Taylor Swift and the means of production

2025-10-052025-09-30 PNRJ development economics, futurism, inequality, market failure, politics Ai, artificial intelligence, capital, capitalism, development, future, human capital, inequality, labor, Marx, music, stock market, Taylor Swift

Oct 5 JDN 2460954

This post is one I’ve been meaning to write for awhile, but current events keep taking precedence.

In 2023, Taylor Swift did something very interesting from an economic perspective, which turns out to have profound implications for our economic future.

She re-recorded an entire album and released it through a different record company.

The album was called 1989 (Taylor’s Version), and she created it because for the last four years she had been fighting with Big Machine Records over the rights to her previous work, including the original album 1989.

A Marxist might well say she seized the means of production! (How rich does she have to get before she becomes bourgeoisie, I wonder? Is she already there, even though she’s one of a handful of billionaires who can truly say they were self-made?)

But really she did something even more interesting than that. It was more like she said:

“Seize the means of production? I am the means of production.”

Singing and songwriting are what is known as a human-capital-intensive industry. That is, the most important factor of production is not land, or natural resources, or physical capital (yes, you need musical instruments, amplifiers, recording equipment and the like—but these are a small fraction of what it costs to get Talor Swift for a concert), or even labor in the ordinary sense. It’s one where so-called (honestly poorly named) “human capital” is the most important factor of production.

A labor-intensive industry is one where you just need a lot of work to be done, but you can get essentially anyone to do it: Cleaning floors is labor-intensive. A lot of construction work is labor-intensive (though excavators and the like also make it capital-intensive).

No, for a human-capital-intensive industry, what you need is expertise or talent. You don’t need a lot of people doing back-breaking work; you need a few people who are very good at doing the specific thing you need to get done.

Taylor Swift was able to re-record and re-release her songs because the one factor of production that couldn’t be easily substituted was herself. Big Machine Records overplayed their hand; they thought they could control her because they owned the rights to her recordings. But she didn’t need her recordings; she could just sing the songs again.

But now I’m sure you’re wondering: So what?

Well, Taylor Swift’s story is, in large part, the story of us all.

For most of the 18^th, 19^th, and 20^th centuries, human beings in developed countries saw a rapid increase in their standard of living.

Yes, a lot of countries got left behind until quite recently.

Yes, this process seems to have stalled in the 21^st century, with “real GDP” continuing to rise but inequality and cost of living rising fast enough that most people don’t feel any richer (and I’ll get to why that may be the case in a moment).

But for millions of people, the gains were real, and substantial. What was it that brought about this change?

The story we are usually told is that it was capital; that as industries transitioned from labor-intensive to capital-intensive, worker productivity greatly increased, and this allowed us to increase our standard of living.

That’s part of the story. But it can’t be the whole thing.

Why not, you ask?

Because very few people actually own the capital.

When capital ownership is so heavily concentrated, any increases in productivity due to capital-intensive production can simply be captured by the rich people who own the capital. Competition was supposed to fix this, compelling them to raise wages to match productivity, but we often haven’t actually had competitive markets; we’ve had oligopolies that consolidate market power in a handful of corporations. We had Standard Oil before, and we have Microsoft now. (Did you know that Microsoft not only owns more than half the consumer operating system industry, but after acquiring Activision Blizzard, is now the largest video game company in the world?) In the presence of an oligopoly, the owners of the capital will reap the gains from capital-intensive productivity.

But standards of living did rise. So what happened?

The answer is that production didn’t just become capital-intensive. It became human-capital-intensive.

More and more jobs required skills that an average person didn’t have. This created incentives for expanding public education, making workers not just more productive, but also more aware of how things work and in a stronger bargaining position.

Today, it’s very clear that the jobs which are most human-capital-intensive—like doctors, lawyers, researchers, and software developers—are the ones with the highest pay and the greatest social esteem. (I’m still not 100% sure why stock traders are so well-paid; it really isn’t that hard to be a stock trader. I could write you an algorithm in 50 lines of Python that would beat the average trader (mostly by buying ETFs). But they pretend to be human-capital-intensive by hiring Harvard grads, and they certainly pay as if they are.)

The most capital-intensive industries—like factory work—are reasonably well-paid, but not that well-paid, and actually seem to be rapidly disappearing as the capital simply replaces the workers. Factory worker productivity is now staggeringly high thanks to all this automation, but the workers themselves have gained only a small fraction of this increase in higher wages; by far the bigger effect has been increased profits for the capital owners and reduced employment in manufacturing.

And of course the real money is all in capital ownership. Elon Musk doesn’t have $400 billion because he’s a great engineer who works very hard. He has $400 billion because he owns a corporation that is extremely highly valued (indeed, clearly overvalued) in the stock market. Maybe being a great engineer or working very hard helped him get there, but it was neither necessary nor sufficient (and I’m sure that his dad’s emerald mine also helped).

Indeed, this is why I’m so worried about artificial intelligence.

Most forms of automation replace labor, in the conventional labor-intensive sense: Because you have factory robots, you need fewer factory workers; because you have mountaintop removal, you need fewer coal miners. It takes fewer people to do the same amount of work. But you still need people to plan and direct the process, and in fact those people need to be skilled experts in order to be effective—so there’s a complementarity between automation and human capital.

But AI doesn’t work like that. AI substitutes for human capital. It doesn’t just replace labor; it replaces expertise.

So far, AI is currently too unreliable to replace any but entry-level workers in human-capital-intensive industries (though there is some evidence it’s already doing that). But it will most likely get more reliable over time, if not via the current LLM paradigm, than through the next one that comes after. At some point, AI will come to replace experienced software developers, and then veteran doctors—and I don’t think we’ll be ready.

The long-term pattern here seems to be transitioning away from human-capital-intensive production to purely capital-intensive production. And if we don’t change the fact that capital ownership is heavily concentrated and so many of our markets are oligopolies—which we absolutely do not seem poised to do anything about; Democrats do next to nothing and Republicans actively and purposefully make it worse—then this transition will be a recipe for even more staggering inequality than before, where the rich will get even more spectacularly mind-bogglingly rich while the rest of us stagnate or even see our real standard of living fall.

The tech bros promise us that AI will bring about a utopian future, but that would only work if capital ownership were equally shared. If they continue to own all the AIs, they may get a utopia—but we sure won’t.

We can’t all be Taylor Swift. (And if AI music catches on, she may not be able to much longer either.)

The AI bubble is going to crash hard

2025-09-072025-09-01 PNRJ critique of neoclassical economics, current events, futurism, market failure, public policy Ai, artificial intelligence, bubble, capital, Claude, crash, Ed Zitron, energy, investment, large language model, LLM, Paul Krugman, stock market, technology, Trump

Sep 7 JDN 2460926

Based on the fact that it only sort of works and yet corps immediately put it in everything, I had long suspected that the current wave of AI was a bubble. But after reading Ed Zitron’s epic takedowns of the entire industry, I am not only convinced it’s a bubble; I’m convinced it is probably the worst bubble we’ve had in a very long time. This isn’t the dot-com crash; it’s worse.

The similarity to the dot-com crash is clear, however: This a huge amount of hype over a new technology that genuinely could be a game-changer (the Internet certainly was!), but won’t be in the time horizon on which the most optimistic investors have assumed it will be. The gap between “it sort of works” and “it radically changes our economy” is… pretty large, actually. It’s not something you close in a few years.

The headline figure here is that based on current projections, US corporations will have spent $560 billion on capital expenditure, for anticipated revenue of only $35 billion.

They won’t pay it off for 16 years!? That kind of payoff rate would make sense for large-scale physical infrastructure, like a hydroelectric dam. It absolutely does not make sense in an industry that is dependent upon cutting-edge technology that wears out fast and becomes obsolete even faster. They must think that revenue is going to increase to something much higher, very soon.

The corps seem to be banking on the most optimistic view of AI: That it will soon—very soon—bring about a radical increase in productivity that brings GDP surging to new heights, or even a true Singularity where AI fundamentally changes the nature of human existence.

Given the kind of errors I’ve seen LLMs make when I tried to use them to find research papers or help me with tedious coding, this is definitely not what’s going to happen. Claude gives an impressive interview, and (with significant guidance and error-correction) it also managed pretty well at making some simple text-based games; but it often recommended papers to me that didn’t exist, and through further experimentation, I discovered that it could not write me a functional C++ GUI if its existence depended on it. Somewhere on the Internet I heard someone describe LLMs as answering not the question you asked directly, but the question, “What would a good answer to this question look like?” and that seems very accurate. It always gives an answer that looks valid—but not necessarily one that is valid.

AI will find some usefulness in certain industries, I’m sure; and maybe the next paradigm (or the one after that) will really, truly, effect a radical change on our society. (Right now the best thing to use LLMs for seems to be cheating at school—and it also seems to be the most common use. Not exactly the great breakthrough we were hoping for.) But LLMs are just not reliable enough to actually use for anything important, and sooner or later, most of the people using them are going to figure that out.

Of course, by the Efficient Roulette Hypothesis, it’s extremely difficult to predict exactly when a bubble will burst, and it could well be that NVIDIA stock will continue to grow at astronomical rates for several years yet—or it could be that the bubble bursts tomorrow and NVIDIA stock collapses, if not to worthless, then to far below its current price.

Krugman has an idea of what might be the point that bursts the bubble: Energy costs. There is a clear mismatch between the anticipated energy needs of these ever-growing data centers and the actual energy production we’ve been installing—especially now that Trump and his ilk have gutted subsidies for solar and wind power. That’s definitely something to watch out for.

But the really scary thing is that the AI bubble actually seems to be the only thing holding the US economy above water right now. It’s the reason why Trump’s terrible policies haven’t been as disastrous as economists predicted they would; our economy is being sustained by this enormous amount of capital investment.

US GDP is about $30 trillion right now, but $500 billion of that is just AI investment. That’s over 1.6%, and last quarter our annualized GDP growth rate was 3.3%—so roughly half of our GDP growth was just due to building more data centers that probably won’t even be profitable.

Between that, the tariffs, the loss of immigrants, and rising energy costs, a crashing AI bubble could bring down the whole stock market with it.

So I guess what I’m saying is: Don’t believe the AI hype, and you might want to sell some stocks.

The problem with “human capital”

2023-12-042023-11-26 PNRJ core principles, critique of neoclassical economics, ethics Buzz Aldrin, capital, capitalism, Elon Musk, human capital, ideology, investment, labor, Mauritania, neoliberal, net wealth, net worth, profit, slavery, value, worth

Dec 3 JDN 2460282

By now, human capital is a standard part of the economic jargon lexicon. It has even begun to filter down into society at large. Business executives talk frequently about “investing in their employees”. Politicians describe their education policies as “investing in our children”.

The good news: This gives businesses a reason to train their employees, and governments a reason to support education.

The bad news: This is clearly the wrong reason, and it is inherently dehumanizing.

The notion of human capital means treating human beings as if they were a special case of machinery. It says that a business may own and value many forms of productive capital: Land, factories, vehicles, robots, patents, employees.

But wait: Employees?

Businesses don’t own their employees. They didn’t buy them. They can’t sell them. They couldn’t make more of them in another factory. They can’t recycle them when they are no longer profitable to maintain.

And the problem is precisely that they would if they could.

Indeed, they used to. Slavery pre-dates capitalism by millennia, but the two quite successfully coexisted for hundreds of years. From the dawn of civilization up until all too recently, people literally were capital assets—and we now remember it as one of the greatest horrors human beings have ever inflicted upon one another.

Nor is slavery truly defeated; it has merely been weakened and banished to the shadows. The percentage of the world’s population currently enslaved is as low as it has ever been, but there are still millions of people enslaved. In Mauritania, slavery wasn’t even illegal until 1981, and those laws weren’t strictly enforced until 2007. (I had graduated from high school!) One of the most shocking things about modern slavery is how cheaply human beings are willing to sell other human beings; I have bought sandwiches that cost more than some people have paid for other people.

The notion of “human capital” basically says that slavery is the correct attitude to have toward people. It says that we should value human beings for their usefulness, their productivity, their profitability.

Business executives are quite happy to see the world in that way. It makes the way they have spent their lives seem worthwhile—perhaps even best—while allowing them to turn a blind eye to the suffering they have neglected or even caused along the way.

I’m not saying that most economists believe in slavery; on the contrary, economists led the charge of abolitionism, and the reason we wear the phrase “the dismal science” like a badge is that the accusation was first leveled at us for our skepticism toward slavery.

Rather, I’m saying that jargon is not ethically neutral. The names we use for things have power; they affect how people view the world.

This is why I always endeavor to always speak of net wealth rather than net worth—because a billionare is not worth more than other people. I’m not even sure you should speak of the net worth of Tesla Incorporated; perhaps it would be better to simply speak of its net asset value or market capitalization. But at least Tesla is something you can buy and sell (piece by piece). Elon Musk is not.

Likewise, I think we need a new term for the knowledge, skills, training, and expertise that human beings bring to their work. It is clearly extremely important; in fact in some sense it’s the most important economic asset, as it’s the only one that can substitute for literally all the others—and the one that others can least substitute for.

Human ingenuity can’t substitute for air, you say? Tell that to Buzz Aldrin—or the people who were once babies that breathed liquid for their first months of life. Yes, it’s true, you need something for human ingenuity to work with; but it turns out that with enough ingenuity, you may not need much, or even anything in particular. One day we may manufacture the air, water and food we need to live from pure energy—or we may embody our minds in machines that no longer need those things.

Indeed, it is the expansion of human know-how and technology that has been responsible for the vast majority of economic growth. We may work a little harder than many of our ancestors (depending on which ancestors you have in mind), but we accomplish with that work far more than they ever could have, because we know so many things they did not.

All that capital we have now is the work of that ingenuity: Machines, factories, vehicles—even land, if you consider all the ways that we have intentionally reshaped the landscape.

Perhaps, then, what we really need to do is invert the expression:

Humans are not machines. Machines are embodied ingenuity.

We should not think of human beings as capital. We should think of capital as the creation of human beings.

Marx described capital as “embodied labor”, but that’s really less accurate: What makes a robot a robot is much less about the hours spent building it, than the centuries of scientific advancement needed to understand how to make it in the first place. Indeed, if that robot is made by another robot, no human need ever have done any labor on it at all. And its value comes not from the work put into it, but the work that comes out of it.

Like so much of neoliberal ideology, the notion of human capital seems to treat profit and economic growth as inherent ends in themselves. Human beings only become valued insofar as we advance the will of the almighty dollar. We forget that the whole reason we should care about economic growth in the first place is that it benefits people. Money is the means, not the end; people are the end, not the means.

We should not think in terms of “investing in children”, as if they were an asset that was meant to yield a return. We should think of enriching our children—of building a better world for them to live in.

We should not speak of “investing in employees”, as though they were just another asset. We should instead respect employees and seek to treat them with fairness and justice.

That would still give us plenty of reason to support education and training. But it would also give us a much better outlook on the world and our place in it.

You are worth more than your money or your job.

The economy exists for people, not the reverse.

Don’t ever forget that.

The inequality of factor mobility

2023-09-242023-09-17 PNRJ critique of neoclassical economics, public policy, tribal paradigm #Scandinaviaisbetter, Cambodia, capital, capitalism, China, factor mobility, free trade, GDP, immigration, intelelctual property, Ireland, labor, labor productivity, Norwa, Norway, production, productivity, trade, TRIPS accord, United States

Sep 24 JDN 2460212

I’ve written before about how free trade has brought great benefits, but also great costs. It occurred to me this week that there is a fairly simple reason why free trade has never been as good for the world as the models would suggest: Some factors of production are harder to move than others.

To some extent this is due to policy, especially immigration policy. But it isn’t just that.There are certain inherent limitations that render some kinds of inputs more mobile than others.

Broadly speaking, there are five kinds of inputs to production: Land, labor, capital, goods, and—oft forgotten—ideas.

You can of course parse them differently: Some would subdivide different types of labor or capital, and some things are hard to categorize this way. The same product, such as an oven or a car, can be a good or capital depending on how it’s used. (Or, consider livestock: is that labor, or capital? Or perhaps it’s a good? Oddly, it’s often discussed as land, which just seems absurd.) Maybe ideas can be considered a form of capital. There is a whole literature on human capital, which I increasingly find distasteful, because it seems to imply that economists couldn’t figure out how to value human beings except by treating them as a machine or a financial asset.

But this four-way categorization is particularly useful for what I want to talk about today. Because the rate at which those things move is very different.

Ideas move instantly. It takes literally milliseconds to transmit an idea anywhere in the world. This wasn’t always true; in ancient times ideas didn’t move much faster than people, and it wasn’t until the invention of the telegraph that their transit really became instantaneous. But it is certainly true now; once this post is published, it can be read in a hundred different countries in seconds.

Goods move in hours. Air shipping can take a product just about anywhere in less than a day. Sea shipping is a bit slower, but not radically so. It’s never been easier to move goods all around the world, and this has been the great success of free trade.

Capital moves in weeks. Here it might be useful to subdivide different types of capital: It’s surely faster to move an oven or even a car (the more good-ish sort of capital) than it is to move an entire factory (capital par excellence). But all in all, we can move stuff pretty fast these days. If you want to move your factory to China or Indonesia, you can probably get it done in a matter of weeks or at most months.

Labor moves in months. This one is a bit ironic, since it is surely easier to carry a single human person—or even a hundred human people—than all the equipment necessary to run an entire factory. But moving labor isn’t just a matter of physically carrying people from one place to another. It’s not like tourism, where you just pack and go. Moving labor requires uprooting people from where they used to live and letting them settle in a new place. It takes a surprisingly long time to establish yourself in a new environment—frankly even after two years in Edinburgh I’m not sure I quite managed it. And all the additional restrictions we’ve added involving border crossings and immigration laws and visas only make it that much slower.

Land moves never. This one seems perfectly obvious, but is also often neglected. You can’t pick up a mountain, a lake, a forest, or even a corn field and carry it across the border. (Yes, eventually plate tectonics will move our land around—but that’ll be millions of years.) Basically, land stays put—and so do all the natural environments and ecosystems on that land. Land isn’t as important for production as it once was; before industrialization, we were dependent on the land for almost everything. But we absolutely still are dependent on the land! If all the topsoil in the world suddenly disappeared, the economy wouldn’t simply collapse: the human race would face extinction. Moreover, a lot of fixed infrastructure, while technically capital, is no more mobile than land. We couldn’t much more easily move the Interstate Highway System to China than we could move Denali.

So far I have said nothing particularly novel. Yeah, clearly it’s much easier to move a mathematical theorem (if such a thing can even be said to “move”) than it is to move a factory, and much easier to move a factory than to move a forest. So what?

But now let’s consider the impact this has on free trade.

Ideas can move instantly, so free trade in ideas would allow all the world to instantaneously share all ideas. This isn’t quite what happens—but in the Internet age, we’re remarkably close to it. If anything, the world’s governments seem to be doing their best to stop this from happening: One of our most strictly-enforced trade agreements, the TRIPS Accord, is about stopping ideas from spreading too easily. And as far as I can tell, region-coding on media goes against everything free trade stands for, yet here we are. (Why, it’s almost as if these policies are more about corporate profits than they ever were about freedom!)

Goods and capital can move quickly. This is where we have really felt the biggest effects of free trade: Everything in the US says “made in China” because the capital is moved to China and then the goods are moved back to the US.

But it would honestly have made more sense to move all those workers instead. For all their obvious flaws, US institutions and US infrastructure are clearly superior to those in China. (Indeed, consider this: We may be so aware of the flaws because the US is especially transparent.) So, the most absolutely efficient way to produce all those goods would be to leave the factories in the US, and move the workers from China instead. If free trade were to achieve its greatest promises, this is the sort of thing we would be doing.

Of course that is not what we did. There are various reasons for this: A lot of the people in China would rather not have to leave. The Chinese government would not want them to leave. A lot of people in the US would not want them to come. The US government might not want them to come.

Most of these reasons are ultimately political: People don’t want to live around people who are from a different nation and culture. They don’t consider those people to be deserving of the same rights and status as those of their own country.

It may sound harsh to say it that way, but it’s clearly the truth. If the average American person valued a random Chinese person exactly the same as they valued a random other American person, our immigration policy would look radically different. US immigration is relatively permissive by world standards, and that is a great part of American success. Yet even here there is a very stark divide between the citizen and the immigrant.

There are morally and economically legitimate reasons to regulate immigration. There may even be morally and economically legitimate reasons to value those in your own nation above those in other nations (though I suspect they would not justify the degree that most people do). But the fact remains that in terms of pure efficiency, the best thing to do would obviously be to move all the people to the place where productivity is highest and do everything there.

But wouldn’t moving people there reduce the productivity? Yes. Somewhat. If you actually tried to concentrate the entire world’s population into the US, productivity in the US would surely go down. So, okay, fine; stop moving people to a more productive place when it has ceased to be more productive. What this should do is average out all the world’s labor productivity to the same level—but a much higher level than the current world average, and frankly probably quite close to its current maximum.

Once you consider that moving people and things does have real costs, maybe fully equaling productivity wouldn’t make sense. But it would be close. The differences in productivity across countries would be small.

They are not small.

Labor productivity worldwide varies tremendously. I don’t count Ireland, because that’s Leprechaun Economics (this is really US GDP with accounting tricks, not Irish GDP). So the prize for highest productivity goes to Norway, at $100 per worker hour (#ScandinaviaIsBetter). The US is doing the best among large countries, at an impressive $73 per hour. And at the very bottom of the list, we have places like Bangladesh at $4.79 per hour and Cambodia at $3.43 per hour. So, roughly speaking, there is about a 20-to-1 ratio between the most productive and least productive countries.

I could believe that it’s not worth it to move US production at $73 per hour to Norway to get it up to $100 per hour. (For one thing, where would we fit it all?) But I find it far more dubious that it wouldn’t make sense to move most of Cambodia’s labor to the US. (Even all 16 million people is less than what the US added between 2010 and 2020.) Even given the fact that these Cambodian workers are less healthy and less educated than American workers, they would almost certainly be more productive on the other side of the Pacific, quite likely ten times as productive as they are now. Yet we haven’t moved them, and have no plans to.

That leaves the question of whether we will move our capital to them. We have been doing so in China, and it worked (to a point). Before that, we did it in Korea and Japan, and it worked. Cambodia will probably come along sooner or later. For now, that seems to be the best we can do.

But I still can’t shake the thought that the world is leaving trillions of dollars on the table by refusing to move people. The inequality of factor mobility seems to be a big part of the world’s inequality, period.

Scalability and inequality

2022-05-152022-05-08 PNRJ core principles, inequality, mathematical models, statistics biology, capital, chemistry, DNA, exponential growth, fat tail, growth, inequality, labor, normal distribution, Pareto distribution, PCR, physics, scalability, scale

May 15 JDN 2459715

Why are some molecules (e.g. DNA) billions of times larger than others (e.g. H2O), but all atoms are within a much narrower range of sizes (only a few hundred)?

Why are some animals (e.g. elephants) millions of times as heavy as other (e.g. mice), but their cells are basically the same size?

Why does capital income vary so much more (factors of thousands or millions) than wages (factors of tens or hundreds)?

These three questions turn out to have much the same answer: Scalability.

Atoms are not very scalable: Adding another proton to a nucleus causes interactions with all the other protons, which makes the whole atom unstable after a hundred protons or so. But molecules, particularly organic polymers such as DNA, are tremendously scalable: You can add another piece to one end without affecting anything else in the molecule, and keep on doing that more or less forever.

Cells are not very scalable: Even with the aid of active transport mechanisms and complex cellular machinery, a cell’s functionality is still very much limited by its surface area. But animals are tremendously scalable: The same exponential growth that got you from a zygote to a mouse only needs to continue a couple years longer and it’ll get you all the way to an elephant. (A baby elephant, anyway; an adult will require a dozen or so years—remarkably comparable to humans, in fact.)

Labor income is not very scalable: There are only so many hours in a day, and the more hours you work the less productive you’ll be in each additional hour. But capital income is perfectly scalable: We can add another digit to that brokerage account with nothing more than a few milliseconds of electronic pulses, and keep doing that basically forever (due to the way integer storage works, above 2^63 it would require special coding, but it can be done; and seeing as that’s over 9 quintillion, it’s not likely to be a problem any time soon—though I am vaguely tempted to write a short story about an interplanetary corporation that gets thrown into turmoil by an integer overflow error).

This isn’t just an effect of our accounting either. Capital is scalable in a way that labor is not. When your contribution to production is owning a factory, there’s really nothing to stop you from owning another factory, and then another, and another. But when your contribution is working at a factory, you can only work so hard for so many hours.

When a phenomenon is highly scalable, it can take on a wide range of outcomes—as we see in molecules, animals, and capital income. When it’s not, it will only take on a narrow range of outcomes—as we see in atoms, cells, and labor income.

Exponential growth is also part of the story here: Animals certainly grow exponentially, and so can capital when invested; even some polymers function that way (e.g. under polymerase chain reaction). But I think the scalability is actually more important: Growing rapidly isn’t so useful if you’re going to immediately be blocked by a scalability constraint. (This actually relates to the difference between r- and K- evolutionary strategies, and offers further insight into the differences between mice and elephants.) Conversely, even if you grow slowly, given enough time, you’ll reach whatever constraint you’re up against.

Indeed, we can even say something about the probability distribution we are likely to get from random processes that are scalable or non-scalable.

A non-scalable random process will generally converge toward the familiar normal distribution, a “bell curve”:

[Image from Wikipedia: By Inductiveload – self-made, Mathematica, Inkscape, Public Domain, https://commons.wikimedia.org/w/index.php?curid=3817954]

The normal distribution has most of its weight near the middle; most of the population ends up near there. This is clearly the case for labor income: Most people are middle class, while some are poor and a few are rich.

But a scalable random process will typically converge toward quite a different distribution, a Pareto distribution:

[Image from Wikipedia: By Danvildanvil – Own work, CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=31096324]

A Pareto distribution has most of its weight near zero, but covers an extremely wide range. Indeed it is what we call fat tailed, meaning that really extreme events occur often enough to have a meaningful effect on the average. A Pareto distribution has most of the people at the bottom, but the ones at the top are really on top.

And indeed, that’s exactly how capital income works: Most people have little or no capital income (indeed only about half of Americans and only a third(!) of Brits own any stocks at all), while a handful of hectobillionaires make utterly ludicrous amounts of money literally in their sleep.

Indeed, it turns out that income in general is pretty close to distributed normally (or maybe lognormally) for most of the income range, and then becomes very much Pareto at the top—where nearly all the income is capital income.

This fundamental difference in scalability between capital and labor underlies much of what makes income inequality so difficult to fight. Capital is scalable, and begets more capital. Labor is non-scalable, and we only have to much to give.

It would require a radically different system of capital ownership to really eliminate this gap—and, well, that’s been tried, and so far, it hasn’t worked out so well. Our best option is probably to let people continue to own whatever amounts of capital, and then tax the proceeds in order to redistribute the resulting income. That certainly has its own downsides, but they seem to be a lot more manageable than either unfettered anarcho-capitalism or totalitarian communism.

Capitalism can be fair

2021-08-222021-08-15 PNRJ core principles, ethics capital, capitalism, fairness, Marxism, profit, socialism, surplus

Aug 22 JDN 2459449

There are certainly extreme right-wing libertarians who seem to think that capitalism is inherently fair, or that “fairness” is meaningless and (some very carefully defined notion of) liberty is the only moral standard. I am not one of them. I agree that many of the actual practices of modern capitalism as we know it are unfair, particularly in the treatment of low-skill workers.

But lately I’ve been seeing a weirdly frequent left-wing take—Marxist take, really—that goes to the opposite extreme, saying that capitalism is inherently unfair, that the mere fact that capital owners ever get any profit on anything is proof that the system is exploitative and unjust and must be eliminated.

So I decided it would be worthwhile to provide a brief illustration of how, at least in the best circumstances, a capitalist system of labor can in fact be fair and just.

The argument that capitalism is inherently unjust seems to be based on the notion that profit means “workers are paid less than their labor is worth”. I think that the reason this argument is so insidious is that it’s true in one sense—but not true in another. Workers are indeed paid less than the total surplus of their actual output—but, crucially, they are not paid less than what the surplus of their output would have been had the capital owner not provided capital and coordination.

Suppose that we are making some sort of product. To make it more concrete, let’s say shirts. You can make a shirt by hand, but it’s a lot of work, and it takes a long time. Suppose that you, working on your own by hand, can make 1 shirt per day. You can sell each shirt for $10, so you get $10 per day.

Then, suppose that someone comes along who owns looms and sewing machines. They gather you and several other shirt-makers and offer to let you use their machines, in exchange for some of the revenue. With the aid of 9 other workers and the machines, you are able to make 30 shirts per day. You can still sell each shirt for $10, so now there is total revenue of $300.

Whether or not this is fair depends on precisely the bargain that was struck with the owner of the machines. Suppose that he asked for 40% of the revenue. Then the 10 workers including yourself would get (0.60)($300) = $180 to split, presumably evenly, and each get $18 per day. This seems fair; you’re clearly better off than you were making shirts by yourself. The capital owner then gets (0.40)($300) = $120, which is more than each of you, but not by a ridiculous amount; and he probably has costs to deal with in maintaining those machines.

But suppose instead the owner had demanded 80% of the revenue; then you would have to split (0.20)($300) = $60 between you, and each would only get $6 per day. The capital owner would then get (0.80)($300) = $240, 40 times as much as each of you.

Or perhaps instead of a revenue-sharing agreement, the owner offers to pay you a wage. If that wage is $18 per day, it seems fair. If it is $6 per day, it seems obviously unfair.

If this owner is the only employer, then he is competing only with working alone. So we would expect him to offer a wage of $10 per day, or maybe slightly more since working with the machines may be harder or more unpleasant than working by hand.

But if there are many employers, then he is now competing with those employers as well. If he offers $10, someone else might offer $12, and a third might offer $15. Competition should drive the system toward an equilibrium where workers are getting paid their marginal value product—in other words, the wage for one hour of work should equal the additional value added by one more hour of work.

In the case that seems fair, where workers are getting more money than they would have on their own, are they getting paid “less than the value of their labor”? In one sense, yes; the total surplus is not going all to the workers, but is being shared with the owner of the machines. But the more important sense is whether they’d be better off quitting and working on their own—and they obviously would not be.

What value does the capital owner provide? Well, the capital, of course. It’s their property and they are letting other people use it. Also, they incur costs to maintain it.

Of course, it matters how the capital owner obtained that capital. If they are an inventor who made it themselves, it seems obviously just that they should own it. If they inherited it or got lucky on the stock market, it isn’t something they deserve in a deep sense, but it’s reasonable to say they are entitled to it. But if the only reason they have the capital is by theft, fraud, or exploitation, then obviously they don’t deserve it. In practice, there are very few of the first category, a huge number of the second, and all too many of the third. Yet this is not inherent to the capitalist work arrangement. Many capital owners don’t deserve what they own; but those who do have a right to make a profit letting other people use their property.

There are of course many additional complexities that arise in the real world, in terms of market power, bargaining, asymmetric information, externalities, and so on. I freely admit that in practice, capitalism is often unfair. But I think it’s worth pointing out that the mere existence of profit from capital ownership is not inherently unjust, and in fact by organizing our economy around it we have managed to achieve unprecedented prosperity.

How much wealth is there in the world?

2019-07-142019-07-07 PNRJ inequality capital, GDP, inequality, wealth

July 14 JDN 2458679

How much wealth is there in the world? If we split it all evenly, how much would each of us have?

It’s a surprisingly complicated question: What counts as wealth? Presumably we include financial assets, real estate, commodities—anything that can be sold on a market. But what about natural resources? Shouldn’t we somehow value clean air and water? What about human capital—health, knowledge, skills, and expertise that make us able to work better?

I’m going to stick with tradeable assets for now, because I’m interested in questions of redistribution. If we were to add up all the wealth in the United States, or all the wealth in the world, and split it all evenly, how much would each person get? Even then, there are questions about how to price assets: Do we current market prices, or what was actually paid for them in the past? How much do we depreciate? How do we count debt that was used to buy non-financial assets (such as student loans)?

The Federal Reserve reports an official estimate of the US capital stock at $56.2 trillion (in 2011 dollars). Assuming that a third of income is capital income, that means that of our GDP of $18.9 trillion (in 2012 dollars), this would make the rate of return on capital 11%. That rate of return strikes me as pretty clearly too high. This must be an underestimate of our capital stock.

The 2015 Global Wealth Report estimates total US wealth as $63.5 trillion, and total world wealth as $153.2 trillion. This was for 2014, so using the US GDP growth rate of about 2% and the world GDP growth rate of 3.6%, the current wealth stocks should be about $70 trillion and $183 trillion respectively.

This gives a much more plausible rate of return: One third of the US GDP of $19.6 trillion (in 2014 dollars) is $6.53 trillion, yielding a rate of return of about 9%.

One third of the world GDP of $78 trillion is $26 trillion, yielding a rate of return of about 14%. This seems a bit high, but we’re including a lot of countries with very little capital that we would expect to have very high rates of return, so it might be right.

Credit Suisse releases estimates of total wealth that are supposed to include non-financial assets as well, though these are even more uncertain than financial assets. They estimate total US wealth as $98 trillion and total world wealth as $318 trillion.

There’s a lot of uncertainty around all of these figures, but I think these are close enough to get a sense of what sort of redistribution might be possible.

If the US wealth stock is about $70 trillion and our population is about 330 million, that means that the average wealth of an American is $200,000. If our wealth stock is instead about $98 trillion, the average wealth of an American is about $300,000.

Since the average number of people in a US household is 2.5, this means that average household wealth is somewhere between $500,000 and $750,000. This is actually a bit less than I thought; I would have guessed that the mythical “average American household” is a millionaire. (Of course, even Credit Suisse might be underestimating our wealth stock.)

If the world wealth stock is about $180 trillion and the population is about 7.7 billion, global average wealth per person is about $23,000. If instead the global wealth stock is about $320 trillion, the average wealth of a human being is about $42,000.

Both of these are far above the median wealth, which is much more representative of what a typical person has. Median wealth per adult in the US is about $65,000; worldwide it’s only about $4,200.

This means that if we were to somehow redistribute all wealth in the United States, half the population would gain an average of somewhere between $140,000 and $260,000, or on a percentage basis, the median American would see their wealth increase by 215% to 400%. If we were to instead somehow redistribute all wealth in the world, half the population would gain an average of $19,000 to $38,000; the median individual would see their wealth increase by 450% to 900%.

Of course, we can’t literally redistribute all the wealth in the world. Even if we could somehow organize it logistically—a tall order to be sure—such a program would introduce all sorts of inefficiencies and perverse incentives. That would really be socialism: We would be allocating wealth entirely based on a government policy and not at all by the market.

But suppose instead we decided to redistribute some portion of all this wealth. How about 10%? That seems like a small enough amount to avoid really catastrophic damage to the economy. Yes, there would be some inefficiencies introduced, but this could be done with some form of wealth taxes that wouldn’t require completely upending capitalism.

Suppose we did this just within the US. 10% of US wealth, redistributed among the whole population, would increase median wealth by between $20,000 and $30,000, or between 30% and 45%. That’s already a pretty big deal. And this is definitely feasible; the taxation infrastructure is all already in place. We could essentially buy the poorest half of the population a new car on the dime of the top half.

If instead we tried to do this worldwide, we would need to build the fiscal capacity first; the infrastructure to tax wealth effectively is not in place in most countries. But supposing we could do that, we could increase median wealth worldwide by between $2,000 and $4,000, or between 50% and 100%. Of course, this would mean that many of us in the US would lose a similar amount; but I think it’s still quite remarkable that we could as much as double the wealth of most of the world’s population by redistributing only 10% of the total wealth. That’s how much wealth inequality there is in the world.

Just how rich is rich?

2019-05-262019-05-16 PNRJ core principles, ethics, inequality, public policy Ann Arbor, Bill Gates, billionaires, capital, capital gains, capitalism, GiveDirectly, Gordon Gekko, Jeff Bezos, millionaires, Mitt Romney, poor, Queen Elizabeth, rich, Scandinaviaisbetter, socialism, wealth

May 26 JDN 2458630

I think if there is one single thing I would like more people to know about economics, it is the sheer magnitude of global inequality. Most people seem to have no idea just how rich some people are—and how poor so many others are. They have a vision in their head of what “rich” and “poor” are, and their “rich” is a low-level Wall Street trader making $400,000 a year (the kind of people Gordon Gekko mocks in the film), and “poor” is someone who lives under a bridge in New York City. (They’re both New Yorkers, I guess. New Yorkers seem to be the iconic Americans, which is honestly more representative than you might think—80% of Americans live in urban or suburban areas.)

If we take a global perspective, this is not what “rich” and “poor” truly mean.

In next week’s post I’ll talk about what “poor” means. It’s really appallingly bad. We have to leave the First World in order to find it; many people here are poor, but not that poor. It’s so bad that I think once you really understand it, it can’t but change your whole outlook on the world. But I’m saving that for next week.

This week, I’ll talk about what “rich” really means in today’s world. We needn’t leave the United States, for the top 3 and 6 of the top 10 richest people in the world live here. And they are all White men, by the way, though Carlos Slim and Amancio Ortega are at least Latino.

Going down the list of billionaires ranked by wealth, you have to get down to 15th place before encountering a woman, and it’s really worse than that, because Francoise Bettencourt (15), Alice Walton (17), Jacqueline Mars (33), Yang Huiyan (42), Susan Klatton (46), Laurena Powell-Jobs (54), Abigail Johnson (71), and Iris Fontbona (74) are all heirs. The richest living woman who didn’t simply inherit from her father or husband is actually Gina Rinehart, the 75th richest person in the world. (And note that, while also in some sense an heir, Queen Elizabeth is not on that list; in fact, she’s nowhere near the richest people in the world. She’s not in the top 500.)

You have to get to 20th place before encountering someone non-White (Ma Huateng), and all the way down to 65th before encountering someone not White or East Asian (the Hinduja brothers). Not one of the top 100 richest people is Black.

Just how rich are these people? Well, there’s a meme going around saying that Jeff Bezos could afford to buy every homeless person in the world a house at median market price and still, with just what’s left over, be a multi-billionaire among the top 100 richest people in the world.

And that meme is completely correct. The math checks out.

There are about 554,000 homeless people in the US at any given time.

The median sale price of a currently existing house in the US is about $253,000.

Multiply those two numbers together, and you get $140 billion.

And Jeff Bezos has net wealth of $157 billion.

This means that he would still have $17 billion left after buying all those houses. The 100th richest person in the world has $13 billion, so Jeff Bezos would still be higher than that.

Even $17 billion is enough to spend over $2 million every single day—over $20 per second—and never run out of money as long as the dividends keep paying out.

Jeff Bezos in fact made so much in dividends and capital gains this past quarter that he was taking in as much money as the median Amazon employee’s annual salary—which is more than what I make as a grad student, and only slightly less than the median US individual income—every nine seconds. Yes, you read that correctly: Nine (9) seconds. In the time it took you to read this paragraph, Jeff Bezos probably received more in capital gains than you will make this whole year. And if not (because you’re relatively rich or you read quickly), I’m sure he will have in the time it takes you to read this whole post.

When Mitt Romney ran for President, a great deal was made of his net wealth of over $250 million. This is indeed very rich, richer than anyone really needs or probably deserves. But compared to the world’s richest, this is pocket change. Jeff Bezos gets that much in dividends and capital gains every day. Bill Gates could give away that much every day for a year and still not run out of money. (He doesn’t quite give that much, but he does give a lot.)

I grew up in Ann Arbor, Michigan. Ann Arbor is a medium-sized city of about 120,000 people (230th in the US by population), and relatively well-off (median household income about 16% higher than the US median). Nevertheless, if Jeff Bezos wanted to, he could give every single person in Ann Arbor the equivalent of 30 years of their income—over a million dollars each—and still have enough money left to be among the world’s 100 richest people.

Or suppose instead that all the world’s 500 richest people decided to give away all the money they have above $1 billion—so they’d all still be billionaires, but only barely. That $8.7 trillion they have together, minus the $500 billion they’re keeping, would be $8.2 trillion. In fact, let’s say they keep a little more, just to make sure they all have the same ordering: Give each one an extra $1 million for each point they are in the ranking, so that Jeff Bezos would stay on top at $1 B + 500 ($0.001 B) = $1.5 billion, while Bill Gates in second place would have $1 million less, and so on. That would leave us with still over $8 trillion to give away.

How far could that $8 trillion go? Well, suppose we divided it evenly between all 328 million people in the United States. How much would each person receive? Oh, just about $24,000—basically my annual income.

Or suppose instead we spread it out over the entire world: Every single man, woman, and child on the planet Earth gets an equal share. There are 7.7 billion people in the world, so by spreading out $8 trillion between them, each one would get over $1000. For you or I that’s a big enough windfall to feel. For the world’s poorest people, it’s more than they make in several years. It would be life-changing for them. (Actually that’s about what GiveDirectly gives each family—and it is life-changing.)

And let me remind you: This would be leaving them billionaires. They’re just not as much billionaires as before—they only have $1 billion instead of $20 billion or $50 billion or $100 billion. And even $1 billion is obviously enough to live however you want, wherever you want, for the rest of your life, never working another day if you don’t want to. With $1 billion, you can fly in jets (a good one will set you back $20 million), sail in yachts (even a massive 200-footer wouldn’t run much above $200 million), and eat filet mignon at every meal (in fact, at $25 per pound, you can serve it to yourself and a hundred of your friends without breaking a sweat). You can decorate your bedroom with original Jackson Pollock paintings (at $200 million, his most expensive painting is only 20% of your wealth) and bathe in bottles of Dom Perignon (at $400 per liter, a 200-liter bath would cost you about $80,000—even every day that’s only $30 million a year, or maybe half to a third of your capital income). Remember, this is all feasible at just $1 billion—and Jeff Bezos has over a hundred times that. There is no real lifestyle improvement that happens between $1 billion and $157 billion; it’s purely a matter of status and power.

Taking enough to make them mere millionaires would give us another $0.5 trillion to spend (about the GDP of Sweden, one-fourth the GDP of Canada, or 70% of the US military budget).

Do you think maybe these people have too much money?

I’m not saying that we should confiscate all private property. I’m not saying that we should collectivize all industry. I believe in free markets and private enterprise. People should be able to get rich by inventing things and starting businesses.

But should they be able to get that rich? So rich that one man could pay off every mortgage in a whole major city? So rich that the CEO of a company makes what his employees make in a year in less than a minute? So rich that 500 people—enough to fill a large lecture hall—own enough wealth that if it were spread out evenly they could give $1000 to every single person in the world?

If Jeff Bezos had $1.5 million, I’d say he absolutely earned it. Some high-level programmers at Amazon have that much, and they absolutely earned it. If he had $15 million, I’d think maybe he could deserve that, given his contribution to the world. If he had $150 million, I’d find it hard to believe that anyone could really deserve that much, but if it’s part of what we need to make capitalism work, I could live with that.

But Jeff Bezos doesn’t have $1.5 million. He doesn’t have $15 million. He doesn’t have $150 million. He doesn’t have $1.5 billion. He doesn’t even have $15 billion. He has $150 billion. He has over a thousand times the level of wealth at which I was already having to doubt whether any human being could possibly deserve so much money—and once it gets that big, it basically just keeps growing. A stock market crash might drop it down temporarily, but it would come back in a few years.

And it’s not like there’s nothing we could do to spread this wealth around. Some fairly simple changes in how we tax dividends and capital gains would be enough to get a lot of it, and a wealth tax like the one Elizabeth Warren has proposed would help a great deal as well. At the rates people have seriously proposed, these taxes would only really stop their wealth from growing; it wouldn’t meaningfully shrink it.

That could be combined with policy changes about compensation for corporate executives, particularly with regard to stock options, to make it harder to extract such a large proportion of a huge multinational corporation’s wealth into a single individual. We could impose a cap on the ratio between median employee salary (including the entire supply chain!) and total executive compensation (including dividends and capital gains!), say 100 to 1. (Making in 9 seconds what his employees make in a year, Jeff Bezos is currently operating at a ratio of over 3 million to 1.) If you exceed the cap, the remainder is taxed at 100%. This would mean that as a CEO you can still make $100 million a year, but only if your median employee makes $1 million. If your median employee makes $30,000, you’d better keep your own compensation under $3 million, because we’re gonna take the rest.

Is this socialism? I guess maybe it’s democratic socialism, the high-tax, high-spend #ScandinaviaIsBetter welfare state. But it would not be an end to free markets or free enterprise. We’re not collectivizing any industries, let alone putting anyone in guillotines. You could still start a business and make millions or even hundreds of millions of dollars; you’d simply be expected to share that wealth with your employees and our society as a whole, instead of hoarding it all for yourself.

Why “marginal productivity” is no excuse for inequality

2017-05-282017-10-08 PNRJ critique of neoclassical economics, development economics, ethics, inequality capital, China, income, India, J.K. Rowling, marginal productivity, Microsoft, productivity, returns to scale, salary, wage

May 28, JDN 2457902

In most neoclassical models, workers are paid according to their marginal productivity—the additional (market) value of goods that a firm is able to produce by hiring that worker. This is often used as an excuse for inequality: If someone can produce more, why shouldn’t they be paid more?

The most extreme example of this is people like Maura Pennington writing for Forbes about how poor people just need to get off their butts and “do something”; but there is a whole literature in mainstream economics, particularly “optimal tax theory”, arguing based on marginal productivity that we should tax the very richest people the least and never tax capital income. The Chamley-Judd Theorem famously “shows” (by making heroic assumptions) that taxing capital just makes everyone worse off because it reduces everyone’s productivity.

The biggest reason this is wrong is that there are many, many reasons why someone would have a higher income without being any more productive. They could inherit wealth from their ancestors and get a return on that wealth; they could have a monopoly or some other form of market power; they could use bribery and corruption to tilt government policy in their favor. Indeed, most of the top 0.01% do literally all of these things.

But even if you assume that pay is related to productivity in competitive markets, the argument is not nearly as strong as it may at first appear. Here I have a simple little model to illustrate this.

Suppose there are 10 firms and 10 workers. Suppose that firm 1 has 1 unit of effective capital (capital adjusted for productivity), firm 2 has 2 units, and so on up to firm 10 which has 10 units. And suppose that worker 1 has 1 unit of so-called “human capital”, representing their overall level of skills and education, worker 2 has 2 units, and so on up to worker 10 with 10 units. Suppose each firm only needs one worker, so this is a matching problem.

Furthermore, suppose that productivity is equal to capital times human capital: That is, if firm 2 hired worker 7, they would make 2*7 = $14 of output.

What will happen in this market if it converges to equilibrium?

Well, first of all, the most productive firm is going to hire the most productive worker—so firm 10 will hire worker 10 and produce $100 of output. What wage will they pay? Well, they need a wage that is high enough to keep worker 10 from trying to go elsewhere. They should therefore pay a wage of $90—the next-highest firm productivity times the worker’s productivity. That’s the highest wage any other firm could credibly offer; so if they pay this wage, worker 10 will not have any reason to leave.

Now the problem has been reduced to matching 9 firms to 9 workers. Firm 9 will hire worker 9, making $81 of output, and paying $72 in wages.

And so on, until worker 1 at firm 1 produces $1 and receives… $0. Because there is no way for worker 1 to threaten to leave, in this model they actually get nothing. If I assume there’s some sort of social welfare system providing say $0.50, then at least worker 1 can get that $0.50 by threatening to leave and go on welfare. (This, by the way, is probably the real reason firms hate social welfare spending; it gives their workers more bargaining power and raises wages.) Or maybe they have to pay that $0.50 just to keep the worker from starving to death.

What does inequality look like in this society?
Well, the most-productive firm only has 10 times as much capital as the least-productive firm, and the most-educated worker only has 10 times as much skill as the least-educated worker, so we might think that incomes would vary only by a factor of 10.

But in fact they vary by a factor of over 100.

The richest worker makes $90, while the poorest worker makes $0.50. That’s a ratio of 180. (Still lower than the ratio of the average CEO to their average employee in the US, by the way.) The worker is 10 times as productive, but they receive 180 times as much income.

The firm profits vary along a more reasonable scale in this case; firm 1 makes a profit of $0.50 while firm 10 makes a profit of $10. Indeed, except for firm 1, firm n always makes a profit of $n. So that’s very nearly a linear scaling in productivity.

Where did this result come from? Why is it so different from the usual assumptions? All I did was change one thing: I allowed for increasing returns to scale.

If you make the usual assumption of constant returns to scale, this result can’t happen. Multiplying all the inputs by 10 should just multiply the output by 10, by assumption—since that is the definition of constant returns to scale.

But if you look at the structure of real-world incomes, it’s pretty obvious that we don’t have constant returns to scale.

If we had constant returns to scale, we should expect that wages for the same person should only vary slightly if that person were to work in different places. In particular, to have a 2-fold increase in wage for the same worker you’d need more than a 2-fold increase in capital.

This is a bit counter-intuitive, so let me explain a bit further. If a 2-fold increase in capital results in a 2-fold increase in wage for a given worker, that’s increasing returns to scale—indeed, it’s precisely the production function I assumed above.
If you had constant returns to scale, a 2-fold increase in wage would require something like an 8-fold increase in capital. This is because you should get a 2-fold increase in total production by doubling everything—capital, labor, human capital, whatever else. So doubling capital by itself should produce a much weaker effect. For technical reasons I’d rather not get into at the moment, usually it’s assumed that production is approximately proportional to capital to the one-third power—so to double production you need to multiply capital by 2^3 = 8.

I wasn’t able to quickly find really good data on wages for the same workers across different countries, but this should at least give a rough idea. In Mumbai, the minimum monthly wage for a full-time worker is about $80. In Shanghai, it is about $250. If you multiply out the US federal minimum wage of $7.25 per hour by 40 hours by 4 weeks, that comes to $1160 per month.

Of course, these are not the same workers. Even an “unskilled” worker in the US has a lot more education and training than a minimum-wage worker in India or China. But it’s not that much more. Maybe if we normalize India to 1, China is 3 and the US is 10.

Likewise, these are not the same jobs. Even a minimum wage job in the US is much more capital-intensive and uses much higher technology than most jobs in India or China. But it’s not that much more. Again let’s say India is 1, China is 3 and the US is 10.

If we had constant returns to scale, what should the wages be? Well, for India at productivity 1, the wage is $80. So for China at productivity 3, the wage should be $240—it’s actually $250, close enough for this rough approximation. But the US wage should be $800—and it is in fact $1160, 45% larger than we would expect by constant returns to scale.

Let’s try comparing within a particular industry, where the differences in skill and technology should be far smaller. The median salary for a software engineer in India is about 430,000 INR, which comes to about $6,700. If that sounds rather low for a software engineer, you’re probably more accustomed to the figure for US software engineers, which is $74,000. That is a factor of 11 to 1. For the same job. Maybe US software engineers are better than Indian software engineers—but are they that much better? Yes, you can adjust for purchasing power and shrink the gap: Prices in the US are about 4 times as high as those in India, so the real gap might be 3 to 1. But these huge price differences themselves need to be explained somehow, and even 3 to 1 for the same job in the same industry is still probably too large to explain by differences in either capital or education, unless you allow for increasing returns to scale.

In most industries, we probably don’t have quite as much increasing returns to scale as I assumed in my simple model. Workers in the US don’t make 100 times as much as workers in India, despite plausibly having both 10 times as much physical capital and 10 times as much human capital.

But in some industries, this model might not even be enough! The most successful authors and filmmakers, for example, make literally thousands of times as much money as the average author or filmmaker in their own country. J.K. Rowling has almost $1 billion from writing the Harry Potter series; this is despite having literally the same amount of physical capital and probably not much more human capital than the average author in the UK who makes only about 11,000 GBP—which is about $14,000. Harry Potter and the Philosopher’s Stone is now almost exactly 20 years old, which means that Rowling made an average of $50 million per year, some 3500 times as much as the average British author. Is she better than the average British author? Sure. Is she three thousand times better? I don’t think so. And we can’t even make the argument that she has more capital and technology to work with, because she doesn’t! They’re typing on the same laptops and using the same printing presses. Either the return on human capital for British authors is astronomical, or something other than marginal productivity is at work here—and either way, we don’t have anything close to constant returns to scale.

What can we take away from this? Well, if we don’t have constant returns to scale, then even if wage rates are proportional to marginal productivity, they aren’t proportional to the component of marginal productivity that you yourself bring. The same software developer makes more at Microsoft than at some Indian software company, the same doctor makes more at a US hospital than a hospital in China, the same college professor makes more at Harvard than at a community college, and J.K. Rowling makes three thousand times as much as the average British author—therefore we can’t speak of marginal productivity as inhering in you as an individual. It is an emergent property of a production process that includes you as a part. So even if you’re entirely being paid according to “your” productivity, it’s not really your productivity—it’s the productivity of the production process you’re involved in. A myriad of other factors had to snap into place to make your productivity what it is, most of which you had no control over. So in what sense, then, can we say you earned your higher pay?

Moreover, this problem becomes most acute precisely when incomes diverge the most. The differential in wages between two welders at the same auto plant may well be largely due to their relative skill at welding. But there’s absolutely no way that the top athletes, authors, filmmakers, CEOs, or hedge fund managers could possibly make the incomes they do by being individually that much more productive.

Sometimes people have to lose their jobs. This isn’t a bad thing.

2016-10-082017-10-08 PNRJ ethics, inequality, macroeconomics, public policy active labor market policy, capital, Denmark, education, Eleizer Yudkowsky, employment, employment protection legislation, hires, income, jobs, labor, Less Wrong, Miles Kimball, Parade magazine, productivity, race, rent, robots, separations, technology, unemployment, wealth

Oct 8, JDN 2457670

Eleizer Yudkowsky (founder of the excellent blog forum Less Wrong) has a term he likes to use to distinguish his economic policy views from either liberal, conservative, or even libertarian: “econoliterate”, meaning the sort of economic policy ideas one comes up with when one actually knows a good deal about economics.

In general I think Yudkowsky overestimates this effect; I’ve known some very knowledgeable economists who disagree quite strongly over economic policy, and often following the conventional political lines of liberal versus conservative: Liberal economists want more progressive taxation and more Keynesian monetary and fiscal policy, while conservative economists want to reduce taxes on capital and remove regulations. Theoretically you can want all these things—as Miles Kimball does—but it’s rare. Conservative economists hate minimum wage, and lean on the theory that says it should be harmful to employment; liberal economists are ambivalent about minimum wage, and lean on the empirical data that shows it has almost no effect on employment. Which is more reliable? The empirical data, obviously—and until more economists start thinking that way, economics is never truly going to be a science as it should be.

But there are a few issues where Yudkowsky’s “econoliterate” concept really does seem to make sense, where there is one view held by most people, and another held by economists, regardless of who is liberal or conservative. One such example is free trade, which almost all economists believe in. A recent poll of prominent economists by the University of Chicago found literally zero who agreed with protectionist tariffs.

Another example is my topic for today: People losing their jobs.

Not unemployment, which both economists and almost everyone else agree is bad; but people losing their jobs. The general consensus among the public seems to be that people losing jobs is always bad, while economists generally consider it a sign of an economy that is run smoothly and efficiently.

To be clear, of course losing your job is bad for you; I don’t mean to imply that if you lose your job you shouldn’t be sad or frustrated or anxious about that, particularly not in our current system. Rather, I mean to say that policy which tries to keep people in their jobs is almost always a bad idea.

I think the problem is that most people don’t quite grasp that losing your job and not having a job are not the same thing. People not having jobs who want to have jobs—unemployment—is a bad thing. But losing your job doesn’t mean you have to stay unemployed; it could simply mean you get a new job. And indeed, that is what it should mean, if the economy is running properly.

Check out this graph, from FRED:

The red line shows hires—people getting jobs. The blue line shows separations—people losing jobs or leaving jobs. During a recession (the most recent two are shown on this graph), people don’t actually leave their jobs faster than usual; if anything, slightly less. Instead what happens is that hiring rates drop dramatically. When the economy is doing well (as it is right now, more or less), both hires and separations are at very high rates.

Why is this? Well, think about what a job is, really: It’s something that needs done, that no one wants to do for free, so someone pays someone else to do it. Once that thing gets done, what should happen? The job should end. It’s done. The purpose of the job was not to provide for your standard of living; it was to achieve the task at hand. Once it doesn’t need done, why keep doing it?

We tend to lose sight of this, for a couple of reasons. First, we don’t have a basic income, and our social welfare system is very minimal; so a job usually is the only way people have to provide for their standard of living, and they come to think of this as the purpose of the job. Second, many jobs don’t really “get done” in any clear sense; individual tasks are completed, but new ones always arise. After every email sent is another received; after every patient treated is another who falls ill.

But even that is really only true in the short run. In the long run, almost all jobs do actually get done, in the sense that no one has to do them anymore. The job of cleaning up after horses is done (with rare exceptions). The job of manufacturing vacuum tubes for computers is done. Indeed, the job of being a computer—that used to be a profession, young women toiling away with slide rules—is very much done. There are no court jesters anymore, no town criers, and very few artisans (and even then, they’re really more like hobbyists). There are more writers now than ever, and occasional stenographers, but there are no scribes—no one powerful but illiterate pays others just to write things down, because no one powerful is illiterate (and even few who are not powerful, and fewer all the time).

When a job “gets done” in this long-run sense, we usually say that it is obsolete, and again think of this as somehow a bad thing, like we are somehow losing the ability to do something. No, we are gaining the ability to do something better. Jobs don’t become obsolete because we can’t do them anymore; they become obsolete because we don’t need to do them anymore. Instead of computers being a profession that toils with slide rules, they are thinking machines that fit in our pockets; and there are plenty of jobs now for software engineers, web developers, network administrators, hardware designers, and so on as a result.

Soon, there will be no coal miners, and very few oil drillers—or at least I hope so, for the sake of our planet’s climate. There will be far fewer auto workers (robots have already done most of that already), but far more construction workers who install rail lines. There will be more nuclear engineers, more photovoltaic researchers, even more miners and roofers, because we need to mine uranium and install solar panels on rooftops.

Yet even by saying that I am falling into the trap: I am making it sound like the benefit of new technology is that it opens up more new jobs. Typically it does do that, but that isn’t what it’s for. The purpose of technology is to get things done.

Remember my parable of the dishwasher. The goal of our economy is not to make people work; it is to provide people with goods and services. If we could invent a machine today that would do the job of everyone in the world and thereby put us all out of work, most people think that would be terrible—but in fact it would be wonderful.

Or at least it could be, if we did it right. See, the problem right now is that while poor people think that the purpose of a job is to provide for their needs, rich people think that the purpose of poor people is to do jobs. If there are no jobs to be done, why bother with them? At that point, they’re just in the way! (Think I’m exaggerating? Why else would anyone put a work requirement on TANF and SNAP? To do that, you must literally think that poor people do not deserve to eat or have homes if they aren’t, right now, working for an employer. You can couch that in cold economic jargon as “maximizing work incentives”, but that’s what you’re doing—you’re threatening people with starvation if they can’t or won’t find jobs.)

What would happen if we tried to stop people from losing their jobs? Typically, inefficiency. When you aren’t allowed to lay people off when they are no longer doing useful work, we end up in a situation where a large segment of the population is being paid but isn’t doing useful work—and unlike the situation with a basic income, those people would lose their income, at least temporarily, if they quit and tried to do something more useful. There is still considerable uncertainty within the empirical literature on just how much “employment protection” (laws that make it hard to lay people off) actually creates inefficiency and reduces productivity and employment, so it could be that this effect is small—but even so, likewise it does not seem to have the desired effect of reducing unemployment either. It may be like minimum wage, where the effect just isn’t all that large. But it’s probably not saving people from being unemployed; it may simply be shifting the distribution of unemployment so that people with protected jobs are almost never unemployed and people without it are unemployed much more frequently. (This doesn’t have to be based in law, either; while it is made by custom rather than law, it’s quite clear that tenure for university professors makes tenured professors vastly more secure, but at the cost of making employment tenuous and underpaid for adjuncts.)

There are other policies we could make that are better than employment protection, active labor market policies like those in Denmark that would make it easier to find a good job. Yet even then, we’re assuming that everyone needs jobs–and increasingly, that just isn’t true.

So, when we invent a new technology that replaces workers, workers are laid off from their jobs—and that is as it should be. What happens next is what we do wrong, and it’s not even anybody in particular; this is something our whole society does wrong: All those displaced workers get nothing. The extra profit from the more efficient production goes entirely to the shareholders of the corporation—and those shareholders are almost entirely members of the top 0.01%. So the poor get poorer and the rich get richer.

The real problem here is not that people lose their jobs; it’s that capital ownership is distributed so unequally. And boy, is it ever! Here are some graphs I made of the distribution of net wealth in the US, using from the US Census.

Here are the quintiles of the population as a whole:

And here are the medians by race:

Medians by age:

Medians by education:

And, perhaps most instructively, here are the quintiles of people who own their homes versus renting (The rent is too damn high!)

All that is just within the US, and already they are ranging from the mean net wealth of the lowest quintile of people under 35 (-$45,000, yes negative—student loans) to the mean net wealth of the highest quintile of people with graduate degrees ($3.8 million). All but the top quintile of renters are poorer than all but the bottom quintile of homeowners. And the median Black or Hispanic person has less than one-tenth the wealth of the median White or Asian person.

If we look worldwide, wealth inequality is even starker. Based on UN University figures, 40% of world wealth is owned by the top 1%; 70% by the top 5%; and 80% by the top 10%. There is less total wealth in the bottom 80% than in the 80-90% decile alone. According to Oxfam, the richest 85 individuals own as much net wealth as the poorest 3.7 billion. They are the 0.000,001%.

If we had an equal distribution of capital ownership, people would be happy when their jobs became obsolete, because it would free them up to do other things (either new jobs, or simply leisure time), while not decreasing their income—because they would be the shareholders receiving those extra profits from higher efficiency. People would be excited to hear about new technologies that might displace their work, especially if those technologies would displace the tedious and difficult parts and leave the creative and fun parts. Losing your job could be the best thing that ever happened to you.

The business cycle would still be a problem; we have good reason not to let recessions happen. But stopping the churn of hiring and firing wouldn’t actually make our society better off; it would keep people in jobs where they don’t belong and prevent us from using our time and labor for its best use.

Perhaps the reason most people don’t even think of this solution is precisely because of the extreme inequality of capital distribution—and the fact that it has more or less always been this way since the dawn of civilization. It doesn’t seem to even occur to most people that capital income is a thing that exists, because they are so far removed from actually having any amount of capital sufficient to generate meaningful income. Perhaps when a robot takes their job, on some level they imagine that the robot is getting paid, when of course it’s the shareholders of the corporations that made the robot and the corporations that are using the robot in place of workers. Or perhaps they imagine that those shareholders actually did so much hard work they deserve to get paid that money for all the hours they spent.

Because pay is for work, isn’t it? The reason you get money is because you’ve earned it by your hard work?

No. This is a lie, told to you by the rich and powerful in order to control you. They know full well that income doesn’t just come from wages—most of their income doesn’t come from wages! Yet this is even built into our language; we say “net worth” and “earnings” rather than “net wealth” and “income”. (Parade magazine has a regular segment called “What People Earn”; it should be called “What People Receive”.) Money is not your just reward for your hard work—at least, not always.

The reason you get money is that this is a useful means of allocating resources in our society. (Remember, money was created by governments for the purpose of facilitating economic transactions. It is not something that occurs in nature.) Wages are one way to do that, but they are far from the only way; they are not even the only way currently in use. As technology advances, we should expect a larger proportion of our income to go to capital—but what we’ve been doing wrong is setting it up so that only a handful of people actually own any capital.

Fix that, and maybe people will finally be able to see that losing your job isn’t such a bad thing; it could even be satisfying, the fulfillment of finally getting something done.

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Human Economics

Cognitive development economics: Understanding the mind in order to feed the world

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