Great summary. Spoiler: intelligence and patience. Though a moralizing God 
helps.  :-)



Where Do Pro-Social Institutions Come From? - Evonomics
http://evonomics.com/pro-social-institutions-come/
(via Instapaper)

By Pseudoerasmus

Where do ‘good’ or pro-social institutions come from? Why does the capacity for 
collective action and cooperative behaviour vary so much across the world 
today? How do some populations transcend tribalism to form a civil society? How 
have some societies gone beyond personal relations and customary rules to 
impersonal exchange and anonymous institutions? In short, how do you “get to 
Denmark”? I first take a look at what the “cultural evolution” literature has 
to say about it. I then turn to the intersection of economics and differential 
psychology.

Cultural Evolution

There’s been a revival of cultural explanations in economics. And by 
coincidence, there’s a coalition of biologists, anthropologists, and 
behavioural economists operating somewhat outside the mainstream of their 
professions under the umbrella of “cultural evolution“. Most of them appear 
convinced that “neither psychology nor economics is currently theoretically 
well-equipped to explain the origins of institutions” [Henrich 2015]. In 
response they offer a unified theory of gene-culture co-evolution or dual 
inheritance theory which models ‘culture’ as a non-genetic Darwinian process. 
From “Culture & social behaviour”:

“[In order] to build a theory of cultural evolution capable of explaining where 
institutions come from, researchers have gone back to the basics, to 
reconstruct our understanding of human evolution and the nature of our species. 
These approaches … have used the logic of natural selection and mathematical 
modeling to ask how natural selection might have shaped our learning psychology 
to most effectively extract ideas, beliefs, motivations and practices from the 
minds of others…

This foundation then allows theorists to model cultural evolution by building 
on empirically established psychological mechanisms. The result is cultural 
evolutionary game theory [64]. This powerful tool has already been deployed to 
understand the emergence of a wide range of social norms and institutions, 
including those related to social stratification [65], ethnic groups [66], 
cultures of honor [67], signaling systems [68], punishment [69–71] and various 
reputational systems [72,73].”

‘Culture’ is defined as any information inside the mind which modifies 
behaviour and which got there through social learning — whether from parents, 
or peers, or society at large. Non-genetically inherited ‘content’ would 
obviously include technology/knowledge (“how to remove toxins from edible 
tubers”), beliefs (“witches can cause blindness”), and customs (use of knife & 
fork). But it also includes what economists would describe as “informal 
institutions”, i.e., mating systems, ethical values, social norms, etc.

Cultural-evolutionists and evolutionary psychologists (a separate academic 
tribe) sometimes bicker over whether culture is responsible for causing the 
massive anthropological diversity of behaviours seen around the world. EP 
(generally) argues phenomena such as food taboos are ‘evoked’ by a universal 
innate psychology in reaction to different physical environments. By contrast 
CE (generally) argues behaviours vary primarily because the information that’s 
stored inside people’s minds varies from society to society. Our genetically 
evolved capacity for social learning enables us to transmit information 
accumulated over the generations, and this shadow of the past can override 
influences of the current physical environment. Without this persistent element 
with its own evolutionary logic, which cultural-evolutionists calls ‘culture’, 
it would be inexplicable why distinct groups living in identical or quite 
similar environments nonetheless still behave very differently.

The subset of culture called ‘norms’ and ‘values’ is well defined here by Nunn 
(2012):

“…decision making heuristics or ‘rules of thumb’ that have evolved given our 
need to make decisions in complex and uncertain environments. Using theoretical 
models, Boyd and Richerson (1985, 2005) show that if information acquisition is 
either costly or imperfect, the use of heuristics or rules of thumb in decision 
making can arise optimally. By relying on general beliefs, values or gut 
feelings about the ‘‘right’’ thing to do in different situations, individuals 
may not behave in a manner that is optimal in every instance, but they do save 
on the costs of obtaining the information necessary to always behave optimally. 
The benefit of these heuristics is that they are ‘‘fast-and frugal,’’ a benefit 
which in many environments outweighs the costs of imprecision (Gigerenzer and 
Goldstein 1996). Therefore, culture, as defined in this paper, refers to these 
decision-making heuristics, which typically manifest themselves as values, 
beliefs, or social norms.”

Some additional points about ‘norms’ in the cultural evolution literature:

as decision-making heuristics, norms strongly influence behaviour;
norms are passed down from generation to generation non-genetically, much like 
the knowledge of making fire or wine;
norms aggregate into ‘institutions’ at the population or group level [Ensminger 
& Henrich 2014]
because norms are largely acquired and internalised before adulthood, they can 
be stable over a very long time, even when they seem maladaptive or adapted to 
past circumstances;
but at the population level norms can change in response to new situations;
I turn now to those ‘norms’ and ‘values’ which enable cooperative behaviour.

The Problem of Ultra-sociality

Cultural-evolutionists have produced a large literature on what is sometimes 
called the “problem of human ultra-sociality“. Its main theme was popularised 
in a book by Paul Seabright: from an evolutionary point of view, how was it 
possible for the human species to go from living in small foraging bands of 
close relatives in the Palaeolithic to the global network of billions of 
anonymously interacting strangers that we see today?

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Modern societies engage in incredibly complex and incredibly large-scale forms 
of cooperative behaviour, with almost infinitesimal divisions of labour 
connected in a delicate skein of confidence and trust. Think of what it takes 
to get the New York Stock Exchange humming along, or the frightening amount of 
organisation and solidarity it took to wage the Second World War (on either 
side). Or, as Peter Turchin wondered, why did so many millions enthusiastically 
volunteer to risk death for unrelated strangers in the Great War?

I think this is a good summary of the cultural-evolutionists’ view on 
‘ultra-sociality’ overall: humans have an instinct for cooperation, but the 
social norms of fairness evolve gradually to accomodate a wider definition of 
‘insiders’ as a society gets larger and more complex.

But a related puzzle gets lost in the shuffle: why does ‘ultra-sociality’ vary 
so much across the world? Why are pro-social institutions not more widespread? 
The poorest countries like Afghanistan have pretty low levels of “social 
capability” in governance, to put it mildly. Why does the South of Italy have 
so little “civic capital” compared with the North of Italy ? Why aren’t most 
countries like Denmark?

Direct & Indirect Reciprocity

Traditional evolutionary biologists had already worked out a couple of 
mechanisms by which members of some species innately cohere as cooperative 
groups. For example, kin selection instinctively prediposes social animals to 
powerfully favour close genetic relatives. This explains things like bee 
colonies, lion prides, and human nepotism.

Amongst unrelated, selfish people, reciprocal altruism can explain exchange and 
cooperation in the absence of a central authority — as long as they live in 
small communities where people know each other and are locked into repeated 
interactions over time. In such a context, the promise of future benefits and 
retaliation against cheating are sufficient for rational calculation to 
generate the “I will share my Mastodon steak with you now, assuming that you 
will share with me in the future” principle.

Even in populations where people don’t know each other directly, it’s still 
possible to generate “spontaneous order” as long as the group has high 
community cohesion due to ethnic or religious identity. This “indirect 
reciprocity” was in my opinion best illustrated by economist Avner Greif. 
Making inferences from documents deposited in the Cairo Geniza, Greif argued 
that informal institutions regulated commerce amongst the Maghribi Jewish 
traders as they conducted long-distance trade with one another in the 
Mediterranean during the Middle Ages. The strength of ethnoreligious ties 
(especially as a minority in a wider world), maintained by strong exclusion of 
outsiders, reproduced a village-like flow of information even within a 
far-flung community and enabled reputation and ostracism to be the instruments 
of policing.

Of course, as anyone who has read Thomas Sowell knows, such commercial 
minorities are abundant even today and operate effectively in corrupt countries 
with weak legal institutions, such as the Lebanese in West Africa and Latin 
America, or the Chinese in Southeast Asia. And even in countries with strong 
legal institutions, ultra-Orthodox Jews conduct a major international trade in 
diamonds without much reliance on external authorities.

But most people agree these mechanisms — kin selection and reciprocity — by 
themselves cannot sustain a cooperative equilibrium in much larger societies 
composed of strangers who may never interact more than once and are separated 
by great distances.

Collective action problems

Whereas the cultural-evolutionists tend to ask “how did large-scale cooperation 
ever get started?”, mainstream economists and political scientists ask a more 
abstract, ahistorical question: “how does any kind of cooperation ever happen 
at all ?” This line of reasoning, which Mancur Olson called the “collective 
action problem”, investigates any situation where the private costs of an 
individual action are high while the benefits of that action redound 
collectively to the group.

In an election, for example, voting is costly to the individual voter because 
he must obtain information about the candidates and physically go to the poll. 
But the benefits of this public good (having a legitimate, accountable 
government) are divided equally by the society at large. Therefore, a 
rationally selfish voter ought then to free-ride on the actions of other 
voters: choose not to vote, knowing that the others will vote and elect a 
government. In fact, many people are free riders. But if everybody acted like 
this, there would be no election ! So why does anyone vote at all ? There 
should be a failure of coordination, but this kind of uncoordinated cooperation 
happens all the same.

Many things are subject to the free rider problem — the maintenance of price 
cartels like OPEC, political demonstrations, law enforcement, common 
environmental resources, taxation, and even the rule of law. All those 
arrangements either fail to happen or are under threat of unravelling because 
they are plagued with free-riders. If you have too many of them, others in the 
group will retaliate or imitate, and the cooperative equilibrium will collapse. 
(Collective action or coordination failures figure prominently in explaining 
recessions. But Germany may be exceptional.)

The standard solution is for the state — a third-party enforcer — to punish the 
louts and ensure compliance with the rules of the game. But the state has 
what’s called in political economy parlance a “commitment problem”: if it’s 
strong enough to enforce the rules of the game, then it’s also strong enough to 
manipulate them in its own interests, or in the interests of the powerful which 
control the state. So why on earth would the state act altruistically to solve 
the coordination problem in the public interest ? Many issues of governance — 
such as corruption or patronage politics — in one way or another, boil down to 
the inability of a population to coordinate on an agreed-upon set of rules, 
because there exists no disinterested nth-order enforcer.

Yet, despite public choice theory, despite capture by special interests, we 
know that the state in well-functioning societies more or less acts in the 
public interest most of the time. In other words, somehow collective action 
problems get solved; somehow socially productive cooperation happens.

Strong Reciprocity

A possible solution is “strong reciprocity“, sometimes also known as 
“altruistic punishment“. Behavioural economists claim to have documented the 
existence of this emotional instinct to engage in costly punishment of 
non-cooperators. In anonymous experiments intended to mimic collective action 
situations, strong reciprocators tend to punish free-riders, even when they are 
not the direct victims, and even when there is no clear or assured benefit in 
the future from doing so. [2nd vs 3rd party punishment] “Strong reciprocity” 
could be the psychological basis of the outrage that one sees in reaction to a 
social norm violation like, say, queue-jumping.

In the 4-player public goods game (PGG), each player is given some money and 
the choice to contribute any fraction of the amount (including zero) to a 
common pool. At the end, the total is multiplied by some factor and then 
divided equally amongst the players. Players only know about one another’s 
contributions at the end of each game. Then the game is repeated many times.

The experiment is designed so that the players, collectively, do their best if 
everyone contributes the maximum amount from the beginning. But an individual 
player has an incentive to free-ride whilst everyone else contributes. The 
worst collective outcome is obtained if everyone decides to free-ride.

PGG comes in two versions, with and without punishment. In the punishment 
version, each player is informed anonymously after each round about everyone 
else’s contributions and is allowed to punish whom ever they deem a free-loader 
by deducting from the free-loader’s final take. But the punisher must pay for 
some fraction of the punishment amount from his own take.

In a version of the game without punishment, repeating the game many times 
always causes cooperation to tank, because those who initially made high 
contributions learn about the free riders at the end of each iteration and then 
lower their subsequent contributions. But in the version of the game with 
punishment, a high level of cooperation is sustained. From Fehr & Gächter 2002:



It’s possible three stable personality types exist in repeated public goods 
games: free riders, “unconditional cooperators”, and “conditional cooperators” 
practising “strong reciprocity” or “altruistic punishment”. (Peter Turchin 
calls the three types ‘knaves’, ‘saints’, and ‘moralists’.)

The existence of pro-social instincts has been replicated in dozens of 
societies around the world — at many scales and complexity of social 
organisation, western and non-western, university and non-university students. 
[More on this below; also see the separate post “Experimenting with Social 
Norms in Small-Scale Societies“.]

The implication is that large-scale collective action or market exchange cannot 
be sustained unless self-interest in some fraction of the population is 
constrained by an internalised ethical adherence to the rules of the game. You 
can’t have a society entirely composed of people whose “good behaviour” is 
achieved only through fear of punishment.

What ever you think of such a view, it certainly dovetails with the thinking of 
classical political economists of the 18th century, as well as Hayek and 
neo-institutionalists like Douglass North. The latter even mentions early 
versions of these experiments.

Optimal Institutions?

Successful legal institutions may therefore depend on some interaction between 
conditionally cooperative norms and formal institutions.

Once again Avner Greif: in a series of papers on the nature of market exchange 
in individualist versus collectivist societies, he argues that informal 
institutions can be more efficient than formal ones under certain conditions.

The closed ethnic networks such as those of the Maghribi traders or of Chinese 
clans could be highly efficient because ethical norms and customary rules save 
on transaction costs. Imagine commercial contracts which don’t need to spell 
out every possible contingency or don’t even need to exist, because you can 
trust the parties to settle disputes according to long-standing custom. Or 
suppose you don’t have to do “due diligence” on every single transaction, 
because reputation counts for everything and its loss constitutes social death.

In such a world you save on the high costs of legal institutions, but it’s 
difficult to scale up because community cohesion may break down after a certain 
size. You need formal, legal rules and enforcement to conduct market exchange 
on the scale of millions of people.

But then the optimal arrangement is to have a large society which reproduces 
the cohesion of small-scale communities regulated by social norms, along with a 
predictable but lightly used formal enforcement system which every now and then 
disciplines the determined opportunists and other dickheads. Such is the world 
of high “social capital” as described by Putnam and writ large by Fukuyama.

This is how Putnam contrasted the North of Italy, with its high “social 
capital”, with the Mezzogiorno or the South of Italy:

“Collective life in the civic regions is eased by the expectation that others 
will probably follow the rules. Knowing that others will, you are more likely 
to go along, too, thus fulfilling their expectations. In the less civic regions 
nearly everyone expects everyone else to violate the rules. It seems foolish to 
obey the traffic laws or the tax code or the welfare rules, if you expect 
everyone else to cheat.”

One might argue, the real institutional difference between developed and 
developing countries is actually a “social capital” gap: there are just many 
more coordination failures in developing countries. Never mind countries torn 
by civil war. Never mind countries where the kleptocrat with a monopoly of 
violence does not even bother to hide his plundering. Even the political 
systems of minimally functioning democratic societies are often still organised 
de facto according to segmentary lineages, with clan- and tribe-based political 
parties campaigning to distribute to their members the spoils of the public 
treasury. In societies without clans and tribes, the distributive conflict in 
politics is played out along ethnolinguistic or caste divisions. But even in 
some relatively homogeneous societies, political parties are often a system of 
N-party competitive distribution of public spoils, with only nominal 
ideological differences between the parties. Greece is an upper-middle-income 
country and it’s still like that.

But how do you improve a society’s collective action capacity? How do people 
become more public-spirited? How do people achieve the transition from 
group-specific “limited morality” to “generalised morality”? This is 
effectively the same as asking how does the radius of trust widen beyond small 
kin or clan groups in the first place.

Tribal Social Instincts

One answer offered by cultural-evolutionists is “tribal social instincts”.

‘Tribal’ is an unfortunate choice of words because it normally connotes group 
balkanisation and incoherence. But in the sense used by Boyd & Richerson, it 
refers to a genetically evolved predisposition to combine into groups 
successively larger than friends and family. ‘Tribalism’ is innate, but the 
specific size and manifestation of ‘tribe’ depends on social norms and cultural 
innovations:

“…the ways that people behave toward others can depend heavily on how those 
others are classified—as kin, friends, and community members or outsiders, 
strangers and foreigners. Second, human populations can vary dramatically in: 
(1) how they define closeness and distance of a social partner and (2) how 
these qualities of a partner influence social behavior. Third, these population 
differences are not fixed or static. Populations can change quite dramatically 
within several generations, [as with the Iban of Borneo], from hunting the 
heads of neighboring groups to participating relatively peacefully in a much 
larger nation-state and world system.” [Hruschka & Henrich (2013)]

You get “parochial altruism” or ‘ethnocentrism’ when an expanding in-group 
progressively absorbs outsiders and reclassifies them as insiders. In recorded 
history, the most important way in-group favouritism has been applied to larger 
populations is through symbolic markers of common identity such as language or 
religion or extreme rituals. These create the glue for large associations of 
fictive kinship, “honourary friendship”, and imagined communities.

Then different levels of aggregation — from tribe to states to empires — are 
decided on the basis of intergroup competition. In short: more cooperative 
groups grow larger by outcompeting less cooperative groups in war.

Cooperation within a group is constantly being undermined by competition within 
the group — i.e., free-riding behaviour by those maximising individual fitness. 
That’s because kin bias and tribal bias are in tension. As Boyd & Richerson put 
it:

“These new tribal social instincts were superimposed onto human psychology 
without eliminating those that favor friends and kin. Thus, there is an 
inherent conflict built into human social life. The tribal instincts that 
support identification and cooperation in large groups are often at odds with 
selfishness, nepotism, and face-to-face reciprocity.”

But this tendency for groups to lose internal coherence can be counteracted by 
competition between groups through “multi-level selection” and “cultural group 
selection“. In the cultural-evolution jargon: between-group cultural variation 
in pro-social traits exceeds the within-group variation.

Groups whose cultural innovations — such as “high moralising gods” — tend to 
suppress or moderate the anti-social instincts of their members and promote the 
pro-social ones, grow bigger and more powerful than groups which remain riddled 
with group-suicidally selfish actors or subgroups. (Think: the small yet 
cohesive Prussia versus the large but fragmented Austria-Hungary.) Those less 
able to cohere as groups, all else equal, get exterminated, assimilated, or 
reduced to insignificance. Those wishing or able to survive imitate the 
cultural innovations of the successful ones.

War and violence feature prominently in the cultural-evolution literature since 
that has characterised so much of human history. Thus the mathematical 
ecologist Peter Turchin, asking “how are empires [even] possible” in the first 
place, models group solidarity as an endogenous variable in the rise and fall 
of empires between 1500 BCE and 1500 CE.

(For claims about how norms and institutions co-evolve more peacefully, see the 
separate post “Experimenting with Social Norms in Small-Scale Societies“.)

The prominence of war in the cultural-evolutionist explanations of the most 
ancient human institutions such as hierarchy, the state, and ethnocentrism has 
a clear parallel with the literature in economic history on “state capacity” in 
which the rise of effective states in the early modern period is also linked to 
war. (See Brewer, Tilly, Hoffman, Dincecco 2015, etc.) It also has an obvious 
link with the literature in comparative historical development inspired by 
Jared Diamond stressing the importance of “an early start” in agriculture and 
state history (Bockstette et al., Borcan et al., Spolaore & Wacziarg).

Social Norms and ‘Stateness’

But if the long history of ‘stateness’ and agriculture, plus a long history of 
state-level warfare, are somehow crucial to the development of a ‘modern‘ 
society and state, that naturally prompts the question of how and why. It 
cannot be merely the long history of state experience. From Olsson & Paik, log 
GDP per capita in 2005 plotted against time since adoption of agriculture:



On a global scale, it’s as Jared Diamond argued: a long history of agriculture 
(and therefore also of the state) is a good thing, but within regions, it may 
not be such a good thing after all. (Statistically, this is Simpson’s Paradox.)

So at this point, cultural-evolutionists say “history matters” and often 
reference the empirical work in mainstream economics and other social sciences 
which demonstrates that “institutional shocks” in the past can leave a 
persistent imprint on contemporary culture. This evidence sorts well with the 
cultural-evolutionist assumption that cultural inertia can persist for a long 
time.

The “history matters” literature in economics finds real effects, by which I 
mean it does establish that culture matters, social norms or cultural values do 
change, and this has consequences for political and economic development on the 
margins. But the overall effects found by this literature seem to me kind of 
small, or highly local, or particular to their datasets. Or in some cases it 
cannot rule out reverse causality, e.g., it could be economic development which 
results in big cultural changes, such as rising levels of trust.

I myself have little doubt that the experience of communism, for example, 
changed West and East Germans’ values regarding social welfare. Nor do I doubt 
different (cultural) preferences for leisure and work contribute non-trivially 
to the US-European differences in work hours. Whether your ancestors used the 
plough or the hoe, may still influence your views on gender norms. And it makes 
perfect sense to me that the strength of family ties explains political 
attitudes which influence the demand for labour market regulations in northern 
versus southern Europe.

So different institutional paths chosen thanks to differences in culture and 
history do matter.

But as the gap gets bigger between countries I grow more sceptical about how 
powerful ‘culture’ — as defined above — can really be in explaining the massive 
global variation in state capacity and economic development.

There are always clever ways of magnifying the impact of culture by modelling 
culture-institutions-geography interactions. Thanks in part to ancient 
biogeographic conditions, a particular cultural group is able to set up 
institutions reflecting their prevailing norms in a newly settled country; the 
‘bad’ institutions persist and persist and persist, because this group controls 
the resources and has no incentive to make a “credible commitment” to 
“inclusive institutions” or an “open access order”; and because the ‘bad’ 
institutions persist, pro-market norms fail to emerge and the ‘bad’ norms 
reinforce the ‘bad’ institutions. There are like 3 or 4 tangled traps in there.

So is ‘good’ governance just a matter of time, a long time, but still a matter 
of time? Jerry Hough and Robin Grier have argued just that in a recent book. 
That book also makes a de facto cultural evolution argument in which state 
capacity, markets, and “rational-legal values” co-evolve. Or is ‘bad’ 
governance an issue of timing mismatch, when democracy arrives before a strong 
state, as Fukuyama has repeatedly argued? Interestingly, both Fukuyama and 
Hough & Grier point to the corruption-ridden United States of the 19th century 
as an important piece of evidence.

I think the “really long time” argument has some validity, but that just 
prompts the question: why have some countries — those of East Asia come to mind 
— have had such rapid and dramatic institutional revolutions ?

I don’t find plausible theories for answering that question in cultural 
evolution. So I turn to the intersection of economics and differential 
psychology.

Intelligence and Cooperation

{ Don’t be turned off! There is no hereditarian dogma here. At the end I talk 
about Pinker and the Flynn Effect. }

In the workhorse model of (non)cooperation — the prisoner’s dilemma — two 
players are faced with the decision to cooperate or defect based on a matrix of 
4 possible payoff combinations.

Suppose a sedentary peasant would end up with $4 (the loot + his own output), 
if he ambushed and robbed a passing horse-backed nomad, but only $3 if he 
traded goods with him. The nomad faces the identical decision: $4 with robbing, 
$3 with trading. If both decided to rob, then they would be left with $2 each.

It’s set up so that each has a perfectly rational self-interest in robbing the 
other, but the trading world is clearly better than both-turn-to-robbery world.

It’s well known from simulations of “infinitely repeated” prisoner’s dilemma 
games that cooperation is best sustained when both players adopt some variety 
of conditional cooperation strategy: cooperate first, but then copy the other 
play’s earlier choice. [See Axelrod.] The gains to both parties are bigger in 
the long run if both parties behave like that. And, as we have already seen, 
real people do in practise show an instinct for conditional cooperation.

But Proto, Rustichini & Sofianos (2014) demonstrates that in a multi-round 
Prisoners’ Dilemma experiment with actual human participants and real money, 
the intelligent are much more likely to practise conditional cooperation.

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In this experiment, subjects were first administered Raven’s Progressive 
Matrices, a test which measures fluid intelligence (i.e., not based on 
knowledge). They were also tested for risk attitudes and the Big Five 
personality traits. In the end, 130 participants were allocated to two groups — 
“high Raven” and “low Raven” — and the only statistically significant 
difference between the two groups was in fluid intelligence. The participants 
did not know how they were grouped. (Edit: Also relevant: “Participants in 
these non-economists sessions had not taken any game theory modules or 
classes.”)

Then within each group, different pairs of participants repeatedly played the 
prisoner’s dilemma — the maximum number of rounds was 10 but a computer decided 
whether to terminate the session after each round with a fixed probability. 
There were multiple sessions of these rounds of games.



[Blue: high Ravens group, Red: low Ravens group. X-axis: each period represents 
10 rounds; Y-axis: the fraction of players cooperating.]

The high Raven group not only diverged early from the low Ravens, but also 
sustained cooperation much longer. There actually wasn’t much difference 
between the two groups in the early rounds. The difference grew incrementally, 
in drips and drabs, but in the end, it was substantial. This suggests high 
Ravens learnt the optimal behaviour from the previous rounds better than the 
other group.

Proto et al. sliced and diced the data in various ways and found that:

reciprocation is much stronger with the smart: high Ravens are more likely than 
the low Ravens, to match prior cooperation with cooperation in kind, and punish 
prior defection with defection in kind;
reaction times — the time it took to decide whether to cooperate or defect — 
were shorter and declined faster for the high Ravens;
the only statistically significant difference in individual participant 
characteristics was fluid intelligence;
when the monetary payoffs were manipulated to make cooperation less profitable 
in the long run, the high Ravens were no more cooperative than the low Ravens — 
if anything, the low Ravens were slightly more cooperative !
But the most amazing result has to be this: “Low Raven subjects play Always 
Defect with probability above 50 per cent, in stark contrast with high Raven 
subjects who play this strategy with probability statistically equal to 0. 
Instead, the probability for the high Raven to play more cooperative strategies 
(Grim and Tit for Tat) is about 67 per cent, while for the low Raven this is 
lower (around 45 per cent).”

Understanding the benefits of working together in complex situations — which is 
what a repeated prisoner’s dilemma simulates — implicitly requires reasoning 
skills, the ability to learn from mistakes, the ability to anticipate, and 
accurate beliefs about other people’s motives.

The ethical implication: the intelligent are more likely to practise the Golden 
Rule, and this actually breeds trust; and the less intelligent are more likely 
to think they can get away with it, and this breeds mistrust. You only need 
intelligence to generate this difference. You can immediately see where social 
and civic capital might come from, at least in part.

The Proto et al. study replicates and extends a few earlier studies on 
intelligence and cooperation [Al-Ubaydli et al. (2014); Jones 2008). Moreover, 
it’s consistent with cross-cultural findings from Public Goods Games as 
described below.

Anti-social Punishment

Earlier I mentioned that in the Public Goods Game there were possibly 3 stable 
personality types: free riders, unconditional cooperators, and conditional 
cooperators who punish free-riders. But when the PGG was conducted in 16 
different cities around the world, Herrmann, Thöni, & Gächter (2008) reported 
the existence of “anti-social punishment”.

That is, in addition to people actively punishing free-riders, in some cases 
there were people actively punishing cooperators !Another interesting thing is 
that subjects in both Seoul and Chengdu started at fairly low levels of 
cooperation but rapidly converged to Northwest European levels of cooperation:



Anti-social punishment kills cooperation in non-western countries except East 
Asia. Hmmm. What’s different about the Koreans and the Chinese ?

When the punishment option is entirely removed in a separate treatment, 
cooperation levels plummeted across the board and even the rank order changed 
to some extent:



Those Danes remained ever true to stereotype, but what a fall for most other NW 
Europeans ! This suggests pro-social punishment is important to sustaining 
collective action in western countries.

Interestingly, the authors found in their regressions that the “rule of law” 
indicator was not a statistically significant predictor of social punishment, 
but it was strongly inversely correlated with antisocial punishment. That is, 
weak rule of law and anti-social punishment tend to go hand in hand. It’s 
probably a feedback effect.

Patience and Cooperation

Patience also matters to whether cooperation is sustained. Low time preference 
is correlated with intelligence [Shamosh & Gray (2008)], but the association is 
not so big that you can’t have many smart people who are more impatient than 
some less intelligent people. So patience is a quasi-separate factor in 
cooperation.

Intuitively, if the benefits of cooperation accrue in the long run, then less 
patient and more impulsive people are less likely to cooperate. In the repeated 
prisoners’ game, the degree of ‘patience’ is represented by discounting the 
total gains in each period after the first one. In the nomad-peasant example 
from above, if both were impatient, the $6 cooperative payoff in (say) the 9th 
round would only be worth (say) $4, because a dollar in the future is not worth 
the same as a dollar today. But for more patient people, the future payoff will 
be closer to $6.

But the Stag Hunt may better highlight the role of patience in cooperation. 
It’s similar to the prisoner’s dilemma, but the payoffs to cooperation are 
obviously superior to those of non-cooperation (defection). The choice is 
between cooperating to hunt stag (which requires team effort) or going it alone 
chasing rabbits. The scenario is set up so that non-cooperation is riskless — a 
sure thing for both parties — whereas cooperation is risky because you don’t 
know whether the other party will come through, and the big payoff absolutely 
requires both to participate.



Many social situations are more like a stag hunt than a prisoner’s dilemma, and 
intuitively you would think taste for risk would predict cooperative behaviour 
in such cases. But in fact Al-Ubaydli, Jones & Weel (2013) finds that patience 
is the most important element in successful cooperation in Stag Hunt 
experiments with real people. The study participants had been tested for 
patience, intelligence, risk aversion, and personality traits; and “risk 
aversion and intelligence have no bearing on any aspect of behavior or outcomes 
at conventional significance levels”.



[There are other interesting details to this study, such as increasing returns 
to pairs of patient players, but it would take too much space to describe.]

Need I say, that populations vary substantially in patience? Wang et al. (2011) 
asked subjects in 45 countries about how much they value offers of money now, 
in the near future, the medium future, and in the far future. Based on their 
answers the authors computed discount rates for each group.

But people tend to be “time inconsistent”, i.e., they can be very patient about 
long-term rewards, but simultaneously very impulsive about things right in 
front of them. If your future self tearfully regrets that your past self was 
such an idiot as to consume 5 slices of cake after each meal, then you are a 
“hyperbolic discounter”.

Wang et al. found that countries and regions vary a lot more in their present 
bias than in their long-term discount factor:

The above says: how people in the present value rewards they expect to receive 
(say) 10 years into the future, is pretty similar across the world — although 
small differences can make a big difference in the long term through 
compounding. But the degree to which people want things right now, as opposed 
to tomorrow, varies quite dramatically.

By the way, Russia’s β is 0.21 !!! If that has nothing to do with low 
investment rates or insecure property rights for foreign companies, then I will 
eat my shorts !

The role of patience in cooperation is relevant to the “commitment problem” of 
the state in solving collective action problems. In theorising about the 
origins of the state, Mancur Olson gave a famous answer with his dichotomy of 
roving bandits and stationary bandits. In the world of political anarchy, 
roving bandits fight one another for opportunities to pillage the productive 
peasants. But sometimes one of them defeats all the others and establishes 
himself as a “stationary bandit”. He then acquires a strong intrinsic interest 
in restraining his plunder — his ‘taxation’ — in order to let the economy grow. 
It’s the “fatten the goose that lays the golden eggs” principle.

But that depends! If the stationary bandit is impulsive and impatient, he can 
remain a predator for a very long time.

Political scientist Carles Boix in a recent book pointed out that the 
reciprocity of stateless foraging societies cannot be sustained when the 
distribution of resources is too unequal. But even his model depends on 
‘patience’, with the implication that uncoordinated cooperation is still 
possible with more inequality as long as people are patient enough. This is 
actually true of models using prisoner’s dilemma and stag hunt in general. Even 
Acemoglu‘s ruling elite with vested interests in maintaining “extractive 
institutions” would have incentives for “inclusive institutions” if they were 
only patient enough.

So to answer the question at the head of this post, “where do pro-social 
institutions come from?” — if ‘bad’ institutions represent coordination 
failures, then intelligence and patience must be a big part of the answer. This 
need not have the same relevance for social evolution from 100,000 BCE to 1500 
CE. But for the emergence of ‘modern’, advanced societies, intelligence and 
patience matter.

It’s not that people’s norms and values do not or cannot change. They do. But 
that does not seem enough. Solving complex coordination failures and collective 
action problems requires a lot more than just ‘good’ culture.

I am not saying intelligence and patience explain ‘everything‘, just that they 
seem to be an important part of how ‘good’ institutions happen. Nor am I saying 
that intelligence and patience are immutable quantities. Pinker argued in The 
Better Angels of Our Nature that the long-run secular decline in violence may 
be due to the Flynn Effect:

…the pacifying effects of reason, and the Flynn Effect. We have several grounds 
for supposing that enhanced powers of reason—specifically, the ability to set 
aside immediate experience, detach oneself from a parochial vantage point, and 
frame one’s ideas in abstract, universal terms—would lead to better moral 
commitments, including an avoidance of violence.

What is the above describing, other than the increasing ability of people to 
empathise with a wider group of people than friends and family? Intelligence 
and patience allow you to understand, and weigh, the intuitive risks and the 
counterintuitive benefits from collaborating with perfect strangers. With less 
intelligence and less patience you stick to what you know — intuit the benefits 
from relationships cultivated over a long time through blood ties or other 
intimate affiliations.

Your “moral circle” is wider with intelligence and patience than without.

In the 1990s, in the middle of free market triumphalism, it was widely assumed 
that if you let markets rip, the institutions necessary to their proper 
functioning would ‘naturally’ follow. Those with a vested interested in 
protecting their property rights would demand them, politically. That 
assumption went up in flames in the former communist countries and the 
developing countries under economic restructuring.

To paraphrase Garett Jones, one of the co-authors of the stag hunt study: 
smart, patient people are more Coasian; they find a way to cooperate and build 
good institutions.

Originally published here.

2017 July 10

Note: The above was written before Garett Jones’s Hive Mind was published. This 
article, which cites several of Jones’s papers, overlaps with his book on the 
discussion of intelligence, patience, and the “Political Coase theorem”.

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