Tag Archives: Inequality

A Salute To Median Calm

It is a standard trope of fiction that people often get angry when they suffer life outcomes well below what they see as their justified expectations. Such sore losers are tempted to retaliate against the individuals and institutions they blame for their loss, causing increasing damage until others agree to fix the unfairness.

Most outcomes, like income or fame, are distributed with mean outcomes well above median outcomes. As a result, well over half of everyone gets an outcome below what that they could have reasonably expected. So if this sore loser trope were true, there’d be a whole lot of angry folks causing damage. Maybe even most people would be this angry. Hard to see how civilization could function here. This scenario is often hoped-for by those who seek dramatic revolutions to fix large scale social injustices.

Actually, however, even though most people might plausibly see themselves as unfairly assigned to be losers, few become angry enough to cause much damage. Oh most people will have resentments and complaints, and this may lead on occasion to mild destruction, but most people are mostly peacefully. In the words of the old song, while they may not get what they want, they mostly get what they need.

Not only do most people achieve much less than the average outcomes, they achieve far less than the average outcomes that they see in media and fiction. Furthermore, most people eventually realize that the world is often quite hypocritical about the qualities it rewards. That is, early in life people are told that certain admired types of efforts and qualities are the ones with the best chance to lead to high outcomes. But later people learn that in fact that other less cooperative or fair strategies are often rewarded more. They may thus reasonably conclude that the game was rigged, and that they failed in part because they were fooled for too long.

Given all this, we should be somewhat surprised, and quite grateful, to live in such a calm world. Most people fall below the standard of success set by average outcomes, and far below that set by typical media-visible outcomes. And they learn that their losses are caused in part by winners taking illicit strategies and lying to them about the rewards to admired strategies. Yet contrary to the common fictional trope, this does not induce them to angrily try to burn down our shared house of civilization.

So dear mostly-calm near-median person, I respectfully salute you. Without you and your stoic acceptance, civilization would not be possible. Perhaps I should salute men a bit more, as they are more prone to violent anger, and suffer higher variance and thus higher mean to median outcome ratios. And perhaps the old a bit more too, as they see more of the world’s hypocrisy, and can hope much less for success via big future reversals. But mostly, I salute you all. Humans are indeed amazing creatures.

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Toward Better Signals

While we tend to say and think otherwise, in fact much of what we do is oriented toward helping us to show off. (Our new book argues for this at length.) Assuming this is true, what does a better world look like?

In simple signaling models, people tend to do too much of the activities they use to signal. This suggests that a better world is one that taxes or limits such activities. Say by taxing or limiting school, hospitals, or sporting contests. However, this is hard to arrange because signaling via political systems tends to create the opposite: subsidies and minimum required levels of such widely admired activities. (Though socializing such activities under limited government budgets is often effective.) Also, if we put most all of our life energy into signaling, then limits or taxes on just signaling activities will mainly result in us diverting our efforts to other signals.

If some signaling activities have larger positive externalities, then it seems an obvious win to use taxes, subsidies, etc. to divert our efforts into those activities. This is plausibly why we try to praise people more for showing off via charity, innovation, or whistleblowing. Similarly, we tend to criticize activities like war and other violence with large negative externalities. We should continue to do these things, and also look for other such activities worthy of extra praise or criticism.

However, on reflection I think the biggest problem with signals today is the quality of our audience. When the audience that we want to impress knows little about how our visible actions connect to larger consequences, then we also need not attend much to such connections. For example, to show an audience that we care enough about someone via helping them to get medicine, we need only push the sort of medicine that our audience thinks is effective. Similarly for using charity to convince an audience we care about the poor, politics to convince an audience we care about our nation, or using creative activities to convince an audience we promote innovation.

What if our audiences knew more about which medicines helped health, which charities helped the poor, which national policies help the nation, or which creative activities promoted innovation? That would push us to also know more, and lead us to choose more effective medicines, charities, policies, and innovations. All to the world’s benefit. So what could make the audiences that we seek to impress know more about how our activities connect to these larger consequences?

One approach is make our audiences more elite. Today our efforts to gain more likes on social media have us pandering to a pretty broad and ignorant audience. In contrast, in many old-world rags-to-riches stories, a low person rose in rank via a series of encounters with higher persons, each of whom was suitably impressed. The more that we expect to gain via impressing better-informed elites, the better informed will our show-off actions be.

But this isn’t just about who we seek to impress. It is also about whether we impress them via many small encounters, or via a few big ones. In larger encounters, our audience can take more time to judge how much we really understand about what we are doing. Yes risk and randomness could dominate if the main encounters that mattered to us were too small in number. But we seem pretty far away from that limit at the moment. For now, we’d have a better world of signals if we tried more to impress via a smaller number of more intense encounters with better informed elites.

Of course to fill this role of a better informed audience, it isn’t enough for “elites” to merely be richer, prettier, or more popular. They need to actually know more about how signaling actions connect to larger consequences. So there can be outsized gains from better educating elites on such things, and from selecting our elites more from those who are better educated on them. And anything that distracts elites from performing well in this this crucial role can have outsized costs.

Of course there’s a lot more to figure out here; I’ve just scratched the surface. But still, I thought I should plant a flag now, and show that it is possible to think more carefully about how to make a better world, when that world is chock full of signaling.

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Exclusion As A Substitute For Norms, Law, & Governance

Hell may not be other people, but worry sure is. That is, what we worry most about is what other people might do to us. People at the office, near our home, at the store, on the street, and even at church.

To reduce our worries, we can rely on norms, law, and governance. That is, to discourage bad behavior, we can encourage stronger informal social rules, we can adopt more formal legal rules, and we can do more with complex governance mechanisms.

In addition, we can rely on a simple and robust ancient solution: exclusion. That is, we can limit who is allowed with the circles we travel. We can use exclusion to limit who lives in our apartment complex, who shows up at the parties we attend, and who works in a cubicle near us.

Now the modern world tends to say that it disapproves of exclusion. The bad ancient world did much gossiping about what types of people could be trusted how, and then it relied a lot on the resulting shared judgements within their norms, law, and governance. We today have instead been trying to expunge such judgments from our formal systems; they are supposed to treat everyone equally without much reference to the groups to which they belong.

In addition, we’ve become more wary of using harsh punishments, like torture, death, or exile.  And we are more wary of using corruptible quick and dirty evaluations within our norms, law, and governance. For example, we have raised our standards for shunning neighbors, pulling over drivers, convicting folks at court, and approving large bold governance changes. And people today seem less willing to help the law via reports and testimony. Oh we may be more willing to apply norms to people we read about on social media; but we apply them less to the people we meet around us.

As a result of these trends, many people perceive that we have on net weakened the power of our systems of norms, law, and governance to constrain bad behavior. In response, I think they’ve naturally increased their reliance on exclusion. They look more carefully at who they allow into their schools, firms, apartments, and nations. And they are less willing to give a marginal person the benefit of the doubt.

Since we don’t want to look like we are excluding on the basis of simple group affiliations, we instead try to rely on a more intuitive and informal aggregation of many weak clues. We try to get a feel for how much we like them or feel comfortable with them overall. But that need not result in more mixing.

For example, colleges that admit people just on GPA and test scores can be more open to lower class students than colleges that require applicants to have adopted the right set of extracurricular actives, and to have hit on the right themes in their essays. Lower class people can find it is easier to get good grades and scores than to track the new fashions in activities and essays.

Similarly, Tyler Cowen makes the point somewhere that when firms had simple and clear rules on dress and behavior, someone with a low class background could more easily pass as high class; they just had to follow the rules. Today, without such simple rules, people rely more on many subtle clues of clothes, conversation topics, travel locations, favorite music and movies, and so on. Someone with a lower class background finds it harder to adopt all these patterns, and so is more obviously outed and rejected as not one of us.

The point seems to apply more generally. The net effect of our today relying less on norms, law, and governance, and avoiding simple group labels in exclusion, is that we rely more on exclusion based on an intuitive feel that someone is like us.

This may be a cause of our increasing class and political polarization, at home and work. Feeling less protected by norms, law, and governance, and shy of using simple group identifiers, we are more and more surrounding ourselves with others who feel comfortably like us. We can tell ourselves that we aren’t excluding Joe or Sue because they are Republicans, or don’t have a college degree. Its just that those sort of people tend to give off dozens of other off-putting signs that they are just not people like us.

We would call it an outrage if society as a whole excluded them explicitly and formally because of a few simple signs. Only ignorant and rude societies do that. But we feel quite comfortable excluding them from our little part of the world based on our just not feeling comfortable with them. Hey, as anyone knows, in our part of the world it is just really important to have the right people.

Consider this another weak argument for relying more on stronger norms, law, and governance. That could let us rely less on exclusion locally. And mix up a bit more.

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The One Ruler Obsession

I often teach undergraduate law & economics. Sometimes the first paper I assign is to suggest property rules to deal with conflicts regarding asteroids, orbits, and sunlight in the solar system, in the future when there’s substantial activity out there. This feels to students like a complex different situation, and in fact few understand even the basic issues.

Given just two pages to make their case, a large fraction of students (~1/3?) express fear that one person or organization will take over the entire solar system, unless property rules are designed to explicitly prevent that. And a similar fraction suggest the “property rule” of having a single government agency answer all questions. Whatever question or dispute you have, fill out a form, and the agency will decide.

Yet in my lectures I talk a lot about concepts and issues of property rights, but never mention government agency issues or scenarios, nor the scenario of one power taking over everything. And econ undergrads at my school are famous for being relatively libertarian.

I conclude that most people have a strong innate fear of power concentrations, and yet also see the creation of a single central power as an attractive general solution to complicated problems. I’ve seen the same sort of thing with a great many futuristic tech and policy issues. Whatever the question, if it seems complicated, most people are concerned about inequality, especially that it might be taken to the max, and yet they also like the idea of creating a central government-like power to deal with it.

I’ve certainly seen this in concerns about future rampaging robots (= “AI risk”). Many, perhaps most, people express concerns that one AI could take over everything, and many also like the “solution” of one good AI taking over everything.

I recently came across similar reasoning by Frederick Engels back in 1844, in his Outlines of a Critique of Political Economy. Having seen the early industrial revolution, not understanding it well, but fearing where it might lead, Engels claims that the natural outcome is extreme concentration of power. And his solution is to create a different central power (e.g., communism). Of course while there was some increase in inequality and concentration, it wasn’t remotely as bad as Engels feared, except where his words helped to inspire the creation of such concentration. Here is Engels:

Thus, competition sets capital against capital, labour against labour, landed property against landed property; and likewise each of these elements against the other two. In the struggle the stronger wins; and in order to predict the outcome of the struggle, we shall have to investigate the strength of the contestants. First of all, labour is weaker than either landed property or capital, for the worker must work to live, whilst the landowner can live on his rent, and the capitalist on his interest, or, if the need arises, on his capital or on capitalised property in land. The result is that only the very barest necessities, the mere means of subsistence, fall to the lot of labour; whilst the largest part of the products is shared between capital and landed property. Moreover, the stronger worker drives the weaker out of the market, just as larger capital drives out smaller capital, and larger landed property drives out smaller landed property. Practice confirms this conclusion. The advantages which the larger manufacturer and merchant enjoy over the smaller, and the big landowner over the owner of a single acre, are well known. The result is that already under ordinary conditions, in accordance with the law of the stronger, large capital and large landed property swallow small capital and small landed property – i.e., centralisation of property. In crises of trade and agriculture, this centralisation proceeds much more rapidly.

In general large property increases much more rapidly than small property, since a much smaller portion is deducted from its proceeds as property-expenses. This law of the centralisation of private property is as immanent in private property as all the others. The middle classes must increasingly disappear until the world is divided into millionaires and paupers, into large landowners and poor farm labourers. All the laws, all the dividing of landed property, all the possible splitting-up of capital, are of no avail: this result must and will come, unless it is anticipated by a total transformation of social conditions, a fusion of opposed interests, an abolition of private property.

Free competition, the keyword of our present-day economists, is an impossibility. Monopoly at least intended to protect the consumer against fraud, even if it could not in fact do so. The abolition of monopoly, however, opens the door wide to fraud. You say that competition carries with it the remedy for fraud, since no one will buy bad articles. But that means that everyone has to be an expert in every article, which is impossible. Hence the necessity for monopoly, which many articles in fact reveal. Pharmacies, etc., must have a monopoly. And the most important article – money – requires a monopoly most of all. Whenever the circulating medium has ceased to be a state monopoly it has invariably produced a trade crisis; and the English economists, Dr. Wade among them, do concede in this case the necessity for monopoly. But monopoly is no protection against counterfeit money. One can take one’s stand on either side of the question: the one is as difficult as the other. Monopoly produces free competition, and the latter, in turn, produces monopoly. Therefore both must fall, and these difficulties must be resolved through the transcendence of the principle which gives rise to them. (more)

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Boost For Being Best

The fraction of a normal distribution that is six or more standard deviations above the mean is one in ten billion. But the world has almost eight billion people in it. So in principle we should be able to get six standard deviations in performance gain by selecting the world’s best person at something, compared to using an average person.

I’m revising Age of Em for a paperback edition, expected in April. The rest of this post is from a draft of new text elaborating that point, and its implication for em leisure:

Em workers also earn wage premiums when they are the very best in the world at what they do. Even under the most severe wage competition, a best em can earn an extra wage equal to the difference between their productivity and the productivity of the second best em. When clans coordinate internally on wage negotiations, this is the difference in productivity between clans. (Clans who can’t coordinate internally are selected out of the em world, as they don’t cover their fixed costs, such as for training and marketing.)

Out of 10 billion independently and normally distributed (IID) samples, the maximum is on average about 6.4 standard deviations above the mean. Average spacings between the second, third, fourth highest samples are roughly 0.147, 0.075, and 0.05 standard deviations respectively (Branwen 2017). So when ems are selected out of 10 billion humans, the best em clan may be this much better than other em clans on normally distributed parameters. Using the log-normal wage distribution observed in our world (Provenzano 2015), this predicts that the best human in the world at any particular task is four to five times more productive than the median person, is over three percent more productive than the second most productive person, and is five percent more productive than the third most productive person.

If em clan relative productivity is drawn from this same distribution, if maximum em productivity comes at a 70 hour workweek, and if the best and second best em clans do not coordinate on wages they accept, then even under the strongest wage competition between clans, the best clan could take an extra 20 minutes a day more leisure, or two minutes per work hour, in addition to the six minutes per hour and other work breaks they take to be maximally productive.

This 20 minute figure is an underestimate for four reasons. First, the effective sample size of ems is smaller due to age limits on desirable ems. Second, most parameters are distributed so that the tails are thicker than in the normal distribution (Reed and Jorgensen 2004).

Third, differing wealth effects may add to differing productivity effects. On average over the last 11 years, the five richest people on Earth have each been about 10 percent richer than the next richest person. If future em income ratios were like this current wealth ratio, then the best em worker could afford roughly an extra hour per day of leisure, or an additional six minutes per hour.

Fourth, competition probably does not take the strongest possible form, and the best few ems can probably coordinate to some extent. For example, if the best two em clans coordinate completely on wages, but compete strongly with the third best clan, then instead of the best and second best taking 20 and zero minutes of extra leisure per day, they could take 30 and 10 extra minutes, respectively.

Plausibly then, the best em workers can afford to take an additional two to six minutes of leisure per hour of work in a ten hour work day, in addition to the over six minutes per hour of break needed for maximum productivity.

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Baum on Age of Em

In the Journal Futures, Seth Baum gives the first academic review of Age of Em. First, some words of praise: Continue reading "Baum on Age of Em" »

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Big Software Firm Bleg

I haven’t yet posted much on AI as Software. But now I’ll say more, as I want to ask a question.

Someday ems may replace humans in most jobs, and my first book talks about how that might change many things. But whether or not ems are the first kind of software to replace humans wholesale in jobs, eventually non-em software may plausibly do this. Such software would replace ems if ems came first, but if not then such software would directly replace humans.

Many people suggest, implicitly or explicitly, that non-em software that takes over most jobs will differ in big ways from the software that we’ve seen over the last seventy years. But they are rarely clear on what exact differences they foresee. So the plan of my project is to just assume our past software experience is a good guide to future software. That is, to predict the future, one may 1) assume current distributions of software features will continue, or 2) project past feature trends into future changes, or 3) combine past software feature correlations with other ways we expect the future to differ.

This effort may encourage others to better clarify how they think future software will differ, and help us to estimate the consequences of such assumptions. It may also help us to more directly understand a software-dominated future, if there are many ways that future software won’t greatly change.

Today, each industry makes a kind of stuff (product or service) we want, or a kind of stuff that helps other industries to make stuff. But while such industries are often dominated by a small number of firms, the economy as a whole is not so dominated. This is mainly because there are so many different industries, and firms suffer when they try to participate in too many industries. Will this lack of concentration continue into a software dominated future?

Today each industry gets a lot of help from humans, and each industry helps to train its humans to better help that industry. In addition, a few special industries, such as schooling and parenting, change humans in more general ways, to help better in a wide range of industries. In a software dominated future, humans are replaced by software, and the schooling and parenting industries are replaced by a general software industry. Industry-independent development of software would happen in the general software industry, while specific adaptations for particular industries would happen within those industries.

If so, the new degree of producer concentration depends on two key factors: what fraction of software development is general as opposed to industry-specific, and how concentrated is this general software industry. Regarding this second factor, it is noteworthy that we now see some pretty big players in the software industry, such as Google, Apple, and Microsoft. And so a key question is the source of this concentration. That is, what exactly are the key advantages of big firms in today’s software market?

There are many possibilities, including patent pools and network effects among customers of key products. Another possibility, however, is one where I expect many of my readers to have relevant personal experience: scale economies in software production. Hence this bleg – a blog post asking a question.

If you are an experienced software professional who has worked both at a big software firm and also in other places, my key question for you is: by how much was your productive efficiency as a software developer increased (or decreased) due to working at a big software firm?  That is, how much more could you get done there that wasn’t attributable to having a bigger budget to do more, or to paying more for better people, tools, or resources. Instead, I’m looking for the net increase (or decrease) in your output due to software tools, resources, security, oversight, rules, or collaborators that are more feasible and hence more common at larger firms. Ideally you answer will be in the form of a percentage, such as “I seem to be 10% more productive working at a big software firm.”

Added 3:45p: I meant “productivity” in the economic sense of the inputs required to produce a given output, holding constant the specific kind of output produced. So this kind of productivity should ignore the number of users of the software, and the revenue gained per user. But if big vs small firms tend to make different kinds of software, which have different costs to make, those differences should be taken into account. For example, one should correct for needing more man-hours to add a line of code in a larger system, or in a more secure or reliable system.

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The Elephant in the Brain

One of the most frustrating things about writing physical books is the long time delays. It has been 17 months since I mentioned my upcoming book here, and now, 8.5 months after we submitted the full book for review, & over 4 months after 7 out of 7 referees said “great book, as it is”, I can finally announce that The Elephant in the Brain: Hidden Motives in Everyday Life, coauthored with Kevin Simler, will officially be published January 1, 2018. Sigh. See summary & detailed outline at the book’s website.

A related sad fact is that the usual book publicity equilibrium adds to intellectual inequality. Since most readers want to read books about which they’ve heard much publicity lately from multiple sources, publishers try to concentrate publicity into a narrow time period around the official publication date. Which makes sense.

But to create that burst of publicity, one must circulate the book well in advance privately among “thought leaders”, who might blurb or review it, invite the authors to talk on it, or recommend it to others who might do these things. So people who plausibly fit these descriptions get to read such books long before others. This lets early readers seem to be wise judges of future popular talk directions. Not because they actually have better judgement, but because they get inside info.

Alas, I’m stuck in this same equilibrium. I have a full copy of my final book, except for minor copy-editing changes, and I can share it privately with possible publicity helpers. And when the relative cost to send an email is small relative to possible gains, a small chance may be enough. I’ll also give in to some requests based on friendship or prior help given me (as on my last book), especially when combined with promises to buy the book when it comes out.

But just as grading is the worst part of teaching, I hate being put in the role of bouncer, deciding who is cool enough to be let into my book club, or who has enough favors to trade. At least when teaching I’m expert in whatever topic I’m grading. But here I’m much less expert on deciding who can help book publicity. I’d really prefer the intellectual world to be more of an open competition without favoritism for those with inside connections. But here I am, forced to play favorites.

These are a few of the prices one pays today to publish books. But still, books remain an unparalleled way to call attention to ideas that need more space to explain than an article can offer. And for a relatively unknown author, established publishers still offer more attention than you could generate on your own. But maybe, just maybe, I can do something different with my third book, whatever that may be on.

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Cycles of War & Empire

I’ve just read five of Peter Turchin’s books: Historical Dynamics (2003), War & Peace & War (2006), Secular Cycles (2009), Ultra Society (2015), and Ages of Discord (2016). Four of them in the last week. I did this because I love careful big picture thinking, and Turchin is one of the few who does this now on the big question of historical cycles of conflict and empire. While historians today tend to dislike this sort of analysis, Turchin defies them, in part because he’s officially a biologist. I bow to honor his just defiance and careful efforts.

Turchin’s main story is a modest variation on related farmer-era historical cycle stories, such as by Jack Goldstone in 1991, & Ibn Khaldun in 1377 (!):

Different groups have different degrees of cooperation .. cohesiveness and solidarity. .. Groups with high [cohesion] arise on .. frontier .. area where an imperial boundary coincides with a fault line between two [ethnic] communities .. places where between group competition is very intense. .. Only groups possessing high levels of [cohesion] can construct large empires. ..

Stability and internal peace bring prosperity, and prosperity causes population increase .. leads to overpopulation, .. causes lower wages, higher land rents, and falling per capital incomes. At first, low wages and high rents bring unparalleled wealth to the upper class, but as their numbers and appetites grow, they also begin to suffer from falling incomes. Declining standards of life breed discontent and strife. The elites turn to the state for employment and additional income and drive up its expenditures at the same time that the tax revenue declines. .. When the state’s finances collapse, it loses the control of the army and police. Freed from all restraints, strife among the elites escalates into civili war, while the discontent among the poor explodes into popular rebellions.

The collapse of order brings .. famine, war, pestilence, and death. .. Population declines and wages increase, while rents decline. .. Fortunes of the upper classes hit bottom. .. Civil wars thin the ranks of the elites. .. Intra-elite competition subsides, allowing the restoration of order. Stability and internal peace bring prosperity, and another cycle begins. (pp.5-8 W&P&W)

Turchin (& coauthor Nefedov) collect much data to show that this is a robust farmer-era pattern, even if there are many deviations. For example, in Europe, 33 of 43 frontier situations gave rise to big empires, yet only 4 of 57 of non-frontier situations did (p.84 HD). “Secular cycles” vary in duration from one to four centuries; Western Europe saw 8 cycles in 22 centuries, while China saw 8 cycles in 21 centuries (p.306,311 SC). During the low instability part of each cycle, instability shows a rough “alternating generations” 50 year cycle of conflict.

I’ll grant that Turchin seems to have documented a reasonably broad pattern, containing most of his claimed elements. Yes, empires tend to start from frontier groups with high cohesion, and core cohesion changes slowly. First there’s war success and a growing area and population, and bigger cities. Eventually can come crowding and falling wages. Inequality also grows, with more richer elites, and this is quite robust, continuing even after wages fall.

While the amount of external war doesn’t change over the cycle, success in war falls. Many signs of social cohesion decline, and eventually there’s more elite infighting, with crime, duels, misspending state revenue, mistreatment of subordinates, and eventually civil war. Big wars can cut population, and also elite numbers and wealth. Eventually war abates and cohesion rises, though not to as high as when the empire started. A new cycle may begin; empires go through 1-3 cycles before being displaced by another empire.

Just as science fiction is often (usually?) an allegory about issues today, I suspect that historians who blame a particular fault for the fall of the Roman Empire tend to pick faults that they also want to warn against in their own era. Similarly, my main complain about Turchin is that he attributes falling cohesion mainly to increased inequality – an “overproduction” of elites who face “increased competition”. Yes, inequality is much talked about among elites today, but the (less-forager-like) ancients were less focused on it.

As Scheidel said in The Great Leveler, inequality doesn’t seem to cause civil wars, and civil wars tend to increase inequality during and after the war (p.203). External wars reduce inequality for losers and increase it for winners, without changing it much overall. It is only big mass mobilization wars of the 1900s that seem to clearly cause big falls in inequality.

In biology, over multiple generations organisms slowly accumulate genetic mutations, which reduce their fitness. But this degradation is countered by the fact that nature and mates select for better organisms, which have fewer mutations. Similarly, it seems to me that the most straightforward account of the secular cycle is to say since empire founders are selected out of a strong competition for very high cohesion, we should expect cohesion to “regress to the mean” as an empire evolves.

That is, in order to predict most of the observed elite misdeeds later in the secular cycle, all we need to assume is a random walk in cohesion that tends to fall back to typical levels. Yes, we might want to include other effects in our model. For example, civil war may allow a bit more selection for subgroups with more cohesion, and humans may have a psychological inclination to cohere more during and after a big war. But mostly we should just expect cohesion to decline from its initial extreme value, and that’s all a simple model needs.

Yes, Turchin claims that we know more about what causes cohesion declines. But while he goes to great effort to show that the data fit his story on which events happen in what order during cycles, I didn’t see him offering evidence to support his claim that inequality causes less cohesion. He just repeatedly gives examples where inequality happened, and then instability happened, as if that proves that the one caused the other.

We already have good reasons to expect new empires to start with a small area, population, and inequality. And this by itself is enough to predict growing population, which eventually crowds to cut wages, and increasing inequality, which should happen consistently in a very wide range of situations. I don’t see a need for, or data support for, the additional hypothesis that inequality cuts cohesion. We may of course discover more things that influence cohesion, and if so we can add them to our basic secular cycle model. But we don’t need such additions to predict most of the cycle features that Turchin describes.

In his latest book, Turchin points out many U.S. signs today of rising inequality and declining social cohesion, and at the end asks “Will we be capable of taking collective action to avoid the worst of the impending democratic -structural crisis? I hope so.” But I worry that his focus on inequality leads people to think they need to fight harder to cut inequality. In contrast, what we mostly need is just to fight less. The main way that inequality threatens to destroy us is that we are tempted to fight over it. Instead, let us try more to see ourselves as an “us” contrasted with a “them”, an us that needs to stick together, in part via chilling and compromising, especially regarding divisive topics like inequality.

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Both Plague & War Cut Capital Share?

I just finished reading Walter Scheidel’s The Great Leveler: Violence and the History of Inequality from the Stone Age to the Twenty-First Century, and found myself agreeing with Scheidel against his critics. Scheidel is a historian who says that inequality has mainly risen in history when income increased, making more inequality physically possible, and when scale and complexity increased, creating more and bigger chokepoints (e.g., CEO, king) whose controllers can demand more rents.

Big falls in inequality have mainly come from big collapses, such as big wars, revolutions, plagues, and state collapses, which are usually associated with violence. This suggests that a big inequality fall is unlikely anytime soon, and we shouldn’t wish for it, as it would likely come from vast destruction and violence. All of which I find very plausible.

While usually big wars via mass mobilization didn’t change inequality much, in the mid 1900s such wars seemed to have gone along with a big taste for redistribution and revolution. This happened to a lesser extent in Ancient Greece and Rome, and fits a story wherein more forager-like cultures care more about redistribution, especially when primed by visible mass sacrifice.

I noticed one puzzling pattern, however. Income in the world goes to owners of capital, to owners of labor, and to those who can take without contributing to production. As the rich usually get more of their income from capital, compared to labor, one thing that can cause less inequality is a change that makes capital earn a smaller share of total income. The puzzling pattern I noticed is that even though big plagues and big wars should have opposite affects on the capital share, both of them seem to have cut inequality, and both apparently in part via cutting the capital share of income! Let me explain.

Big plagues cut the number of workers without doing much to capital, while big wars like WWI & WWII destroy a much larger fraction of capital than they do of labor. Which event, big plague or big war, reduces the share that capital earns? The answer depends on whether capital and labor are complements or substitutes. If they are substitutes, then destroying capital should cut the capital share of income. But when they are complements, it is destroying labor that should cut the capital share.

The simple middle position between complements and substitutes is the power law (a.k.a. “Cobb-Douglas”) production function, where output Y = La*K1-a, for Labor L, capital K, and constant a in (0,1). (Partial derivatives set wages w = dY/dL and capital rent r = dY/dK.) In this situation, the capital share of income r*K/(r*K+w*L) = 1-a, and so never changes.

If, for example, labor L falls by a factor of 2, while capital K stays the same, then wages rise by the factor 21-a while rents fall by the factor 2a, with the product of these factors being 2. Compared to this simple middle position, if labor and capital are instead complements, then in this example wages would rise and rents would fall by larger factors. If labor and capital are instead substitutes, the factors would be smaller.

Economic papers based on data over the last century usually find labor and capital to be complements, though there are notable exceptions such as Thomas Pietty’s blockbuster book. That fits with data on the Black Death. In the century from 1330 to 1430, Europe’s population fell roughly in half, wages doubled, and rents fell a lot. In England, wages tripled. Similar behavior is seen in other large ancient plagues – wages rose by a factor of four in Mexico! This looks more like what you’d see with complementarity than with a simple power law.

World War I (WWI) killed about 1% of the world population, while the concurrent 1918 flu killed about 4%. World War II (WWII) killed about 3%. But capital was cut much more. The ratio of private wealth to national income fell by a factor of two world wide, and by even larger factors in the main warring nations (source):
WealthToIncomeNow for the puzzle. If capital and labor were still complements during WWI & WWII, then destroying a lot more capital than labor should have resulted in rents on capital rising by a factor so big that product of the two factors increases the capital share of income. Is that what happened? Consider Japan, where 5% of the population died:

Real [Japanese] farm rents fell by four-fifths between 1941 and 1945, and from 4.4% of national income in the mid 1930s to 0.3% in 1946. .. By September 1945, a quarter of the country’s physical capital stock had been wiped out. Japan lost 80% of its merchant ships, 25% of all buildings, 21% of household furnishings and personal effects, 34% of factory equipment, and 24% of finished products. The number of factories in operations and the size of the workforce they employed nearly halved during the final year of the war. p.121

Gains from capital almost disappeared during the war years: the share of rent and interest income in total national income fell from a sixth in the mid-1930s to only 3% in 1946. In 1938, dividends, interest, and rental income together had accounted for about a third of the income of the top 1%, with the remainder divided between business and employment income. By 1945, the share of capital income had dropped to less than an eighth and that of wages to a tenth; business income was the only significant revenue source left to the (formerly) wealthy. p.122

In 1946, real GNP was 45% lower than it had been in 1937. p.124

The sharp drop in top income shares .. were caused above all by a decline in the return on capital. .. Most of these changes occurred during the war itself. p.128

Consider also France and Germany (which lost 2% & 11% of people in WWII, respectively):

During WWI, .. a third of the French capital stock was destroyed, the share of capital income in national household income fell by a third, and GDP contracted by the same proportion. ..In WWII, .. two-thirds of the capital stock was wiped out. .. real rents fell by 90% between 1913 and 1950. p.147

[German] rentiers lost the most: their share of national income plummeted from 15% to 3% even as entrepreneurs were able to maintain their share .. real national income was a quarter to a third lower in 1923 than it had been in 1913. p.152

Maybe I’m missing something, but I don’t see how this is remotely consistent with labor and capital being complements. Yet complementarity seems a good fit to big ancient plagues and more recent empirical studies. What gives?

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