I recently got into a fairly epic Twitter spat with U. of Maryland sociologist Philip N. Cohen when I pointed out, in defense of Charles Murray, that African-Americans’ height didn’t appear to be terribly depressed by nurture the way that Guatemalan Indians’ height appears to be depressed by malnutrition and oppression by Guatemalan mestizos. Witness, say, LeBron James.

Cohen was aghast that anyone would cite outliers, such as LeBron or NBA players, as evidence of anything.

But, actually, a very useful way to get a sense of what factors are driving data distributions is to review their left and right tails.

For example, consider Stanford economist Raj Chetty’s ranking of 2,478 counties in terms of income mobility for the children of working class parents. In which counties are the incomes of young adults around age 30 in 2011-2012 highest relative to the income of their blue collarish parents in 1996-2000? Chetty is looking for enduring truths about how best to nurture the next generation to succeed economically

Chetty has all your IRS 1040 returns from those seven years (anonymized, I hope), so we can look at in which counties kids of parents from the lower half of national income distribution in the late 1990s have done best in the early 2010s. Chetty has tried out various explanations for his findings such as integration and transit, but let’s just look at the Best 1% and the Worst 1% and you’ll get more of a clue than you will from listening to Chetty. Here’s his Top 25:

So, young adults from blue collar families in Sioux County, Iowa made 34.9% more in 2011-12 than you’d expect from their parents’ incomes in 1996-2000.

You’ve probably never heard of most of these counties, other than maybe #1 Sioux County, Iowa. They’re all small, highly white (with maybe a few Hispanics), rural, and have a lot of natural resources, such as crops or energy, per capita to sell to the Chinese.

And here’s Chetty’s Bottom 25:

Young adults in Shannon, South Dakota, which has since been renamed Oglala Lakota County (i.e., the Pine Ridge Indian Reservation) do 34.7% worse.

Chetty’s top and bottom counties in the USA seem pretty plausible as reflecting long term health and long term tragedy.

In contrast to the Top 25, the Bottom 25 are pretty diverse in both senses of the word. Some are Indian reservations, there’s Nome, Alaska, and a lot are quite black, such as Baltimore City.

Horry, SC is the mostly white giant Myrtle Beach golf resort destination that boomed during Chetty’s control period of 1996-2000, but was knocked flat by the Golf Depression in 2011-12.

In general, the Carolinas were hit very hard by 2008. Third worst is Forsyth County, NC, home of Winston-Salem, which has been growing steadily in population for decades.

A couple of years ago, I analyzed Chetty’s county-level analysis and explained in detail what he is doing right and what he is still doing wrong methodologically. As I’ve mentioned, the three remaining big methodological flaws are:

– Regression toward differing racial means is a big reason the top 25 are so white and the bottom 25 are so black and aboriginal.

– Chetty’s results are driven by temporary local booms and busts. For example, the Carolinas were doing well in 1996-2000 due to housing construction, lumber, furniture making, mortgages and banking, and golf, all of which were in collapse in 2011-2012. The Great Plains were doing mediocre in 1996-2000, in part because they have no trees. But after 2008, Carolinas’ trees were not in demand, while China was buying up everything that the Great Plains could produce.

– Cost of living impacts the results. Lots of people moved to lower cost of housing Southern states and put up with lower wages. I don’t think Chetty quite gets that.

– A fourth possible problem involves age of marriage. Chetty is looking at household income, so Utah does well in his analysis due to early marriages because a high proportion of 30 years olds in Utah are Married Filing Jointly taxpayers. In contrast, wealthy New York City looks mediocre because so many 30 year old women are still single. Maybe this is a reasonable way to do it, but I suspect a lot of NYC 30 year old women will have very high family incomes when they are married 40 year olds. Others, of course, will not. NYC is a more high risk/high reward mating market for ambitious women than is Utah.