clearly we can’t give Gemma £100 and give Laura £100,000 and conclude that Laura wanted the dress more because she paid more for it. It might be reasonable if both were in the same place with the same financial resources.

The mathematics behind the S&D graph aren’t that complicated. (It does require thought—but not years’ worth of thought—to understand the Marshallian model.) But still, I think because of the transition from English → maths → English, and the jargon words interposed with normal words, the overall rhetorical effect is to cover the obvious fact of inequality whilst redirecting attention to “optimal” (another jargon word budging in on the default namespace!) allocation.

The hypothesis of logarithmic utility per individual has been around since the 1700’s at least. (Implying €1000 means more to a poor person than to a rich person.) And yet people still use this fallacious reasoning that markets allocate goods to those who “want it the most”.

Sorry: willingness to pay is a function of both desire and of ability to pay.

"600 million Chinese living on \$600/year, and they need to get those people to \$2000/year"

• the same possessions
• made by people doing identical things
• with identical machines.
• There’s a price to equality. The way our lives have to become extensions of the production line.
• We work together
• we holiday together
• we sit in the same traffic jams
• we wear the same clothes
• we live in the same house
• we drive the same car
• we have the same ambitions.
• Nothing that I own is unique.
• That’s the price of watching the clock.

"America is a democracy of common possession"

Boy, you wouldn’t hear this narrative nowadays. Now all I hear talk about is economic inequality.

Nor would there be such an emphasis on mass culture. I guess the internet really has changed things.

God Bless the Child played by Eric Dolphy

people at three different socioeconomic levels in Mumbai

(Source: video.ft.com)

"We earned it"

• Mitt Romney: Everything Ann [Romney] and I have, we earned the old-fashioned way.
• @isomorphisms: No, no, he must have meant farming.
• @isomorphisms: Or taxing some serfs?
• @isomorphisms: Oh, wait, it's obvious. Owning the means of production. Yes, quite.
• I guess this is the flip side of "poor Americans == temporarily embarrassed millionaires". The rich need a rags-to-riches self-narrative as well.
• They can't be satisfied with: "Was born into a good family. Did not become Paris Hilton".
• @isomorphisms: What's not meritorious about "I was born into wealth and worked hard?" I think that reflects quite well on one's parents for not raising a party brat and on one's self for having the discipline and morals to avoid that temptation.
• @isomorphisms: So why does it have to be "It was all me, nobody helped me ever" ?