Happynomics

The Science of Public Happiness

“The science of public happiness was how Keynes saw his work as an economist.”

Richard Davenport-Hines

In his book, Universal Man: The Seven Lives of John Maynard Keynes, British historian and biographer Richard Davenport-Hines described the legendary economist’s outlook as such. And yet, throughout subsequent discussion of Keynesian ideas and macroeconomics, the concept of happiness is not one that often arises.


It isn’t particularly difficult to decipher Keynes’ viewpoint. By manipulating certain economic outcomes, one could raise the living conditions of a nation. This would raise aggregate wellbeing, and by extension, aggregate happiness.


Economics speaks of utility, benefit and value. It assumes that the higher these things are, the better off people are. While this might be true, it fails to relate these things to empirical metrics of human wellbeing. Is it reasonable to link happiness to low price levels or high gross domestic product? Or is human happiness too nebulous to be described as a function of economic variables?

The Easterlin Paradox

In 1974, Professor Richard Easterlin of the University of Pennsylvania published a paper titled “Does Economic Growth Improve the Human Lot? Some Empirical Evidence”. The paper showed that measure of happiness have not grown over time alongside measures of economic prosperity, such as Gross National Income (GNI). This counterintuitive statistical finding was termed the Easterlin Paradox. Easterlin hypothesized that people may care more about their income level relative to their country’s average, rather than their absolute income level.


Over the years, this notion has drawn much criticism. Some studies claim to outright refute the Easterlin Paradox. Using expanded datasets and statistical techniques, Stevenson and Wolfers (2008) present a positive link between happiness and income over time. Veenhoven and Vergunst (2013) likewise illustrated a positive relationship between countries’ happiness and GDP growth. Ball and Chernova (2007) investigated the impacts of relative and absolute income. Taking a dataset of 43 countries, they regress several variables against a country’s average happiness, including multiple measures of relative income. Their findings similarly contradict Easterlin’s ideas, with people seeming to care as much about their relative income as their absolute income.


Other researchers have acknowledged Easterlin’s findings but have presented alternate explanations. Angeles (2011) suggested that the happiness effect of higher incomes were counteracted by other rising social trends, such as divorce. Castriota (2006) noted that the marginal utility of income decreased among those with higher levels of education. The paper suggested that higher income allowed for a more ‘stimulating cultural life’- more freedom to explore alternate ways to gratify oneself outside of consumption. On the other hand, lower income earners lacked this freedom and so live a life more dependent on material-goods for satisfaction. Kahneman and Deaton conducted a study amongst American households and found that income did increase happiness levels, up to a certain point. At around $75,000 USD a year, the marginal effect of income on happiness was diminished. Rather than attribute this to any benefits that happiness might bring, the researchers instead proposed that many of life’s pains were exacerbated by income levels below that threshold. Loneliness, divorce and poor health were mentioned as such pains.

Pro-Happiness Policy-Making

Easterlin’s paradox might serve as a cautionary tale against simply linking happiness to an economic variable. Regardless of the surrounding debate, Easterlin’s paper kick-started a slew of research into the relationship between economics and happiness. Human happiness data is now primarily collected through subjective wellbeing (SWB) measures. Data is typically collected via survey- respondents record their moods, emotions, and overall satisfaction. SWB effectively builds off the happiness data Easterlin originally used, which was also subjective in nature but less entwined with modern psychological methods.


With the proliferation of happiness economics, policy makers have become gradually more interested in boosting societal happiness through policy. Economists no longer solely rely on GDP or GNI as the independent variables against which SWB is measured. A few such variables are discussed below. By considering these factors alongside many others, economists concerned with increasing happiness have alternate avenues to do so.


While employment is expectedly correlated with higher SWB, there are various nuances which affect responses. While increased income can be a factor that raises SWB, it is mainly through the benefit of social and economic security that employment has such an effect.

Participation in leisure activities is strongly associated with higher SWB . Such activities are broadly defined and can range from browsing the internet to going on a jog. Leisure activities which involve physical activity or social interaction have a much greater positive impact on SWB than those which do not .

Cultural factors are an important consideration. Given the evident subjectivity of SWB data, the way different cultures perceive and define happiness poses an interesting challenge. For example, Western societies tend to be more individualistic, while Eastern societies have a more collective outlook. Individualistic societies tend to record higher SWB under conditions which allow greater self-expression, while collectivist societies record higher SWB under conditions promoting self-regulation .

Economics is by no means free of subjectivity, but for the longest time it seemed deeply delving into emotional response was a step too far. The emergent branch of happiness economics is reflective of improved wellbeing measurement, as well as a greater integration of psychology with economic methods.


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