The evolution of happiness

When we experience positive events, we feel happy. But happiness adjusts, with the effects of a positive event normally short-lived. Over the long-term, happiness tends to float around a stable mean. Happiness is also strongly related to our position relative to our peers. How happy we are with our income depends on everyone else’s income.

In line with the first law of behavioural genetics, it is worth looking for an evolutionary foundation to this pattern. How does happiness motivate us to do things in our evolutionary interest?

Evolution did not shape our happiness to simply increase or decrease in line with how events affect our fitness. We need a more nuanced explanation, which Luis Rayo and Gary Becker offered in two papers published in 2007 by asking how our ability to feel happiness would be affected if it is constrained. The long form of their argument is contained in the Journal of Political Economy, with a shorter version published in the American Economic Review Proceedings and Papers.

Rayo and Becker propose two potential constraints. First, there are limits to a person’s sensitivity to happiness. A person can only determine which of two alternative choices they should make if there is more than a certain size difference in happiness for the two choices. Second, there is a bound on the range of happiness that a person can experience (say, limits to nervous system signal strength).

To overcome limits to a person’s sensitivity, evolution could amplify the happiness response to make sure that we knew which of two choices made us happy. But if there is a limit as to how happy we can feel, this solution will not always work. Combining the two constraints, the strength of the happiness signal should be strong where it matters most – over the current relative decisions.

Rayo and Becker relate a couple of cases that are similar. If you move from the sunlight into a dark room, you initially can’t see anything, but your eyes adjust until you can distinguish between the relative shades. Another example comes from Arthur Robson, who likens happiness to a voltmeter. When you are about to measure an electric current, you must first set the voltmeter to the range in which you want to measure the current. If you set the range too high, the meter will barely move. If you set it too low, the reading will go instantly to the maximum value. The voltmeter must first be calibrated to the problem at hand.

To formalise this idea, Rayo and Becker developed several “happiness functions”. In one function, the agents first compare their income against their peers to determine their current social position. They then contrast their current social position against their relative social position in the last period. An advance in social position leads to happiness but it is only short-lived.

Under this function  a general increase in income across society does not increase happiness (consistent with the Easterlin paradox), and happiness will tend to revert to a mean. However, given recent arguments that the Easterlin paradox is an artefact of having happiness measured on a bounded scale, Rayo and Becker’s argument may need to more finely tuned.

This happiness function is also consistent with the positive correlation between income and happiness sometimes observed in cross-section data. People are subject to random shocks and those who have higher income are more likely to have received a recent positive shock.

One thing I didn’t enjoy about the Journal of Political Economy article is that it follows a tradition in much work on the evolution of economic preferences by using a metaphorical principal-agent approach to the analysis. The principal is nature, while the agent is the individual being shaped by evolution.  I’ve never been a fan of this approach, which is generally not adopted in evolutionary biology. It lessens the accessibility of what is often already hard to access work, and I am not convinced that any pay-off from the additional complication is worth it. I’ll post some longer thoughts on this soon.

Rayo, L., & Becker, G. (2007). Evolutionary Efficiency and Happiness Journal of Political Economy, 115 (2), 302-337 DOI: 10.1086/516737

Rayo, L., & Becker, G. (2007). Habits, Peers, and Happiness: An Evolutionary Perspective American Economic Review, 97 (2), 487-491 DOI: 10.1257/aer.97.2.487

3 comments

  1. Great discussion. A question from an economist trained to think in principal-agent terms. You note that you have “never been a fan of this [metaphorical principal-agent] approach, which is generally not adopted in evolutionary biology.” How else would one compactly describe (and solve for) the hypothetical end-point of natural selection given a fixed environment and set of constraints? Thanks.

    1. Having a quick scan of the article, it seems I still owe a piece explaining myself in more detail. Maybe in the next few weeks. In the interim….

      On the alternatives, I am not sure that a lot changes in the way the problem is solved. It is more a question of framing and language. Taking one step back, we can describe what “Nature” does (selects etc) in plain language with the usual provisos about Nature not really selecting anything. I see Robson and Samuelson’s The Evolutionary Foundations of Preferences in the Handbook of Social Economics as largely taking that approach. The language is simpler than if they had stuck to a principle-agent framing and language (even though they think about many of the problems in that way). However, I prefer to take and step further to how biologists communicate the ideas – natural selection results in organisms that appear designed to maximise their inclusive fitness; natural selection will favour those agents that produce the most offspring (or whatever inclusive fitness measure you use) subject to their constraints and environment. etc… Neater and well tested in the public sphere.

      Ultimately my dissatisfaction with the metaphorical principle-agent approach is that much of the work on the evolution of economic preferences is inaccessible and difficult at the best of times, and the principle-agent description is just another barrier. It may help a few mathematically inclined economists, and some of the tools used in the area may be useful in fancier parts of the paper, but it would be nice to generate material that would be absorbed by a wider audience.

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