14 lessons of cooperative economics

7 min readOct 17, 2018

How people actually behave in civil society. Some of this may surprise you.

This is for you if:

You’ve wanted to read this book but were intimidated by its 275 page length.
You’re puzzled by how the way some people behave doesn’t seem to be in their self-interest, and want to understand these seemingly irrational behaviors.
You are interested in game theory and social psychology.
You’ve followed classical economics but somehow didn’t really buy its explanation of how people actually behave.
You’re interested in behavioral economics.
You are interested in how people achieve decentralized consensus in small to large groups of people.
You’re interested in the intersection of economics, psychology, and sociology.
You enjoy listicles.

Tl;dr

Cooperative economics gives a fuller explanation of how people behave in group decision-making settings than classical economics.

The way people behave in everyday life can be explained in large part by cooperative economics.

This is not to say that classical economics, behavioral economics, evolutionary economics do not predict the way people behave — just that cooperative mechanisms resolve certain paradoxes and fill in gaps that are not adequately explained by prevailing ideas.

Overview

These lessons are gleaned from “A Cooperative Species, by Bowles & Gintis, 2011.

The book contrasts cooperative economics with theories based on non-cooperative theories, including kinship, mutualism, and costly signaling. It also delves into the roles evolutionary theory, culture, and institutions play.

My objective is to provide a steelmanning of the book’s arguments.

This article distills the highlights of the main claims of the book. The next part in this series, Part 1 gives an overview of competing alternative explanations. Then, Part 2 summarizes the book’s arguments that human-level cooperation is impossible to model with only non-cooperative game theory. The final part in this series, Part 3 puts things into context with evolutionary game theory and the rise of institutions.

Takeaways

If we assume that the book’s claims are correct, then how can its lessons be used in today’s world?

Some of the key takeaways are:

Mechanisms of cooperative economics provide an effective way of decentralizing group consensus.
The sometimes puzzling manner in which people behave in teams can be explained by how group dynamics trigger social emotions tied to internalized group norms.

Another set of key takeaways is that cooperation is less likely in the following situations:

when there are many participants,
when interactions are infrequent,
when the time horizon is short, or
when others’ actions cannot be clearly observed.

In other words, people who are guided by moral reasoning will change their behavior when they are thrust into situations where that moral reasoning is less effective and possibly risky.

Coordination may still be possible — but it will be more likely due to be based on principles from evolutionary game theory and non-cooperative game theory.

Conversely, non-cooperative mechanisms (that is to say, purely competitive, “self-interested” mechanisms) are more suitable when:

Interactions are infrequent.
Participants are not human.
Participants are anonymous.
Participants cannot communicate.

Click here for a primer on key terminology. That document provides a glossary of terms, as well as some mini-primers on Game Theory, Agent Based Modeling, Evolutionary Economics, and Dynamical Systems.

Click here for an opinionated synopsis. That article contains more of my own opinions, including knowledge gleaned from other sources. This article (the you are reading now) instead attempts to summarize the book’s message with a minimum of my own editorializing.

Caveats

For the purpose of brevity and in order to provide an unbiased steelmanning of the author’s arguments, many of the explanations given here will be terse with little elaboration.

Statements made here should not be considered my own opinion.

This document will focus on conclusions instead of methodology. I leave it to others to argue the science. That said, I find the science to be compelling. I try to provide references backing up each of the key claims.

Key takeaways

Modeling the complex processes underlying human cooperation is a major challenge of contemporary science.

Conventional wisdom in biology and economics is that the reasons why people cooperate so effectively and generously can be fully explained by far-sighted self-interest or to the desire to help close kin. Supposedly, the reason why people make sacrifices to uphold group norms and to help total strangers is just an extension of the following:

Enlightened self-interest.
Mutualistic form of helping based on the expectation of reciprocation in the future.
Indirect reciprocity.
Virtue signaling.

This book argues that these cannot fully explain the full extent of human generosity — or for that matter bitter vindictiveness.

Economic theory, favoring parsimony over realism, has sought to explain cooperation without reference to social preferences, and with a minimalist or fictive description of social institutions. This research trajectory, as we have seen, has produced significant insights. But it may have run its course.

Role of social emotions

Cooperation with fellow group members is essential to survival. Groups that protect the civic-minded from exploitation by the selfish are more effective and are able to compete better with less cooperative groups. Key to this process are the social emotions such as shame and guilt.

Ethics and Morals

People internalize social norms in the form of morals. However, moral judgment is not just relying upon rational thought or even deep seated intuition; rather it is based on social emotions that lay deeper still. For certain acts of altruistic kindness (or revenge), acting ethically is a personal goal rather than simply to prudent way to avoid punishment.

Decentralized Consensus and Execution

Internalizing norms and enforcing them using strategies that are triggered by social emotions turns out to be an excellent way to decentralize the means of coordinating the behavior of groups of people, both for small groups as well as larger ones. The key tasks that group decision-make requires include:

Generating proposals about what should be done next and what could be done better.
Deciding on what to do next and on rules of conduct.
Communicating the plans and rules to everyone in the group.
Enforcing the plans and rules.

Humans utilize sophisticated means of transitioning between self-interested non-cooperative behavior and altruistic cooperative behavior, layering different strategies upon each other to handle situations that require one, or the other, or a mixture of both. We do it so effortlessly that we take it for granted. It is not as simple as many scientists and economists would like to make it out to be — and so it is not as favored as explanations that rely on a (supposedly) simpler form of game theory. But, when the supposedly simpler forms of game theory have to be twisted and turned into devices approaching Rube Goldberg machines in complexity, they actually end up being more complicated.

My two cents

There are numerous models that compete and overlap with this book’s model, such as evolutionary game theory (and evolutionary economics), behavioral economics, and myriad other flavors of economics. The authors seem especially critical of classical economics.

This book argues fairly persuasively that cooperative economics is the better model in certain scenarios. Could it displace classical economics more generally? So far as I can tell there is no grand unified model of economics. Even this book admits that classical economics has proven extremely successful in many practical situations. Moreover, this book admits that non-cooperative game theory is arguably a simpler model in many (though not all) practical scenarios. Likewise, evolutionary economics seems to be better suited in many practical scenarios.

Cooperative, non-cooperative, and evolutionary theories each have strengths in certain regimes. The book presents scenarios in which the player encounters a scenario where it needs to switch from one type of model to a different one mid-game. Initially, other players may seem like cooperating participants, only to suddenly snap into focus as self-regarding opponents.

Measured in dollars one could argue that classical economics is the clear winner. Measured in number of interactions over the history of life as we know it then evolutionary economics could be argued as the clear winner. Measured in terms of what is most **predictive** of what is going to happen in a high-stakes game involving nuanced gameplay by savvy human players, then cooperative models are a strong contender.

Non-cooperative models try to avoid the need for contracts, for example, by relying on reputation. At the end of the day though we still rely heavily on contracts in the real-world. Contracts are not going to disappear for the foreseeable future. Contracts are a correlating device, and so would seem to fall squarely within cooperative economics. Many of the apparent paradoxes in non-cooperative game theory evaporate when a correlating device is introduced.

Though classical and evolutionary models may do an impressive job at modeling most of the world’s transactions, the remainder could either be modeled by improving those theories, or instead by using a different model.

Cooperative game theory has another strong ally on its side : algorithmic game theory (AGT). The cooperative model uses correlated equilibrium as its equilibrium concept, which is more compatible with AGT. Recent results indicate that AGT has computational advantages to classical game theory models. That is outside the scope of this review; however, the book does touch on this very briefly.

For these reasons, I think that this book is worth a look if you are interested in economics or game theory, especially where this involves human players.