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How "Unequal" Is Your State?
Submitted by Salil Mehta via Statistical Ideas blog,
It's an appealing chart from this week's Economic Policy Institute's report, leveraging the fashionable, French economist Piketty's statistics, in order to illustrate how well the "top 1%" are doing in each of the 50 states. The report is provokingly titled: "The Increasingly Unequal States of America". But the report creates distortions in the truth. An important matter affecting hundreds of millions should also include a straight acknowledgement of probability theory. We see through this article, that beyond the obvious national-level inequality (those at the top versus those at the bottom), targeting state-level differences in values is perverse. The latter is more a matter of probability theory, involving large sample sizes.
Let's start by looking at this chart below. It shows the differences in state-level ratios, contrasting the typical incomes at the top 1% versus the typical incomes at the bottom 1%:
Everyone from the press, to news readers, gawk at how much each state's levels are, in relation to the levels of other arbitrary states. But this is irrational. Are liberal states such as California and New York, twice as biased (or twice as unfair) as conservative states such of Arkansas and Maine? Of course not. But that's the poor logic one would convey from the former two states showing nearly twice the inequality values on the chart, versus the latter two states. Ex-post examination of living costs doesn't fully explain things either, as expenses are generally higher in states such as Vermont, Alaska, and Hawaii, versus the expenses in states such as Texas, Illinois, and most of Appalachia.
This week I devoted a couple hours spelling out to a confused Wall Street Journal writer how there is some pertinence here, related to probability theory. Population size theoretically impacts these statistics, and only a small number of these states are grossly unequal enough to warrant exhibiting them through a charming, 50-state map. Whenever we are forced to explore state-level analysis though, it should be done through the prism of simply explaining relative variation, well beyond what random luck would suggest.
The most liberal people suggest that even thinking about this math is unnecessary. Perhaps any glorification of wrongs that need to be righted, justifies the means that it would take to get there. Over time this can conflate math ideas with one's ideological bias. We must separate the discussion of national and structural inequality, among a population, from one where there is a perceived advantage for some groups relative to others.
We can't prove the inappropriateness of inequality, by looking at the differences in relative inequality between states. We enjoy the right in the U.S. to pursue different outcomes. To take risks on the margins. We've been making many billions of these choices, across generations. This means that we always enjoy some separation in outcomes, particularly among the largest populations.
That's how probability theory impacts all of our lives, even in "equal" conditions. We would prefer a safety net against hard times. Yet we will still take risks such as how much and what we learn, what we feed our bodies, what we do on vacation, what financial investments we accept, when we plot a career change... the actions here can't be deemed some unfair inequality. They are the mystical elements we call life!
In a divergent context, we will always see these interesting differences (based upon population size alone), in areas that have nothing to do with the draw of inequality. Such as the state-level distribution of newborn baby sizes, or the performance distributions of high-school athletes. We'll mention others still later in this article. And all of this collectively confirms our understanding that there is something important to the probability math, explaining the relative dispersions connected to population sizes.
Before moving too far ahead, let's first show that the Economic Policy Institute (EPI) chart above has an obvious concordance between income dispersion and the population size itself. We'll use simple arithmetic(!) as well, substituting for a complex probability area known as copula math (here, and here). If there were no connection between a state's inequality calculations and the population rank, then how many states would be in the top 10 of both? What about in the bottom 10 of both? The answers are quite low:
(10/50)*(10/50)*50 = 2 states in the top 10 of both of both variables
(10/50)*(10/50)*50 = 2 states in the bottom 10 of both variables
So only 4 (2+2) states total. But it's easy to certify from the chart that there is much more of a match among these variables than 4.
Of the top 10 populated states, 5 were also among the top 10 "unequal" states: CA, TX, FL, NY, IL. Of the 10 least populated states, 4 were also among the 10 least "unequal" states: VT, AK, ME, HI. So instead of 4 overlapping states, we have a significantly higher 9 (5+4) states overlapping. Additionally, there are no crossover states (e.g., a highly "unequal" less-populated state, nor a less "unequal" highly-populated state). The easy math (9>4 with no crossovers) shows something, and it's not structural inequality.
The only common variable between the selection of the top 10 (and in the selection of the bottom 10) populated states is just population size itself! Does population size coerce inequality? Again, no. Otherwise we could just split California into two smaller states, making citizens suddenly feel there is somehow "greater equality". Or we could reunite Virginia and West Virginia, making the new super-state's citizens feel there is magically "greater inequality". But this sort of statistical reasoning is crazy. It leads one to think inequality can be solved with scissors and glue.
In our popular "Aristocrats in flyovers" article (a name suggesting easier state-level wealth in less-populated flyover states), we dig into the probability theory of extreme data. And there we continue to see this pattern show up repeatedly in diverse datasets. Such as the wealthiest individual per state, or the number of cumulative Miss America winners per state. Again this couldn't be coincidence, and we can also mathematically solve for the theoretical expected values for parametric most extreme individual, as we did in this article here.
Take a look at the bar chart below (of the top 1% income), and see in dots how tight the trend is for relative inequality, versus state population. We mathematically expect the more populated states to have considerably higher top 1% income (a double-digit percent increase!), versus the top 1% income in the less populated states- and this relates to the EPI chart above. Connecticut was the single, unreliable outlier removed, using a parallel statistical process others also do (notice Wyoming is missing in the aforementioned chart.)
We also show a related transformed bar chart, below, instead fixating on changes in the the relative standard confidence interval (as one moves across the chart from the less populated states, to the most populated states). We can now confirm that we mustn't ignore probability modeling as part of this story. We can't persistently pretend that less-progressively larger (a generally concave inequality dispersion function, similar to how it is with most economic data) inequality doesn't exist, for the most populated states.
Don't assume -as many lay people and activists do- that these are sampling errors that must vanish, as the sample population sprouts into the millions. This would be deceitful and cause most people to further jump on top of similar "research" as the EPI chart, falsely connecting most of the state-level calculation differences to genuine differences in inequality.
The conclusions of this article are again as pertinent for the top 1% in a population, as it is for the most extreme person in any group. This is since the top 1% is still extreme enough along the probability distribution (from 0%, to 100%), so that larger populations will lead to less-progressively larger, top percentile thresholds. Of course this is not true for sampling (Ch.5 in Statistics Topics) closer to the middle of a peer distribution (e.g., top 49%, or bottom 49%), where most of us in society have performed through the ages.
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Major click bait!
I"d love to see the same chart from the sixties.
The only common variables are; open borders, common core education, EBT, ZIRP, Hidden Inflation, Zerocare, Pork, and the fact that we live in a ONE party system, that s parades itself as equal halfs.
How do you factor the different cost of living in each state into that equation? I'd think that would make a big difference too.
I would guess that in the lower, middle, and upper classes, those who suck off the government teat are wealthier on average.
This article needs to be simplified for a simpleton like me. Or else, I just need to keep reading more ZH and hope that something gets through my thick skull.
"(a generally concave inequality dispersion function, similar to how it is with most economic data)"
Man, I love this stuff!
If population were the key variable, then Connecticut would not be ‘ahead’ of California & NY.
The author has applied his good knowledge of mathematics in an inappropriate way.
Connecticut has the most inequality because a lot of rich people live
in Greenwich and the other wealthy suburbs of Fairfield County.
In a healthy economy demand drives price... If the cost of living is rising and (WAGES)> demand aren't?
Now, on the other hand... If you see serious deterioration in State Services and infrastructure, then it's being subsidized.
Any Questions? SARC
Nevada's inequality makes total sense. A bunch of low income people gambling away what little they have to "hit it big" and all of that revenue goes into Wynn's pocket as the odds are heavily in favor of the house.
These gambling addicts are such a lost cause they will never even get it. Even if they "hit it big" they take their winnings and dump it right back into the slot machines, only for it to get lost again. No plan, no goal, no ambition, just fantasies of hitting it big. Even if they "hit it big" they would still need to feed the addiction as they have no idea how currency actually works.
I used to be mad at the Zionsts that run these casinos, but at the end of the day they have a role in this universe, the same way that fungus, bacteria, maggots, parasites and vultures feed off of dead corpses. The masses are spiritually, morally, philosophically, and psychologically dead and these parasites are feeding off of their corpses.
South Park did a recent episode where the kids are obsessed with freemium games like Candy Crush. The grandpa was upset with kids and their phones, yet he blows his whole retirement on slots which are just as Pavlovian as the kids' addictions he criticized.
I am not surprised that real math is taking a beating on ZH. Let's admit that most of ZH readers are not engineers or mathematicians, and indeed the article comments betray the unmistakable fact that most don't even have master's-degree-level experience in a technical field. This article belongs here to remind people that real statistics isn't as easy as it looks, and the MSM is horrible at it.
Fascinating and a little surprising.
The Yutes will have trouble believing this, but in the small town Midwest of my youth, money mattered a lot less. Incomes were not wildly different, but jobs were plentiful, and anyone with a job could buy a house, a couple of cars, and have a reasonable chance of raising some not bad kids. How far we have fallen.
So much more makes up the ultimate reasons why 'inequality' exists. Its much like the vaccous 'fairness' argument that goes over most peoples heads, too.
This is just the result of two entrenched political spoils systems.
Both red and blue teams reward their owners and cheerleaders.
'vacuous.'
We must need more immigration, more SNAP, and more bankers; that'll fix it!
Yeah, because it is evil capitalism that has caused the gap to increase between the wealthy and poor over the last 6 years. It has nothing at all to do with the Federal Reserve making it possible to inject trillions into the stock market...
Yawwwwn.
These "inequality" bullshit articles have become as monotonous as the "27 facts proving that the USA is in the crapper" articles.
C'mon, ZH, get a new routine schtick already.
Write something.
+1
I agree instead of yawning, type up something. The comments are more informative most times anyways than most of these articles.
You didn't read the article; it debunks a flawed methodology used in another MSM publication.
thanks bernanke /s
Good article IMO. Picketty sure received tons of accolades, but it is time to poke holes in his claims as the economic guru of the left. This article
is significant for that reason.
Inflationary policies of the governmetn are most pronounced in the states with the high ratios. Productivity opportunities are also greater in the more popular states
While I agree with one of the Author's assertions that the measure of fairness in a nation is not measured by the difference between the rich and poor since there will always be poor and rich...
This quote has me perplexed... " Are liberal states such as California and New York, twice as biased (or twice as unfair) as conservative states such of Arkansas and Maine? Of course not."
He bases his assertion on the population of the various states.
Is the author saying that Wall Street bankers are not that much richer than the poverty ridden upstate New Yorkers? Or that the Hollywood moguls are not that much richer than the illegal aliens that make up a large portion of that state? Or that the oil magnates in Texas are not that much richer in relative terms than the illegals in that state?
...Or that Maine with it's large timber and fishing industries, employing most of the population, inequality is greater than that of New York? And Arkansas has more rich, or richer people, and deeper poverty... than California?
Or is the author making a new class intelligentsia political point that liberal states cannot be more unequal by definition? By the argument that larger populations skew the results?
This article is BS. Gini coefficient is the standard for calculating meaningful inequality.
Of course Washington D.C. is the worst. The best? Why, Utah, of course(?) Guess all that family talk might have something beneficial to offer.
http://en.wikipedia.org/wiki/List_of_U.S._states_by_Gini_coefficient
You didn't read it. The article debunks the statistical method used in another MSM article.
Love to see the chart of California if they did it just by the Bay Area alone. Easily the most "unequal" place I've ever seen.
Take this chart down. Its far too truthful.
Jew New York.
Jew Florida.