Nate Silver’s posted a quick analysis today that purports to show that “education, not income, predicted who would vote for Trump.” This is a pretty important finding, if true, because it stands in contrast to a lot of post-election analysis that claims that Democratic abandonment of the white working class played a large role in Clinton’s defeat.
It would also be an impressive finding before the major academic surveys, such as the National Election Study and the Cooperative Congressional Election Study are released, since they are the gold standard in terms of helping us understand how individual demographic and attitudes predict vote choice.
Silver takes a smart cut at the income and education relationship by partitioning up counties by their median income and percent college degree, and then comparing the 2016 Clinton vote to the 2012 Obama vote. Here he can show in some of the educated counties, Clinton did remarkably well.
He acknowledges that income and education are highly correlated, however, so he takes a different cut at the data, looking at a set of counties with relatively high educational levels and only moderate income levels.
Silver describes one of these counties, Ingham County, MI, where he grew up, as
…home to Michigan State University and the state capital of Lansing, along with a lot of auto manufacturing jobs (though fewer than there used to be). The university and government jobs attract an educated workforce, but there aren’t a lot of rich people in Ingham County.
Clinton, he notes, did quite well there, even though incomes aren’t that high. In most places that fit this description, according to Silver, Clinton did quite well. This is evidence, he argues, that education, not income, was the driving force in the 2016 election.
This table is reproduced here.
Anyone who is familiar with higher education should immediately recognize this list. If you don’t, you will in a moment.
Silver notes that “many of the counties on the list are home to major colleges or universities, although there are some exceptions.” He notes Davidson County, TN and Buncombe County, NC as not “really college towns.”
Not exactly. Below I list the major universities in each of these counties. Silver hit the jackpot with his list: every single one is home to a large university, in most cases, a huge university.
It’s true that college students as a percentage of total residents is pretty small in Davidson, TN and Buncombe, NC, but I’d be pretty skeptical to generalize anything from the homes of country music, bluegrass music–what Silver calls “cultural havens” (Missoula MT and New Hanover NC fit into that category as well).
But the rest? Almost all are college counties. Most are home to huge institutions that are the dominant cultural and economic force in those counties. Of course they have a combination of high education levels and modest income levels. That’s life as a student and employee of a university! It’s no wonder that Clinton did relatively better in those counties.
This list may be indicative of the kind of cultural divide that Silver speculates about at the end of the essay. I’m far less certain that this reveals anything systematic about the relationship of income and education and vote choice more broadly.
It would also be an impressive finding before the major academic surveys, such as the National Election Study and the Cooperative Congressional Election Study are released, since they are the gold standard in terms of helping us understand how individual demographic and attitudes predict vote choice.
Silver takes a smart cut at the income and education relationship by partitioning up counties by their median income and percent college degree, and then comparing the 2016 Clinton vote to the 2012 Obama vote. Here he can show in some of the educated counties, Clinton did remarkably well.
He acknowledges that income and education are highly correlated, however, so he takes a different cut at the data, looking at a set of counties with relatively high educational levels and only moderate income levels.
Silver describes one of these counties, Ingham County, MI, where he grew up, as
Clinton, he notes, did quite well there, even though incomes aren’t that high. In most places that fit this description, according to Silver, Clinton did quite well. This is evidence, he argues, that education, not income, was the driving force in the 2016 election.
This table is r
eproduced here.
Anyone who is familiar with higher education should immediately recognize this list. If you don’t, you will in a moment.
Silver notes that “many of the counties on the list are home to major colleges or universities, although there are some exceptions.” He notes Davidson County, TN and Buncombe County, NC as not “really college towns.”
Not exactly. Below I list the major universities in each of these counties. Silver hit the jackpot with his list: every single one is home to a large university, in most cases, a huge university.
It’s true that college students as a percentage of total residents is pretty small in Davidson, TN and Buncombe, NC, but I’d be pretty skeptical to generalize anything from the homes of country music, bluegrass music–what Silver calls “cultural havens” (Missoula MT and New Hanover NC fit into that category as well).
But the rest? Almost all are college counties. Most are home to huge institutions that are the dominant cultural and economic force in those counties. Of course they have a combination of high education levels and modest income levels. That’s life as a student and employee of a university! It’s no wonder that Clinton did relatively better in those counties.
This list may be indicative of the kind of cultural divide that Silver speculates about at the end of the essay. I’m far less certain that this reveals anything systematic about the relationship of income and education and vote choice more broadly.