Vaguely interesting (March 24)

(1)  “[W]e found no support for the hypothesis that life history strategy predicts cooperation or that early childhood environments interact with current resource scarcity to predict cooperation.”

(2)  “[T]he observed wage patterns are most consistent with men marrying when their wages are already rising more rapidly than expected and divorcing when their wages are already falling, with no additional causal effect of marriage on wages.”

(3)  “The median national [adolescent birth rate (ABR)] fell 40% from 72.4/1,000 in 1990 to 43.6/1,000 in 2012. The largest regional declines in ABR occurred in South Asia (70%), Europe/Central Asia (63%), and the Middle East/North Africa (53%).”

(4)  “Half of the public incorrectly thinks the [ACA] allows undocumented immigrants to receive financial help from the government to buy health insurance.”

(5)  “The ‘game of chicken’ which could be a serious problem for driverless cars.” (Calls to mind Kurzban’s opening story in Hypocrite of the difference between crossing the street in Philadelphia vs. Southern California.)

(6)  “National turnout of eligible voters was 60.2% – 1.6 percentage points above the 58.6% turnout in 2012, though slightly lower than 2008.”

The demographics of liberals and conservatives (with CCES data)

I previously looked how demographics—race, religion, gender, and so on—relate to whether people are more liberal or more conservative on Pew’s ideology scale, which combines ten different issue items (on government spending, environmental regulation, race, immigration, homosexuality, and so on) into a single measure. Today, I’ll do the same thing with data from the recently released 2016 Cooperative Congressional Election Study (CCES).

The best thing about the CCES is that it’s yuge. The Pew data in my prior post included around 16,000 survey-takers, which is pretty damn good, but this CCES sample is over 64,000. (According to, this is pronounced: siks-tee fohr muhth-er fuhk-ing thouzuhnd.)

The pre-election wave of the CCES included a number of questions about policy preferences. I chose a set of ten of these to make my CCES ideology scale—including items on assault rifles, conceal-carry permits, border patrols, deportation, abortion rights, abortion funding, environmental regulations, same-sex marriage, government spending priorities, and the minimum wage (I include the full items at the bottom of this post). Most of the CCES issue questions were in a binary support/oppose format, which made the ideology scale straightforward: For each of the ten policy items, I coded the liberal option as 1 and the conservative option as 0, and then added them all up. Thus, an extreme liberal would score 10 (by giving the liberal response on all ten survey items) and an extreme conservative would score 0.

The CCES has a nice range of demographic information, including race, religion, church attendance, age, gender, education, income, marital status, employment status, sexual orientation, transgender status, whether the respondents have been union members, whether they’ve served in the military, whether they own their home, whether they invest in the stock market, and whether they or their parents are immigrants.

In short, I took the 10-point issue-based ideology scale and started looking for demographic splits. The biggest deals were sexual orientation and religion, so I first split up the sample by the major divisions there. Then I went into the largest of the remaining subgroups and looked for whatever the next-biggest deals were, and created even smaller subgroups, and so on. I stopped when I had 24 subgroups. These 24 groups are mutually exclusive and encompass the entire sample.

And that’s what’s shown on the two charts below. They contain each group’s average score on the 10-point issue-based ideology scale. In the first chart, I show the most liberal six groups and the most conservative six groups. So, the first line is “LGBT; Atheist/agnostic”—these are people who both (1) indicated that they are either lesbian, gay, bisexual, or transgender and (2) chose either atheist or agnostic as their religious category. And it’s just a really liberal group. When asked the ten different issue questions, they chose the liberal responses on 8.5 items on average. In fact, almost two-thirds of these folks are mega-liberals (scoring 9 or 10) while less than 1% are mega-conservatives (scoring 0 or 1). The most conservative group is at the bottom of the chart—straight (i.e., not LGBT), evangelical, white, male homeowners. They average around 2.6, where over 40% are mega-conservatives while less than 3% are mega-liberals.

Overall, on the first chart above, the most liberal groups are a sort of demographic rebel alliance, including many LGBT folks, atheists/agnostics, other non-Christians (Jews, Buddhists, “nothing in particular,” and so on), and racial minorities. (Keep in mind, though, that we’ve got a second chart coming, which will show some not-so-liberal LGBT folks, non-Christians, and racial minorities. For example, LGBT folks who are also either evangelicals or military veterans are actually middle-of-the-road on average.)

The most conservative groups, in contrast, are almost all anchored by straight, evangelical whites. In fact, I ended up with five groups made up of straight, evangelical whites, and they’re all among the six most conservative groups. The other group showing up here includes straight, white, non-evangelical Christians who are male military veterans.

The second chart below shows the 12 groups in the middle. As I mentioned, some of the more interesting ones here involve groups you’d normally think of as pretty liberal—LGBT folks, non-Christians, and racial minorities—that actually aren’t so liberal among some narrower segments. These include: straight atheists and agnostics who’ve never attended college; other straight non-Christians who don’t have 4-year degrees or who are military veterans; straight, Christian Hispanics and Asians; straight, evangelical blacks; and, as already mentioned, LGBT folks who are either evangelicals or veterans.

Another way to frame what’s going on here is to think about the averages on the 10-point issue-based ideology scale as simultaneously influenced by a wide range of characteristics. Some demographic features push the average up in a more liberal direction (being LGBT, atheist/agnostic, black, etc.) and other features push the average down in a more conservative direction (being evangelical, white, a veteran, etc.).

In fact, here’s some actual math allowing you to estimate the average ideological positions of a wide range of very specific profiles:

  • Think of a group defined simultaneously by LGBT status (yes/no), religion (atheists and agnostics vs. other non-Christians vs. non-evangelical Christians vs. evangelicals), whether they attend religious services more than once a week (yes/no), race (white/black/other), veteran (yes/no), whether they have PhDs, MDs, MBAs, or other graduate degrees (yes/no), and gender (female/male).
  • Start with 6.4.
  • Then, if applicable to the group you’re thinking about, add 1.3 for LGBT folks, 1.3 for atheists/agnostics, 0.9 for blacks, 0.7 for folks with graduate degrees, and 0.7 for women.
  • Then, if applicable to the group you’re thinking about, subtract 2.1 for evangelicals, 0.8 for whites, 0.8 for folks who go to religious services more than once a week, 0.7 for veterans, and 0.7 for non-evangelical Christians.

The result gets you very close to that group’s average on the 10-point ideology scale. A quick example. People similar to Barack Obama: start with 6.4, add 0.9 (black), add 0.7 (grad degree), and subtract 0.7 (non-evangelical Christian). The result is 7.3, a rather liberal average.

From these numbers, you can see where the big-deal divisions are. Atheists/agnostics (+1.3) and evangelicals (-2.1) are, thus, on average, 3.4 units away from each other. Blacks (+0.9) and whites (-0.8) are, on average, 1.7 units apart. LGBT folks are, on average, 1.3 units more liberal than straight folks. As shown in the charts above, these can really add up when people contain multiple features pointing in the same direction (e.g., people who are both LGBT and atheist/agnostic), but can also create politically conflicted groups when some major feature pushes one way and another pushes the opposite way (e.g., people who are both evangelical and black).

Unpacking ideology

On the issue-based ideology scale I’m using here, fewer than 30% of the CCES sample are mega-liberals (with scores of 9 or 10) or mega-conservatives (with scores of 0 or 1). The other 70% have at least a couple of liberal views and a couple of conservative views among their ten issue positions. In fact, almost a third of the sample have more-or-less equal numbers of liberal and conservative issue opinions, landing in the middle range from 4 to 6.

Ideological consistency is a big and growing deal, but there remain interesting domain-specific factors creating ideological divergence. I’ve showed some of that in various posts I’ve done (mostly using Pew data) on the demographics of specific issues—for example, racial discrimination, marijuana legalization, income redistribution, and views on immigration and Islam—and especially when I directly contrasted white nationalist vs. economic issues, white nationalist vs. lifestyle issues, and economic vs. lifestyle issues.

And then Kurzban and I have a book that systematically goes through the varying demographic differences driving a wide range of political issues, mostly using data from the General Social Survey (GSS). There, we also spent a lot of time trying to figure out why there are all these domain-specific demographic patterns, and we primarily chalked it up to interests. Really, though, lots of the major pieces of political analysis are hard to tease apart—there’s a big overlap among interests, identities, demographics, ideology, partisanship, and issue positions.

I might do some issue-specific analyses of the CCES data in future posts. But online panels like the CCES are probably better for large-scale ideological patterns than for specific issues. Ideological clustering tends to be significantly stronger in online samples (and then it’s a bit less strong in phone samples like Pew, and then weaker still in knock-on-doors samples like the GSS), so the CCES probably overstates the similarity of demographic predictors across different kinds of issues. But, still, I might give it a shot. It’s just a blog after all.

Notes for nerds: Variables and terminology

I used CCES’s “commonweight” weighting variable for all analyses.

Here are the ten policy items from the CCES that make up my ideology scale: Ban assault rifles (support=1 and oppose=0); Make it easier for people to obtain concealed-carry permit (oppose=1 and support=0); Increase the number of border patrols on the U.S.-Mexico border (not selected=1 and selected=0); Identify and deport illegal immigrants (not selected=1 and selected=0); Always allow a woman to obtain an abortion as a matter of choice (support=1 and oppose=0); Prohibit the expenditure of funds authorized or appropriated by federal law for any abortion (oppose=1 and support=0); Strengthen enforcement of the Clean Air Act and Clean Water Act even if it costs US jobs (support=1 and oppose=0); Allowing gays and lesbians to marry legally (favor=1 and oppose=0); Raise taxes and cut defense rather than cut domestic spending (favor=1 and oppose=0); Raise the federal minimum wage to $12 an hour by 2020 (for=1 and against=0).

To arrive at the issue set, I used stepwise regression involving a number of CCES policy items to predict self-labelled ideology, party identification, and the two-party 2016 presidential vote. I selected the ten items that made the biggest contributions to these regressions. That is, I wanted a set of items, each of which contributed in its own way to predicting broad political orientations and voting.

Some terminology: “White” includes non-Hispanics who were coded as either white, native, or other. “Hispanic/Asian” includes Hispanics (regardless of other racial category), Asians, Middle Easterners, as well as mixed-race individuals. “Evangelical” includes all non-Catholics who identified as “born again or evangelical” as well as Mormons.

Voting against their own interests

In this week’s New York Magazine, Frank Rich repeats the what’s-the-matter-with-Kansas theme, claiming that working-class whites are “voting against their own interests.” I get why it’s a popular line on the left. In short, it frames white working-class support for Republicans as a simple failure of rational understanding, one that, if it could only be remedied, would result in landslide Democratic victories.

But it’s a fantasy. Worse, for liberal strategists it’s dangerous. The Kansas trope is selectively applied and unrealistically narrow, it misunderstands the nature of some central political fights, and it’s largely at odds with what we know about actual patterns of voting and non-voting.

If poorer Republicans are voting against their own interests, doesn’t that mean that wealthier Democrats are as well?

Since grad school, I’ve been involved with a longitudinal study of the Harvard Class of 1977. This class includes Bill Gates, Steve Ballmer, Mad Money’s Jim Cramer, and lots of other overachievers. Its members have median family incomes around the top 1% or 2% of the country. And it has many more Democrats than Republicans.

So why aren’t we asking, you know, what’s the matter with Harvard? Why are they voting against their own interests by supporting big-spending tax-raisers? Are they just fools in the end, unable to align their votes with simple rational understanding?

Actually, no. No, they’re not. And here’s why.

Tangible interests go beyond rich-poor issues

In addition to being a pretty wealthy group, Harvard graduates are also singularly reliant on meritocracy. And the main threat to meritocracy is group-based discrimination, discrimination that seeks to undermine education-based and performance-based regimes in favor of allocating societal benefits to white, native-born, male, heterosexual Christians.

Sure enough, if you look within the Harvard Class of 1977, the tilt towards Democrats is especially strong among blacks, women, LGB folks, and non-Christians. In addition, Democrats are more prevalent among members with family incomes below the top 1%. So, for example, there’s a segment of this Harvard Class that is actually (modestly) more likely to contain Republicans than Democrats: White, Christian men with incomes over $500k who aren’t married to working women (think, e.g., of George W. Bush and Mitt Romney).

So, really, it isn’t that Harvard folks are ignoring their interests. It’s instead that interests are multifaceted. In a time and place in which anti-discriminatory factions are in the opposing coalition from anti-redistribution factions, these ultimate meritocrats mostly choose the anti-discrimination coalition. That is, they do so unless they’re both super-rich and have group-based features that make them less concerned about discrimination, in which case they’re marginally more likely to choose the anti-redistribution coalition.

Is something similar happening with working-class whites? Are they taking into account a broader range of tangible interests? Actually, yes. Yes, they are.

Plunder and some zero-sums

We meritocrats are so opposed to group-based discrimination that we often don’t want to admit that anyone at all might be better off under old-style bias. I’ve been a bit surprised, then, by the popularity of Ta-Nehisi Coates, who (for example, in making the case for reparations) argues forcefully that America’s racial history has largely been about plunder. In a 2013 essay, he states it starkly:

“It is important to remember that atrocity is not simply insanity, that it is often not insanity at all, but hard interest, that even in the Holocaust there were interests, that there were winners and that they saw themselves as such. In our own land, we have long observed this. To better avoid the painful fact that there were ‘winners’ in a slave society, that those winners were not merely great planters, to avoid the fact that ordinary Americans are indicted in all that came from slave society, we discuss the ‘race problem’ as though it were a problem of manners and civility. I am sure the average African-American in 1963 could empathize with the dream of little white boys and little black girls holding hands. But he likely would have settled for a day when white people would no longer see him and his family as a field for plunder.”

And plunder, for Coates, is not limited to slavery or the Jim Crow South, but extends as well to more recent discrimination—in housing and lending markets, in employment, in law enforcement, and so on. Coates writes that “behind every great atrocity stands some particular winner,” but it’s true of the less great and less atrocious as well. When a white hiring manager at a plant is racially biased, there are particular jobs that some whites will get and minorities won’t. When an employer pays women less for the same work, that’s extra profit for the employer. Not everything is zero-sum, of course, but some things are.

The bottom line is that the fight between meritocracy and discrimination may not be about redistribution, but it’s nonetheless about distribution. It’s about the allocation of tangible benefits between white, native-born, straight, Christian men who happen to kind of suck at meritocracy, on one side, and non-whites, immigrants, LGBT folks, non-Christians, and women, particularly when they happen to be good at meritocracy, on the other side.

And, indeed, just as the Harvard folks are particularly Democratic when they’re blacks, LGB, non-Christians, or women, working-class folks are particularly Republican when they’re white, heterosexual, Christian men. Even in the Clinton-Trump race, straight, Christian whites with 4-year college degrees favored Trump, while whites without college degrees who are LGBT or non-Christians actually favored Clinton. These folks are not ignoring their interests.

Recognizing that group-based discrimination has winners is important in developing effective countermeasures. In particular, this isn’t just about teaching perspectives or good morals (or Coates’s “manners and civility”) or whatever; it’s about changing cost-benefit calculations. Indeed, I’ve argued that that’s what political correctness is—it’s the imposition of tangible costs on the coordinating signals of discrimination.

The Kansas thing isn’t really true on its own terms

In short, the main problem with the “voting against their own interests” claim is that it ignores interests that don’t relate to redistributions from rich to poor. And it’s actually discriminatory interests that primarily explain why working-class whites often vote Republican these days and why this is particularly the case among white, heterosexual, Christian men.

But there’s also more. The Kansas line has never really been all that convincing on its face. So, for example, when I looked at the demographics of the Obama elections, there were a couple of Kansas-relevant points: Within whites without college degrees, (1) those with low incomes tended to be less supportive of Republicans than those with higher incomes and (2) those with low incomes were just less likely than others to vote at all.

In other words, in the Obama era (and before) it simply wasn’t the case that whites with both less education and low incomes were particularly big Republican voters. Indeed, the only big Republican group I found among non-degreed, low-income whites was churchgoing evangelicals. And even those folks were noticeably more likely to sit out the Obama elections than were higher-income white evangelicals.

Among Harvard folks, both rich-poor interests and discriminatory interests factor into their voting decisions—that’s why both income and various group-based features predict their partisanship. And the same is true among the working class, where things like race, sexual orientation, religion, and gender have their effects, but so does income.

The Trump election does appear to have pulled a significant number of non-degreed, low-income whites off the electoral sidelines. Trump promised them more discrimination but not less redistribution, which would have been a sweet combo deal for them.

He now seems determined to break the latter promise. This might return some low-income whites to the sidelines, continuing their long dissatisfaction with elites in both parties. But it won’t be because they suddenly realized what their interests are. They’ve known that all along, the Kansas trope notwithstanding.

Vaguely interesting (March 17)

(1)  “Self-deception facilitates interpersonal persuasion.”

(2)  “Is it fun to find out that a study you published in a high profile outlet back in the day does not hold up well to more rigorous scrutiny? Oh hell no. I highly recommend you avoid the experience. How do you avoid the experience? Make sure you’re more rigorous up front. More power. Open science, etc.”

(3)  “Some researchers now believe the brain … can only be understood as an interplay between tremendous numbers of neurons distributed across the central nervous system.”

(4)  How many people in the U.S. have children with more than 1 partner? It’s about 20% of those with 2 or more kids.

(5)  Choose your own adventure: Might moving farther to the economic left help parties reverse the global rise of ethno-nationalism? Yes! No!

(6)  “Well-educated and nonwhite workers in fast-growing and wealthy urban areas are capturing the lion’s share of economic gains.”

The politics of good and bad test takers

Should we increase taxes on the wealthy and use that money to give more help to the poor? Should we increase efforts to deport undocumented immigrants? Because of past discrimination, should businesses make special efforts to hire and promote blacks? Should abortion generally be legal? Should we allow teacher-led prayer in public schools?

There are many demographic differences in public opinion on these kinds of questions—differences related to race, religion, income, gender, and so on. And a lot of them aren’t very hard to understand. For example, poor people and minorities are much more likely than whites with higher incomes to favor increased income redistribution. Native-born folks are much more likely than immigrants to think that immigration is a burden on the country. Blacks are much more likely than whites to think that the country needs to make further changes to address racial discrimination. People who sleep around a lot and have fewer children are much more likely than monogamous, high-fertility types to think that abortion should be legal. Christians are much more likely than non-Christians to favor school prayer.

Another demographic factor that matters involves how well people do on tests. Sometimes surveys give people political knowledge tests, vocabulary tests, basic science tests, and so on. And it turns out that, on various kinds of political issues, good and bad test takers differ on average.

I’ll argue later in this post that—like differences related to race, religion, and so on—the political differences between good and bad test takers also often aren’t very hard to understand. But to see the patterns with test taking, there are hurdles to be cleared. Most politically engaged people are invested in the ideas (1) that there are correct answers to questions of political values and (2) that the people on one’s own political side are basically by definition smarter because they recognize these correct answers. Thus, unlike differences based on income or gender or whatever, people often really want and expect that the better test takers will favor their own political side. In contrast, I’ll suggest a different way to think about it.

But first let’s see what the political differences actually are.

The issue positions of good and bad test takers

The U.S. General Social Survey (GSS) often gives a 10-item multiple-choice vocabulary test. It also recently often includes a set of basic science questions—for example, true or false: The center of the Earth is very hot; All radioactivity is man-made; It is the father’s gene that decides whether the baby is a boy or a girl; Lasers work by focusing sound waves; Electrons are smaller than atoms. I chose a set of 10 of these science items, all of which are entirely non-political (that is, I did not include anything on evolution, global warming, etc.).

In the GSS waves from 2006 to 2014, there were over 3,400 people who were given both the 10-item vocabulary test and the 10-item science test. I’m using this portion of the sample that was given all 20 items—that’s the “test” when I’m talking about “test takers.” These folks were also asked various political issue opinions (some of the political items were asked to all of them and others to only a subset, though every political item I’m looking at was asked to at least 1,300 test takers).

Now, what are the issue differences relating to test performance? I’ve split it up into three charts. The first one below shows issues on which good test takers are more liberal than bad test takers. Rather than showing a bunch of numbers, I’m just using colored circles for various percentiles of test performance from the 5th to the 95th. Red circles indicate conservative averages, blue circles indicate liberal averages, and various shades of reddish and blueish purple are in between.

So, the first line on the first chart involves free speech issues—these are items where respondents are asked whether various unpopular groups should be allowed to give public speeches, have their books in libraries, and teach at public colleges. Here, those with good test performance are much more likely than those with poor test performance to say “yes.”

In addition, the good test takers are more likely than bad test takers to: find no moral issue with homosexuality, favor a ban on school prayer, disagree that traditional gender roles at home are generally best, disagree that blacks lack motivation, favor the legality of same-sex marriage, favor the legality of abortion, favor more government spending on science, agree that blacks lack an equal chance at education, disagree that men are better suited for politics than women, favor the legality of marijuana, favor more government spending on alternative energy, favor more government spending on mass transit, and disagree that blacks should be expected to work their way up without assistance like various white immigrant groups have.

The next chart shows issues on which good test takers are more conservative than bad test takers. Here, the good test takers are more likely than bad test takers to: disagree that businesses should make special efforts to hire and promote women, agree that police are sometimes justified in hitting adult males, favor more government spending on the space program, disagree that businesses should make special efforts to hire and promote blacks, want less government overall, think that the government should not concern itself with reducing income differences between the rich and the poor, disfavor higher government spending on or more help for the poor, disfavor higher government spending on Social Security, think divorces should be harder to get, disfavor higher government spending on welfare, disfavor government help for blacks, and disfavor higher government spending on or more help with healthcare.

And, lastly, the third chart below shows the issues that don’t have a big linear relationship with test performance—that is, the good test takers don’t differ very much from the bad test takers (though, in some cases, the good and bad test takers differ meaningfully from the middle-of-the-road folks; more on that in a bit). These issues involve: whether pornography should be legal, whether there should be more government spending on the environment, whether premarital sex is morally acceptable, whether there should be more government spending on the military, whether immigration levels should be reduced, whether premarital sex between teens is morally acceptable, whether public schools should include sex education, whether courts should be more or less harsh, whether there should be more government spending on education, whether the death penalty should be used, whether birth control should be available to teens without parental consent, whether there should be more government spending on blacks, whether the main cause of racial disparities is discrimination, and whether there should be more government spending on childcare.

As I mentioned, some of the issues show non-linear patterns—typically where both the best and worst test takers are more liberal than folks in the middle. Most of these issues relate (directly or indirectly) to race. So, on the last chart, take a look at the responses on immigration, how harsh courts should be, the death penalty, and whether blacks face discrimination. Similarly, on the second chart, this non-linear pattern shows up on affirmative action for blacks, spending on welfare, and government help for blacks. On the first chart, it peeks through on whether blacks lack a chance at education and whether blacks should be expected to work their own way up.

Are the best test takers liberal or conservative? Both/neither/it depends.

If we focus on the very high end (the 95th percentile), within the issue set I looked at, here are the 15 positions they are most unusually likely to hold relative to the rest of the public: (1) people from unpopular groups should nonetheless have the right to make speeches, teach, and have books in libraries; (2) the existing ban on school prayer should continue; (3) women should not get workplace affirmative action; (4) black achievement isn’t being held back by a lack of motivation; (5) government spending for space exploration should be increased (or at least not reduced); (6) homosexuality isn’t wrong; (7) blacks should not be expected to overcome prejudice and work their own way up like white immigrant groups have; (8) black achievement is being held back by a lack of educational opportunity; (9) Social Security spending should be reduced (or at least not increased); (10) traditional gender roles in the home aren’t generally best; (11) police are sometimes justified in hitting adult males; (12) immigration levels should be increased (or at least not reduced); (13) government healthcare spending should be reduced (or at least not increased); (14) abortion should be legal; (15) same-sex marriage should be legal.

Some of these positions are more typical of people who call themselves “liberal” (1, 2, 4, 6, 7, 8, 10, 12, 14, and 15) while some are more typical of people who call themselves “conservative” (3, 5, 9, 11, and 13). Really, though, the positions are most consistent with what is usually thought of as libertarian, which is a key reason why some libertarians favor epistocracy proposals that allocate more voting power to better test takers. Some issues don’t fit the pattern, though. For example, high-end test takers are more likely than others to favor the Supreme Court’s ban on school prayer and to favor higher government spending on the space program—positions not usually associated with libertarians.

And it’s really not that the best test takers are liberal on “social” issues but conservative on “economic” ones. On social issues, for instance, these folks tend to oppose traditionally discriminatory stuff (e.g., they don’t like school prayer, they don’t endorse stereotypical gender roles, they’re accepting of immigrants and homosexuals, and they see a lack of educational opportunity rather than a lack of motivation as more important to racial disparities) but they tend not to want workplace affirmative action. On economic issues, while they’re stingier than others with government money when it comes to Social Security, healthcare, and the poor, they’re actually more likely than others to favor government money for science, alternative energy, and mass transit.

A matter of interests

At this point, libertarian readers are likely to be high-fiving themselves, while liberal and conservative readers are likely to be coming up with a series of “yeah, but” objections (or, really, many have probably already clicked away). Both reactions, I think, come from the same set of shaky premises. Basically, they both assume that to say “the best test takers generally want political position X to prevail” somehow implies “political position X is something everyone ought to want to prevail”—as though political values present straightforward factual questions that have universally correct answers.

Kurzban and I proposed a different way to think about it. We focused on interests—whether different political outcomes help or hurt one’s self along with one’s family and social network. From this perspective, lots of demographic differences in political positions come into greater focus. It helps explain why poor folks and minorities tend to be a lot more liberal than wealthier whites on government safety nets. It helps explain why racial minorities are most opposed to racial discrimination, religious minorities are most opposed to religious discrimination, LGBT folks are most opposed to discrimination against LGBT folks, immigrants are most opposed to discrimination against immigrants, and so on. It helps explain why churchgoers are so much more conservative on sexual and reproductive lifestyle issues (abortion, pornography, marijuana, etc.), taking into account that people tend to adjust their level of religious attendance to match their own lifestyles.

And it helps make sense of the various patterns involving test-taking performance. Most obviously, good test takers really tend to like meritocracy—that is, they tend to want social advantages to be allocated based on test-taking ability and educational pedigree rather than based on the old divisions of race, religion, gender, and so on. From an interest-based perspective, it’s just not surprising that better test-taking performance correlates with wanting an open marketplace of ideas, with opposing the old barriers to meritocratic success, and so on. It also helps explain their relative opposition to workplace affirmative action—good test takers aren’t defending liberal positions here, but rather meritocratic ones, which involve opposing both disadvantages and advantages that are based on the old group-based criteria. And it helps explain why, when diagnosing the causes of racial inequality, they see it not as hopeless character defects but rather as a lack of educational opportunities.

And it goes the other way as well. If they’re adopting positions in their interests, don’t expect bad test takers to agree that social advantages should mostly come down to test-taking ability and related educational matters. Expect them to seek advantages where they can find them, including in ways meritocrats find deplorable.

While the primary effect of test-taking performance is on issues relating to meritocracy vs. discrimination, there are secondary themes as well. Good test takers tend to wait longer to have kids—and they’re more liberal on abortion. Good test takers tend to be wealthier—and they have stingier views on government spending on the poor. Good test takers are more likely to work in brainy fields—and they have more generous views on government spending on scientific pursuits.

It’s not that these kinds of interests explain everything or are the single most important factor in public opinion. Yet these concrete interests are in the mix of big-deal factors.

Lots of the political outcomes that good test takers want are the sorts of outcomes that would disproportionately benefit good test takers. On many of these issues, it actually wouldn’t be very smart for bad test takers to agree with them.

Vaguely interesting (March 11)

(1)  “White evangelicals believe they face more discrimination than Muslims.”

(2)  “In the first two months of 2017, apprehensions of people crossing into the US from Mexico have fallen by more than half.”

(3)  “1947: 41% of Americans disapprove of ‘having more women serve as governors, senators, doctors, lawyers and in other professions.’”

(4)  “15 percent of American men between the ages of 25 and 54 currently aren’t working.”

(5)  “Since 1996, arrests of juveniles have fallen by two-thirds. Arrests for violent crimes have fallen by more than two-thirds.”

The Trump coalition

I’ve been going through the 2016 Cooperative Congressional Election Study, which was released last week. So far, I’ve noted that the primary demographics dividing Clinton and Trump voters followed the familiar themes of race, religion, and sexual orientation, but that Trump also appears to have attracted substantial numbers of whites without college degrees who didn’t vote in 2012.

The chart below combines these points, using the same breakdown from my demographic post, but showing as well how the 2016 CCES respondents reported voting in the 2012 Obama/Romney election. The sample here is limited to those who were old enough to vote in 2012. It includes both voters and non-voters, which is why the percentage voting for the two major-party candidates often doesn’t come close to 100%—most of the rest were non-voters (but also including some third-party voters).

You can see that Clinton attracted a similar percentage of each group as Obama (that is, the two blue lines within each group are pretty similar), but that there were several groups where Trump attracted substantially bigger percentages than Romney. This was particularly true among the groups that consist of whites without 4-year college degrees. I’ve tagged the biggest ones in the chart (with the T>R boxes), groups in which the percentage voting for Trump exceeded the percentage voting for Romney by 12 to 14 points, even though Clinton had come up short of Obama in these groups by only 3 to 5 points—that is, Trump pulled a bunch of non-voters (or non-major-party voters) off the sidelines among whites without 4-year degrees.

(Note: See the chart notes in my previous post for explanations of various terms.)

The Old Guard vs. the New Blood

The 2016 CCES is suggesting that, by pulling former non-voters into the mix, Trump expanded the Republican coalition without shrinking (much) the Democratic coalition. The Trump coalition, then, is one that adds new blood to an old guard.

So who are the old guard and the new blood? Specifically, among whites without 4-year degrees who voted for Trump (and who were old enough to vote in 2012), what are the major demographic differences between those who voted for Romney and those who didn’t?

The chart below shows two of the major differences. Primarily, among whites without 4-year college degrees who voted for Trump, those who are older and have higher incomes are substantially more likely to have also voted for Romney. For example, around 84% of Trump voters also voted for Romney among Baby Boomers and older folks with incomes above $40,000. Yet when we look at those who are young and poor—among white, non-degreed Trump voters who are Millennials with incomes below $40,000—only around 39% had voted for Romney (most of the rest didn’t vote at all, though, again, all these folks were old enough to vote in 2012).

And you may ask yourself, well, how did I get here?

Thus, as far as I can tell from the 2016 CCES data, the Trump coalition consists of a bunch of prior Republican voters plus a substantial new injection, many of whom are formerly sidelined non-degreed whites who are younger and have lower incomes.

Kurzban and I wrote The Hidden Agenda of the Political Mind between the 2012 and 2016 elections. Based primarily on General Social Survey data, we had spotted the pattern where lots of low-education and low-income whites weren’t voting (something that also shows up in the 2012 CCES data). Our diagnosis was that these folks were a relatively bad fit for the existing parties. In short, there were a lot of downscale whites who weren’t voting because they didn’t have candidates plausibly offering what they generally wanted—white nationalist priorities combined with left-leaning economic positions. We wrote (from p. 191):

“Is it any wonder, then, that so many downscale whites don’t vote? They typically favor robust income redistribution as well as group-based barriers. Democrats, on the one hand, favor income redistribution but oppose group-based barriers, and, worse, when push comes to shove, Democratic elites are more likely to protect human capital and cave on income redistribution. Republicans, on the other hand, oppose income redistribution and favor (some) group-based barriers; yet when push comes to shove, Republican elites are more likely to protect wealthy privilege and cave on group-based barriers. Unlike many European countries, the United States has no nationalist populist party that prioritizes the positions of downscale whites.”

Though we didn’t have a crystal ball, turns out that 2016 was their year. Trump campaigned on a platform of white nationalism (e.g., stressing a crackdown on immigrants and Muslims, favoring stop-and-frisk policing, and generally disdaining “political correctness”). And he combined it with an unorthodox mix of economic themes that emphasized working-class jobs (e.g., in manufacturing and the military) and gave assurances that he’d be gentle in altering redistributive policies (e.g., Trump’s promises that everyone would have great healthcare, that tax cuts wouldn’t be primarily for the rich, and that Social Security would be protected). He built it and they came.

Last in, first out?

So now a key question is whether these new Trump voters will stick around. Republicans are currently pushing an Obamacare replacement that would primarily give large tax cuts to the rich while reducing benefits for the poor. And Republicans see further tax cuts—again mostly for the rich—as another of their early priorities. And, not coincidentally, the drain in revenues created by these tax cuts will lead to further calls to reduce entitlements.

Will these kinds of legislative priorities end up returning significant numbers of Trump’s new blood to the electoral sidelines? Maybe, but it’s complicated. You’ve got to factor in that Trump is already giving his new voters something they wanted (i.e., a change in norms that permits more overt discrimination and reduces the influence of meritocrats), that cutting taxes for the wealthy doesn’t immediately affect working-class lives, that the current Republican plans schedule their Medicaid cuts to happen slowly over time, that there might yet be new infrastructure projects and a larger military to provide some new jobs targeted at working-class men, and so on. And then it’s never just about what one candidate or party offers, but rather it’s about the relative offers between competing candidates and parties. So, some of this depends on countermoves by Democrats, who continue to debate the electoral benefits and costs of adopting Sanders-style economic populism.

The picture of where we are and how we got here is coming into focus. Nevertheless, as the saying goes: Prediction is very difficult, especially about the future.

The demographics of Clinton and Trump voters

We already know a lot about who voted for Clinton and Trump from the exit polls. While there were a number of demographic features that produced meaningful splits—age, gender, rural/urban, and so on—the biggest of the big deals involved race, religion, sexual orientation, and education. According to the exit polls, Clinton did particularly well with blacks, LGBT folks, non-Christians, Latinos, Asians, immigrants, and people who never attend religious services, while Trump did particularly well with white evangelicals, Mormons, and whites without 4-year college degrees.

We now have another major sample. The Cooperative Congressional Election Study (CCES) made its 2016 raw data public last week, providing another look at these kinds of demographics. There are good and not-as-good points about the CCES. On the good side: It’s big (almost 50,000 respondents for the post-election wave), it includes both voters and non-voters, and it has a nice range of demographic variables. On the not-as-good side: It’s an online panel, which skews toward more sophisticated respondents and thus tends to be less reliable with downscale groups. So, for example, an unrepresentatively large percentage of the sample reported voting, which probably comes from a combination of the fact that it’s a more sophisticated volunteer sample (and those folks are more likely to vote) as well as the fact that there’s usually some self-reporting bias on this kind of question.

Nonetheless, on the whole, it’s a seriously helpful study. It’s nice to see the processed results from the exit polls, but then it becomes frustrating because you can’t ask follow-up questions like, you know, what was the deal with non-degreed whites who were not Christian? Or what was up with Hispanic evangelicals? The CCES data lets us look.

Here’s my analysis of the demographic splits that mattered most in the CCES sample. Turns out that it reveals the same basic big-deal items as the exit polls: race, religion, sexual orientation, and education. But, here, we get to see more fine-grained groups. The chart below shows the results, splitting the CCES sample (including both voters and non-voters) into 12 mutually exclusive demographic groups.

(Notes: The “Neither” response category includes both non-voters and third-party voters. “White” is a bigger category here than it usually is, including non-Hispanics who were coded as either white, native, or other; my guess is that lots of the CCES “natives” and “others” are actually whites giving cute answers. “Hispanic/Asian” includes Hispanics (regardless of other racial category), Asians, Middle Easterners, as well as mixed-race individuals. “LGBT” means people who indicated that they were lesbian, gay, bisexual, or transgender, and “Straight” means people who did not. “Evangelical” includes all non-Catholics who identified as “born again or evangelical” as well as Mormons. “Specific non-Christian” means everyone who chose a non-Christian religious identity (i.e., Jew, Muslim, Buddhist, Hindu, atheist, and agnostic) but excluding “nothing in particular” and “other”; basically, I think that among less-educated folks these latter categories pick up large numbers of Christians who just think of themselves as “Christian” rather than the given option of “Protestant.” “Religious middle” means people who are neither “Evangelical” nor “Specific non-Christian”—i.e., it combines non-evangelical Christians with the “nothing in particular” and “other” folks. Results are weighted.)

Dividing the public

The first thing you want to know about American voters these days is race, with blacks on the left, whites on the right, and other groups in between. Then, within blacks, there isn’t much else that really matters in predicting partisanship—it’s such a solidly Democratic group that additional demographic features tend not to be very interesting in the end. If I had made an additional split for this sample within blacks, it would have been by gender. Black men were a bit less likely to be such unwavering Clinton supporters (something that showed up in the exit polls as well).

Within Hispanics/Asians, the next-biggest deal is religion, with non-Catholic evangelicals and Mormons actually favoring Trump over Clinton. Within non-evangelical Hispanics/Asians, there aren’t other big demographic deals; had I done an additional split here, it would have been by home ownership, where the non-homeowners were particularly likely to support Clinton over Trump. (Also, Hispanic/Asian military veterans were pretty substantially to the right of non-veterans, though there weren’t enough Hispanic/Asian veterans in the sample (just a few hundred) to justify a further split.)

Within whites, the next-biggest deal is also religion, with non-Christians on the left, evangelicals on the right, and non-evangelical Christians in between. But I decided to first split out whites into those with and without 4-year college degrees, given that this division is currently receiving the most attention. Also, I decided to split out LGBT folks after education but before religion; this is because there aren’t a huge number of LGBT folks, and so you need to split them out pretty early to have big enough groups to be confident in what you’re seeing. I didn’t do further divisions within the white LGBT groups, but if I had pushed the data I would have split out Christians and non-Christians. White Christian LGBT folks were much more divided on the Clinton-Trump decision, while white non-Christian LGBT folks were very solid Clinton supporters.

Finally, military veterans were generally more supportive of Trump. This showed up just once in the chart, but if I had kept going with smaller splits, there would have been other groups where this division appeared.

So that’s the chart. The Clinton coalition was predominately blacks, white LGBT and non-Christian folks (both degreed and, to a lesser extent, non-degreed), and non-evangelical Hispanics and Asians.

The Trump coalition was predominately white, straight evangelicals (both non-degreed and, to only a somewhat lesser extent, degreed) along with white, non-degreed, straight veterans in the religious middle. Also leaning in Trump’s direction were white, non-degreed, straight non-veterans in the religious middle, as well as Hispanic and Asian evangelicals.

And, lastly, one group was pretty much split down the middle: white, degreed, straight, non-evangelical Christians. This group is politically quite important—indeed, it’s the group that contains both Clinton and Trump (not to mention Paul Ryan, Nancy Pelosi, John Roberts, and so on). Had I kept going with a further division here, it would have been to split out veterans (who favored Trump bigly) and non-veterans (who favored Clinton).

Big deals and not-as-big deals

I suspect, given the usual conversations around demographics, that some readers will be surprised with some of the things not showing up on the chart. For example, when people think of demographic splits, two of the things that typically come to mind are age and gender. Aren’t those big deals in partisan politics? Actually, no. No they’re not. They’re deals. In fact, they’re non-trivial deals. But they aren’t big deals.

Age differences in partisan voting these days have much to do with the racial and religious differences between younger and older folks. There are just a lot more minorities and non-Christians among younger cohorts. Thus, when you start splitting out a sample by the biggest deals—race and religion—you end up teasing out some of the key sources of age differences, so there often isn’t much statistical need at that point to make further splits based explicitly on age. Age is very similar to urban/rural and other regional differences in this regard—yes, there are political differences between different kinds of places, but they largely come down to the major racial, religious, and educational differences between cities and rural areas and between different parts of the country.

With gender, I’ve just never found that it regularly shows up as a major thing. Sometimes it’s a solid second-tier predictor. For example, when I look at whites who are college-educated and not super-religious, there are often substantial differences between men and women on average. And, frankly, I was expecting to see some bigger gender differences in the 2016 CCES sample, given that this was the first time a woman ran as a major party candidate. But no. It’s not that there were no reliable differences between men and women; it’s just that they weren’t sizable enough to make the cut.

Also absent from the chart are any splits based on income or church attendance. When I looked at the Obama elections using 2012 CCES data, income and church attendance were important secondary themes. But not this time. In fact, I didn’t see any indication in the 2016 CCES data that income differences were making more than a trivial contribution to the election. Church attendance had an impact, though not nearly enough to justify further splits once I made the main religion splits.

Identity politics and the changing party coalitions

The main patterns—the strong race/religion/LGBT differences, the increased salience of education among whites, and the decline in importance for income and church attendance—all point in the same direction: The 2016 election was mainly about Christian white nationalism. It was about discrimination vs. inclusion. It was about making America great again vs. being stronger together. These issues pit the interests of white, straight Christians with less education against the interests of minorities and meritocrats.

Democrats have faced some post-election complaints for relying too heavily on “identity politics.” It’s a weird charge in at least two ways. First, Trump surely deserves much of the blame for pushing these issues to the front burner. Prior Republican nominees had run campaigns that were focused more on small government and religious lifestyle issues (thus the typical relevance of income and church attendance), which makes Democratic positions on redistribution and lifestyle issues more salient (topics Clinton didn’t neglect, but that received less attention). Second, it makes little sense to look at the kinds of demographic splits in the chart above and think that race, sexual orientation, and religion are more relevant for one side than the other. These were the major drivers of both coalitions. And it can’t be the case that a party organized around racial minorities, LGBT folks, and non-Christians is about “identity” but a party organized around white, straight Christians is somehow not. Particularly when their candidate was so focused on a white nationalist message.

To be sure, there were strong elements of continuity between the 2016 election and other recent elections. The current major racial and religious divisions have been around since the last substantial reorganization of the parties in the mid-to-late-20th century that first drew blacks to Democrats and then drew white evangelicals and white Catholics to Republicans.

But we’re also seeing ongoing changes. Trump’s unprecedented success with non-degreed whites was based in part on converting former Obama voters, but seems to have been more about drawing former non-voters to the polls. Either way, this alters somewhat the Republican center of gravity—it’s still mostly white, straight Christians, but now with relatively more non-degreed folks and relatively fewer high-income and churchgoing folks. These kinds of coalitions are inherently fluid, with slow evolutions punctuated with periods of faster shifts that are difficult to anticipate.

Was Trump’s bump with non-degreed whites mainly from Obama voters or new voters?

According to exit polls from the 2016 presidential race, Trump did especially well with whites who don’t have 4-year college degrees. The polls showed Trump with a 37-point advantage over Clinton (66 to 29) among these folks, which was a real increase from Romney’s 25-point advantage over Obama (61 to 36). In addition, various state-level and county-level analyses have pointed to locations in which there are lots of non-degreed whites as those where Trump tended to outperform Romney’s numbers.

This has led some observers to talk about how Trump converted large numbers of former Obama voters—for example, the often-repeated claim the Trump won lots of folks who “voted for Obama twice.” Yet that’s getting ahead of the data. If it were the case that the exact same people voted in 2016 as in 2012, then it would be a safe assumption that lots of non-degreed whites who voted for Obama turned around and voted for Trump. But they weren’t the exact same people. Some folks who voted in 2012 sat out 2016. Some 2016 voters had previously not voted in 2012.

So where did Trump’s increased margin come from? Surely it involved a mix of converted Obama voters and former non-voters. But what’s the breakdown? Which was the bigger deal?

With the release on Friday of the 2016 Cooperative Congressional Election Study (CCES), we’ve got new data that provides an estimate. The 2016 CCES asked its respondents in its pre-election survey whether and for whom they had voted in 2012, and then asked those same folks in its post-election survey whether and for whom they had voted in 2016. This allows us to see not just margins among those who turned out, but also patterns of non-voting. I limited the sample to those old enough to vote in 2012 and who reported both their 2012 and 2016 votes (or non-votes).

The first chart below shows the basic percentages. According to the respondents’ recollections, in 2012 around 34% voted for Obama, 45% voted for Romney, and the other 21% voted for neither (most of these folks didn’t vote at all, but some reported voting for third-party candidates or not being able to recall). In 2016, 31% reported voting for Clinton, 59% for Trump, and 11% for neither. Thus, Trump’s gains with these folks appears to have been more a matter of attracting new voters rather than converting Obama voters—that is, only a bit fewer came out for Clinton than for Obama, but a lot more came out for Trump than for Romney.

We can see this directly in the chart below, which shows the full messy picture of 2012 to 2016 voting patterns among non-degreed whites in the CCES sample (again, limited to those old enough to vote in both elections). The biggest two groups were two-time voters within the same party—those who voted for Romney and then Trump (41%) and those who voted for Obama and then Clinton (25%). And then there are also various smaller percentages for every other combination. The two we’re particularly interesting in are those who voted for neither Obama nor Romney and then voted for Trump (11%) and those who voted for Obama and then Trump (6%)—in short, there are almost twice as many former non-voters (or non-major-party voters) here as there are converted Obama voters.

This isn’t, of course, the last word on this topic. It’s one sample. And it has some issues (e.g., it’s from an online panel, which tend to have trouble providing good estimates of downscale folks; e.g., while the reports on 2016 voting occurred right after the election, the respondents were reporting on their 2012 votes almost 4 years later, which is a lot of time for the quirks of memory and reporting bias to get amplified). But it’s something. For now, I’d say that we have a really compelling convergence of evidence that Trump did unusually well with non-degreed whites, and that we have indications that this improved performance was probably driven more by people who had voted for neither Obama nor Romney in 2012 than by former Obama voters (though we still need more data).

Vaguely interesting (Mar 2)

(1)  “Basically, midterm electorates are smaller, older, [whiter, and more educated] than presidential ones, but the demographic voting patterns and divisions that we see in midterms are quite similar to presidential contests.”

(2)  “Why African Americans left the South in droves — and what’s bringing them back.”

(3)  “[W]hite overrepresentation and minority underrepresentation has been a defining feature of American politics for decades. In fact, the report finds that we may currently be at peak levels of both overrepresentation and underrepresentation.”

(4)  “These days, it can feel as if the entire country has been given over to a vast psychological experiment being run either by no one or by Steve Bannon.”

(5)  “This is just the sort of science story that shimmies to the top of newsfeeds. That is to say, it’s of little consequence, and it’s very likely wrong. … If anything, a study’s silliness only serves as journalistic cover, by making it seem peevish to delve into the details.”

(6)  “Poor immigrants use public benefits at significantly lower rates than poor citizens. … Nonetheless, the notion that noncitizens make disproportionate use of public benefits remains widespread.”

Social science for the pleeps