Asymptosis

A friend and I were discussing Brooks’ recent column about Anthony Kronman’s new book, “Confessions of a Born-Again Pagan.” I thought I’d share my thoughts here. Full disc: I haven’t read Kronman’s book, only Brooks’ column.

Some good stuff in there. Love the focus on books and writers. (Though Brooks’ [and Kronman’s?] barely-concealed dog-whistle adulation for dead white guys’ books is both predictable and predictably infuriating…)

Imagine you had to choose, and could choose: you can spend your whole life and raise your family in either of two equally prosperous countries. In one country people work lots of hours to attain that prosperity. In the other country people work far less. You don’t know anything else about these countries.

Which would you choose? The answer seems kind of obvious, right? Equally prosperous, and less work for me and my family? Sign me up!

But that straightforward question is almost never asked, explicitly, in discussions of prosperity, growth, and national well-being. The most obvious measure of that difference — hours worked per capita — is buried, invisible, and unavailable in the various national data sets scattered around the web. (The typical national measure you see out there is hours worked per worker.)

For the curious, here’s how more-prosperous countries (OECD and a handful of others) sort on the “hard-working” scale:

This average includes the whole population — workers, children, students, retirees, etc. — so it’s an index of how much the average person has to work over the course of their life. (More hours during working years, less or none during non-working years; it’s an average.) 

There’s one main generalized takeaway from this that I see: The less-work end of the spectrum is dominated by western European countries. People there work far less hours in the course of their lives. People in “Anglo”-model countries work far more.

Going back to choosing a country: you also want to know how prosperous it is in pure money terms, using something like GDP per capita. Here’s that (I’ve excluded tiny, crazy-high-GDP Luxembourg here — think: banking — to show other countries more clearly):

If you’re a rational shopper, you’ll choose Norway (yeah, they’ve got the advantage of all that oil…), Ireland, the Netherlands, or another country in the upper left. If an extra $5,000 or $10,000 a year is worth sacrificing four or five extra weeks of work, choose the U.S. (Think: “buying” an extra month of time with your family, doing things you like and love, every year. You decide. But do I need to remind you that 1. Life is short, and 2. “Family values” really do have value?)

One perhaps-surprising takeaway from this graph: hard-working countries aren’t richer. QTC. Causation? It seems improbable that working less would cause higher prosperity. Higher prosperity could quite reasonably cause people to work less. (The good old substitution effect, income versus leisure.) But the most likely conclusion is that high productivity (GDP per hour worked) is the 800-pound gorilla when it comes to prosperity. Long hours worked have zero or negative apparent effect on prosperity.

(Interesting parallel: hours worked per household member in the U.S. only “explain” seven percent of the variance between household incomes. Whodathunkit?)

Rather than eyeballing that scatter plot, you might want a handy index of which country to choose. Here’s one approach to what I’ll call Work-Weighted Prosperity: GDP/Capita divided by Hours Worked/Capita. If people in one country have to work lots of hours to get that prosperity, it gets ranked lower.

The takeaway here? Move to Luxembourg and get into banking.

The curious among you are probably wondering about different countries’ working-age populations (doesn’t actually vary that much), and the percentage of working age that are working (varies somewhat more). Here’s the spreadsheet.

Cross-posted at Angry Bear.

The meme is ubiquitous, and widely documented: Rich people work longer hours. Obvious implication: they deserve what they get, right? Ditto the poor.

Bunk.

Why? All the research supporting that meme looks at workers, not families. It completely ignores students, the retired, and anyone else who isn’t working. Alert the media: workers work and earn more than non-workers.

And, news flash: rich families are full of non-workers. If you look at families and their hours worked per person, you see a very different picture:

Here’s the same 3+ household data for working-age families only: those with a head of household under age 65.

Pretty much the same story.

This is all based on a fast-and-dirty random census pull of about 5,000 U. S. households, from IPUMS. It uses 3+ households as a proxy for families — probably not a bad proxy. A professional economist doing proper due diligence would fine-tune that, or even better turn to the Panel Study of Income Dynamics (PSID), which has better microdata to track families. Careful work would even allow them to track extended, multi-generation families, not just nuclear families living together. (Think: dynasties.) I’d expect the pattern we see here to be more pronounced in that view (though that’s just a surmise).

Here’s some more evidence, from across the pond:

Figure 1: Average hours of work across the distribution of earnings: UK, 2013

Figure 2: Changes in post-tax real hourly earnings and average hours for the median and top 1 per cent

Even as rich people’s incentives to work have skyrocketed, their hours worked have plummeted. This even though they’re far more likely to be doing interesting, engaging work in pleasant environments. Curious.

But still: low-income people work less. More of them are unemployed. Is that a surprise to anyone? (I’ll leave the “voluntary” argument to my gentle readers.)

There’s a stylized fact out there, universally repeated by economists and pundits, that seems to misrepresent the state of the world. There are some nice tractable research projects here for those who are paid to do such things.

Cross-posted at Angry Bear.

I have two daughters in college, a freshman and a junior.

You’d love them. Everybody does.

So when I see this video of a policeman casually walking along a line of college kids who are just sitting there, pepper spraying them right in the face,

…and I think about this:

… I think how easily it could have been one of my girls. College students, doing what college students do, expressing their passion and their commitment, putting themselves — their bodies — out there to make the world a better place.

I think about how easily it could have been one of them.

And I cry.

Update: It turns out, millionaires don’t care about income taxes.

You’re a Washington business owner making $500,000 a year.

You have millions, maybe tens of millions, in the bank.

You live in a big, gorgeous house on the water on Mercer Island, with sunset views and your sailboat and powerboat out front.

You and your family are actively involved in the community — arts, sports, non-profits, civic groups, and assorted commercial ventures.

Quite possibly, most of your family is here, and maybe has lived here for generations.

You have a large circle of long-time friends here that you love.

If you have school-age kids, they’re in schools that they love. (If the public schools don’t cut it where you are, they’re in great private schools.)

You have everything you want.

So…you’re obviously going to move your family to to Alaska or Wyoming to save $5,000 a year in taxes — for you, mere pocket change. (Note: if you’re only making a measly $400,001 a year, your extra taxes would be … five cents. And that’s not even considering the $4,000 a year your business[es] will save in B&O taxes.)

Yes, you could pretend that your legal residence is elsewhere. But if you’re like most of the people described above — I know, have known, lots of them, so I’m here to tell you — you’re also not willing to lie and cheat to save $5,000 a year.

While you’re thinking about it, check out Sightline Daily’s takedown of The Seattle Times‘ deceptive math.

Update: Instead of saying “Probably Not” in the title, I probably should have said “We have no idea.”

Being a Seattle parent with kids in private schools, I’ve been assailed for years by pronouncements and lectures by and about the Seattle-based Gottman Institute (tagline: “Researching and Restoring Relationships”). Their most widely known claim is their ability to predict, after watching a married couple for fifteen minutes, whether they’ll get divorced.

The basic Gottman theory — that facial expressions of contempt during couples’ interactions are predictive of divorce — seems very plausible, intuitively. But there are many intuitively plausible surmises that are just wrong.

And no matter how intuitively plausible it is, the claim always seemed fishy to me. But I never did the research to find out if their predictions were really accurate. Happily, somebody has finally done it for me. Here’s Andrew Gelman, god of all things statistical, blogging about a Slate article excerpted from Laurie Abraham’s Husbands and Wives Club.

Short story, their “predictions” are built on quicksand. Here’s how they do it.

Gather data on a bunch of couples — say, six variables for each couple. Determine which of those couples get divorced. Then run a program that finds an equation correlating the (presumably) predictive variables to the results. (These quite remarkable programs — the realm of ultimate-wonk physicists only a decade or two ago — are now available for free download, or as $49 Excel plug-ins. To quote my buddy Olav, “Isn’t it great living in the future?”)

Here’s what’s wrong: these programs will always find an equation that correlates the variables to the results. (With a greater or lesser “fit” to the data.) Does that mean the equation is predictive? Only if it makes an accurate prediction when applied to a different set of data.

That is what Gottman has not done, at least in his published papers. Every one of them has a new equation that — surprise — “predicts” the divorces in the group with surprising accuracy — the same group that was used to generate the equation.

Now this is true: if the program finds a good data-fitting equation (which Gottman seems to have done — multiple times), there’s a greater chance that the equation will actually be predictive. But there’s only one way to know: use it to predict. If the prediction fails, the predictive ability of the equation is falsified.

Gottman has not (to my knowledge) attempted any falsifiable predictions, so we have no idea if his predictions are true or false.

The Gottman Institute presumably has all the data to hand, and could test past predictions against future results. I’m wondering: will they now do so?

Google doesn’t turn up any hits for “Abraham” on the gottman.com site, so I’m thinking they haven’t responded. One can rather understand why. Abraham says in a comment to the Slate post (and, she says, in a footnote in the book — it’s not search-insideable on Amazon) that she repeatedly requested an interview in May 2009 but Gottman wouldn’t see her until October — too late for her book. I do wish she’d tried again before the excerpt was published, giving him ample benefit of the doubt.

But absent that, I’m quite curiously waiting to see what we hear from The Gottman Institute.

I can’t even begin to match the thinking and research that Bryan Caplan has done on the subject of kids and happiness (he’s writing a book titled Selfish Reasons to Have More Kids), but I can add my two bits, which generally support everything he says.

Short story, the research generally says “no.” Over large population samples, having kids makes people slightly less happy. But Bryan discusses a new (and very well-executed and convincing) study by Luis Angeles that contradicts that consensus.

The results in brief: overall, having two or three kids makes parents happier. Having one, two, or three kids makes married parents happier–but especially two or three.

This is totally in keeping with what I’ve said for a long time: The second kid makes parenting much easier, because single children want your constant and undivided attention, and it just gets wearing. My best piece of evidence is the wonderful line that one mother I knew reported from her child:

“Momma, look at me with your whole face!”

Kids are attention sponges/black holes. Two kids provide each other with much of the attention that each craves.

Angeles’ study supports this. A jump in reported life satisfaction (actually going from negative to positive for the full sample) comes when the second kid arrives. There’s another big jump with the third, then satisfaction drops with four or more.

Correlations Between Number of Children and Parents’ Reported Life Satisfaction (Fixed Effects)

(*, **, and *** denote statistical significance at 10, 5 and 1% levels. Note that with one exception–widows with one child, which hit 10% significance–these married-couple results are the only ones in Table 4 with statsig below the 10% level.)

Hypothesis: having two parents provides a sufficient baseline quantity of adult attention (for three or fewer children), at which point the attention provided by one or two siblings goes a long way toward satisfying the the children’s (seemingly bottomless) attention needs/wants.

This takes a big load off the parents, increasing their life satisfaction.

With four or more children, even two parents can’t provide the baseline level of sufficient adult attention–the other kids’ attention doesn’t suffice to replace that, and the load lands back on the parents who can’t satisfy it, resulting in reduced life satisfaction for the parents.

An old family friend told me and my spouse when we had our first child, “You can’t give them too much attention. You can give them the wrong kind of attention, but not too much. Kids act up when they’re not getting enough attention.”

My experience and observations bear that out in spades.

Another piece of advice based on all this (along with Bryan’s very wise “get a nanny if you can afford it” suggestion): have lots of play dates.

Bryan Caplan has done yeoman’s duty for us all by reviewing “all the major research on the response of fertility to economic incentives.”

He finds a “striking contrast” between two types of literature:

In the “birth subsidy” literature, researchers usually find fairly large effects in the expected direction.  In the welfare literature, in contrast, most researchers find little or no evidence that welfare increases fertility–or that welfare reform reduces it.

Turning to what he calls the “single best piece in both literatures put together: Kevin Milligan’s ‘Subsidizing the Stork’,” (which devises a natural experiment based on Quebec subsidies for having children from 1988 to 1997), he reports Milligan’s finding that financial incentives have a big impact on fertility choices: “up to a 25% increase in fertility for families eligible for the full amount.”

But perhaps even more interesting: young, unmarried women are far less responsive to incentives.

…both findings suggest that, as a rule, young unmarried women get pregnant by mistake.  They’re far from affirmatively wanting a baby, so modest financial incentives don’t change their plans.

This suggests that policy efforts and government funds are best directed toward sex ed and encouraging/subsidizing contraception for teenage girls, rather than taking away benefits that supposedly encourage them to have children.

Yet again, we have Supreme Court justices giving credence to the wacky notion that William Shakespeare of Stratford did not write the plays of William Shakespeare. Reported in the the WSJ.

It just goes to show that even supreme court justices who have long histories of probity and prudence can issue totally loony opinions. (cf Taney, Dred Scott.)

I’m not going to take the time to address the ridiculous points made in the article. It’s already been done, and at length. (What an unfortunate waste of good scholarly skills.)

http://shakespeareauthorship.com/

My main point: we have 29 extant editions of Shakespeare’s plays (not counting poems and etc.) that were published during his lifetime with his name on them as author. By many different printers and publishers. And the First Folio — published seven years after his death by his decades-long business partners, compatriots, and dedicatees in his will — trumpets him as author with attestations by them and several other leading writers of the day.

No anti-Stratfordian has explained how this vast, decades-long conspiracy could or would have been coordinated so hermetically that the “truth” only emerged in the nineteenth century, the discovery of an industrious fellow named “Looney.”

Read the pamphlets and broadsheets of Shakespeare’s day — their closest equivalent to today’s news outlets — and you’ll see how similar those writers were to today’s bloggers. They loved uncovering juicy news and insider gossip. (And yes — not that it’s pertinent to the matter at hand — like today’s bloggers they did their fair share of embroidery.)

Do anti-Stratfordians really believe that a huge conspiracy — requiring hundreds of people (and theater people at that) to keep a Really Big Secret for more than three decades — never came to anyone’s attention? Or if it did, that all of those broadsheetbloggers agreed to supress it?

Yeah, and alien abductions are common occurrences.

Here’s an admittedly condensed conversation I had with my friend Robin Williams, who’s published a beautifully written and wonderfully produced book (like all her books) arguing that Mary Sidney Herbert wrote the Shakespeare plays:

Me: Robin, we have all these published plays with his name on them.

Robin: Yeah, but even traditional scholars admit that some of them weren’t written by him.

Me: Well, yeah… [That’s because publishers were trying to capitalize on his name to sell books.]

Robin: See? There’s not a single shred of evidence that Shakespeare wrote the plays.

Like I said: sigh.

I’d really like to see how these judges would rule if there was a human life, a billion dollars, or a fundamental constitutional principle at stake.

My favorite comment on this subject:

The plays weren’t written by William Shakespeare. They were written by another guy with the same name.

I wrote recently about the fact that non-remunerated work — anything that doesn’t involve a money transfer — isn’t included in GDP. So painting your mother’s house, fixing your car, or cooking dinner isn’t reflected in that key measure of our prosperity and well-being — even though that work quite clearly contributes greatly to our prosperity and well-being.

Which got me wondering: how much of that type of work do we do? And what’s it worth?

The American Time Use Survey (ATUS), conducted by the U.S. Bureau of Labor Statistics, measures the amount of time people spend doing various activities such as paid work, childcare, volunteering, commuting, and socializing (PDF). I extracted activities that most of us would call “productive.”

2007 average hours per person (over age 15) per day
Housework    0.64
Food preparation and cleanup    0.52
Lawn and garden care    0.21
Household management    0.14
Purchasing goods and services    0.78
Caring for and helping household members    0.53
Caring for and helping nonhousehold members    0.2
Volunteering (organizational and civic activities)    0.16

Total hours per day    3.18
Total hours per year    1160.7

There are approximately 200 million Americans over age 15, meaning that we put in something like 232 billion home-work hours per year.

Value at different wage rates
At $5 an hour    $1.2 trillion
At $10 an hour    $2.3 trillion
At $15 an hour    $3.5 trillion
At $20 an hour    $4.6 trillion

This last — $20 an hour — was the median hourly wage in America for 2007 (not including benefits). Half the people make more, half the people make less.

Okay, the official GDP for 2007 was $13.8 trillion. Add $4.6 trillion and you get a total GDP of $18.5 trillion.

Home-work makes up 25% of that total GDP, or in other words increases reported GDP by 33%.

Now you have to figure that Europeans — with their shorter work weeks and long vacations — have a lot more time for home-work than we do. That may go a long way to explaining why the quality of life feels so gosh-darned good over there, even while their official GDP per capita hovers at 75-80% of the U.S.

If you truly believe in family values, those are some numbers worth pondering.