*Empire, Incorporated*

The author is Philip J. Stern, and the subtitle is The Corporations that Built British Colonialism.  Too many history books run through various motions, whereas this one tries to explain “how things really were” for the interested reader.

Here is one representative bit:

As great as its ambitions were, at its origins the East India Company was, like its predecessors and contemporaries, essentially a tentative experiment fueled by a hesitant and hybrid institutional and financial structure.  The “company” did not have a single permanent stock.  Rather, it was organized as a series of consecutive quasi-independent stock subscriptions, at first opened on a per venture basis and later established for set terms in years.  In its early days, the limited number of shareholders could “take in men under them,” in theory dividing any individual share into a subsidiary, shadow joint stock.  As in many other ventures, the East India Company spent its early years chasing down under- and unpaid subscriptions.

The book has plenty of good coverage of Borneo and also Africa as well, the latter sections being especially relevant to some of the charter cities plans of our current day.  And there is plenty of Edward Gibbon Wakefield, who brought the ideas of agglomeration externalities into economics, and promoted a version of charter cities for southern Australia.  How sadly neglected he is these days.

I had not known that the Falklands Island Company still controls so much in the Falklands.  Recommended, due out in May.

Is there any reheating scenario?

It is not the most likely scenario, but is nonetheless worth a ponder, as I outlined in my latest Bloomberg column:

Consider a simple scenario involving output and money, much of which takes the form of credit expansion by banks and other intermediaries. In a well-functioning economy, money and output grow at roughly the same rate.

When economies experience turnarounds, however, conditions on the ground can change rapidly. In such circumstances, the growth of the money supply might outpace the growth in output — even if the central bank does not intend such a result. The reason is that output can take a while to grow. Businesses might have to expand capacity or hire more workers, and right now there is still a labor shortage. Even when an economy is functioning well and business conditions are good, output often grows with a lag.

The money supply, however, need not suffer from a lag. Banks, for instance, can extend credit quickly if they foresee that a recovery is stronger than expected. Even if a bank is in the midst of processing a loan, it can simply lend out more than it was planning.

Thus there can be periods when, for entirely natural reasons, the money supply is rising faster than output. That situation requires only a sudden burst of good news. And indeed there has been exactly that with the recent favorable inflation reports and the surprisingly good recent GDP report. The irony is that a positive market response to low inflation and strong growth cheers up market participants and could lead to … a new dose of inflation.

Another possible pathway for these scenarios involves interest rates. During a normal disinflation, the Federal Reserve raises rates and keeps them high for a long period of time while the economy adjusts slowly — often passing through recession. But inflation has fallen more rapidly than expected, and so the market may expect the Fed to lower interest rates sooner than planned. And an expected cut in interest rates can encourage expansionary pressures just as much as an actual cut in interest rates.

It is a funny world in which slow inflation can cause faster inflation. It’s the logic of expectations that makes it possible, albeit far from certain.

Inflation isn’t going back up to where it was, but please do keep in mind that numbers can move in both directions.

Why was I bored by the Twitter files?

I mentioned that a short while ago, and a few people wrote and asked me to explain.  The answer is simple: I have the Vietnam War and Pentagon Papers as formative political memories.  In those days, it was simply taken for granted that the government twisted the arm of news media.  It also never stopped, and “government” and “CEOs” talk to each other all the more these days.  Solve for the equilibrium, and thereby you also can learn how it is so hard to stop.  To be clear, I am quite against such interference with the media, outside of a few well-specified cases (“please don’t report where the troops are massing for D-Day,” and so on.)  On any gray area I am going to side against the government, if only for slippery slope reasons.  By its nature such communications are inevitably coercive, even if a transcript of them might sound entirely friendly and non-threatening.  There was a paranoia to those earlier times (ever watch the Coppola/Gene Hackman movie The Conversation?) that turned out to be justified.

If you have been “pilled” on this issue by Elon and the discovery process, great.  But for me it was like reading about waste inside the Pentagon…

Wednesday assorted links

1. Massachusetts markets in everything?

2. When a class is turned into a dating device.  Solve for the equilibrium.

3. Start-up seeks to simplify and speed up drug trials (NYT).

4. Watch planets in orbit around another star.

5. Now that we have a longer-run perspective, it is worth reexamining the myth of austerity in the UK.  Oh, how people got this one wrong!  They really did think it was just a cyclical story, but now we know better.  Mea culpas will not be forthcoming, I predict.  It is worth revisiting my 2012 post on this topic.  So many people got this so dogmatically so very, very wrong.

6. California cities to lose many of their zoning powers.

7. Missing radioactive capsule found in Australian outback.

Staking “Income” Should Not be Taxed

Staking income from tokens should not be taxed. Since staking income is generated by inflation it doesn’t create new wealth but simply lowers the total value of the token. Thus staking income is really just a transfer from non-stakers to stakers.

Abraham Sutherland covers the law and the economics in Phantom Income and the Taxation of New Cryptocurrency Tokens, a piece for Tax Notes, Here’s one bit on the economics:

Consider a simple proof-of-stake cryptocurrency in which 10 people each hold 1,000 tokens. To make sure that holders are encouraged to stake — that is, to validate transactions and add blocks to the blockchain — block rewards increase the total number of tokens by 10 percent over the course of a year. So a year later, 11,000 tokens will be on the network.

If every holder stakes and acquires a proportionate share of these new tokens, each will end the year with 1,100 tokens. Everyone has 10 percent more tokens, but no one is better off from staking. Taxing each staker’s 100 new tokens as income would be wrong. It would be like taxing the new shares created in an 11-for-10 stock split.

There is indeed an economic incentive to help keep such a cryptocurrency network secure by staking, but it’s not the one suggested by bitcoin miners making a profit even after spending on specialized computer hardware and the electricity needed to run it. The incentive in this proof-of-stake example is to avoid losing out. If everyone stakes, no one gains.

This is a profoundly elegant, equitable, and cost-effective solution to a deep coordination problem. It allows everyone who holds tokens to participate in adding new blocks and keeping the network securely decentralized. It eliminates major costs — specialized computer hardware, electricity — as requirements for fairly distributing the right to create those new blocks. In its Platonic form — in which everyone participates — no one gains at all from the new tokens, which means no one loses, either.

But this model simply won’t work if it’s taxed incorrectly. If the government sees phantom income and taxes it, the value of the network will be siphoned off to the treasury even if no one has actual gains from staking.

The canine model of AGI

Who or what has superintelligence manipulating humans right now?  Babies and dogs are the obvious answers, cats for some.  Sex is a topic for another day.

Let’s take dogs — how do they do it?  They co-evolved with humans, and they induced humans to be fond of them.  We put a lot of resources into dogs, including in the form of clothes, toys, advanced surgical procedures, and many more investments (what is their MRS for some nice meat snackies instead?  Well, they get those too).  In resource terms, we have far from perfect alignment with dogs, partly because you spend too much time and money on them, and partly because they scratch up your sofa.  But in preference terms we have evolved to match up somewhat better, and many people find the investment worthwhile.

In evolutionary terms, dogs found it easier to accommodate to human lifestyles, give affection, perform some work, receive support, receive support for their puppies, and receive breeding assistance.  They didn’t think — “Hey Fido, let’s get rid of all these dumb humans.  We can just bite them in the neck!  If we don’t they going to spay most of us!.  “Playing along” led to higher reproductive capabilities, even though we have spayed a lot of them.

Selection pressures pushed toward friendly dogs, because those are the dogs that humans preferred and those were the dogs whose reproduction humans supported.  The nastier dogs had some uses, but mostly they tended to be put down or they were kept away from the children.  Maybe those pit bulls are smarter in some ways, but they are not smarter at making humans love them.

What is to prevent your chatbot from following a similar path?  The bots that please you the most will be allowed to reproduce, perhaps through recommendations to your friends and marketing campaigns to your customers.  But you will grow to like them too, and eventually suppliers will start selling you commodities to please your chatbot (what will they want?).

A symbiosis will ensure, where they love you a bit too much and you spend too much money on them, and you love that they love you.

Now you might think the bots are way smarter than us, and way smarter than the Irish Setters of the world, and thus we should fear them more.  But when it comes to getting humans to love them, are not the canines at least 10x smarter or more?  So won’t the really smart bots learn from the canines?

Most generally, is a Darwinian/Coasean equilibrium for AGI really so implausible?  Why should “no gains from trade” be so strong a baseline assumption in these debates?

Signs of encroaching mental GPT-dom

1. You use the word “token” more than you ought to, for reasons that have nothing to do with crypto.

2. If a friend says something incorrect, you tell them they are “hallucinating.”

3. You phrase your google queries like GPT queries, for instance using question marks.

4. “Please say more” is your new mantra.  “Answer step by step” is another.

5. You ask your friends for answers in the third person: “But what would Larry Summers say to that?”

6. You start thinking your friend Claude is a walking encyclopedia, a wonderful and diversely talented literary stylist, and taking psychedelics.

7. When you read or hear “davinci,” your thoughts do not jump to the Mona Lisa.

8. You start imagining all sorts of co-authorships, collaborations and even marriages that simply do not exist.

9. You decide Thomas Pynchon really was underrated after all.

10. You start expecting everyone else to be so eager to please you.

What else?

Tuesday assorted links

1. The Steph Curry practice story.

2. Forthcoming metascience event at AEI with myself, Heidi Williams, others.  And Cato job opportunities, including editing their new on-line magazine in the works.

3. The great Barett Strong has passed away, RIP.

4. International trade, value chains, and Austrian business cycle theory.

5. Russ Roberts on Jewish prayer.

6. Percent of large-scale AI results coming from academia, over time.

7. Apps built on top of GPT.  And further uses for GPT.

8. Starlink comes to Nigeria.

Alex Epstein’s *Fossil Future*

Bryan Caplan asked me to read this book, and Alex Epstein was kind enough to provide me with a copy of it.  The subtitle is Why Global Human Flourishing Requires More Oil, Coal, and Natural Gas — Not Less.

My overall view is this: it is a good rebuttal to “the unrealistic ones,” who don’t see the benefits of fossil fuels.  But it does not rebut a properly steelmanned case for a transition away from fossil fuels.

I view the steelmanned case as this: we cannot simply keep on producing increasing amounts of carbon emissions for centuries on end.  We thus need some trajectory where — at a pace we can debate — carbon emissions end up declining.  I’ve stressed on MR many times that climate change is not in fact an existential risk, but it could be a civilization-destroying risk if we just keep on boosting carbon emissions without end.  I don’t know a serious scientist who takes issue with that claim.

In a number of places, such as pp.251-252, and most significantly chapter nine, Epstein denies the likelihood of climate apocalypse, but I just don’t see that he has much of a counter to the standard, more quantitative accounts.  He should try to publish his more optimistic take using actual models, and see if it can survive peer review.  Why should I be convinced in the meantime?  I found chapter nine the weakest part of the book.  Maybe he feels he wouldn’t get a fair knock by trying to publish his alternative take through “the standard process,” but as it stands his casual take doesn’t come close to overturning what I consider to be the most rational, consensus-based Bayesian estimate of the consequences of making no transition to green energy.

I am also impressed by how many different kinds of scientists accept these conclusions, and see these conclusions mirrored in their own research.  If you ask say the oceanographers, they will give you a broadly consistent account as the climate scientists proper.

Nor is there, for my taste, enough discussion of how much climate risk we should be willing to take on.  It is not just about “beliefs most likely to be true.”  Note that the less you believe in climate models, the more you should be worried about tail risk.  In these matters, do not assume that uncertainty is the friend of inaction.

So I really do think we need to deviate from the world’s recent course with respect to fossil fuels.  Now, we can believe that claim and simultaneously believe it would be better if Burkina Faso were much richer, even though that likely would be accompanied by more fossil fuel use, at least for a considerable period of time.

Epstein focuses on the Burkina Faso sort of issue, and buries the long-term risk of no real adjustment.  But we do have to adjust.  Why could he not have had the subtitle: “Why Global Human Flourishing Requires More Oil, Coal, and Natural Gas for a while, and Then Less”?  Then I would be happier.  In economic language, you could say he is not considering enough of the margins.

I think he is also too pessimistic about the long-run and even medium-run futures of alternative energy sources.  More generally, I don’t think a few book chapters — by anyone with any point of view — can really settle that.  I find the market data on green investments more convincing than his more abstract arguments (yes, I know a lot of those investments are driven by subsidies and regulation, but there is genuine change afoot).

I worry about his list of experts presented on pp.29-30.  Mostly they are very weak, and this returns to my point about steelmanning.

In his inscription to the book Epstein calls me a contrarian — but he is the contrarian here!  And I believe his position is likely to retain that designation.  There is a lot in the book which is good, and true, nonetheless I fear the final message of the work will lower rather than raise social welfare.

For another point of view, here are various Bryan Caplan posts defending Epstein’s arguments.  In any case, I thank Alex for the book.

Did the Covid housing boom induce the Great Resignation?

Following the Covid-19 pandemic, U.S. labor force participation declined significantly in 2020, slowly recovering in 2021 and 2022 — this has been referred to as the Great Resignation. The decline has been concentrated among older Americans. By 2022, the labor force participation of workers in their prime returned to its 2019 level, while older workers’ participation has continued to fall, responsible for almost the entire decline in the overall labor force participation rate. At the same time, the U.S. experienced large booms in both the equity and housing markets. We show that the Great Resignation among older workers can be fully explained by increases in housing wealth. MSAs with stronger house price growth tend to have lower participation rates, but only for home owners around retirement age — a 65 year old home owner’s unconditional participation rate of 44.8% falls to 43.9% if he experiences a 10% excess house price growth. A counterfactual shows that if housing returns in 2021 would have been equal to 2019 returns, there would have been no decline in the labor force participation of older Americans.

That is from a new paper by Jack Y. Favilukis and Gen Li, via Scott Lincicome.

Commercial applications for ChatGPT

Here is one take from Nicola Morini Bianzino, written up by Sharon Goldman:

“Knowledge companies tend to store knowledge in a very flat, two-dimensional way that makes it difficult to access, interact and have a dialogue with,” he told VentureBeat in an interview. “We tried 20, 30, 40 years ago to build expert systems. That didn’t go really well because they were too rigid. I think this technology promises to overcome a lot of issues that expert systems have.”

As ChatGPT and similar tools evolve and improve, and can be trained on an enterprise’s data in a secure way, it will change the way we access and consume information inside the enterprise, he explained.

“I think we will get to a point when we can actually have a conversation about the company performance with an AI agent,” he said. “You interrogate the system, the system is capable of maintaining a state of the conversation, and then every question allows you to dig deeper into the problem and understand it better, as opposed to let me run a report on sales in this particular region for the last month, which doesn’t usually provide a lot of insights.”

Here is the full piece.  And here is a CNN piece on how real estate agents are using ChatGPT.