The church vs. the clan

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Jonathann F. Schulz writes,

Church marriage prohibitions pushed Europe away from a kin-based society and paved the way for the development of inclusive institutions. . . this paper highlights the role of kin networks for the formation of commune cities in Europe. This suggests that the seeds of the Great Divergence (Pomeranz, 2000) between Europe and other regions of the world were already planted by the Church’s incest prohibitions in late antiquity. Even today, medieval Church exposure and the absence of strong kin networks are associated with higher civicness and, ultimately, with more inclusive national institutions.

Pointer from Tyler Cowen.

Cousin marriage is still prevalent in parts of the world. There are those, including Schulz, who see this as a source of major cultural differences.

The time-to-learn effect and the science slowdown

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Scott Alexander writes,

There are eighteen times more people involved in transistor-related research today than in 1971. So if in 1971 it took 1000 scientists to increase transistor density 35% per year, today it takes 18,000 scientists to do the same task. So apparently the average transistor scientist is eighteen times less productive today than fifty years ago. That should be surprising and scary.

He is citing Bloom, Jones, Reenen & Webb (2018). This paper was discussed at a conference Alexander attended. He writes,

constant growth rates in response to exponentially increasing inputs is the null hypothesis. If it wasn’t, we should be expecting 50% year-on-year GDP growth, easily-discovered-immortality, and the like. Nobody expected that before reading BJRW, so we shouldn’t be surprised when BJRW provide a data-driven model showing it isn’t happening. I realize this in itself isn’t an explanation; it doesn’t tell us why researchers can’t maintain a constant level of output as measured in discoveries. It sounds a little like “God wouldn’t design the universe that way”

My favorite economics professor, Bernie Saffran, was wont to observe that learning takes calendar time as well as studying time. A student cannot master a concept merely by putting in a certain amount of hours studying it. It takes some amount of days or weeks or months for a concept to sink in. You could write L = f(T,t) where L is learning, T is the amount of time you spend studying, and t is the passage of calendar time. Throwing more T at a subject brings diminishing returns, unless you also increase t. We can speculate that some of the brain rewiring that takes place is unconscious, and you cannot artificially speed up this process.

Suppose that there is an analogous factor at work at the level of society. That is, scientific discovery depends on calendar time as well as the time that scientists spend working on a problem. It takes a while for X to sink in, and only after X has sunk in can we go on and discover Y.

Alexander sees no reason to expect that we can speed up scientific progress with simple policy changes or institutional tweaks. I am inclined to agree.

But having said that, I can think of institutional habits that may be holding progress back. I probably will write an essay on those. UPDATE: The essay offers two modest reforms.

Why some things get expensive

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My latest essay deals with a question posed by Patrick Collison. He asks why things like education and health care keep getting more expensive. My answer is part Baumol, part Hanson, part Caplan, and part Kling. An excerpt:

It may seem puzzling that the demand for health care and education keeps rising while measurable outcomes, such as longevity or skill attainment, show little response to higher spending. One reason is that the perceived benefits of health care and education may be high relative to their effects on outcomes. You may not be cured of your ailment, but the effort is what matters to you, so you seek treatment. Sending your child to an expensive college may not improve her skills, but your own sense of status depends on it, so you fork over the tuition.

Read the whole thing.

Tyler Cowen and Paul Krugman

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Forget your priors and lower your guard. This is about as good a conversation as you will get among economists. Early in the discussion Tyler suggests that this sort of conversation could be more educational than a conventional economic lecture, and I think that is true. I think if I were teaching from it, I would pause every few minutes to explain to students what is going on, and also perhaps to explain my own point of view where it is not expressed by either of the speakers.

About 28 or 29 minutes in, Krugman makes the point that some really major industries do not conform to textbook economic models, and he raises the question of why we then rely so much on the textbook model. I strongly agree, and in fact I have drafted a long essay about the implications. I wish they would have spent more time on this topic,abut perhaps they exhausted everything they could say.

Would forecasting tournaments reduce polarization?

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Barbara Mellers, PhilipTetlock, and Hal R.Arkes claim that they would.

We explore the power of an emerging methodology, forecasting tournaments, to encourage clashing factions to do something odd: to translate their beliefs into nuanced probability judgments and track accuracy over time and questions. In theory, tournaments advance the goals of “deliberative democracy” by incentivizing people to be flexible belief updaters whose views converge in response to facts, thus depolarizing unnecessarily polarized debates. We examine the hypothesis that, in the process of thinking critically about their beliefs, tournament participants become more moderate in their own political attitudes and those they attribute to the other side.

Pointer from Tyler Cowen.

I have my doubts.

1. People who hold polarized beliefs are not interested in making probability statements. It’s like asking a religious fanatic to give the probability that he is mistaken. It probably would be easy to steer people to rational thinking about politics if politics were about policy. But it’s not.

2. The interesting forecasts are conditional forecasts. As Scott Sumner put it, “(Unconditional) prediction is overrated.”
If there is strict gun control, will that reduce gun violence? We can argue about that, and we can even make empirical arguments, but we cannot run the controlled experiment that allows forecasts to be tested.

What I’m reading

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Grand Improvisation: America Confronts the British Superpower, 1945-1957, by Derek Leebaert. He writes,

Today it’s said habitually that “with the destruction at home in 1947, the British gave up trying to maintain a global empire” and that “a global political vacuum created by the collapse of the British empire” followed. . .people came to believe that some enormous transition had occurred years earlier, in 1947. It hadn’t. The events that transpired during these weeks, which surrounded the Truman Doctrine as well as the Marshall Plan, are very different from what historians believe.

His thesis seems to be that the diminution of Britain’s global role was less rapid and inevitable than we now take it to be. At the time, Britain still seemed formidable.

I think that I am well read on World War II and Vietnam. But this “in between” era is one with which I am less familiar. I believe that I am learning a lot.

My favorite elements of the book are his sketches of key officials, some well known and others less so. The story of Britain’s foreign secretary, Ernest Bevin, a left-wing politician who nonetheless valued Britain’s imperial prestige and came to loathe Stalin’s aggression, is new and interesting to me.

President Eisenhower made a decision not to send its forces into Vietnam (then known as Indochina) in 1954. Leebaert’s account of this decision differs somewhat from that of David Halberstam. Halberstam has Eisenhower shrewdly accessing the opinion of anti-interventionists, including Congressional leaders and General Matt Ridgway. Leebaert has Eisenhower wanting to intervene, but finding little Congressional support (one crucial opponent was Senator Lyndon Johnson!) without any help from the British. The Eisenhower Administration ardently sought British help, but the Brits declined.

There was in interesting tie-in between Vietnam and Suez. Both the Americans and the British entertained the idea of the Brits helping America in Vietnam in exchange for the Americans taking sides with the British on Suez. Had that deal materialized, events would have played out differently in both places. But in the end, neither the Americans nor the British were willing to sacrifice what it saw as its interests in one area in order to get support from the other side elsewhere.

Fragility

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Andreas Kern and Cora Jungbluth write,

Driven by an almost uninterrupted property boom, household debt has exploded. China’s home ownership is now the highest in the world at 89.68 %, rising from almost zero two decades ago.

Did you know that? I sure didn’t. Anyway, the point of the article is that China’s firms, households, and government have taken on very high levels of debt. This would seem to make the Chinese economy fragile.

Fragility in my mind means something that can fail catastrophically, with spillover effects that are impossible to contain. Something that can fail gracefully is not fragile. That is why the retail sector is not as fragile as the banking sector. Closing down Sears does not create huge spillover effects.

In general, what are the sources of fragility that we might worry about? Unsustainable government debt is high on my list. I suspect also that the electric grid is fragile. Bruce Schneier has me concerned with the Internet of Things.

Are the big tech firms fragile? Can Amazon fail gracefully, of would it necessarily fail catastrophically?

Colin Woodard watch

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Adam Ramey writes,

we show that the migrations of millions of Okies from the central plains to California has a demonstrable effect on political outcomes to this day, even after accounting for other relevant geographic and demographic factors. After demonstrating this pattern at the electoral level, we leverage a decade’s worth of survey data and show that Hispanics living in areas with large Okie migrations in the 1930s are much more likely to have conservative social values and, importantly, to vote and identify as Republicans. Put together, these results suggest that the historical legacies of migration can have a strong and sustained impact even after nearly a century after the fact.

Pointer from Tyler Cowen.

Woodard has staked out the position that cultural differences across U.S. regions are the result of early settlement patterns. He does not hesitate to include in “Greater Appalachia” regions far from the vicinity of the mountain range. In the nineteenth century, folks migrated from Appalachia to parts of the Midwest and to rural Texas and Oklahoma. Then in the 1930s they settled in parts of California.

Scott Alexander on the Representative Agent model

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He writes,

Suppose that one-third of patients have some gene that makes them respond to Prozac with an effect size of 1.0 (very large and impressive), and nobody else responds. In a randomized controlled trial of Prozac, the average effect size will show up as 0.33 (one-third of patients get effect size of 1, two-thirds get effect size of 0).

Economists instinctively fall back on the “representative agent” model, in which you average the population results of whatever study you do. So an economist would say that the effect size is 0.33. But the point is that there is not one parameter that represents the whole population. One needs to take into account differences.

Where this bothers me the most is in the realm of expectations. Someone will take a survey of, say, consumer expectations for home price increases. The results will diverge across consumers. But the economist will report a single number for consumer expectations.