cooperation

The evolution of human cooperation

pnrj cognitive science, core principles, tribal paradigm , , , , , , ,

Jun 17 JDN 2458287

If alien lifeforms were observing humans (assuming they didn’t turn out the same way—which they actually might, for reasons I’ll get to shortly), the thing that would probably baffle them the most about us is how we organize ourselves into groups. Each individual may be part of several groups at once, and some groups are closer-knit than others; but the most tightly-knit groups exhibit extremely high levels of cooperation, coordination, and self-sacrifice.

They might think at first that we are eusocial, like ants or bees; but upon closer study they would see that our groups are not very strongly correlated with genetic relatedness. We are somewhat more closely related to those in our groups than to those outsides, usually; but it’s a remarkably weak effect, especially compared to the extremely high relatedness of worker bees in a hive. No, to a first approximation, these groups are of unrelated humans; yet their level of cooperation is equal to if not greater than that exhibited by the worker bees.

However, the alien anthropologists would find that it is not that humans are simply predisposed toward extremely high altruism and cooperation in general; when two humans groups come into conflict, they are capable of the most extreme forms of violence imaginable. Human history is full of atrocities that combine the indifferent brutality of nature red in tooth and claw with the boundless ingenuity of a technologically advanced species. Yet except for a small proportion perpetrated by individual humans with some sort of mental pathology, these atrocities are invariably committed by one unified group against another. Even in genocide there is cooperation.

Humans are not entirely selfish. But nor are they paragons of universal altruism (though some of them aspire to be). Humans engage in a highly selective form of altruism—virtually boundless for the in-group, almost negligible for the out-group. Humans are tribal.

Being a human yourself, this probably doesn’t strike you as particularly strange. Indeed, I’ve mentioned it many times previously on this blog. But it is actually quite strange, from an evolutionary perspective; most organisms are not like this.

As I said earlier, there is actually reason to think that our alien anthropologist would come from a species with similar traits, simply because such cooperation may be necessary to achieve a full-scale technological civilization, let alone the capacity for interstellar travel. But there might be other possibilities; perhaps they come from a eusocial species, and their large-scale cooperation is within an extremely large hive.

It’s true that most organisms are not entirely selfish. There are various forms of cooperation within and even across species. But these usually involve only close kin, and otherwise involve highly stable arrangements of mutual benefit. There is nothing like the large-scale cooperation between anonymous unrelated individuals that is exhibited by all human societies.

How would such an unusual trait evolve? It must require a very particular set of circumstances, since it only seems to have evolved in a single species (or at most a handful of species, since other primates and cetaceans display some of the same characteristics).

Once evolved, this trait is clearly advantageous; indeed it turned a local apex predator into a species so successful that it can actually intentionally control the evolution of other species. Humans have become a hegemon over the entire global ecology, for better or for worse. Cooperation gave us a level of efficiency in producing the necessities of survival so great that at this point most of us spend our time working on completely different tasks. If you are not a farmer or a hunter or a carpenter (and frankly, even if you are a farmer with a tractor, a hunter with a rifle, or a carpenter with a table saw), you are doing work that would simply not have been possible without very large-scale human cooperation.

This extremely high fitness benefit only makes the matter more puzzling, however: If the benefits are so great, why don’t more species do this? There must be some other requirements that other species were unable to meet.

One clear requirement is high intelligence. As frustrating as it may be to be a human and watch other humans kill each other over foolish grievances, this is actually evidence of how smart humans are, biologically speaking. We might wish we were even smarter still—but most species don’t have the intelligence to make it even as far as we have.

But high intelligence is likely not sufficient. We can’t be sure of that, since we haven’t encountered any other species with equal intelligence; but what we do know is that even Homo sapiens didn’t coordinate on anything like our current scale for tens of thousands of years. We may have had tribal instincts, but if so they were largely confined to a very small scale. Something happened, about 50,000 years ago or so—not very long ago in evolutionary time—that allowed us to increase that scale dramatically.

Was this a genetic change? It’s difficult to say. There could have been some subtle genetic mutation, something that wouldn’t show up in the fossil record. But more recent expansions in human cooperation to the level of the nation-state and beyond clearly can’t be genetic; they were much too fast for that. They must be a form of cultural evolution: The replicators being spread are ideas and norms—memes—rather than genes.

So perhaps the very early shift toward tribal cooperation was also a cultural one. Perhaps it began not as a genetic mutation but as an idea—perhaps a metaphor of “universal brotherhood” as we often still hear today. The tribes that believed this ideas prospered; the tribes that didn’t were outcompeted or even directly destroyed.

This would explain why it had to be an intelligent species. We needed brains big enough to comprehend metaphors and generalize concepts. We needed enough social cognition to keep track of who was in the in-group and who was in the out-group.

If it was indeed a cultural shift, this should encourage us. (And since the most recent changes definitely were cultural, that is already quite encouraging.) We are not limited by our DNA to only care about a small group of close kin; we are capable of expanding our scale of unity and cooperation far beyond.
The real question is whether we can expand it to everyone. Unfortunately, there is some reason to think that this may not be possible. If our concept of tribal identity inherently requires both an in-group and an out-group, then we may never be able to include everyone. If we are only unified against an enemy, never simply for our own prosperity, world peace may forever remain a dream.

But I do have a work-around that I think is worth considering. Can we expand our concept of the out-group to include abstract concepts? With phrases like “The War on Poverty” and “The War on Terror”, it would seem in fact that we can. It feels awkward; it is somewhat imprecise—but then, so was the original metaphor of “universal brotherhood”. Our brains are flexible enough that they don’t actually seem to need the enemy to be a person; it can also be an idea. If this is right, then we can actually include everyone in our in-group, as long as we define the right abstract out-group. We can choose enemies like poverty, violence, cruelty, and despair instead of other nations or ethnic groups. If we must continue to fight a battle, let it be a battle against the pitiless indifference of the universe, rather than our fellow human beings.

Of course, the real challenge will be getting people to change their existing tribal identities. In the moment, these identities seem fundamentally intractable. But that can’t really be the case—for these identities have changed over historical time. Once-important categories have disappeared; new ones have arisen in their place. Someone in 4th century Constantinople would find the conflict between Democrats and Republicans as baffling as we would find the conflict between Trinitarians and Arians. The ongoing oppression of Native American people by White people would be unfathomable to someone of the 11th century Onondaga, who could scarcely imagine an enemy more different than the Seneca west of them. Even the conflict between Russia and NATO would probably seem strange to someone living in France in 1943, for whom Germany was the enemy and Russia was at least the enemy of the enemy—and many of those people are still alive.

I don’t know exactly how these tribal identities change (I’m working on it). It clearly isn’t as simple as convincing people with rational arguments. In fact, part of how it seems to work is that someone will shift their identity slowly enough that they can’t perceive the shift themselves. People rarely seem to appreciate, much less admit, how much their own minds have changed over time. So don’t ever expect to change someone’s identity in one sitting. Don’t even expect to do it in one year. But never forget that identities do change, even within an individual’s lifetime.

Reasonableness and public goods games

pnrj cognitive science, critique of neoclassical economics, experimental economics, heuristics and biases , , , , , , , ,

Apr 1 JDN 2458210

There’s a very common economics experiment called a public goods game, often used to study cooperation and altruistic behavior. I’m actually planning on running a variant of such an experiment for my second-year paper.

The game is quite simple, which is part of why it is used so frequently: You are placed into a group of people (usually about four), and given a little bit of money (say $10). Then you are offered a choice: You can keep the money, or you can donate some of it to a group fund. Money in the group fund will be multiplied by some factor (usually about two) and then redistributed evenly to everyone in the group. So for example if you donate $5, that will become $10, split four ways, so you’ll get back $2.50.

Donating more to the group will benefit everyone else, but at a cost to yourself. The game is usually set up so that the best outcome for everyone is if everyone donates the maximum amount, but the best outcome for you, holding everyone else’s choices constant, is to donate nothing and keep it all.

Yet it is a very robust finding that most people do neither of those things. There’s still a good deal of uncertainty surrounding what motivates people to donate what they do, but certain patterns that have emerged:

  1. Most people donate something, but hardly anyone donates everything.
  2. Increasing the multiplier tends to smoothly increase how much people donate.
  3. The number of people in the group isn’t very important, though very small groups (e.g. 2) behave differently from very large groups (e.g. 50).
  4. Letting people talk to each other tends to increase the rate of donations.
  5. Repetition of the game, or experience from previous games, tends to result in decreasing donation over time.
  6. Economists donate less than other people.

Number 6 is unfortunate, but easy to explain: Indoctrination into game theory and neoclassical economics has taught economists that selfish behavior is efficient and optimal, so they behave selfishly.

Number 3 is also fairly easy to explain: Very small groups allow opportunities for punishment and coordination that don’t exist in large groups. Think about how you would respond when faced with 2 defectors in a group of 4 as opposed to 10 defectors in a group of 50. You could punish the 2 by giving less next round; but punishing the 10 would end up punishing 40 others who had contributed like they were supposed to.

Number 4 is a very interesting finding. Game theory says that communication shouldn’t matter, because there is a unique Nash equilibrium: Donate nothing. All the promises in the world can’t change what is the optimal response in the game. But in fact, human beings don’t like to break their promises, and so when you get a bunch of people together and they all agree to donate, most of them will carry through on that agreement most of the time.

Number 5 is on the frontier of research right now. There are various theoretical accounts for why it might occur, but none of the models proposed so far have much predictive power.

But my focus today will be on findings 1 and 2.

If you’re not familiar with the underlying game theory, finding 2 may seem obvious to you: Well, of course if you increase the payoff for donating, people will donate more! It’s precisely that sense of obviousness which I am going to appeal to in a moment.

In fact, the game theory makes a very sharp prediction: For N players, if the multiplier is less than N, you should always contribute nothing. Only if the multiplier becomes larger than N should you donate—and at that point you should donate everything. The game theory prediction is not a smooth increase; it’s all-or-nothing. The only time game theory predicts intermediate amounts is on the knife-edge at exactly equal to N, where each player would be indifferent between donating and not donating.

But it feels reasonable that increasing the multiplier should increase donation, doesn’t it? It’s a “safer bet” in some sense to donate $1 if the payoff to everyone is $3 and the payoff to yourself is $0.75 than if the payoff to everyone is $1.04 and the payoff to yourself is $0.26. The cost-benefit analysis comes out better: In the former case, you can gain up to $2 if everyone donates, but would only lose $0.25 if you donate alone; but in the latter case, you would only gain $0.04 if everyone donates, and would lose $0.74 if you donate alone.

I think this notion of “reasonableness” is a deep principle that underlies a great deal of human thought. This is something that is sorely lacking from artificial intelligence: The same AI that tells you the precise width of the English Channel to the nearest foot may also tell you that the Earth is 14 feet in diameter, because the former was in its database and the latter wasn’t. Yes, WATSON may have won on Jeopardy, but it (he?) also made a nonsensical response to the Final Jeopardy question.

Human beings like to “sanity-check” our results against prior knowledge, making sure that everything fits together. And, of particular note for public goods games, human beings like to “hedge our bets”; we don’t like to over-commit to a single belief in the face of uncertainty.

I think this is what best explains findings 1 and 2. We don’t donate everything, because that requires committing totally to the belief that contributing is always better. We also don’t donate nothing, because that requires committing totally to the belief that contributing is always worse.

And of course we donate more as the payoffs to donating more increase; that also just seems reasonable. If something is better, you do more of it!

These choices could be modeled formally by assigning some sort of probability distribution over other’s choices, but in a rather unconventional way. We can’t simply assume that other people will randomly choose some decision and then optimize accordingly—that just gives you back the game theory prediction. We have to assume that our behavior and the behavior of others is in some sense correlated; if we decide to donate, we reason that others are more likely to donate as well.

Stated like that, this sounds irrational; some economists have taken to calling it “magical thinking”. Yet, as I always like to point out to such economists: On average, people who do that make more money in the games. Economists playing other economists always make very little money in these games, because they turn on each other immediately. So who is “irrational” now?

Indeed, if you ask people to predict how others will behave in these games, they generally do better than the game theory prediction: They say, correctly, that some people will give nothing, most will give something, and hardly any will give everything. The same “reasonableness” that they use to motivate their own decisions, they also accurately apply to forecasting the decisions of others.

Of course, to say that something is “reasonable” may be ultimately to say that it conforms to our heuristics well. To really have a theory, I need to specify exactly what those heuristics are.

“Don’t put all your eggs in one basket” seems to be one, but it’s probably not the only one that matters; my guess is that there are circumstances in which people would actually choose all-or-nothing, like if we said that the multiplier was 0.5 (so everyone giving to the group would make everyone worse off) or 10 (so that giving to the group makes you and everyone else way better off).

“Higher payoffs are better” is probably one as well, but precisely formulating that is actually surprisingly difficult. Higher payoffs for you? For the group? Conditional on what? Do you hold others’ behavior constant, or assume it is somehow affected by your own choices?

And of course, the theory wouldn’t be much good if it only worked on public goods games (though even that would be a substantial advance at this point). We want a theory that explains a broad class of human behavior; we can start with simple economics experiments, but ultimately we want to extend it to real-world choices.

When are we going to get serious about climate change?

pnrj development economics, futurism, market failure, public policy , , , , , , , , , , , , , , ,

Oct 8, JDN 24578035

Those two storms weren’t simply natural phenomena. We had a hand in creating them.

The EPA doesn’t want to talk about the connection, and we don’t have enough statistical power to really be certain, but there is by now an overwhelming scientific consensus that global climate change will increase hurricane intensity. The only real question left is whether it is already doing so.

The good news is that global carbon emissions are no longer rising. They have been essentially static for the last few years. The bad news is that this is almost certainly too little, too late.

The US is not on track to hit our 2025 emission target; we will probably exceed it by at least 20%.

But the real problem is that the targets themselves are much too high. Most countries have pledged to drop emissions only about 8-10% below their 1990s levels.

Even with the progress we have made, we are on track to exceed the global carbon budget needed to keep warming below 2 C by the year 2040. We have been reducing emission intensity by about 0.8% per year—we need to be reducing it by at least 3% per year and preferably faster. Highly-developed nations should be switching to nuclear energy as quickly as possible; an equitable global emission target requires us to reduce our emissions by 80% by 2050.

At the current rate of improvement, we will overshoot the 2 C warming target and very likely the 3C target as well.

Why aren’t we doing better? There is of course the Tragedy of the Commons to consider: Each individual country acting in its own self-interest will continue to pollute more, as this is the cheapest and easiest way to maintain industrial development. But then if all countries do so, the result is a disaster for us all.
But this explanation is too simple. We have managed to achieve some international cooperation on this issue. The Kyoto protocol has worked; emissions among Kyoto member nations have been reduced by more than 20% below 1990 levels, far more than originally promised. The EU in particular has taken a leadership role in reducing emissions, and has a serious shot at hitting their target of 40% reduction by 2030.

That is a truly astonishing scale of cooperation; the EU has a population of over 500 million people and spans 28 nations. It would seem like doing that should get us halfway to cooperating across all nations and all the world’s people.

But there is a vital difference between the EU and the world as a whole: The tribal paradigm. Europeans certainly have their differences: The UK and France still don’t really get along, everyone’s bitter with Germany about that whole Hitler business, and as the acronym PIIGS emphasizes, the peripheral countries have never quite felt as European as the core Schengen members. But despite all this, there has been a basic sense of trans-national (meta-national?) unity among Europeans for a long time.
For one thing, today Europeans see each other as the same race. That wasn’t always the case. In Medieval times, ethnic categories were as fine as “Cornish” and “Liverpudlian”. (To be fair, there do still exist a handful of Cornish nationalists.) Starting around the 18th cenutry, Europeans began to unite under the heading of “White people”, a classification that took on particular significance during the trans-Atlantic slave trade. But even in the 19th century, “Irish” and “Sicilian” were seen as racial categories. It wasn’t until the 20th century that Europeans really began to think of themselves as one “kind of people”, and not coincidentally it was at the end of the 20th century that the European Union finally took hold.

There is another region that has had a similar sense of unification: Latin America. Again, there are conflicts: There are a lot of nasty stereotypes about Puerto Ricans among Cubans and vice-versa. But Latinos, by and large, think of each other as the same “kind of people”, distinct from both Europeans and the indigenous population of the Americas.

I don’t think it is coincidental that the lowest carbon emission intensity (carbon emissions / GDP PPP) in the world is in Latin America, followed closely by Europe.
And if you had to name right now the most ethnically divided region in the world, what would you say? The Middle East, of course. And sure enough, they have the worst carbon emission intensity. (Of course, oil is an obvious confounding variable here, likely contributing to both.)

Indeed, the countries with the lowest ethnic fractionalization ratings tend to be in Europe and Latin America, and the highest tend to be in the Middle East and Africa.

Even within the United States, political polarization seems to come with higher carbon emissions. When we think of Democrats and Republicans as different “kinds of people”, we become less willing to cooperate on finding climate policy solutions.

This is not a complete explanation, of course. China has a low fractionalization rating but a high carbon intensity, and extremely high overall carbon emissions due to their enormous population. Africa’s carbon intensity isn’t as high as you’d think just from their terrible fractionalization, especially if you exclude Nigeria which is a major oil producer.

But I think there is nonetheless a vital truth here: One of the central barriers to serious long-term solutions to climate change is the entrenchment of racial and national identity. Solving the Tragedy of the Commons requires cooperation, we will only cooperate with those we trust, and we will only trust those we consider to be the same “kind of people”.

You can even hear it in the rhetoric: If “we” (Americans) give up our carbon emissions, then “they” (China) will take advantage of us. No one seems to worry about Alabama exploiting California—certainly no Republican would—despite the fact that in real economic terms they basically do. But people in Alabama are Americans; in other words, they count as actual people. People in China don’t count. If anything, people in California are supposed to be considered less American than people in Alabama, despite the fact that vastly more Americans live in California than Alabama. This mirrors the same pattern where we urban residents are somehow “less authentic” even though we outnumber the rural by four to one.
I don’t know how to mend this tribal division; I very much wish I did. But I do know that simply ignoring it isn’t going to work. We can talk all we want about carbon taxes and cap-and-trade, but as long as most of the world’s people are divided into racial, ethnic, and national identities that they consider to be in zero-sum conflict with one another, we are never going to achieve the level of cooperation necessary for a real permanent solution to climate change.

The temperatures and the oceans rise. United we must stand, or divided we shall fall.

Happy Capybara Day! Or the power of culture

pnrj cognitive science, core principles, critique of neoclassical economics , , , , , , , , , , , ,

JDN 2457131 EDT 14:33.

Did you celebrate Capybara Day yesterday? You didn’t? Why not? We weren’t able to find any actual capybaras this year, but maybe next year we’ll be able to plan better and find a capybara at a zoo; unfortunately the nearest zoo with a capybara appears to be in Maryland. But where would we be without a capybara to consult annually on the stock market?

Right now you are probably rather confused, perhaps wondering if I’ve gone completely insane. This is because Capybara Day is a holiday of my own invention, one which only a handful of people have even heard about.

But if you think we’d never have a holiday so bizarre, think again: For all I did was make some slight modifications to Groundhog Day. Instead of consulting a groundhog about the weather every February 2, I proposed that we consult a capybara about the stock market every April 17. And if you think you have some reason why groundhogs are better at predicting the weather (perhaps because they at least have some vague notion of what weather is) than capybaras are at predicting the stock market (since they have no concept of money or numbers), think about this: Capybara Day could produce extremely accurate predictions, provided only that people actually believed it. The prophecy of rising or falling stock prices could very easily become self-fulfilling. If it were a cultural habit of ours to consult capybaras about the stock market, capybaras would become good predictors of the stock market.

That might seem a bit far-fetched, but think about this: Why is there a January Effect? (To be fair, some researchers argue that there isn’t, and the apparent correlation between higher stock prices and the month of January is simply an illusion, perhaps the result of data overfitting.)

But I think it probably is real, and moreover has some very obvious reasons behind it. In this I’m in agreement with Richard Thaler, a founder of cognitive economics who wrote about such anomalies in the 1980s. December is a time when two very culturally-important events occur: The end of the year, during which many contracts end, profits are assessed, and tax liabilities are determined; and Christmas, the greatest surge of consumer spending and consumer debt.

The first effect means that corporations are very likely to liquidate assets—particularly assets that are running at a loss—in order to minimize their tax liabilities for the year, which will drive down prices. The second effect means that consumers are in search of financing for extravagant gift purchases, and those who don’t run up credit cards may instead sell off stocks. This is if anything a more rational way of dealing with the credit constraint, since interest rates on credit cards are typically far in excess of stock returns. But this surge of selling due to credit constraints further depresses prices.

In January, things return to normal; assets are repurchased, debt is repaid. This brings prices back up to where they were, which results in a higher than normal return for January.

Neoclassical economists are loath to admit that such a seasonal effect could exist, because it violates their concept of how markets work—and to be fair, the January Effect is actually weak enough to be somewhat ambiguous. But actually it doesn’t take much deviation from neoclassical models to explain the effect: Tax policies and credit constraints are basically enough to do it, so you don’t even need to go that far into understanding human behavior. It’s perfectly rational to behave this way given the distortions that are created by taxes and credit limits, and the arbitrage opportunity is one that you can only take advantage of if you have large amounts of credit and aren’t worried about minimizing your tax liabilities. It’s important to remember just how strong the assumptions of models like CAPM truly are; in addition to the usual infinite identical psychopaths, CAPM assumes there are no taxes, no transaction costs, and unlimited access to credit. I’d say it’s amazing that it works at all, but actually, it doesn’t—check out this graph of risk versus return and tell me if you think CAPM is actually giving us any information at all about how stock markets behave. It frankly looks like you could have drawn a random line through a scatter plot and gotten just as good a fit. Knowing how strong its assumptions are, we would not expect CAPM to work—and sure enough, it doesn’t.

Of course, that leaves the question of why our tax policy would be structured in this way—why make the year end on December 31 instead of some other date? And for that, you need to go back through hundreds of years of history, the Gregorian calendar, which in turn was influenced by Christianity, and before that the Julian calendar—in other words, culture.

Culture is one of the most powerful forces that influences human behavior—and also one of the strangest and least-understood. Economic theory is basically silent on the matter of culture. Typically it is ignored entirely, assumed to be irrelevant against the economic incentives that are the true drivers of human action. (There’s a peculiar emotion many neoclassical economists express that I can best describe as self-righteous cynicism, the attitude that we alone—i.e., economists—understand that human beings are not the noble and altruistic creatures many imagine us to be, nor beings of art and culture, but simply cold, calculating machines whose true motives are reducible to profit incentives—and all who think otherwise are being foolish and naïve; true enlightenment is understanding that human beings are infinite identical psychopaths. This is the attitude epitomized by the economist who once sent me an email with “altruism” written in scare quotes.)

Occasionally culture will be invoked as an external (in jargon, exogenous) force, to explain some aspect of human behavior that is otherwise so totally irrational that even invoking nonsensical preferences won’t make it go away. When a suicide bomber blows himself up in a crowd of people, it’s really pretty hard to explain that in terms of rational profit incentives—though I have seen it tried. (It could be self-interest at a larger scale, like families or nations—but then, isn’t that just the tribal paradigm I’ve been arguing for all along?)

But culture doesn’t just motivate us to do extreme or wildly irrational things. It motivates us all the time, often in quite beneficial ways; we wait in line, hold doors for people walking behind us, tip waiters who serve us, and vote in elections, not because anyone pressures us directly to do so (unlike say Australia we do not have compulsory voting) but because it’s what we feel we ought to do. There is a sense of altruism—and altruism provides the ultimate justification for why it is right to do these things—but the primary motivator in most cases is culture—that’s what people do, and are expected to do, around here.

Indeed, even when there is a direct incentive against behaving a certain way—like criminal penalties against theft—the probability of actually suffering a direct penalty is generally so low that it really can’t be our primary motivation. Instead, the reason we don’t cheat and steal is that we think we shouldn’t, and a major part of why we think we shouldn’t is that we have cultural norms against it.

We can actually observe differences in cultural norms across countries in the laboratory. In this 2008 study by Massimo Castro (PDF) comparing British and Italian people playing an economic game called the public goods game in which you can pay a cost yourself to benefit the group as a whole, it was found not only that people were less willing to benefit groups of foreigners than groups of compatriots, British people were overall more generous than Italian people. This 2010 study by Gachter et. al. (actually Joshua Greene talked about it last week) compared how people play the game in various cities, they found three basic patterns: In Western European and American cities such as Zurich, Copenhagen and Boston, cooperation started out high and remained high throughout; people were just cooperative in general. In Asian cities such as Chengdu and Seoul, cooperation started out low, but if people were punished for not cooperating, cooperation would improve over time, eventually reaching about the same place as in the highly cooperative cities. And in Mediterranean cities such as Istanbul, Athens, and Riyadh, cooperation started low and stayed low—even when people could be punished for not cooperating, nobody actually punished them. (These patterns are broadly consistent with the World Bank corruption ratings of these regions, by the way; Western Europe shows very low corruption, while Asia and the Mediterranean show high corruption. Of course this isn’t all that’s going on—and Asia isn’t much less corrupt than the Middle East, while this experiment might make you think so.)

Interestingly, these cultural patterns showed Melbourne as behaving more like an Asian city than a Western European one—perhaps being in the Pacific has worn off on Australia more than they realize.

This is very preliminary, cutting-edge research I’m talking about, so be careful about drawing too many conclusions. But in general we’ve begun to find some fairly clear cultural differences in economic behavior across different societies. While this would not be at all surprising to a sociologist or anthropologist, it’s the sort of thing that economists have insisted for years is impossible.

This is the frontier of cognitive economics, in my opinion. We know that culture is a very powerful motivator of our behavior, and it is time for us to understand how it works—and then, how it can be changed. We know that culture can be changed—cultural norms do change over time, sometimes remarkably rapidly; but we have only a faint notion of how or why they change. Changing culture has the power to do things that simply changing policy cannot, however; policy requires enforcement, and when the enforcement is removed the behavior will often disappear. But if a cultural norm can be imparted, it could sustain itself for a thousand years without any government action at all.