My years in Fall River, Mass.

by  Tyler Cowen in

I lived there from ages 4 to 7, which spans 1966 to 1969.  At that time, Fall River about forty years past its textiles manufacturing peak, as southern competition had deindustrialized the city.  My father was invited to run the Chamber of Commerce there, with the hope that he could help revitalize things, and so the family moved.

I recall liking New England, and preferring it to my earlier Hudson County, NJ environs.  All of a sudden we had a large yard and things felt nicer.  The neighbors were chattier and less surly.  The dog (Zero) could run around the neighborhood free, which I found both astonishing and good.  I did not understand that the city had fantastic architecture.  My father complained about it being provincial.

Whenever we would drive back and forth from NJ to Fall River, my sister and I would see a building in Providence, RI and for whatever reason we called it “the monkey squisher.”  For trips to the shore, we would go to Cape Cod, and let the dog run on the beach.

Mr. and Mrs. Jennings were the immediate neighbors, and they treated us almost like their own kids.  Their own boy was grown and in the service.  Two other neighbors were Kathy and Carol Fata (sp?), who were slightly older than Holly and me, and again super-friendly.  I believe they were either Lebanese or Syrian, which was common in Fall River at that time.

Most of all, I was into baseball and baseball cards in those years.  I used them to learn some math and statistics, and of course to learn about the players.  I watched baseball games on TV all the time, and to this day I remember some baseball stats from that era.  I received an autographed baseball from Russ Gibon, Red Sox catcher at the time.  Naturally I was a Red Sox fan.  I had an allowance of a quarter a week, and on the way home from school would stop at a small newspaper store and buy baseball cards.  The 1968 World Series was a huge thrill for me, and I was rooting for the Detroit Tigers and Mickey Lolich.  I still remember the close call at the plate with Bill Freehan and Lou Brock.

Most of my reading was books on science and dinosaurs, or books on baseball.  I was especially fond of a science book series called “Ask Me Why?”.  I looked at maps plenty, and my favorite map was that of Italy, due to the shape of the country.

I recall watching the 1968 presidential election, and having my mother explain it to me.  I also watched on TV the funeral procession for RFK, and I asked my grandmother, who then lived with us, why the police guards were not moving.  “If they move an inch, they take them out and shoot them!” she snapped back loudly and decisively.  In those days, people said things like that.

My kindgarten teacher we called “Mrs. Penguin,” though I doubt that was her real name.  She would twist the ears of kids who made trouble, though that was not me.  I had a letter box, but it bored me because my reading skills were ahead of those of my classmates.  There was a girl named Stephanie in my class, and I thought she was cute.  School simply did not seem like a very efficient way to learn.

In my hazy memories, I very much think of the Fall River days as good ones.

Might we end up with a modest stagflation?

by  Tyler Cowen

CPI inflation has come in at three percent, and there are signs of vulnerability in labor markets, as I discuss in my latest Bloomberg column:

What about unemployment? There is a general consensus that the labor market has stayed broadly stable, but hiring is slowing down and people are less likely to quit their jobs. The overall situation appears more vulnerable. Meanwhile, the global geopolitical order is fraying, and the current policy uncertainty may damage the prospects for domestic investment. While I am optimistic about the economic prospects for artificial intelligence, progress could be bumpy rather than smooth.

If you accept the notion that inflation is more likely to rise than fall, and that the labor market is more likely to worsen than improve, then the chances for a modest stagflation are reasonably high.

I believe also that the rate-cutting decision of December 2024 likely was a mistake.

My excellent Conversation with Gregory Clark

by  Tyler Cowen in

Here is the audio, video, and transcript.  Here is the episode summary:

How much of your life’s trajectory was set in motion centuries ago? Gregory Clark has spent decades studying social mobility, and his findings suggest that where you land in society is far more predictable than we like to think. Using historical data, surname analysis, and migration patterns, Clark argues that social mobility rates have remained largely unchanged for 300 years—even across radically different political and economic systems.

He and Tyler discuss why we should care about relative mobility vs growing the size of the pie, how physical mobility does and doesn’t matter, why England was a meritocracy by 1700, how assortative mating affects economic and social progress, why India industrialized so late, a new potential explanation why Britain’s economic performance has been lukewarm since WWI, Malthusian societies then and now, whether a “hereditarian” stance favors large-scale redistribution or a free-market approach, the dynamics of assimilation within Europe and the role of negative selection in certain migrations, the challenge of accurately measuring living standards, the neighborhood-versus-family debate over what drives mobility, whether we need datasets larger than humanity itself to decode the genetics of social outcomes, and much more.

Here is one of many interesting excerpts:

COWEN: How do you think about the social returns to more or less assortative mating? Say in the United States — do we have too much of it, too little of it? If we had more of it, you’d have, say, very smart or determined people marrying those like them, and you might end up with more innovation from their children and grandchildren. But you might also be messing with what you would call the epistemic quality of the median voter. There’s this trade-off. How do you think about that? What side of the margin are we at?

CLARK: Assortative mating turns out to be a fascinating phenomenon, and in this new book, we actually have records of 1.7 million marriages in England from 1837 until now. What is astonishing in England is the degree to which people end up assorting in marriage so that basically, they’re matching with people that are as close to them, essentially genetically, as their siblings in marriage. It’s really interesting because people could mate in any way.

You could think I want the tallest person, the handsomest person, the youngest person, but for some reason, consistently, people seem to want to match to people who are close in social status. Now that doesn’t affect anything about the average level of ability in a society, but if it’s consistently followed over generations, it will widen the distribution of ability.

COWEN: Yes, and are we doing too much of that or too little of it in the United States?

CLARK: It depends what your view is. If you think that the engine of high-tech society now, like the United States, is the top 1 percent or 5 percent of the ability distribution, then you would say the more assortative is mating, the more people will be in that extreme and the greater will be economic growth.

In the new book, I actually speculate about, was assortative mating in Northern Europe a discovery of the late Middle Ages that actually then helped propel things like the Scientific Revolution, the Enlightenment, the Industrial Revolution, because as I say, it’s a remarkably constant feature of British society.

We can only trace it back to about 1750, the actual degree of assortativeness. So, in that sense, you can’t have too much if that’s your view about how society operates.

COWEN: At least we could have more of it. There might be some margin where you’d have too much.

CLARK: But it does produce more inequality, so if you’re worried about inequality in society, you don’t want assortative mating. The one way to correct a lot of inequality would just be to have much more random matching.

One of the remarkable things about Denmark is, education is essentially free until you’re age 24. They give you subsidies for your living expenses, for childcare provision — it’s all available. They’ve compressed the income distribution quite sharply.

There is this periodic survey of how well students do, the PISA measures. Nordic countries have not reduced the inequality of PISA measures compared to much more unequal societies like the United States. Again, it’s just interesting that a high degree of inequality is still found within these societies. It turns out that in Nordic societies, people are mating again very strongly assortatively even now. That is the thing that you would worry more about, that there is going to be this trade-off between assortative mating and the degree of inequality in a society.

Stimulating throughout, with lots of debate.

Wednesday assorted links

by  Tyler Cowen

1. Plane crashes are still on a downward trend.

2. 2015 Matt Yglesias on whether American democracy is doomed.

3. 3.1%.

4. Does technology do more to help submarine tracking or submarine autonomy?

5. Good piece on Macca.

6. The actual budget news: House Republicans reluctant to cut Medicaid.  And does the bond market believe in DOGE?

7. It seems China has passed peak fuel consumption!? (Bloomberg)

8. Germany’s trains are less punctual than Britain’s (FT).

9. Are the independent agencies still independent? I agree with Matt: “My guess is that in the long run, bringing independent agencies more closely under presidential control is going to make policy outcomes more left-wing.”

10. FTC following the Lina Khan merger guidelines.

Baudrillard on AI

by  Tyler Cowen in

If men create intelligent machines, or fantasize about them, it is either because they secretly despair of their own intelligence or because they are in danger of succumbing to the weight of a monstrous and useless intelligence which they seek to exorcize by transferring it to machines, where they can play with it and make fun of it. By entrusting this burdensome intelligence to machines we are released from any responsibility to knowledge, much as entrusting power to politicians allows us to disdain any aspiration of our own to power.

If men dream of machines that are unique, that are endowed with genius, it is because they despair of their own uniqueness, or because they prefer to do without it – to enjoy it by proxy, so to speak, thanks to machines. What such machines offer is the spectacle of thought, and in manipulating them people devote themselves more to the spectacle of thought than to thought itself.

Jean Baudrillard – The Transparency of Evil_ Essays on Extreme Phenomena (Radical Thinkers)-Verso.

For the pointer I thank Petr.

*Steven Weinberg: A Life in Physics*

by  Tyler Cowen in

A fun book, I enjoyed the read.  Here is one bit:

There is another contribution to my productivity.  While sitting at my desk at home doing physics or preparing classes, or doing some science writing, I picked up the habit of watching classic movies or the History Channel on television.  My TV is always turned on in its corner of my desk.  Doing the two things at once doubles the value of my time.  And the movie keeps ne gnawing at a problem in physics when I might otherwise have knocked back my chair and decamped in frustration.

And:

At this time, Louise [his wife] literally saved my life.  Through my friendship with Bernie Feld, I found myself welcome at, and attending, international meetings of various experts on the problems of the international order.  Louise understood the situation better than I did.  She advised me to have nothing further to do with Bernie’s world, if I wanted to get anything done in physics.  She made me see that this was a world of disheartened older men giving themselves something important-looking to do, but that I was an optimistic young man with real work to do.  I do not exaggerate when I confess that she saved my life.

You can order it here.

Does Peer Review Penalize Scientific Risk Taking?

by  Tyler Cowen in

Scientific projects that carry a high degree of risk may be more likely to lead to breakthroughs yet also face challenges in winning the support necessary to be carried out. We analyze the determinants of renewal for more than 100,000 R01 grants from the National Institutes of Health between 1980 and 2015. We use four distinct proxies to measure risk taking: extreme tail outcomes, disruptiveness, pivoting from an investigator’s prior work, and standing out from the crowd in one’s field. After carefully controlling for investigator, grant, and institution characteristics, we measure the association between risk taking and grant renewal. Across each of these measures, we find that risky grants are renewed at markedly lower rates than less risky ones. We also provide evidence that the magnitude of the risk penalty is magnified for more novel areas of research and novice investigators, consistent with the academic community’s perception that current scientific institutions do not motivate exploratory research adequately.

That is from a new NBER working paper by Pierre Azoulay & Wesley H. Greenblatt.

An Economic Approach to Homer’s Odyssey: Part II

by  Tyler Cowen in

My three-part essay for Liberty Fund continues, here is the opener:

In the previous article, I outlined what an economic approach to reading Homer’s epic, The Odyssey,1 might look like. I also noted that what most strikes me about The Odyssey is Homer’s treatment of comparative political regimes. Looking at the wide variety of regimes Odysseus encounters is the focus of this article.

Given that human behavior, at least in The Odyssey, can be understood in terms of the non-standard assumptions described in my previous essay, what are then the possible states of affairs? Which polities might we look to for arranging human interactions and maintaining political order? Utopia is not readily achieved, not only because of material constraints, but also because human behavior is too restless and too desirous of alternative states of affairs. A straightforward order based on political virtue is also beyond human grasp, again because it clashes with the nature of human beings as we understand them. What then might fit with a vision of humans as restless, intoxicating, deceiving, and self-deceiving creatures? The travel explorations of The Odyssey can be understood as, in part, an attempt to address this question.

I will now consider the major and some of the minor polities described by The Odyssey, roughly in the order they appear in the story.

The discussion starts with Pylos and Sparta…

It’s happening at The New York Times

by  Tyler Cowen in

The New York Times is greenlighting the use of AI for its product and editorial staff, saying that internal tools could eventually write social copy, SEO headlines, and some code.

In an email to newsroom staff, the company announced that it’s opening up AI training to the newsroom, and debuting a new internal AI tool called Echo to staff, Semafor has learned. The Times also shared documents and videos laying out editorial do’s and don’t for using AI, and shared a suite of AI products that staff could now use to develop web products and editorial ideas.

“Generative AI can assist our journalists in uncovering the truth and helping more people understand the world. Machine learning already helps us report stories we couldn’t otherwise, and generative AI has the potential to bolster our journalistic capabilities even more,” the company’s editorial guidelines said.

Here is the full story, via the excellent Samir Varma.

Naming AI models correctly

by  Tyler Cowen in

Are you confused by all the model names and terminology running around?  Here is a simple guide to what I call them:

o1 pro — The Boss

4o — Little Boss

o3 mini — The Mini Boss

GPT 4o with scheduled tasks — Boss come back later

o1 — Cheapskates’ boss

Deep Research — My research assistant

GPT-4 — Former Boss

DeepSeek — China Boss

Claude — Claude

Llama 3.3, or whichever — Meta.  I never quite got used to calling Facebook “Meta,” so I call the AI model Meta too.  Hope that’s OK!

Grok 3 — Elon

Gemini 2.0 Flash — China Boss suggests “Laggy Larry,” but I don’t actually call it that.

Perplexity.ai — Google

Got that?  Easy as pie!