Category Archives: In the news

So you want to know the Asian divorce rate (save the ACS marital events edition)

One of the most popular posts ever on this blog is about Asian incomes, and especially the variation in average incomes across Asian national-origin groups and cities. Turns out the diverse Asian groups have different divorce rates as well. Why not? It would be nuts to assume the immigrants and their descendants from everywhere from Bangladesh to Japan had common family practices and behavior.

We can figure this out with the American Community Survey (see below; data from which is provided by IPUMS.org). The ACS is big enough to measure divorce rates for Asian subgroups if you pool together a few years — for this I use the 2008-2012 file. For reliability, here I am just showing those groups that had a sample of at least 1,000 married people. And I’m including as separate groups those that selected more than one “race” – Japanese-White, Korean-White, and Filipino-White (you’ll see why I separated them out). Note these are multiple-race individuals, not couples in which the two spouses reported different races.

The national refined divorce rate — divorces per 1,000 people — fell from 20 to 18 at the start of the recession in 2008, before rebounding back up to 19 by 2012. So compare these numbers with about 19 as the national average divorce rate (click to enlarge).

asian divorce rates 08-12.xlsx

Look at that spread! Now won’t you feel a little foolish for even asking what the “Asian” divorce rate is? I leave the interpretation to the relevant experts (media note: but I’ll be happy to speculate if it will help you get your story past the editor).

A further wrinkle: gender. Unfortunately, because the ACS is a household survey, if someone is divorced, the person they divorced is usually not living in the same household, which means we don’t know who they divorced (or even the other spouse’s gender!). Naturally, men and women in the same ethnic group can have different divorce rates to the extent that they marry outside their own group (or get gay divorced at different rates).

So here are the divorce rates for the same groups, but separately by gender. Groups above the line have higher divorce rates for men (Pakistanis, Cambodians), those below the line have higher divorce rates for women (Korean, Vietnamese, Korean-White). Click to enlarge:
asiandivorcegenderBy now you’ve realized what a wonderful treasure-trove of data this is for understanding the incredibly expanding family complexity that pulses all around us. Or, as they say, “Pretty nice data you got there. I’d hate to see something happen to it.” Read on.

Speak up

Last week I reported “millennial” generation divorce rates for 25 metropolitan areas. That’s something you can only get from the very large American Community Survey (because we have no national registry of marital events).

In addition to local areas, however, the vast size of the ACS lets us drill down into very small groups in the population — like small Asian subgroups. For another example, remember the big ruckus over same-sex marriage (you know, homogamy)? I for one would love to have good national data on same-sex marriage patterns when the equality-deniers finally lope back into their caves and the dust settles.

But now the feds are proposing to scrap the marital events (did you get married, divorced, or widowed last year?) and marital history (how many times have you been married, and when was the last time?) questions from the ACS just to save a few million dollars. I hope you’ll help demographic science convince them not to. (In the previous post I listed a bunch of divorce facts we only know because of the ACS questions.)

The information about the planned cuts to the American Community Survey is here: https://www.federalregister.gov/articles/2014/10/31/2014-25912/proposed-information-collection-comment-request-the-american-community-survey-content-review-results:

Direct all written comments to Jennifer Jessup, Departmental Paperwork Clearance Officer, Department of Commerce, Room 6616, 14th and Constitution Avenue NW., Washington, DC 20230 (or via the Internet at jjessup@doc.gov).

Comments will be accepted until December 30.

* Contrary to popular belief, there is no “Asian” category on the Census/ACS form. People are identified as Asian if they pick any of the Asian national origins listed on the “race” question. It’s all pretty American-exceptional. Here is the question, from this form:

acs2010raceq

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Policy, politics, and promoting education versus marriage

Here are three ideas I disagree with:

1. Most people aren’t smart enough to make going to college worth it.

Maybe the best-known purveyor of this idea is Charles Murray, who argued in his 2008 book Real Education (offshore bootlegged copy here) that the “consensus intellectual benchmark” for understanding real college-level material is an IQ of 115, which by definition is only 16% of the population — but probably only 10% are really, truly smart enough (and efforts to improve education at lower levels to prepare more people for college are futile, so don’t even think about spending more on education, because so many people are “born lazy“).

2. We’ve done so much for poor people, it’s time for them to do something for themselves.

This is clearly related to idea #1, insofar as the government spends billions of dollars educating people for college — and subsidizing the colleges they attend — who could instead just work hard and enjoy life in a job requiring less education. But it extends to all kinds of social welfare and anti-poverty programs, as illustrated by the exasperated people in the policy establishment from Brookings to Heritage.

3. Poor women should get married before they have children.

This idea is pervasive, as I’ve discussed many times under the single mothers tag, in response to people blaming single mothers for rising inequality, poverty, low upward mobility, and crime.

One response

Here I offer one response to these three ideas combined. It is possible to increase access to college education, which would increase stability and opportunity for poor people and their children.

In demography, there is a long-running debate over whether there is a biological limit to human longevity, and whether and how fast we may be approaching it. Regardless of the ultimate answer, so far it’s clear that projections based on an inevitable tapering off of increases in life expectancy have repeatedly proved wrong (here’s a review and a recent paper). The same might be said of college education. Here is the trend in 25-34 year-old U.S. civilians with at least a BA degree, from Census numbers:

college completion trends.xlsx

There was more talk about hitting the limits of college access 10 years ago, but even then it was increasing rapidly among women. Yes, we can and should improve college education. But I see nothing here to suggest a ceiling approaching. Still, people keep assuming that expanding education isn’t feasible.

For example, while Murray holds forth on the intelligence limitations among the poor, his colleague Brad Wilcox argues for a cultural press on those with less than a college degree:

They can go down the road of not having marriage as the keystone to their family formation, family life, or we can hold the line, if you will, and try to figure out creative strategies for strengthening marriage in this particular middle demographic in the United States.

In addition to upscaling their deficient values, however, couldn’t we also move them out of the less-than-college category altogether? Not so fast, says Wilcox in a recent interview:

On the education front, the U.S. spends a ton of money and devotes unparalleled attention to college. But the reality is that only one-third of adults, even today, will get a college degree, a B.A. or B.S. We can do a lot better in both funding and focusing on vocational education and apprenticeship training.

Really, America, be reasonable: Our “ton of money” is “unparalleled.” Don’t set your sights too high. Who do you think you are, anyway, Poland (college graduation rate: 53%), Ireland (46%), or Portugal (41%)? From OECD numbers:

college graduation rates OECD.xls

I know expanding college access (the real kind, not the for-profit kind) suggests expanding a broken financial aid system, and the economic returns aren’t guaranteed, but for my purposes it’s not just about getting a better job. People who go to college — and those who know they are going to go to college before they do — usually delay having children, not because some moralizing think tank tells them it’s wrong, but because they’re trying to rationally sequence their lives. Of course, married couples have relatively low poverty rates, but even for parents who aren’t married, higher education sure helps. From the American Community Survey via IPUMS.org:

H8.xlsx

Trying to get more poor people to get married is both offensive and useless. But increasing access to higher education is both uplifting and useful. The choice between early birth with low education and later birth with higher education is not hard to make, but unless it’s feasible — with a readily apparent, practical, path toward completion — there is no choice to make.

The increase in college education has already helped keep child poverty levels from rising as marriage rates have fallen. Among women old enough to have finished college (ages 22-44) the percentage of babies born to mothers with college degrees (married or not) has increased from 23% in 1990 to 35% in 2010. From the Current Population Survey via IPUMS.org:

H8.xlsx

Promoting marriage among the poor is a moralizing salve for the self-esteem — and anti-tax self-interest — of pious elites, with zero proven success in helping anybody poor. Promoting access to higher education is good policy and good politics.

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Pregnancy discrimination and the gender gap, involuntary job choice edition

From Rachel Swarns at the New York Times comes the story of a woman, Angelica Valencia, fired from her $8.70-an-hour produce packing job because her doctor said she couldn’t work overtime because she was three months into a risky pregnancy. There actually is a new law on her side, but her employer somehow didn’t get around to notifying her of her right to reasonable accommodation.

Before reading my comment on this, why not check out this new video from the chapter on gender in my book. The video accompanies a much more compelling version of this graphic, showing the gender composition of some occupations, calculated from the American Community Survey:

figures 4-6.xlsx

Count that gender gap

OK, Back to Angelica Valencia. I’m not an expert on pregnancy discrimination, but I want to use this to comment on how we look at the gender gap in pay. The Census Bureau reports on the gender gap this way:

In 2013, the median earnings of women who worked full time, year-round ($39,157) was 78 percent of that for men working full time, year-round ($50,033).

Critics complain that this doesn’t account for occupational choice, time out of the labor force, and so on. As Ruth Davis Konigsberg sneeringly put it in Time:

Women don’t make 77 cents to a man’s dollar. They make more like 93 cents, as long as they don’t major in art history.

And Hanna Rosin helpfully explained:

Women congregate in different professions than men do, and the largely male professions tend to be higher-paying.

So what does the story of Angelica Valencia pregnancy tell us (besides the pitfalls of majoring in art history)? Valencia may end up winning some back pay in a lawsuit. But let’s assume someone just like her didn’t, and ended up instead in a lower-paying job that doesn’t like overtime, such as at McDonald’s. If we insist on statistically controlling for occupation, hours, job tenure, and time out of the labor force in order to see the real wage gap, people like Valencia may not show up as underpaid women — if they’re paid the same as men in the same jobs, holding constant hours, job tenure, and time out of the labor force. So the very thing that makes Valencia earn less — being fired for getting pregnant — disappears from the wage gap analysis. Instead, the data shows that women take more time off work, work fewer hours, change jobs more often, and “choose” less lucrative occupation.

Sure, a lot of women chose to get pregnant (and a lot of men choose to become fathers). But getting fired and ending up in a lower paid job as a result is not part of that choice (and it doesn’t happen to fathers). The overall difference in pay between men and women, which reflects a complicated mix of factors, is a good indicator of inequality.

For background on the motherhood penalty in wage, you might start here or here (including the sources citing these).

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Life expectancy update, disparity edition

The good news is that U.S. life expectancy is at a record high, 78.8 as of 2012.

What about life disparity — the inequality in life expectancy? With the economic crisis and rise in income inequality, it would be great to know. However, the National Center for Health Statistics hasn’t released detailed life tables with data more recent than 2008, so I can’t yet update the data for the analysis I did last year, so here it is reposted instead:

Life Expectancy, Life Disparity

Reposted from July 23, 2013

In 2008 the life expectancy at birth in the U.S. was 78.1. That means that if a group children born in 2008 lived every year of their lives exposed to the risks of death observed in 2008, their average lifespan would be 78.1 years. But those who made it to age 60 would live an average of 22.7 more years, for a total of 82.7. And those who live to age 99 would live an average of 2.4 more years, for an average of 101.4.

So “life expectancy” as commonly used is not a prediction of how long today’s babies will live — since we hope the future is better than living 2008 over and over — and it’s not a prediction of how long your elderly loved ones will live.

Life disparity

Life expectancy — for any age — is a measure of central tendency: the average number of years of life remaining. And so there is a dispersion around that mean. That dispersion is inequality. A very nice article in the open-access journal BMJ Open, by James Vaupel, Zhen Zhang and Alyson A van Raalte, describes the measure of life disparity. It’s complicated, but a neat tool.

Life disparity is the average number of years people are expected to live when they die. For example, in the U.S. in 2008 an infant who died on the first day of life died 78.1 years early. And a 78-year-old who died, counterintuitively, died 10 years early (since the life expectancy at 78 is 10). To understand what this measure means, consider that if everyone died at exactly 78.1 years of age, life expectancy would be unchanged but life disparity would be 0. On the other hand, the greatest life disparity would occur if all early occurred at age 0.

Life disparity and life expectancy usually go together. That’s because reducing early deaths has the biggest effect on both measures. Here is the cool figure from that paper:

The association between life disparity in a specific year and life expectancy in that year for males in 40 countries and regions, 1840–2009. The black triangle represents the USA in 2007; the USA had a male life expectancy 3.78 years lower than the international record in 2007 and a life disparity 2.8 years greater. The brown points denote years after 1950, the orange points 1900–1949 and the yellow points 1840–1900. The light blue triangles represent countries with the lowest life disparity but with a life expectancy below the international record in the specific year; the dark blue triangles indicate the life expectancy leaders in a given year, with life disparities greater than the most egalitarian country in that year. The black point at (0,0) marks countries with the lowest life disparity and the highest life expectancy. During the 170 years from 1840 to 2009, 89 holders of record life expectancy also enjoyed the lowest life disparity.

The association between life disparity in a specific year and life expectancy in that year for males in 40 countries and regions, 1840–2009. The black triangle represents the USA in 2007; the USA had a male life expectancy 3.78 years lower than the international record in 2007 and a life disparity 2.8 years greater. The brown points denote years after 1950, the orange points 1900–1949 and the yellow points 1840–1900. The light blue triangles represent countries with the lowest life disparity but with a life expectancy below the international record in the specific year; the dark blue triangles indicate the life expectancy leaders in a given year, with life disparities greater than the most egalitarian country in that year. The black point at (0,0) marks countries with the lowest life disparity and the highest life expectancy. During the 170 years from 1840 to 2009, 89 holders of record life expectancy also enjoyed the lowest life disparity.

Countries at the bottom left (0,0) have both the world’s highest life expectancy and the lowest life disparity in the world for that year, which occurred 89 times over 170 years. Countries below the diagonal have relatively low life disparity given their life expectancy; those above the diagonal (like the U.S.) have higher-than-expected life disparity for their level of life expectancy. In our case that reflects the fact that we do a pretty good job keeping old people alive, but let too many young people die.

U.S. improvement

The good news is that life expectancy is increasing in the U.S. (and most other places), and that the inequality between Blacks and Whites is getting smaller, as reported by the National Center for Health Statistics. That is, the Black-White inequality in average expectation of life at birth has shrunk.

The mixed news is that life disparity is much higher for Blacks than Whites — but that gap is falling as well. Here are those numbers for 1998 and 2008 (I did the life disparity calculations from this and this, and will happily share the spreadsheet). Click to enlarge:

expectancydisparity

So Black deaths are more dispersed than White deaths: 14 and 13 for males and females, compared with 12 and 11. For comparison, the Swedish female life disparity is 9. What does a higher disparity mean? Generally, a larger share of early deaths. That’s why the race gap in life expectancy at birth is greater than the race gap in life expectancy at older ages — average 65-year-old Whites and Blacks have more similar life expectancies than do infants.

Why is life disparity more interesting than life expectancy alone, and how does this help explain Black-White inequality in the U.S.? For one thing, high life disparity indicates either relatively unhealthy or dangerous living conditions at younger ages. So it’s partly a measure of the quality of life. Vaupel et al. add:

Reducing early-life disparities helps people plan their less-uncertain lifetimes. A higher likelihood of surviving to old age makes savings more worthwhile, raises the value of individual and public investments in education and training, and increases the prevalence of long-term relationships. Hence, healthy longevity is a prime driver of a country’s wealth and well-being. While some degree of income inequality might create incentives to work harder, premature deaths bring little benefit and impose major costs. Moreover, equity in the capability to maintain good health is central to any larger concept of societal justice.

I think what they say about differences between countries would apply to differences between groups within a society as well.

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This word ‘generation,’ I do not think it means what you think it means

The people who make up these things drive me bananas.

NPR launched a new series on “millennials” yesterday, called “New Boom,” with this dramatic declaration: “There are more millennials in America right now than baby boomers — more than 80 million of us.”

The definition NPR gives for this generation is “people born between 1980 and 2000.” And it’s true there are more than 80 million of them. In fact, there are 91 million of them, according to the 2012 American Community Survey data you can get from IPUMS.org.* That’s OK, though, because there are only 76 million Baby Boomers, so the claim checks out.

But what’s a generation?

The Baby Boom was a demographic event. In 1946, after the end of World War II, the crude birth rate — the number of births per 1,000 population — jumped from 20.4 to 24.1, the biggest one-year change recorded in U.S. history. The birth rate didn’t fall back to its previous level until 1965. That’s why the Baby Boom went down in history as 1946 to 1964. Because that’s when it happened.

This figure shows the number of living people by birth year, and the crude birth rate recorded in each year, using the NPR definition of millennials (in red), compared with the baby boom (purple):

mellenials.xlsx

Even with population growth I reckon the people born in the years 1946-1964 might outnumber the self-promoting millennials if not for the weight of mortality pulling down the purple bars. But if the young NPR reporters want to brag about outnumbering a generation that is starting to lose its older members to old age (and who are, after all, their parents), then I guess the shoe fits.

The Baby Boom was not a generation. It was a cohort, “a group of people sharing a common demographic experience” (in this case birth during the same period). That demographic event happens to have lasted 18 years, which is unfortunate because that may have contributed to the tendency to declare “generations” of similar lengths.

The Pew Research people, who do lots of interesting work on social change that uses generational concepts, use these slightly different definitions for four generations: Silent Generation, born 1928-1945; the Baby Boom Generation, born 1946-1964; Generation X, born 1965-1980; Millennial Generation, born 1981 and later (Pew says “no chronological endpoint has been set for this group,” which is awkward because if they’re really still going, the oldest are 33 and they have children that are the same generation as themselves**). Ironic, isn’t it, that Pew constructs “Generation X” as the shortest of the four (some generation, a mere 16 years!) before declaring them “America’s neglected ‘middle child.’

Real generations rarely have starting and ending points on a population level. Populations usually just keeping having births every year in smooth patterns of increase or decrease without discrete edges, so generations overlap. Even in families it gets hard to nail down generations once you start moving horizontally; siblings born many years apart are in the same generation, but the cousins get all confused.

Meaningful cohorts, on the other hand, can be defined all over the place, such as: the people who graduated college during the Great Recession, people who introduced the Internet to their parents, and so on. These are not generations.

In 2010, when crisis was really in the air, I was on the NPR show The State of Things in North Carolina, discussing the Baby Boom (no audio online). After attempting to clarify the difference between a generation and a cohort, I offered this dramatic example of a cohort — people born in 1960 specifically:

So if you were born in 1960, graduated college in 1982, and entered the labor force in the middle of an awful recession, then managed to pull some kind of career together, got married and divorced, by the 90s it was time to be downsized already for the first time, you’re 40 in 2000, and it’s time for the dot-com bubble, you’re out of your job again, and here you are ready for your retirement, finally, you’ve been left in your own 401(k), having to put together your own pension, and of course now that’s in the tank and your house isn’t worth anything. So that insecurity and instability is really imprinted this group. We talk about the 60s, and civil rights and antiwar, and great music and everything, but that’s seeming like a long time ago now for people who are looking at retirement.

I don’t know if anyone actually had that experience, but it seems likely.

Anyway, if people really want to keep using these generation labels, and it seems unlikely to stop now given the marketing payoff from naming rights, than that’s the way it goes. But please don’t ask demographers to define them.

Notes

* This is a little different from the population estimates the Census Bureau produces, which are coded by age rather than year of birth. I use the ACS data because they report year of birth, and because it’s easier. The differences are very small.

** Thanks to Mo Willow for pointing this out.

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The persistence of gender differences, Catholic furor edition

The Pope’s convention of male moral pontificators is convening to discuss family matters. One of the most important questions, as Ross Douthat has described at great length, is how to strike the right balance between laxity and rigorism on the question of divorce, to maximize Church membership by keeping divorced people (and their children) on the rolls while sending the minimum of those members to hell for adultery after they remarry.

catholic-laxity-game

(This is a great project for a sociologist interested in simulations.)

Divorce is a leading issue, but homosexuality looms. In yesterday’s New York Times, Frank Bruni writes about the American Catholic Church leadership’s obsession with homosexuality:

…Catholic officials here have elected to focus on this one issue and on a given group of people: gays and lesbians. Their moralizing is selective, bigoted and very sad. It’s also self-defeating, because it’s souring many American Catholics, a majority of whom approve of same-sex marriage, and because the workers who’ve been exiled were often exemplars of charity, mercy and other virtues as central to Catholicism as any guidelines for sex. But their hearts didn’t matter. It was all about their loins. Will the church ever get away from that?

As Bruni reports, employees at Catholic institutions are still being fired for acknowledging their homosexuality (the starting point, incidentally, of the new movie Love Is Strange, for the couple played by John Lithgow and Alfred Molina).

loveisstrange

Bruni may speak for the majority of American Catholics when he condemns the Church’s witch-hunt. But as the synod approached, a group speaking for the academic right wing of the anti-gay movement within American Christianity beseeched the Holy Father to use the occasion to “express timeless truths about marriage,” which are that cohabitation, divorce, homosexuality, and pornography are wrong.

(Aside: Academics will appreciate the funny requests for money for themselves and their movement in the letter. They want money for “cross-discipline, longitudinal research on the role of pornography and ‘no fault’ divorce in the marriage crisis,” and they want “mandatory courses [for seminarians] covering social science evidence on the benefits of marriage, threats to marriage, and the consequences of divorce and cohabitation to children and society.”)

The letter calls for opening a new front in the war on modern marriage law, using the language of religious freedom to prevent divorce (as they have urged with regard to marriage equality):

Many do not know that religious freedom is routinely violated by divorce judges who ignore or demean the views of a spouse who seeks to save a marriage, keep the children in a religious school, or prevent an abandoning spouse from exposing the children to an unmarried sexual partner.

In other words, they want to argue — in court — that divorced spouses who have new partners are violating the religious freedom of their ex-spouses. (By this logic, I guess, I could argue that them even making this argument violates my religious freedom not to live in a society where someone makes this argument.)

They would like the Pope to:

Support efforts to preserve what is right and just in existing marriage laws, to resist any changes to those laws that would further weaken the institution, and to restore legal provisions that protect marriage as a conjugal union of one man and one woman, entered into with an openness to the gift of children, and lived faithfully and permanently as the foundation of the natural family.

Regnerus himself (follow the Regnerus tag for background) is taking the long view in his new role as movement intellectual. And the logic he uses helps explain Bruni’s puzzle over the Church’s homosexuality obsession. In an interview on a Christian radio station last month, Regnerus said there are a lot of objectionable marriage laws outside the same-sex marriage debate. He went on:

It’s important for us to not sort of just get caught up in the big kahuna around same-sex marriage, and to remember, as we’ve seen with the abortion debate, incremental change, legally, can occur even after all hope seems lost. But there’s also sort of – nobody’s holding us back from creating a marriage culture in, say, the Catholic Church or broader evangelicalism. We hold ourselves back, right? I tend to think the way things are rolling at the moment, it’s not just as if same-sex marriage fell out of the sky, and was on our plate. I mean, it was paved, right? The road to there was paved in part by all sorts of poor laws around opposite-sex marriage, right? And the giving away of what we might call the sort of functional definition of marriage, visions of complementarity, you know? We have bought, hook, line, and sinker, the idea that essentially men and women are interchangeable in our marriages. And it’s hard to get away from that, but I think we’re going to have to. So in some ways we want to fashion a counter-cultural movement regardless of what the states signal.

The way I see the way he sees it, the mission is to protect and restore gender differentiation itself. That agenda, not just old-fashioned patriarchal views, underlies the anti-homosexual obsession, the opposition to marriage equality and single motherhood, and the effort to protect the male religious hierarchy.

Different genders

I object to this agenda personally on moral grounds, naturally. But my scientific opinion is that the concern is misplaced. In some broad ways, of course, gender differences have eroded — for example, as women have gained political rights and access to gainful employment. And on the rare occasions when they choose to, men can even be nurses, teachers, and stay-at-home parents. You might call all that a convergence of gender roles. But gender differentiation is alive and well.

boysactivities

In some respects the gender binary is resurgent after a brief surge of androgyny in popular culture around 1970 (which Jo Paoletti traces in the fascinating forthcoming book, Sex and Unisex). A visit to the Sociological Images Pinterest board on pointlessly gendered products helps reinforce this point — there are even gendered kids’ Bibles:

kidsbibles

Or consider the relative frequency of the phrases “toys for boys” and “toys for girls” in American English as a fraction of references to “toys for children,” from Google ngrams:

toysngrams

In fact, it seems to me that gender difference is proliferating. But it’s not just the binary difference.

One of the benefits of the high visibility of the marriage rights movement has been its exposure of gender variance. Far from a convergence around a single gender, as the traditionalist Christians fear — or the elimination of gender — instead I think we have a growing diversity of gender perspectives and identities. The very narrow interpretation of this is that “men and women are interchangeable.” The reality is that no one is.

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The number one cause of traffic fatalities

Please don’t text while driving.

Note: I have updated this post to reflect a response I received from Matt Richtel.

A data illustration follows the rant.

I don’t yet have a copy of Matt Richtel’s new book, A Deadly Wandering: A Tale of Tragedy and Redemption in the Age of Attention. Based on his Pulitzer-prize winning reporting for the New York Times, however, I’m afraid it’s unlikely to do justice to the complexity of the relationship between mobile phones and motor vehicle accidents. Worse, I fear it distracts attention from the most important cause of traffic fatalities: driving.

A bad sign

The other day Richtel tweeted a link to this old news article that claims texting causes more fatal accidents for teens than alcohol. The article says some researcher estimates “more than 3,000 annual teen deaths from texting,” but there is no reference to a study or any source for the data used to make the estimate. As I previously noted, that’s not plausible.

In fact, only 2,823 teens teens died in motor vehicle accidents in 2012 (only 2,228 of whom were vehicle occupants). So, I get 7.7 teens per day dying in motor vehicle accidents, regardless of the cause. I’m no Pulitzer-prize winning New York Times journalist, but I reckon that makes this giant factoid on Richtel’s website wrong, which doesn’t bode well for the book:

richtelpage

In fact, I suspect the 11-per-day meme comes from Mother Jones (or someone they got it from) doing the math wrong on that Newsday number of 3,000 per year and calling it “nearly a dozen” (3,000 is 8.2 per day). And if you Google around looking for this 11-per day statistic, you find sites like textinganddrivingsafety.com, which, like Richtel does in his website video, attributes the statistic to the “Institute for Highway Safety.” I think they mean the Insurance Institute for Highway Safety, which is the source I used for the 2,823 number above. (The fact that he gets the name wrong suggests he got the statistic second-hand.) IIHS has an extensive page of facts on distracted driving, which doesn’t have any fact like this (they actually express skepticism about inflated claims of cellphone effects).

After I contacted him to complain about that 11-teens-per-day statistic, Richtel pointed out that the page I linked to is run by his publisher, not him, and that he had asked them to “deal with that stat.” I now see that the page includes a footnote that says, “Statistic taken from the Insurance Institute for Highway Safety’s Fatality Facts.” I don’t think that’s true, however, since the “Fatality Facts” page for teenagers still shows 2,228 teens (passengers and drivers) killed in 2012. Richtel added in his email to me:

As I’ve written in previous writings, the cell phone industry also takes your position that fatality rates have fallen. It’s a fair question. Many safety advocates point to air bags, anti-lock brakes and wider roads — billions spent on safety — driving down accident rates (although accidents per miles driven is more complex). These advocates say that accidents would’ve fallen far faster without mobile phones and texting. And they point out that rates have fallen far faster in other countries (deaths per 100,000 drivers) that have tougher laws. In fact, the U.S. rates, they say, have fallen less far than most other countries. Thank you for your thoughtful commentary on this. I think it’s a worthy issue for conversation.

I appreciate his response. Now I’ll read the book before complaining about him any more.

The shocking truth

I generally oppose scare-mongering manipulations of data that take advantage of common ignorance. The people selling mobile-phone panic don’t dwell on the fact that the roads are getting safer and safer, and just let you go on assuming they’re getting more and more dangerous. I reviewed all that here, showing the increase in mobile phone subscriptions relative to the decline in traffic accidents, injuries, and deaths.

That doesn’t mean texting and driving isn’t dangerous. I’m sure it is. Cell phone bans may be a good idea, although the evidence that they save lives is mixed. But the overall situation is surely more complicated than TEXTING-WHILE-DRIVING EPIDEMIC suggests. The whole story doesn’t seem right — how can phones be so dangerous, and growing more and more pervasive, while accidents and injuries fall? At the very least, a powerful part of the explanation is being left out. (I wonder if phones displace other distractions, like eating and putting on makeup; or if some people drive more cautiously while they’re using their phones, to compensate for their distraction; or if distracted phone users were simply the worst drivers already.)

Beyond the general complaint about misleading people and abusing our ignorance, however, the texting scare distracts us (I know, it’s ironic) from the giant problem staring us in the face: our addiction to private vehicles itself costs thousands of lives a year (not including the environmental effects).

To illustrate this, I went through all the trouble of getting data on mobile phone subscriptions by state, to compare with state traffic fatality rates, only to find this: nothing:

cellphones traffic deaths with NEJM.xlsx

What does predict deaths? Driving. This isn’t a joke. Sometimes the obvious answer is obvious because it’s the answer:

cellphones traffic deaths with NEJM.xlsx

If you’re interested, I also put both of these variables in a regression, along with age and sex composition of the states, and the percentage of employed people who drive to work. Only the miles and drive-to-work rates were correlated with vehicle deaths. Mobile phone subscriptions had no effect at all.

Also, pickups?

Failing to find a demographic predictor that accounts for any of the variation after that explained by miles driven, I tried one more thing. I calculated each state’s deviation from the line predicted by miles driven (for example Alaska, where they only drive 6.3 thousand miles per person, is predicted to have 4.5 deaths per 100,000 but they actually have 8.1, putting that state 3.6 points above the line). Taking those numbers and pouring them into the Google correlate tool, I asked what people in those states with higher-than-expected death rates are searching for. And the leading answer is large, American pickup trucks. Among the 100 searches most correlated with this variable, 10 were about Chevy, Dodge, or Ford pickup trucks, like “2008 chevy colorado” (r = .68), shown here:

deaths-searches

I could think of several reasons why places where people are into pickup trucks have more than their predicted share of fatal accidents.

So, to sum up: texting while driving is dangerous and getting more common as driving is getting safer, but driving still kills thousands of Americans every year, making it the umbrella social problem under which texting may be one contributing factor.

I used this analogy before, and the parallel isn’t perfect, but the texting panic reminds me of the 1970s “Crying Indian” ad I used to see when I was watching Saturday morning cartoons. The ad famously pivoted from industrial pollution to littering in the climactic final seconds:

Conclusion: Keep your eye on the ball.

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