For at least three years, the website for New York Times reporter Matt Richtel’s book, A Deadly Wandering, about the dangers of texting and driving, has prominently featured a bogus internet meme statistic claiming that 11 teens per die from texting and driving accidents every day. I first debunked it in 2014, by simply pointing out that not even 11 teens die per day from all auto accidents regardless of cause.
I wrote about it again here. I also complained that Richtel had a financial interest in hyping teen texting deaths, and that it was unreasonable to say traffic fatalities were “soaring at a rate not seen in 50 years,” when in fact fatalities were almost at a 50-year low (down more than 60% from 1966, on a per capita basis, and still below the pre-recession levels).
I emailed Richtel, as well as the publisher. I tweeted. All to no avail — until sometime between last September (the last archived copy at the Wayback Machine) and today, when I saw they had finally removed the bogus statistic. Here’s the change:
The footnote stayed the same, which is funny because it’s not a “statistic” anymore (it never was on the IIHSFF site).
Anyway, because I complained so much it’s important to acknowledge the change.
Meanwhile, while Richtel and his publisher were taking three years to do 10 minutes work to correct an egregious factual error, the meme was still going around. I happened to see it today as I was reading an editorial in the Moscow-Pullman (Idaho) Daily News, in support of our lawsuit against Trump (long story), when I saw this letter:
Letter: Texting while driving is more lethal than school shootings
May 29, 2018
Kudos to the Daily News Editorial Board for having the courage to state (“Our View: Gun reform alone can’t prevent mass killings,” May 23) “it is not the guns killing people, it is the people pulling the trigger …” It sounds like something the NRA would say. And the real problem facing us is ” how to prevent weapons from getting into the wrong hands ” As a longtime NRA member I support all rational steps taken to do exactly that.
Blaming the NRA or gun manufacturers for school shooting deaths is akin to blaming Facebook and/or Apple iPhones and/or Ford Motor Company for teen texting-while-driving deaths, which some reports say cause an average of 11 teen deaths in America every day. It’s not Facebook or the cellphone or the automobile maker that runs that car through the red light or up a tree. It’s the distracted person behind the wheel. Let’s see what kind of reaction we get when we try to separate those young people from their cellphones for their own safety and that of those in the car with them. Mom and dad, have at it.
Texting while driving is vastly more lethal to our teens than school shootings.
What if everything you learned about traffic fatalities you got from Matt Richtel at the New York Times?
On April 27, Richtel wrote:
Over the last seven years, most states have banned texting by drivers, and public service campaigns have tried an array of tactics — “It can wait,” among them — to persuade people to put down their phones when they are behind the wheel.
Yet the problem, by just about any measure, appears to be getting worse. Americans confess in surveys that they are still texting while driving, as well as using Facebook and Snapchat and taking selfies. Road fatalities, which had fallen for years, are now rising sharply, up roughly 8 percent in 2015 over the previous year, according to preliminary estimates.
I left the paragraph breaks as they were, so you can see the connection he implied. Sure seems that all that texting is driving up the rate of fatalities, although there is no evidence offed for that. Of course, since you only read Richtel, you don’t know that since 1994, cell phone subscription rates have risen 1200% while traffic fatalities have fallen 13%. (My series on this, with all these facts, is under the texting tag.)
But what about this “now rising sharply” fact? The same fact – an estimated 8% increase in one year, grew from “now rising sharply” on April 27 to “soaring at a rate not seen in 50 years” by May 22.
When I complained to the NYT Science Desk that this was a misleading representation of a traffic fatality rate that is still at historically low levels, someone checked it out and nicely informed me they had “confirmed the article accurately states the fact: preliminary estimates indicate road fatalities are rising at a rate not seen in 50 years.” Complaint denied.
Assuming you share my obsession with this problem of hyping traffic fatalities – and distracting the public with stories of bad drivers instead of paying attention to the real problem, which is rampant car culture itself – then you’ll want to make a distinction between the facts themselves and the NYT representation of them.
The fact here is actually kind of weird. Instead of using the official traffic fatality rates, which the National Highway Traffic Safety Administration hasn’t released yet for 2015, Richtel here is reporting the preliminary 2015 estimate from a private group, the National Safety Council. The weird thing is that NSC uses a different method, counting people as dead from a traffic incident if they die from any cause within a year of the accident, while NHTSA only counts them as dead from the incident if they die within 30 days. The rule is arbitrary either way, but I prefer to NHTSA method in the absence of a compelling argument. (As any Law & Order fan can tell you, people who die can have that death attributed to something that happened years earlier if the medical examiner owes the detectives a favor.) Not surprisingly, NSC produces estimates that are higher – about 8% higher, about 3,000 deaths more than the roughly 35,000 NHTSA reports. The longer death window seems bad for comparing rates over time, because the population is aging and therefore the death rate will probably rise among people who have had an accident in the previous year just because they’re older on average.
Anyway, since NSC doesn’t report their long-term trend (at least on the free part of their website), I applied their estimate of the “soaring” 2015 change – an 8.2% increase in total deaths – to the NHTSA series (helpfully recorded on this Wikipedia page), to extend the series to 2015. We also now have the Federal Highway Administration’s report on vehicle miles traveled in 2015 (+4% from 2014), so I can use that estimate of total deaths to calculate deaths per mile for 2015, as well as deaths per person (using the average of the Census Bureau’s monthly estimates for the year, which was 321.4 million, +0.8%). By these calculations, Richtel’s soaring 8.2% increase in total deaths becomes a 4% increase in deaths per mile, and a 7.3% increase in deaths per person. Here are the 50-year trends, with recessions shown:
The dramatic increase in deaths for 2015, which is quite large on a relative scale during this time period – in fact, at no time in last 50 years has the number of deaths increase by 8.2% in one year – looks kind of small. But perhaps more important, it seems in line with the cyclical nature of the trend. Death rates fall during recessions and rebound afterwards. In fact, the declines in 2008 and 2009 – which were 9.3% and 9.5% respectively – are also unprecedented during this period, so a larger rebound is not surprising.
So how should Richtel describe the trend? Keep in mind this is a reporter who is still promoting a book premised on the crisis of distracted driving – the homepage for which, despite notifications to the author and publisher, still repeats the bogus internet meme that 11 teens per day die from texting while driving.
After I complained on Twitter, Richtel tweeted to his followers:
So I put the description question to the test of my Twitter readers, offering them a poll. I made two figures, one from the actual death trend (with my 2015 estimate), and one with the same trend in reverse, and asked people (without comment) which one they thought was better described by Richtel’s phrase:
Here are two trends. Based only on the description given, which series do you think fits best? (poll follows) pic.twitter.com/l8ooOIETbv
I don’t think it’s very strong vindication to barely eke out a majority in a poll where people are asked to choose which is right, what you said or the exact opposite of what you said. I would think real reporting would have a higher rate of concordance than that.
The guests were researcher David Strayer; Jeff Larason, director of highway safety for Massachusetts; Joan Claybrook, former administrator of the National Highway Traffic Safety Administration; and Ben Leiberman, the co-founder of Distracted Operators Risk Casualties (DORCs), which is trying to develop the technology (and legislation) to allow police to scan phones at the scene of an accident to determine whether they were being used at the time of the crash.
I am pretty sure that every one of these guests knows that our roads are safer now than they have ever been, and that accident and fatality rates are at historic lows. And yet the entire conversation — without explicitly stating any trend facts — was conducted as if it is self-apparent that the problem is getting worse and worse. Several callers said they see more and more drivers on their phones; someone said one-in-four drivers is using a phone; someone said texting and driving is as dangerous as driving drunk. Maybe more and more people are using their phones while they drive, but that’s not making the roads less safe than they used to be.
Why can’t they handle the truth? Texting and other distractions are dangerous, and people shouldn’t do them — and the roads are getting safer over time. Here are the fatality trends for the last 20 years, from NHTSA:
In the last 20 years, fatalities per mile have fallen 38% and fatalities per person have fallen 34%. That doesn’t make texting and driving okay, okay? But it’s true.
Further, much was made in the conversation about the special risks posed by younger drivers, who are said to be less skilled and more distractable behind the wheel. This also highly misleading. A separate data series, maintained by the Insurance Institute for Highway Safety, has fatal accidents by the age of the driver going back to 1975. This shows that the steepest decline in fatal accidents has been among teenage drivers — a stunning 71% decline in fatal accidents per person in that age group since the peak in 1978. In fact, teen drivers are now involved in fewer fatal accidents per person than 20-34-year-olds:
I can understand that for advocates a story of continuously increasing peril is attractive. That doesn’t justify their refusal to speak facts, but it’s at least predictable. The guests all spoke of the need for more money to be devoted to the problem, more legislation, more awareness — all things that (no offense) pay their personal and professional bills.*
Less forgivable are the journalists who refuse to look seriously at the issue even as they devote inordinate amounts of time to it. This is a serious disservice, because the media-consuming public may want to seriously consider how to allocate resources to address different problems. Call me crazy, but knowing the facts seems important for this process. And in this case it’s not just that the facts are a little out of line with the narrative — they absolutely and dramatically contradict it.
Now for the fact you think I would be reluctant to mention: for the first time in two decades, the rate of property-damage-only accidents has increased for three years in a row. This may be a better measure of accident risk, because the fatality numbers could be partly driven by things like improved medical response time or auto safety devices. Still, property-only accidents per mile are down 21% since 1994 (while mobile phone subscriptions have risen more than 1200%).
That is an interesting turnaround, worth looking into. Unfortunately, I don’t have much confidence in the current crop of experts to offer a credible explanation for it.
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:
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).
What does predict deaths? Driving. This isn’t a joke. Sometimes the obvious answer is obvious because it’s the answer:
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.
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:
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:
Brad Wilcox has written up his best case for how marriage protects women and girls from violence. I discussed his initial post earlier, but the blowup has prompted me to provide more general advice for the critical data citizen — reader, writer, and editor — who has to decide what to believe when someone comes at them with a data story.
I have some tips about that at the end, but first this elaborate setup.
The information in this section is true
Consider three stories:
When Melanie Thernstrom’s toddler, Kieran, first ate cheese, he immediately had a massive allergic attack. His face swelled, his skin turned red and scaly, and he started gasping for breath. They jumped in their car and rushed to the hospital, where doctors were able to save him.
Chicago mother Tynisha Hilliard had six children in the car when someone opened fire. “Mommy, I’m shot,” said her nine-year-old boy from the back seat. Hilliard immediately sped to the nearest hospital. “My reaction was to save my son. That’s all I can do, save my son,” she said. After emergency surgery for a gunshot wound to the chest, the boy was expected to survive.
When Dodgers catcher A. J. Ellis’s wife, Cindy, went into labor, they hopped in the car and headed for NYU hospital, normally a 35-minute drive. Despite racing through traffic with a police escort, they didn’t make it in time – the baby was born in the back seat – but they arrived at the hospital moments later, met by an emergency crew that whisked mother and child to care and safety in the hospital.
What do these stories have in common? Children’s lives saved by cars.
Is this part of a wider phenomenon? I know what you’re thinking: The pollution from cars hurts children, the vast resources devoted to infrastructure for cars could be spent instead in ways that help children, the need for gas causes wars all the time, and the individualism promoted by car culture contributes to social isolation instead of community efficacy.
Maybe. But let’s theorize a little. Here are three ways cars might be good for children’s health:
Kids whose families have cars can get them to doctors in an emergency. Considering that in modern societies a lot of what kills children is various kinds of accidents and medical emergencies, this could be a major advantage.
Say what you want about individualism, but it’s emerged as a modern character trait in tandem with the cultural shift that brought us the view of children as priceless individuals. Car culture is a major prop of individualism, so it’s reasonable to hypothesize that people who drive individual cars are more totally devoted to their priceless individual children’s well-being (rather than, say, the well-being of children in general).
Being able to transport oneself at will — any time, any place — may create a sense of self-efficacy, of mastery over one’s environment, which makes people refuse to accept failure (or illness or death), and thus devote themselves more confidently to their survival and the survival of their children.
Don’t take a theoretical word for it, though — let’s go to the data. Here are three small studies.
Cars and children’s health across countries
First we examine the relationship between the number of passenger cars per capita and the rate of child malnutrition in 110 countries (all the countries in the World Bank’s database that have measures of both variables in the last 10 years — mostly poor countries). The largest — India, China, Brazil, and the USA — are highlighted (click to enlarge).
This is a very strong relationship. This single variable, cars per capita, statistically explains no less than 67% of the variation in child malnutrition rates.
But, you liberals object, cars are surely more common in wealthier countries, so this relationship may be spurious. Sure, income and cars are positively correlated (r=.86, in fact). But when I fit a regression model with both per capita income and per capita cars, cars still have a highly significant statistical association with malnutrition (p<.001). (All the regression models are in the appendix at the end.)
Cars and child death rates across US states
Second, we take a closer look within the United States. Here there is a lot less variation in both the number of cars and the condition of children. Still, there is a clear relationship between private cars per person and the death rate of children and teenagers: Children are substantially less likely to die in states with more privately owned passenger cars (click to enlarge).
Again, there is less variation in income between U.S. states than there is between countries of the world. But to make sure this is not just a function of state income, I fit a regression model with cars and a control for median household income. The statistical effect of private cars remains significant at the p<.05 level, confirming it is unlikely to be due to chance.
Car commuting and children’s disabilities within the US
Third, let’s go still further, not just comparing US states but comparing children according to the car-driving habits of their parents within the US. For this I got data on children’s disabilities (four kinds of disability) and the means of transportation to work for their parents using the 2010-2012 American Community Survey, with a sample of more than 700,000 children ages 5-11.
Sure enough, children who live with parents who drive to work are substantially less likely to have disabilities than those who don’t live with a parent who drives to work:
Again, could this be because richer families are more likely to include car-driving parents? The regressions (below) show that, although it is true that children in richer households are less likely to have disabilities, the statistical effect of parents’ commuting method remains highly significant in the model that includes household income.
In summary: Children are less likely to be malnourished if they live in a country with more cars per person; they are less likely to die if they live in a state with more cars per person, and they are less likely to have disabilities if they live with parents who commute to work by car. All of these relationships are statistically significant with controls for income (of the country, state, or family). These are facts.
Compare this analysis to the question of marriage and violence. In their piece for the Washington Post (discussed here), Brad Wilcox and Robin Fretwell Wilson wrote about #YesAllWomen:
This social media outpouring makes it clear that some men pose a real threat to the physical and psychic welfare of women and girls. But obscured in the public conversation about the violence against women is the fact that some other men are more likely to protect women, directly and indirectly, from the threat of male violence: married biological fathers. The bottom line is this: Married women are notably safer than their unmarried peers, and girls raised in a home with their married father are markedly less likely to be abused or assaulted than children living without their own father.
With the facts above I can accurately offer this parallel construction:
Some cars pose a real threat to the health and safety of children. But obscured in the public conversation about auto safety, pollution, and environmental degradation is the fact that some other cars are more likely to protect children, directly and indirectly, from threats to their health and safety: cars driven by their own, responsible, caring parents. The bottom line is this: Children in places with more cars — and in families where parents commute by car — are notably healthier than peers without cars.
At the end of his followup post, Brad concludes:
Of course, none of these studies definitively prove that marriage plays a causal role in protecting women and children. But they are certainly suggestive. What we do know is this: Intact families with married parents are typically safer for women and children. … That’s why the conversation about violence against women and girls … should incorporate the family factor into efforts to reduce the violence facing women and girls.
I am equally confident in my conclusion:
Of course, my brief studies don’t definitively prove that cars plays a causal role in protecting children’s health and safety. But they are certainly suggestive. What we do know is this: Societies and families with cars are typically safer and healthier for children. That’s why the conversation about children’s well-being should incorporate the car factor into efforts to reduce the harms too many children continue to experience.
Both the marriage story and the car story are misleading data manipulations that substitute data volume for analytical power and present results in a way intended to pitch a conclusion rather than tell the truth.
When is a non-causal story “certainly suggestive”? When the person giving you the pitch wants you to believe the conclusion.
Please do not conclude from this that all data stories are equally corrupt, and everyone just picks the version that agrees with their preconception. Not all academics lie or distort their findings to fit their personal, political, or scientific conclusions. I may be more motivated to criticize Brad Wilcox because I disagree with his conclusions (and there may be people I agree with who use bad methods that I haven’t debunked), but that doesn’t mean I’m dishonest in my interpretation and presentation of evidence. Like a real climate scientist debunking climate-change deniers, I am happy that discrediting him is both morally good and scientifically correct (and I think that’s not a coincidence).
There are two main problems with both the cars story and the marriage story. First is selection into the independent variable condition (marriage and car ownership). People end up in these conditions partly because of their values on the dependent variable. For example, women in marriages are less likely to be raped on average because women don’t want to marry men who have raped them, or likely will rape them — the absence of rape causes marriage. In the case of children with disabilities, there is evidence that children’s disabilities increase the odds their parents will divorce (which means at least one of the parents isn’t in the household and so can’t be a car-commuting parent in the ACS data).
The other main problem is omitted variables. Other things cause both family violence and children’s health, and these are not adequately controlled even if researchers tell you they control for them. Controlling for household income (and other easily-measured demographics) does not capture all the benefits and privileges that married (or car-owning) people have and transfer to their children. For tricky questions of selection and omitted variables, we need to get closer to experimental conditions in order to provide causal explanations.
Tips for critical reading
So, based on Wilcox’s car story and my car story, here are practical tips to help you avoid getting hoodwinked by a propagandist with a PhD — or a data journalist looking at a mountain of data and a tight deadline. These are some things to watch out for:
Scatter plot proof
Impressive bivariate relationships; they may be presented with mention of control variables but no mention of adjusted effect size. That’s what I did with my scatter plots above. If you have adjusted results but don’t show them, it’s selling a small net effect with a big unadjusted label. (Wilcox examples here; Mark Regnerus does this, too.)
A classic example is the Obama food stamp meme, but Wilcox had a great example a few years ago when he wanted to show the drop in divorce that resulted from hard times pulling families together during the recession. If you assume divorce is always going up (it fell for decades), this looks like a dramatic change (he called it “the first annual dip since 2005”):
No head-to-head comparison of alternative explanations
This is a lot to ask, but real social scientists take seriously the alternative explanations for what they observe, and try to devise ways to test them against each other. Editors often see this as a low-hanging fruit for removal, because cutting it both shortens the piece and strengthens the argument. In the rape versus marriage story, Wilcox nodded to the alternative explanation that “women in healthy, safe relationships are more likely to select into marriage” — which he called “part of the story” — but he offered nothing to help a reader or editor adjudicate the relative size of that “part” of the story. This connects to the next red flag.
Greater than zero proof
Sometimes just showing that something exists at all is offered as evidence of its importance. That’s why I included three anecdotes about children being saved by private passenger cars — it happened, it’s real. The trick is to identify whether something matters in addition to existing. Here’s a Wilcox example where he showed that a tiny number of people said they didn’t divorce because of the recession; here’s an example in which Nate Cohn at the NYTimes Upshot said that 2% of Hispanics changing their race to White was “evidence consistent with the theory that Hispanics may assimilate as white Americans.” Neither of these provide any comparison to show how important these discoveries were relative to anything else — other reasons people delay divorce? other reasons for race-code changes? — they just exist. This is reasonable if you’re discovering a new subatomic particle, but with social behavior it’s less impressive.
Piles of studies
The reason I presented the car results as the three separate “studies” was to make the point that you can have a lot of studies, but if none of them prove your point it doesn’t matter. For example, in his post Wilcox linked to a series of publications about how children whose parents weren’t married were more likely to be sexually abused, but none of them handle the problem of selection into marriage I described above. Similarly, a generation of research showed that women who have babies as teenagers suffer negative economic consequences, but those effects were all exaggerated because people didn’t take selection into account (women with poor economic prospects are more likely to have babies as teenagers).
Describing one side of inequality as a social good
Let’s say that, in street fights, the person with a gun beats the person with a knife more than 50% of the time. Do we conclude people should have more guns? Some benefits are absolute and have no zero-sum quality to them. (I can’t think of any, but I assume there are some.) Normally, however, we’re talking about relative benefits. The benefits of marriage, or the economic benefits of education, are measured relative to people who aren’t married or schooled.
The typical description of such a pattern is, “This causes a good outcome, we should have more of it.” But we should always consider whether the best thing, socially, might be to reduce the benefit — that is, solve the problems of the people who don’t have the asset in question — rather than try to increase the number of people with the asset.
The benefit of cars that comes from being able to get to the hospital quicker may only be relative to the poor suckers stuck in an ambulance while your personal cars are blocking up Manhattan.
A powerful new documentary by Werner Herzog is making the rounds (presented by the phone companies), showing the consequences of accidents caused by phone-distracted driving. It got me to revisit my posts on mobile phones and traffic accidents and do some more speculating about this.
A new report from the federal government shows that, of 29,757 fatal crashes in 2011, 10% were reported to involve a distracted driver. Of those distracted-driver crashes, 12% involved a driver using a cell phone. Thus, the 350 fatal crashes in which a driver on a cell phone was reported to be involved account for 1.2% of all fatal crashes. (This is probably an undercount, as accidents can’t be coded this way without witnesses or a driver confession.)
Meanwhile, from 1994 to 2011, mobile phone subscriptions increased more than 1200%, from 24 million to 316 million. During that time, the number of traffic fatalities per mile driven has fallen 36%, and property-damage-only accidents per mile have fallen 31%. The improved safety of American roads is a big accomplishment. Here are the trends:
Sources: Accidents and deaths: this and earlier reports; Subscribers: this.
According to the US Department of Transportation, 5% of drivers are observed talking on handheld phones at any one time. Rates of distraction are presumably higher than this. There is an epidemic of distraction — and there is voluminous evidence that such distraction is dangerous — coinciding with large, continuous declines in traffic dangers.
How is this possible? Either (a) there is no connection between phones and accidents; (b) there is a positive causal connection, but it is swamped by whatever is making the roads safer; or, (c) cell phones are making the roads safer (say, by displacing other, more dangerous distractions, or by causing people to drive cautiously while they’re doing something they know is dangerous). It’s just a question. Anyway.
Cars kill people
The 1971 Keep America Beautiful Campaign featured this video: “People Start Pollution. People Can Stop It.” It shows intense industrial pollution in the background as an American Indian paddles his canoe. Then:
Some people have a deep, abiding respect for the natural beauty that was once this country. [Someone throws a bag of fast food waste out of a passing car, and it lands at the feet of the canoer, now standing on the shore.] And some people don’t.
The “crying Indian” ad tried to hang the global pollution crisis on the personal malfeasance of individuals who litter (which is a real problem).
Is the anti-phone campaign trying to hang the problem of 30,000 road deaths per year in the U.S. on the reckless behavior of individuals who drive distracted? Distracted people causing carnage and destruction on the roads is terrible, of course. But a system of transportation that relies on people driving around in private cars is a much more fundamental problem.
I’m sure someone else has figured out how many lives are saved (presumably) from using public transportation versus private cars, but I didn’t easily find it. In addition to the environmental health benefits, clearly countries where people get around in cars have a lot more road deaths:
The number of rail deaths is very small: in these countries the car/rail death ratio averaged 36, almost three-times the car/rail mile ratio. (The U.S. is not on the chart because I didn’t have rail miles traveled. But the U.S. road death rate of 10.4 per 100,000 would make us 4th in this group, behind only Greece, Poland, and Portugal.)
Let’s put it this way: Some people have a deep, abiding respect for the safety of their fellow citizens. And some people don’t. Public transportation saves lives.