The latest World Happiness Report, which showed that Indians are grumpier than most other peoples of the world (bit.ly/2nhIGtN), has attracted a fair amount of attention in the country. India ranked 122 out of 155 countries in the latest rankings, provoking several columnists to speculate on the reasons for such unhappiness in a country where surveys routinely find consumers to be upbeat (bit.ly/2l267TD) and citizens to be optimistic (pewrsr.ch/2o0zLLo).
The current obsession with the happiness index springs from rising discontent over the conventional measures of well-being, including measures such as per capita incomes and gross domestic product (GDP). So much so that one now reads headlines such as “Happiness is the new GDP”.
Since the 1970s, Bhutan has been using an index of Gross National Happiness instead of GDP to measure success. Many other countries have been trying to replicate the Bhutan model of happiness maximization. In the US, for instance, the state of Maryland (bit.ly/2nfkZmR) officially reports a measure called Genuine Progress Indicator which accounts for inequality, environmental degradation, health, and leisure.
In 2016, Madhya Pradesh became the first Indian state to set up a “department of happiness” (bit.ly/2nGXBtX).
Will we truly be better off with a happiness index replacing the GDP (and the related measure of per-capita income)?
The answer suggested by a wide body of research is a big no. And the reason is simple: if finding happiness is difficult, measuring it is even more so.
A seminal 1964 paper published by the American economist Richard Easterlin (bit.ly/2nfjKEk) showed that happiness and GDP did not move in the same direction although happiness and incomes within countries were correlated. The so-called ‘Easterlin paradox’ has spawned a number of research papers which have grappled with this and similar issues.
A recently published report by the London School of Economics is the latest in this tradition, and it suggests (bit.ly/2hpe18q) that mental health has greater impact on reported life satisfaction than income. To put it in numbers, income gaps explain only 1%of the variation in happiness in the community whereas differences in emotional well-being explain over 4%, the report found. An individual’s assessment of her well-being is determined by prevalent social norms, the report says. There is very little evidence that income drives happiness. Interestingly, the study also finds that spending on diagnosing depression and anxiety is likely to reduce misery by 20% which equals the effect of measures that are aimed at eradicating poverty, unemployment, and serious illnesses.
If making people happy is so important, why are policymakers not making it their primary target?
One reason why many economists and economic policy-makers do not wish to accord primacy to the pursuit of happiness is that they believe that it is inextricably linked to the pursuit of money and material well-being. To put it rather crudely, many economists think that money does buy happiness, at least till a certain level of income. In a 2010 study (bit.ly/2o5Q8YG), the Nobel Prize-winning economist Angus Deaton and the psychologist Daniel Kahneman took the Gallup poll data for about 500,000 residents in the US to show that happiness increases with income although there is an upper bound beyond which the income effect dissipates. Deaton and Kahneman also put a number to it: $75,000. Anything that goes beyond $75,000 doesn’t add anything to emotional well-being although the levels of “life-evaluation” or life satisfaction increased with levels of income even beyond this point, according to the authors.
Some of these results are consistent with the previous findings on the subject.
An important 2003 research paper (bit.ly/2oGTkex) by Rafael Di Tella of the Harvard Business School and his colleagues showed that reported happiness monotonically increases with income, and decreases during economic shocks such as a recession. The paper showed that reported happiness is strongly correlated to GDP across countries, and that these effects are persistent over time.
Many other economists are sceptical of the entire business of measuring happiness objectively because of the profound problems such a project raises. Economists are sceptical of the existing self-reported happiness surveys partly because they are not very sure what the numbers really mean.
Consider, for instance, the 2016 World Happiness Report (bit.ly/1Z09EQw). The report is based on responses to questions such as “how people see their lives”, where people are asked to evaluate their current lives on a scale of 0 to 10. The other popular survey, by Gallup, asks people about their experiences and feelings— “smiling, stress, pain, enjoyment”—responses to which are then combined to create an index.
The problem with such methodologies is that the data, or the answers to the questions, are not independent of space and time. In some countries, people might shy away from responding positively even when they are actually “happy”. On the other hand, some people may be compelled to respond that they are satisfied with their lives because of the prevalent norms in the society or community they live in. This makes the cross-country comparison of happiness deeply problematic.
The reliability of surveys in tracking happiness over time is equally dodgy.
Consider someone who has lost a job today and she reports a score of 3 on the UN Happiness Survey. Three years later, she still chooses 3 although she’s back in the workforce. This problem is known as hedonic treadmill in psychology. The idea is fairly simple: people return to their usual levels of mood fairly quickly after a major event of their lives (new job, marriage, etc.). Most studies in economics ignore hedonic adaption in their analysis of happiness.
A 2015 National Bureau of Economic Research (NBER) working paper by Miles Kimball of the University of Michigan and his co-authors try to model happiness while correcting for hedonic adaptation (bit.ly/2oM5HTE). But most other happiness studies tend to ignore this issue.
This is not to suggest that the data on happiness is entirely useless.
When conventional economic data analysis fails to yield any conclusive answer to a policy conundrum, such data can come to the rescue, if used carefully. A good example is a 2002 research paper (bit.ly/2o0xqA5) by Jonathan Gruber and Sendhil Mullainathan of MIT that looks into the effect of cigarette taxes on happiness. The existing empirical evidence on smoking till then was entirely consistent with two radically different models of smoking behaviour: a rational-addiction model, posited by the likes of Gary Becker, which suggested that higher taxes would leave smokers worse off, and an alternative time-inconsistent model, which suggested that higher taxes would make smokers better off by acting as a self-control device. To solve the policy conundrum, the researchers examined the direct impact of taxes on subjective well-being to come up with a result that seemed to support the time-inconsistent model: smokers were “happier” with higher taxes.
While such research can provide useful insights, the mission to replace GDP with a happiness index is doomed to fail. After all, despite its fair share of problems, the measurement of GDP is a fairly robust exercise, comparable to a large extent across space and time. The GDP measures the total output of all goods and services produced using prices as a common metric of value. Although it often excludes the informal economy or unpaid labour, the fixity of its definition across countries and over time makes it a reliable yardstick. But when it comes to measures such as the happiness index, it is hard to understand what people really mean when they respond to a question such as: “Are you satisfied or dissatisfied with your freedom to choose what you do with your life?”
To aggregate these responses and to come up with a measure that is consistent across time and space appears to be a nearly impossible task.
In 1781, the English philosopher Jeremy Bentham proposed a moral philosophy that put happiness at the centrepiece of action. Bentham wrote: “Take an account of the number of persons whose interest appears to be concerned, and repeat the above process with respect to each. Sum up the number. Take the balance; which, if it be on the side of pleasure, will give the general good tendency of the act, with respect to the total number or community of individuals concerned.”
Bentham presented a laundry list of important pleasures and pains. Sum up 14 pleasures and subtract 12 pains and you get a number that one could call happiness.
Easterlin took the Benthamite idea seriously and his 1974 paper argued that happiness matters. In a 2013 American Economic Review paper, economists Betsey Stevenson and Justin Wolfers (brook.gs/2nH5xeM) challenged his findings and marshaled evidence from multiple data sets to argue that there is really no paradox: subjective well-being and income tend to move together.
“The relationship between well-being and income is roughly linear-log and does not diminish as incomes rise,” the duo concluded. “If there is a satiation point, we are yet to reach it.”
Easterlin has remained unmoved though, and has maintained his position that happiness should replace GDP. To make his case, he cites China’s poor satisfaction with life since the 1990s (bit.ly/2nputI9) as an example. But, this decline in well-being also coincided with the emergence of unemployment and the fraying of social safety nets. The feedback effects from general economic conditions within a country to mental health are large. People are unhappy when they are insecure about their jobs, or when the government takes away their entitlements.
When one sifts through the various World Happiness Reports, it is clear that the variation in well-being as measured by happiness indices is very well explained by a number of economic variables including GDP.
The pursuit of happiness, at least for the developing world, lies in the pursuit of wealth and material well-being, irrespective of what the monarchy in Bhutan may say.
Sumit Mishra teaches economics at the Institute for Financial Management and Research (IFMR), Sri City.