The happy science

Exploring the pitfalls of relating happiness and economic metrics

 
Author: David Orrell
October 21, 2010

Economics is often called the dismal science. The expression goes back to 1849, when Thomas Carlyle described the new field as “a dreary, desolate, and indeed quite abject and distressing one; what we might call, by way of eminence, the dismal science.” To the founders of neoclassical economics, though, it was actually all about happiness.

Neoclassical (ie mainstream) economics is based on the theory of utility, which Jeremy Bentham, the English philosopher and social reformer, defined as that which appears to “augment or diminish the happiness of the party whose interest is in question.” According to Bentham, the purpose of society was to satisfy the “greatest happiness principle” which meant providing the greatest happiness – ie utility – to the most people.

Neoclassical economists in the 19th century like Bentham’s follower William Stanley Jevons saw utility as a kind of quasi-physical quantity, which played a similar role in the economy as energy did in physics. Of course, while it is possible to measure energy using physical instruments, utility is a little more elusive; but Jevons argued that it can be inferred from prices: “Just as we measure gravity by its effects in the motion of a pendulum, so we may estimate the equality or inequality of feelings by the decisions of the human mind. The will is our pendulum, and its oscillations are minutely registered in the price lists of the markets.”

Relative spheres
The economy therefore came to be seen, in the words of Jevons’s contemporary Francis Edgeworth, as a machine for “realising the maximum energy of pleasure, the Divine love of the universe.” But there’s one problem with this theory. If the economy is supposed to be maximising happiness, and has been steadily growing larger – then why aren’t we getting happier?

In the US, since 1972, the General Social Survey has asked respondents: “Taken all together, how would you say things are these days, would you say that you are very happy, pretty happy, or not too happy?” The answer has been quite stable over that time – about a third say they are very happy, a little over half are pretty happy, and around 12 percent go for the last option. However the trend is slightly negative, and earlier results from the Gallup organisation showed that the number of people describing themselves as very happy peaked back in the mid-1950s at around 45 percent. Similar results have been found for other rich countries.

Over the same period, GDP has soared in real terms (in the US by about a factor three). So it seems that economic growth and happiness are not the same things. Indeed, this has to be the case, because the economy was nowhere near its present size for most of its history, so either we are the happiest generation ever, or the theory is wrong. In fact, studies of reported happiness levels show that income has a strong effect on a country’s overall happiness only if it is below a minimum level of around $15,000 per year, and there is nothing at all gained from going above $25,000 per year.

Part of the answer to the puzzle is that what counts is not absolute wealth, but relative wealth, as compared to one’s peers. As John Stuart Mill put it, “Men do not desire to be rich, but to be richer than other men.” This was illustrated by a US Gallup poll which asked “What is the smallest amount of money a family of four needs to get along in this community?” The answer simply tracked the average income. As other people get richer, we feel we must do the same just to maintain the same relative position.

New metrics
It follows that wealthy countries don’t become happier by becoming wealthier still. And because we tend to compare ourselves with those of our peers who are better off, any increase in social inequality – of the sort seen in most rich countries over the past few decades – can have the effect of decreasing overall happiness.

So what can we do about this? One proposed solution is to develop new economic metrics to replace GDP. After all, if economics is about happiness, then we should at least make sure we are measuring the right thing.

One problem with the GDP is that it includes a lot of activity that doesn’t seem aimed to optimise joy. For example, if the crime rate goes up, then GDP may actually increase because we spend more on security. Higher pollution can boost GDP because we need to spend money cleaning it up. But crime and pollution have obvious and immediate detrimental effects on mental wellbeing. Simon Kuznets, who pioneered the development of GDP, warned in 1934 that “the welfare of a nation can scarcely be inferred from a measure of national income.”

A 2009 study commissioned by the French government concluded that the GDP should be replaced by new metrics which account for factors like social inequality, crime rates, resource depletion, environmental damage, and reported happiness life satisfaction. There are a number of alternatives now available, ranging from the New Economic Foundation’s Happy Planet Index – the ratio of life satisfaction to ecological footprint – to the Buddhist state of Bhutan’s Gross National Happiness.

Alternatives to GDP are certainly called for. Personally, though, I am starting to believe that one detriment to human happiness is – economic metrics. All such metrics are misleading because of all the stuff they leave out, and they quickly become an end in themselves. Fuzzy, ambiguous, and multi-dimensional concepts such as a “healthy economy” or a “good life” can never be reduced to hard numbers. And to me there’s something vaguely scary about the idea of government economists trying to optimise my happiness.

For example, it has been found that a good way to become happier is to stop watching the news. Maybe that explains why Cuba scores seventh highest in the world on the Happy Planet Index – none of those pesky writers criticising government policy.

David Orrell is a mathematician and author. His most recent book is Economyths: Ten Ways That Economics Gets It Wrong