Deep Rationality: The Evolutionary Economics of Decision Making

Even though I consider that I am across the literature at the boundary of economics and evolutionary biology, now and then an article pops up that I somehow missed. The latest article of this type is a 2009 article by Douglas Kenrick and colleagues, titled (as is this post) Deep Rationality: The Evolutionary Economics of Decision Making (unfortunately I can’t locate an ungated copy). I found it through Dan Ariely’s reading list for his Coursera course A Beginner’s Guide to Irrational Behaviour. Kenrick has also posted on the article over at his blog

I don’t feel overly guilty about not seeing this article earlier, as the authors have not referenced a lot of the literature in economics that I would consider relevant. Regardless, there is a lot to like about this article, particularly the way that it looks to incorporate an evolutionary approach into behavioural economics. I have often posted my criticism that much behavioural economics lacks a framework, without which it is just a list of biases and heuristics. It is good to see someone trying to offer that framework.

The authors’ basic argument is that people have evolved domain specific decision rules. Decisions depend on the current environment, plus the decision maker’s sex, mating strategy and stage in the life cycle. As a result, many decisions that are called inconsistent or irrational in behavioural economics are actually “deeply rational” to the domain in which the decision is being made.

In making their case, the authors start out with a brief kick at economics by noting that most economic theorists “have remained relatively agnostic about the roots of utility.” They do note the work of Gandolfi, Gandolfi and Barash, but otherwise do not mention the wealth of articles on the evolution of preferences by the likes of Arthur Robson, Larry Samuelson and others (my economics and evolutionary biology reading list gives a taste). Thus, when they suggest that we need to go deeper than Gandolfi, Gandolfi and Barash’s approach of equating utility to fitness, they miss some literature which does just that.

Regardless, the need to go beyond “fitness equals utility” by considering factors such as life history or differences in mating strategy is important. The authors suggest that we should consider human decision making as being geared to solve recurring adaptive problems in different domains, whereby successful solutions in each are associated with increased fitness. The body of their article focuses on some examples of this approach.

In one section, they address attitudes to risk. Humans are normally risk averse, which Kenrick and colleagues suggest is consistent with empirical observations of loss aversion. Although this short-hand equating of risk aversion and loss aversion works some of the time, it sells these concepts short, along with the way that they are incorporated into Kahneman and Tversky’s prospect theory. Under prospect theory, people evaluate choices from a reference point, they show loss aversion (losses hurt more than gains) and they are risk averse when faced with two potential gains. However, in the domain of losses, they are actually risk seeking. When you combine these features with the human tendency to overweight small probabilities, you obtain the fourfold pattern of risk attitudes. When an agent faces a moderate probability of a gain or a small probability of a loss, they will be risk averse. However, when faced with a low probability of a gain or a moderate probability of a loss, they will be risk seeking.

Kenrick and colleagues do make the important point that the attitudes to risk as predicted by prospect theory will vary with evolutionarily relevant factors. Men with mating motives will be more likely to take financial risks.  Women would not respond in the same way to mating primes as women know that men give a lower value to the resources possessed by a mate. In the social domain, such as networks of friends, there tends to be loss aversion in both sexes, although this may reverse for men with mating motives.

This is a point of the article where a hat tip to the existing literature might have been most useful, as some economists have spent a lot of time considering the evolutionary foundations of attitudes to risk. For example, Rubin and Paul examined the effect of mating motives on risk preferences in 1979. They developed a model where male fitness depended on attracting a mate, which was in turn a function of their resources (income). Rubin and Paul suggested that young men who do not have a mate are likely to be risk seeking in obtaining income as they have no mate to lose. Older men who already have a mate will tend to be risk averse, particularly given the huge level of income required to attract a second mate.

In another section, Kenrick and colleagues look at the economic approach to choosing a basket of goods within a budget constraint. In this case, the weighting of various goods will depend upon the domain in which an agent is making a mate choice. For example, promotion of a colleague at work may influence status motives and accordingly, the worker’s preferences between more time in the office and leisure will shift.

They also make the interesting distinction between traits in a potential mate being necessities or luxuries. Consider a female who needs a male to have a minimal level of resources to make sure her offspring survive. Due to diminishing marginal utility (another economic concept) as the male’s resources increase, she may start to look at other traits if there are plenty of males with enough resources. The pattern of consumption will be that resources are a necessity, while other traits are luxuries. A similar pattern might emerge for male preferences, initially prioritising fertility related traits, but then considering other traits if there are plentiful fertile females. Thus, when the necessity traits are scarce, we might expect large sex differences in mate preferences as each sex focuses on obtaining their different necessities. As these traits become more plentiful, traits that are luxuries are sought. If there is overlap between the luxuries of one sex with the necessities of the other sex, we would see smaller differences between the sexes in the traits sought in mates.

One issue Kenrick and colleagues do not spend much time on is why evolution has shaped domain specific decision rules. The foundation of modular decision making is addressed in the evolutionary psychology literature, but to sell this concept to economists, you need to sell them the constrained rationality that is inherent in the modular approach. Most evolutionary analysis of economic preferences struggles to incorporate “irrationality” through constraints, often due to a view that evolution is the ultimate rationality machine (and most economists fixation, conscious or not, with rationality). Selling to economists the picture of constrained, path dependent evolution that leads to modular decision making and “deep rationality” could improve the economic endeavour considerably.

Kenrick, D., Griskevicius, V., Sundie, J., Li, N., Li, Y., & Neuberg, S. (2009). Deep Rationality: The Evolutionary Economics of Decision Making Social Cognition, 27 (5), 764-785 DOI: 10.1521/soco.2009.27.5.764


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