Tag Archives: demography

Why Heritage is wrong on the new Census race/ethnicity question

Sorry this is long and rambly. I just want to get the main points down and I’m in the middle of other things. I hope it helps.

Mike Gonzalez, a Bush-era speech writer with no background in demography (not that there’s anything wrong with that), now a PR person for the Heritage Foundation, has written a noxious and divisive op-ed in the Washington Post that spreads some completely wrong information about the U.S. Census Bureau’s attempts to improve data collection on race and ethnicity. It’s also a scary warning of what the far right politicization of the Census Bureau might mean for social science and democracy.

Gonzalez is upset that “the Obama administration is rushing to institute changes in racial classifications,” which include two major changes: combining the Hispanic/Latino Origin question with the Race question, and adding a new category, Middle Eastern or North African (MENA). Gonzalez (who, it must be noted, perhaps with some sympathy, recently wrote one of those useless books about how the Republican party can reach Hispanics, made instantly obsolete by Trump), says that what Obama has in mind “will only aggravate the volatile social frictions that created today’s poisonous political climate in the first place.” Yes, the “poisonous political climate” he is upset about (did I mention he works for the Heritage Foundation?) is the result of the way the government divides people by race and ethnicity. Not actually dividing them, of course (which is a real problem), but dividing them on Census forms. (I hadn’t heard this particular version of why Trump is Obama’s fault — who knew?)

How will the new reforms make the Trump situation he helped create worse? Basically, by measuring race and ethnicity, which Gonzalez would rather not do (as suggested by the title, “Think of America as one people? The census begs to differ,” which could have been written at any time in the past two centuries).

Specifically, Gonzalez claims, completely factually inaccurately, that Census would “eliminate a second question that lets [Hispanics] also choose their race.” By combining Hispanic origin and race into one question — on which, as before, people will be free to mark as many responses as they like — Gonzalez thinks Census would “effectively make ‘Hispanic’ their sole racial identifier.” He is upset that many Latinos will not identify themselves as “White” if they have the option of “Hispanic” on the same question, even if they are free to mark both (which he doesn’t mention). Some will, but that is not because anyone is taking away any of their choices.

The Census Bureau, of course, because they always do, because they are excellent, has done years of research on these questions, including all the major stakeholders in a long interactive process that is scrupulously documented and (for a government bureaucracy) quite transparent. Naturally not everyone is happy, but in the end the trained demographic professionals come down on the side of the best science.

Race that Latino

The most recent report on the research I found was a presentation by Nicholas Jones and Michael Bentley from the Census Bureau. This is my source for the research on the new question.

First, why combine Hispanic with race? You have probably seen the phrase “Hispanics may be of any race” on lots of reports that use Census or other government data. The figure below is from the first edition of my book, using 2010 data, in which I group all 50 million Hispanics, and show the races they chose: about half White, the rest other race or more than one race (usually White and other race). Notice that by this convention Hispanics are removed from the White group anyway, just because we don’t want to have people in the same picture twice (“non-Hispanic Whites” is already a common construction).

family_fig03-02

The “may be of any race” language is the awkward outcome of an approach that treats Hispanic as an “ethnicity” (actually a bunch of national origins, maybe a panethnicity), while White, Black, Asian, Pacific Islander, and American Indian are treated as “races.” The distinction never really made sense. These things have been measured using self-identification for more than half a century, so we’re not talking about genetics and blood tests, we’re talking about how people identify themselves. And there just isn’t a major categorical difference between race and ethnicity for most people — people of any race or ethnicity may identify with a specific national origin (Italian, Pakistani, Mexican), as well as a “race” or panethnic identify such as Asian, or Latino. And now that the government allows people to select multiple races (since 2000), as well as answering the Hispanic question, there really is no good justification for keeping them separate. As you can see from my figure above, when we analyze the data we mostly pull all the Hispanics together regardless of their races. The new approach just encourages them to decide how they want that done, which is usually a better approach.

Of course, Asians and Pacific Islanders have been answering the “race” question with national origin prompts for several decades. There was no “Asian” checkbox in 2000 or 2010 (or on the American Community Survey). So they have been using their ethnicity to answer the race question all along — that’s because for some reason you just can’t get “Asian” immigrants, especially recent immigrants — that is, people from India, Korea, and Japan, Vietnam, and so on — to see themselves as part of one panethnic group. Go figure, must be the centuries of considering themselves separate peoples, even “races.” So, a new question that combines the more ethnic categories (Mexican, Pakistanis, etc.), with America’s racial identities (Black, White, etc.), just works better, as long as you let people check as many boxes as they want. This is what the “race” question looked like in 2014. Note there is no “Asian” checkbox:

acsrace2014

As a general guide, the questionnaire scheme works best when (a) everyone has a category they like, and (b) few people choose “other.” That is the system that will yield the most scientifically useful data. It also will tend to match the way people interact socially, including how they discriminate against each other, burn crosses on each other’s lawns, and randomly attack each other in public. We want data that helps us understand all that.

Through extensive testing, it has become apparent that, when given a question that offers both race and Hispanic origin together, Latino respondents are much more likely to answer Hispanic/Latino only, rather than cluttering up the race question with “some other race” responses (often writing in “Hispanic” or “Latino” as their “other race”). If I read the presentation right, in round numbers, given the choice of answering the “race” question with “Hispanic,” in the test data about 70% chose Hispanic alone; about 20% chose White along with Hispanic, and 5% choose two races. In fact, the number of Latinos saying their only race is White probably won’t change much; the biggest difference is that you no longer have almost 40% of Latinos saying they are “some other race,” or choosing more than one race (usually White and Other) which usually just means they don’t see a race that fits them on the list.

In the end, the size of the major groups (Hispanics and the major races) are not changed much. Here’s the summary:

betterhispanic

In fact, the only major group that will shrink is probably the non-group “multiracial” population, which today is dominated by Hispanics choosing White and “some other race.”

It’s really just better data. It’s not a conspiracy. It’s not eliminating the White race or discouraging assimilation of Hispanics. In short, keep calm and collect better data. We can fight about all that other stuff, too.

I’m sure Gonzalez doesn’t really think this will “eliminate Hispanics’ racial choices.” He’s dog-whistling to people who think the government is trying to reduce the number of Whites by not letting Hispanics be White. His statements are factually incorrect and the Washington Post shouldn’t have printed them. (I don’t know how the Post does Op-Eds; when I wrote one for the NY Times it was pretty thoroughly fact-checked.)

MENA

The Migration Policy Institute estimates there are about 2 million MENAs in the U.S. now, about half of them immigrants. This is a pretty small population, mostly Arab-speaking immigrants and their descendants, and more Christian (relative to Muslim) than the countries they left. This is especially true of the more recent immigrants, which don’t include a lot of Iranians (who aren’t Arab).

Census could have instead defined them by linguistic origin (Arab), and captured most, but they instead are going with country of origin, which is consistent with how the other race/ethnic groups are identified (for better or worse). Their testing showed that this measure captures most people with MENA ancestry, encourages them to identify their ancestry, cuts down on them identifying as White, and cuts down on them using “some other race.”

The difference is dramatic for those identifying as White, which fell from 85% to 20% in the test once a MENA category was offered. Would it be better if they just identified as White? I’m really not trying to shrink the count of Whites, I just think this is more accurate. I don’t care about the biology of Whiteness and whether Iranians are part of it, for example (and don’t ever say “Caucasian,” please), I care about the experience and identity of the people we’re talking about — as well as the beliefs of the people who hate them and those who want to protect them from discrimination. Counting them seems better than shoehorning them into a category most of them avoid when given the chance.

Here’s one version of the proposed new combined question, from that Census presentation:

newraceq

Yuck

Why not Mike Gonzalez to run Census? Unbelievably, he probably knows more about it than Trump’s education and HUD department heads know about their new portfolios.

But that’s just one odious possibility. It makes me kind of sick to think of the possible idiots and fanatics Trump might put in charge of the Census Bureau, after all this work on research and testing, designed to get the best data we can out of a very messy and imperfect situation.

What else would they do? Will they continue to develop ways to identify and count same-sex couples? The Supreme Court says they can get married, but there is no law that says the Census Bureau has to count them. What about multilingual efforts to reach immigrant communities? This has been a focus of Census Bureau development as well. And so on.

It is absolutely in Trump’s interest, and the interests of those who he serves (not the people who voted for him), to reduce the quality and quantity of social science data the government produces and enables us to produce.

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How do Black-White parents identify their children?

In 2015 the American Community Survey yields an estimate of 66,913 infants who have one Black parent and one White parent present in the household. (Either parent may be multiracial, too.)

What is the race of those infants? 73% of them were identified as both White and Black by whoever filled out the Census form.

bwinfants

(Note “other” doesn’t mean they specified “other,” it just means they used some other combination of races.)

These are children age 0 living with both parents, so it’s a pretty good bet they’re mostly biological parents, though some are presumably adopted. This is based on a sample of 507 such infants. If you pooled some years of ACS there is plenty to study here. Someone may already have done this – feel free to post in the comments.

That’s it, just FYI.

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Electoral representation by demographic group

I’m told that one point of our electoral system is to ensure representation of small states. That’s why small states get two senators even if they have tiny populations, and why each state gets at least three electors in the electoral college (equal to the size of their Congressional delegation). You could make a case for finding ways to make sure small groups are represented, even over-represented, because otherwise they would be ignored. So you discount California voters to make sure Wyoming voters get to be part of the process.

Regardless of the history, which suggests the electoral college was created to protect the interests of slave owners, it’s now the case that Whites have more power in the electoral college, because they dominate the small states. As Lara Merling and Dean Baker show, Blacks have 5% less representation, Latinos have 9% less, and Asian Americans have 7% less representation than Whites.

So it is unfair in its results by the contemporary race/ethnic distribution, but that’s not a fixed quality of the system (it’s merely very durable). Underlying the premise, though, is the idea that the identities to be represented are geographic in nature. There are some issues that have geographic boundaries, like land use or climate-related questions, but the point of an analysis like Merling and Baker’s — like much of Civil Rights law — is that identities also adhere in demographic groups, by gender, race/ethnicity, and age. So the geographic system creates inequities according the demographic system. I don’t see why we should prioritize the geographic in our electoral system, now that geography is so much less of a defining feature in our communication systems and popular culture.

What if we redid the electoral system by the demographic categories of gender, race/ethnicity and age, and then let geographic groups complain if they end up underrepresented, instead of the other way around? Before you write to the governor (again) and demand that I be fired: This does not even rise to the level of a suggestion, it’s literally just a thought.

Here’s how it would look, if we divided 435 seats across 40 demographic identity states, using data from the 2015 American Community from IPUMS.org*:

newhor

Compared with the 114 Congress (the one finishing now), this one is more diverse, with 224 instead of 108 women, 56 versus 38 Latinos, 24 versus 13 Asian/Pacific Islanders, and 8 versus 2 American Indians. Only Blacks fare a little worse, dropping form 47 to 44. This also gives us a great improvement in age diversity, as the current average age in the House is 57 and this distribution implies an average age of something like 47.

For comparison, here is the Electoral College we would get under this system, which simply adds two electors to each of these House of Representatives districts, representing their Senate delegations:

newec

Now instead of fighting over New Hampshire or Wyoming, presidential candidates would campaign for swing-groups such as middle-aged American Indians, or young Latinos.

This system would also have a built in version of term limits feature, as people who aged out of their districts presumably would have to run in the next age group up. People who changed gender or race/ethnic identity could also switch districts.

Someone could take some voter or opinion data and figure out how our elections would turn out with this (if someone already has done this, please add it in the comments).


* Because they rounded to zero, I added one House seat to old American Indian men and women, and took one away from middle-aged White women, the largest group. Note also that we might have to redistrict this when the race categories change, as they are expected to in 2020, to add Middle Eastern / North Africans (MENAs).

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The liberalization of divorce attitudes proceeds apace

The 2016 Gallup poll results on what is morally acceptable versus morally wrong came out over the summer, and they show that U.S. attitudes toward divorce continue to grow more positive. The acceptable attitude has gained 5 points in the last 5 years:

divorcegallup

This parallels results from the General Social Survey, which asks, “Should divorce in this country be easier or more difficult to obtain than it is now?” The latest GSS is still 2014, but it also shows a marked increase in the liberal easier view over the same time period:

divorcegss

See more under the divorce tag.

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Get your dependency ratio off my lawn

Old people work more than they used to. This is important if you’re worried about what an aging population means for the economy.

When they taught me demography, I learned about the dependency ratio, which was the number of people presumed to be dependents (those ages 0-14 and 65+) relative to those presumed to be working (those ages 15-64). It’s a traditional measure, and a little archaic now that people spend much more time in school. But it’s nice because it sort of assumes that those “working age” adults are being productive whether they have jobs or not – it’s not just counting employed people – so it has an unstated recognition of (mostly women’s) unpaid labor.

In some economic work (see my paper here for an old review) people assume that non-employed women are being productive. But we don’t usually assume that about old people. That is, non-employed younger adults are assumed to be doing unpaid work, while non-employed old people are assumed to be really retired. I’m sure people are looking at the unpaid work of old people (I just haven’t yet). But their paid work profile has changed a lot, too – especially women’s.

This means the catastrophic view of productivity effects of again needs to be tempered by a better understanding of how much old people work. Here’s what I mean.

First, what the World Bank calls “Dependency Ratio, old,” which is the number of people age 65 and older as a percentage of the population ages 15-64. This is supposed to reflect the burden of age on the the young(er).* Here is it for the USA and the world (click to enlarge):

dependency ratio old

That’s the Baby Boom generation hitting older ages there at the end of the USA trend. As a result, the dependency ratio (old) has increased 30% in the USA since 1980, and the world is following.

But old people work more (or, we don’t label people “old” as early, you might say). Here’s the average annual hours of paid work for people in the USA ages 65 and older. Note this includes all those working no hours in the average, which is what you need to do if you’re interested in the total economic benefit/burden ratio (click to enlarge).

dependency ratio old

Since 1980, women ages 65-74 have increased their hourly employment hours by 138%, and men’s have gone up 44%. For the 75-plus community, the relative increases are even greater: 172% for women and 55% for men.

Now, if you add up those hours, you can calculate how much of a burden old people are relieving from the young by their employment hours. In this figure I calculate the total hours worked for each age-gender group and divide it by the total number of people ages 65 and older. Looking at the bottom blue area, for example, this shows that in 2015, the total population of men ages 65-74 did 166 hours of paid work for each person age 65 and older. Regardless of the size of the old population, then, there is that much less supporting of them to do (click to enlarge).

hours worked per person 65 and older

The per-person contribution of paid work hours from people 65 and older has increased 72% since 1980, from 206 to 354 hours per year. Most of the increase is from women’s employment, and it’s just starting. The oldest Baby Boom women, the women who led the increase in women’s employment over their careers, are still only 69 in 2015. Further, this measurement of paid hours may be an indicator of the unpaid productivity of these groups as well, as their health and activity levels improve.

It may be useful to track the population age composition over time (as in the World Bank data above), but it’s not reasonable to assume a constant level of dependency associated with people of different ages.

*Note: Of course, I use terms like “burden” in the classical demographic sense and tongue-in-cheek. I actually want more old people to live longer and work less, because that burden is what life is all about. But there is the issue of making sure everyone has their needs met.

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On Asian-American earnings

In a previous post I showed that generalizations about Asian-American incomes often are misleading, as some groups have above-average incomes and some have below-average incomes (also, divorce rates) and that inequality within Asian-American groups was large as well. In this post I briefly expand that to show breakdowns in individual earnings by gender and national-origin group.

The point is basically the same: This category is usually not useful for economic statistics, and should usually be dropped for data on specific groups when possible.

Today’s news

What’s new is a Pew report by Eileen Patten showing trends in race and gender wage gaps. The report isn’t focused on Asian-American earnings, but they stand out in their charts. This led Charles Murray, who is fixated on what he believes is the genetic origin of Asian cognitive superiority, to tweet sarcastically, “Oppose Asian male privilege!” Here is one of Pew’s charts:

pewraceearn

The figure, using the Current Population Survey (CPS), shows Asian men earning about 14.5% more per hour than White men, and Asian women earning 11% more than White women. This is not wrong, exactly, but it’s not good information either, as I’ll argue below.

First a note on data

The CPS data is better for some labor force questions (including wages) than the American Community Survey, which is much larger. However, it’s too small a sample to get into detail on Asian subgroups (notice the Pew report doesn’t mention American Indians, an even smaller group). To do that I will need to activate the ACS, which is better for race/ethnic detail.

As a reminder, this is the “race” question on the 2014 American Community Survey, which I use for this post:

acsrace2014

There is no “Asian” or “Pacific Islander” box to check. So what do you do if you are thinking, “I’m Asian, what do I check?” The question is premised on that assumption that is not what you’re thinking. Instead, you choose from a list of national origins, which the Census Bureau then combines to make “Asian” (the first 7 boxes) and “Pacific Islander” (the last 3) categories. And you can check as many as you like, which is good because there’s a lot of intermarriage among Asians, and between Asians and other groups (mostly Whites). This is a lot like the Hispanic origin question, which also lists national origins — except that question is prefaced by the unifying phrase, “Is Person 1 of Hispanic, Latino, or Spanish origin?” before listing the options, each beginning with “Yes”, as in “Yes, Cuban.”

Although changes have not been announced, it is likely that future questions will combine the race and Hispanic-origin questions, and also preface the Asian categories with the umbrella term. This may mark the progress of getting Asian immigrants to internalize the American racial classification system, so that descendants from groups that in some cases have centuries-old cultural differentiation start to identify and label themselves as from the same racial group (who would have put Pakistanis and Japanese in the same “race” group 100 years ago?). It’s hard to make this progress, naturally, when so many people from these groups are immigrants — in my sample below, for example, 75% of the full-time, year-round workers are foreign-born.

Earnings

The problem with the earnings chart Pew posted, and which Charles Murray loved, is that it lumps all the different Asian-origin groups together. That is not crazy but it’s not really good. Of course every group has diversity within it, so any category masks differences, but in my opinion this Asian grouping is worse in that regard than most. If someone argued that all these groups see themselves as united under a common identity that would push me in the direction of dropping this complaint. In any event, the diversity is interesting even if you don’t object to the Pew/Census grouping.

Here are two breakouts. The first is immigration. As I noted, 75% of the full-time, year-round workers (excluding self-employed people, like Pew does) with an Asian/Pacific Islander (Asian for short) racial identification are foreign born. That ranges from less than 4% for Hawaiians, to around 20% for the White+Asian multiple-race people, to more than 90% for Asian Indian men. It turns out that the wage advantage is mostly concentrated among these immigrants. Here is a replication of the Pew chart using the ACS data (a little different because I had to use FTFY workers), using the same colors. On the left is their chart, on the right is the same data limited to US-born workers.

api1

Among the US-born workers the Asian male advantage is reduced from 14.5% to 4.2% (the women’s advantage is not much changed; as in Pew’s chart, Hispanics are a mutually exclusive category.) There are some very high-earning Asian immigrants, especially Indians. Here are the breakdowns, by gender, comparing each of the larger Asian-American groups to Whites:

api2

Seven groups of men and nine groups of women have hourly earnings higher than Whites’, while nine groups of men and seven groups have women have lower earnings. In fact, among Laotians, Hawaiians, and Hmong, even the men earn less than White women. (Note, in my old post, I showed that Asian household incomes are not as high as they look when they are compared instead with those of their local peers, because they are concentrated in expensive metropolitan markets.)

Sometimes when I have a situation like this I just drop the relatively small, complex group, which leads some people to accuse me of trying to skew results. (For example, I might show a chart that has Blacks in the worst position, even though American Indians have it even worse.)

But generalization has consequences, so we should use it judiciously. In most cases “Asian” doesn’t work well. It may make more sense to group people by regions, such as East-, South-, and Southeast Asia, and/or according to immigrant status.

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The fathers behind teen births (or, statistical memes and motivated blind trust)

When makes people trust statistical memes? I don’t know of any research on this, but it looks like the recipe includes a combination of scientific-sounding specificity, good graphics, a source that looks credible, and – of course – a number that supports what people already believe (and want their Facebook friends to believe, too).

If that’s the problem, and assuming the market can’t figure out how to make journalism work, I have no solution except seizing the Internet and putting it under control of the Minister of Sociology, or, barring that, encouraging social scientists to get engaged, help reporters, and make all their good work available publicly, free, and fast.

Today’s cringe:

13179054_1158267840891715_8960394622916968249_n

The blogger TeenMomNYC takes credit for creating this, and the Facebook version has been shared tens of thousands of times. Its popularity led to this story from Attn: “The Truth About Teenage ‘Baby Mamas’ is Quite Revealing.” (If anyone did want to study this issue, this is a neat case study, because she posted 8 “did you know” graphics on Facebook at the same time, and none of the others took off at all – why?)

I don’t know anything about TeenMomNYC, but I share her desire to stop stigmatizing and shaming young mothers. I wish her work were not necessary, but I applaud the effort. That said, I don’t necessarily think shaming young fathers (even if they’re not quite as young) is a solution to that, but that’s not the point. My point is, what is this statistic?

According to the footnote (thanks!), it comes from this 1995 National Academies report, and (except for changing “29” to “29.7”) it represents it accurately. From p. 205:

These data highlight an additional component of the sexual abuse picture— the evidence that an appreciable portion of the sexual relationships and resulting pregnancies of young adolescent girls are with older males, not peers. For example, using 1988 data from the NSFG and The Alan Guttmacher Institute, Glei (1994) has estimated that among girls who were mothers by the age of 15, 39 percent of the fathers were ages 20–29; for girls who had given birth to a child by age 17, the comparable figure was 53 percent. Although there are no data to measure what portion of such relationships include sexual coercion or violence, the significant age difference suggests an unequal power balance between the parties, which in turn could set the stage for less than voluntary sexual activity. As was recently said at a public meeting on teen pregnancy, “can you really call an unsupervised outing between a 13-year-old girl and a 24-year-old man a ‘date’?”

This is an important point, and was good information in 1995, when it cited a 1994 analysis of 1988 data, which asked women ages 15-44 a retrospective question. In other words, this refers to births that took place as early as 1958, or between 28 and 58 years ago. That is historical, and really shouldn’t be used like this today, given how much has changed regarding teen births.

The analysis is of the 1988 National Survey of Family Growth, a survey that was repeated as recently as 2011-2013. Someone who knows how to use NSFG should figure out the current state of the age gap between young mothers and fathers and let TeenMomNYC know.

Even if I didn’t know the true, current statistic, this would give me pause. Births to women before age 15 are extremely rare. The American Community Survey, which asks millions of women whether they have had a birth in the previous year, does not even ask the question of women younger than 15. The ACS reports there were 179,000 births in the previous year among women who were under 20 when interviewed, of which only 6,500 were to women age 15 at the interview. So that’s 3.7% of teen births, and 3 out of every thousand 15-year-old women. In 1958 this was much more common, and the social environment was much different.

Another issue is the age range of the fathers, 20-29, which is very wide when dealing with such young mothers. Look at the next phrase from the 1995 report: “girls who had given birth to a child by age 17, the comparable figure was 53 percent.” Realize that the great majority of girls who had a birth “by age 17” were 17 when they did, and the great majority of those men were probably close to 20. I’m not very positive about 20-year-old men having children with 17-year-old women, but it’s pretty different from 29-versus-13.

I can’t find the original source for this, but this report from the Resource Center for Adolescent Pregnancy Protection attributes this table to the California Center for Health Statistics in 2002, which shows that the father was age 20 or older  for 23% of women who had a birth before age 15. And of those, 93% were 20-24 (rather than 25+).

cateen

Anyway, this is a good case of a well-intentioned but under-resourced effort to sway people with true information, picked up by click-bait media and repeated because people think it will help them win arguments, not because they have any real reason to believe it’s true (or not true).

So I really hope someone with the resources, skills, and training to answer this question will produce the real numbers regarding father’s age for teen births, and post them, with accompanying non-technical language, along with their code, on the Open Science Framework (or other open-access repository).

Fixing the media and its economy is a tall order, but academics can do better if we put our energy into this work, reward it, and restructure our own system so that good information gets out better, faster and more reliably.

Related posts:

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