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.