The dangers of happiness

The idea that government policy should be focused more explicitly on promoting happiness or well-being (two terms used interchangeably) has been gaining support in the west. Proponents of this view argue that happiness indicators, based on surveys that purport to measure how happy people feel, have stagnated over decades. And a key reason is that governments have aimed to maximise a narrowly-defined, materially-based measure of economic welfare, Gross Domestic Product (GDP), rather than a more holistic indicator of welfare based on well-being.

But economists have known for a long time that GDP is an imperfect measure of the overall well-being of a country. In fact, no-one has stated this more clearly than Simon Kuznets, the founding father of modern methods of estimating GDP, in his Nobel Prize lecture in 1971.

In principle, using a wider measure of well-being is unobjectionable. As far back as the early 1970s, for example, the leading economists Bill Nordhaus and James Tobin made the first serious attempt to modify GDP by taking into account environmental factors.

But the devil is not so much in the detail, as in the whole attempt to turn this into a practical measure. For all its faults, GDP has a clear theoretical underpinning that measures the value added by the various activities carried out in the economy. In contrast, happiness or well-being indices inevitably involve a large amount of arbitrary judgement on what is in and what is out.

The old canard of the lack of correlation between happiness and GDP in the west is raised frequently. It is a mystery as to why this persists. There are powerful technical statistical arguments as to why this is not a serious point. Angus Deaton, professor of economics and international affairs at Princeton University, has successfully correlated percentage changes in GDP with happiness (and has found differing patterns when people evaluate their whole lives rather than their day-to-day emotional experiences), which is exactly what the statistical theory would suggest.

Meanwhile, the lack of correlation between measured well-being and the level of a whole range of factors that enhance human welfare is barely mentioned at all by happiness advocates. For example, in the United States, life expectancy for whites rose from 72 years in 1972 to 78.2 now. For blacks, the increase was even higher, from 64.6 to 73.2, representing not merely an absolute rise, but a narrowing of the gap with whites. Gender inequality, as measured by the median earnings of women compared to men, has fallen sharply. In 1972, women earned 58% of what men earned. By 2008, it had risen to 80%. Yet there was no correlation between happiness and any of these improvements. 

In both Britain and America, income inequality has risen sharply over the past 30 years, but happiness has not fallen as a result. We are told that there have been large rises in depression over recent decades; but this is not reflected by a downturn in measured happiness. (It is worth noting that, on technical statistical grounds, the lack of correlations in the three examples just cited is not subject to the same criticism that can be made when well-being and the level of GDP are compared, as both well-being and these three factors have bounds – they cannot rise without limit.)

The conclusion to draw from all of this is not that government policy is completely futile in trying to improve the human lot. It is that measures of happiness or well-being contain little or no useful information.

Standard eulogies pervade the happiness policy literature of the Kingdom of Bhutan, the only country in the world to adopt Gross National Happiness rather than GDP or GNP (Gross National Product) as its principal policy target. Despite this, Bhutan is far from an idyllic state. Unemployment and theft are rising. Further, the happiness of the majority is increased by active discrimination against the Nepalese minority, many of whom have been forced into refugee camps. Nationalist movements that persecute minorities are popular with citizens of many countries – and increase their happiness.

The danger is that governments will try to manipulate and control any measure of happiness or well-being that they construct. Most of these efforts will almost certainly be futile, in much the same way as short-term forecasting and control of GDP has, over the decades, been shown to be an essentially fruitless exercise. But it will not stop them from trying.

Government attempts to increase measured happiness, rather than making life better for us, may actually do the opposite: create arbitrary objectives that divert energies of public servants from core responsibilities; give many people the message that happiness emanates from national policy rather than our own efforts; and create pressure for government to appear to increase an indicator that has never before shifted systematically in response to any policy or socio-economic change.

These are exactly the mistakes of the target-driven mentality that pervaded the centrally-planned economies of the old Soviet bloc. We should learn from these rather than replicate them.

The real risk is that the well-being fanatics will use this as yet another excuse to show that experts – contrary to almost all available evidence – really do know better than ordinary people what is good for them. The assertion that “people are surprisingly bad judges of what makes them happy” is found throughout the happiness literature. Indeed, these happiness-policy activists often claim to know much better than elected politicians what is best for their voters. This elevation of the “expert” armed with a clipboard and some regression analysis is one of the most disturbing aspects of the happiness policy approach. 

No one can object to providing people with more information, and a wider measure of well-being is in principle very helpful. But the government must take great care about how it is used in practice.

GDP is not an all-encompassing measure of welfare; it simply measures the size of the economy. There are many things important to our well-being that are not captured by it. Those things need to be sustained by a strong civil society and a democratically-accountable, well-run government. If we cannot make convincing cases for them without “scientific proof” that they make people happy, we are totally morally adrift. Government does not fail because it does not measure happiness; it fails when its energies are misdirected on the basis of poor quality information.

Paul Ormerod is the author of three best-selling books on economics, Death of Economics, Butterfly Economics and Why Most Things Fail, a Business Week US Business Book of the Year. 

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