When ‘culture’ is the best explanation

culture- cute kids

A recent blog post about ‘culture’ making a lousy explanation of social and economic phenomena sheds even more light on the bizarre culture that is economics.

The core criticism is that “since “culture” is compatible with any conceivable set of facts, it is not falsifiable.” Which is surprising for a member of the economics club that subscribes to the unfalsifiable belief that some utility function drives all human behaviour.

In a stroke of irony their argument boils down to “our culture is to not accept culture as an explanation of behaviour”.


So why am I so defensive about culture as a useful principle in economic theory?

I guess I should first offer an economic definition of culture. Culture is the total learnt cooperative behaviours of a society, which includes the way members of that society draw meaning from the behaviour of others. Society simply means the relevant group – such as country, State, club, school, workplace, or family.

To be more clear, culture is the way we understand the meaning of signals. Think how meaning attaches to secret club handshakes or greetings, or even the behaviours surrounding social activities like eating, drinking, sports events and so forth. In Australia it can be impolite to stand at the football so people behind can’t see. In England it is impolite for a true fan to sit.


Sociologists are not so limited in their thinking. They widely adopt models that allow for learnt behaviours of individuals through interaction with others. Philip Bonacich’s fantastic introductory text covers many models that offer tantalising explanations for social phenomena that arise in aggregate from the interactions of individuals – from epidemics, to racial segregation, to power in exchange networks, to evolving strategies in the prisoner’s dilemma.

Paul Ormerod, a fellow fan of Alan Kirman’s ants model, has written multiple books offering tools that rely on social interaction and learnt behaviour to explain economic phenomena. He explains how Watt’s model of cascading network failure can reveal how and why fashion fads arise, why investors tend to go with the herd, and why some industries produce superstars even though no one can objectively tell the difference in the quality of their skills. The methodological individualism so fondly embraced by the econ crowd embraces the concept of utility, but stops short of answering the far more important question – where does our utility function come from if not our environment and our interactions with others?

Diego Gambetta has extensively studies how criminals interact and coordinate. The classic problem of criminal activity is how criminals cooperate with each other when they need to simultaneously follows the rules of the criminal world, yet break the rules of the rest of the world. Under these conditions, how can one criminal possibly trust another? What sort of culture, or learnt cooperative behaviours, allow criminals to navigate this problem? Gambetta examines how the culture of the mafia has evolved to overcome such coordination problems.


In my most recent paper I argue that social networks are the key to understanding the purpose and function of political donations. In the stylised model each agent’s utility relies on interactions with others over time. The model describes the process of signalling alliances given existing social networks, and a learnt cultural interpretation of the available signals.

In fact a whole field of agent-based modelling has arisen that allows aggregation of individual choices during repeated interactions. Much of the field studies social networks and the dissemination of cultures that allow for ongoing cooperation.

Finally, most economists ignore what are known as the folk theorems of repeated games; that it is possible to sustain any cooperative outcome when a game is expected to be repeated indefinitely. So while the textbooks are filled with explanations of the Nash equilibrium of the prisoner’s dilemma being to defect, in real life where interactions with others repeat indefinitely, cooperation is easily sustained with very basic strategies.


Where there are multiple possible cooperative strategies in a game, we might call the one that the players evolve to cooperate with the ‘culture’ of the game. And what is most interesting is that if a player in one game moves to another game they must learn the culture of the new game to ensure cooperation.

Say in game 1 the culture is for all players to play strategy A. If players cooperate by choosing the same letter as other players they increase each others’ payoffs. In game 2, players are all cooperating on B. We have two cultures that overcome the coordination problem within the same game rules. In game 1, choose A. In game 2, choose B.

Now if we take a player out of game 1 and put them in game 2, they are likely to continue their strategy of choosing A. But since all other players are choosing B, they will never be able to cooperate with another player. They must adapt to the local culture and choose B if they wish to increase their payoffs, and the payoff of those with whom they interact.


It is genuinely unfortunate that to be taken seriously by the economics ‘in crowd’ you have to start with a theory that ignores time, has a unique equilibrium, and aggregates all agents into one. There are so many avenues of research being pursued at the fringe of the profession, and within other disciplines, such as sociology anthropology, and psychology, that have so much to offer in terms of explaining and predicting social and economic phenomena by happily embracing cultural explanations.

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