The World Happiness Report 2018 has been published today (but no e-copy is available yet), so I will wait for the e-copy to became available. Meanwhile, as I was anticipating the report and was in an analytical mood, I reread the World Happiness Report 2017 and want to share some of my thoughts and observation based around that while we get ready for the new report to take the conversation forward.

 

 

The World Happiness reports are  based around measuring life satisfaction using a Cantril ladder and this is used as a proxy for happiness/ subjective well-being in most of the analysis. Sometimes, positive and negative affect, as experienced the day before, is also used as a measure of experiential happiness.

 

The world happiness report measures happiness of more than 150 countries, sampling about 1000 respondents in each country and uses data from Gallup World Poll. The Cantril ladder measures national happiness on a  scale form 0 to 10 and the top 10 happiest nations have an average national happiness level of about 7.4, while the most miserable, bottom 10 nations had an average national happiness of only about 3.4 , thus there being around 4 point gap of happiness that if bridged can make the world more happier.

 

The report measures six other correlates viz GDP per capita, social support, healthy life expectancy, social freedom, generosity, and absence of corruption, constructs that are theoretically and empirically linked to well-being. As expected GDP per capita and healthy life expectancy, which are indications of material prosperity,  do have an impact on national happiness, but the rest of the four factors that make up the social fabric of the country have a much larger effect.

 

To illustrate, social support was measured by a yes/no answer to the question as to whether one could count on someone in times of need. If one could move 10 % more people (who reported no) towards yes, then the increase in national happiness is predicted to be of the same amount that would be achieved by doubling the per capita GDP. And of course doubling the per capita GDP is much more difficult than ensuring that 10 % more population have someone they can count to in times of stress.

 

Similar effect, though of lower magnitude, was present for the rest of the social indicators. Also, other parameters like Gini coefficient which measures income inequality , and well-being inequality itself, were found to be associated with lower national well-being.

 

The case that economic growth and GDP is not the be all and end all, is aptly illustrated by the case study of China. China raised its GDP five fold between 1990’s and 2015-16, but the Subjective well- being (SWB) actually declined. The SWB during this period was U shaped with a trough in 2000-05, while the GDP was actually increasing and inflation at an all time low. As per this economic trend, SWB should have increased or at least maintained it 1990’s levels.

 

However, the situation becomes crystal clear when one looks at graphs showing unemployment rate and social fabric/ safety net indices (pension/ health benefits) during the same time which clearly paint a different picture of China’s economy and social method of alleviating misery structure. The unemployment rates peaked in 2000-05 while the safety net showed a trough, and this causally explained the trough in SWB much better, than the GDP story. Further analysis showed that it is those who are at lower rungs of economic ladder who are most affected in such circumstances.

 

The story of America is similar: per capita GDP growth which has tripled since 1960 has not lead to corresponding gains in happiness; as a matter of fact SWB is declining while GDP is growing in recent years. This is attributed to breakdown in social fabric.

 

An interesting fact that was highlighted by data from African nations, was that happiness depends on good governance and this can be conceptualized as both the ability to deliver services as well as democratic institutions. It was found that ability to deliver services was much more important, at least in African context, and people of Africa were willing to trade democracy for access to services.

 

The report also had a section on how we can best alleviate misery and increase happiness for the maximum people; increasing income, increasing years of education, reducing unemployment, ensuring people stay married/ have a partner, preventing physical illness and preventing mental illness (depression and anxiety) were all considered important as each of this predicts happiness. However, it was found that the mots cost effective is by focusing on alleviating mental illness as that impact happiness levels more than anything, including physical illness.

 

Another analysis showed that emotional health at age 16 was better predictor of adult happiness than academic competence at that age. This makes a strong case for focusing on emotional and behavioral development of children and for positive education.

 

Another section of the report looked at work determinants of happiness and found that unemployment was again a big no-no, causing a lot of misery directly and indirectly even in those not unemployed. Of course blue collar workers had lower satisfaction levels than white collar workers and the usual factors that affect job and overall satisfaction, like autonomy at work were highlighted.

 

Overall, I think its a wake up call to policy makers, to focus more on social determinants of happiness and not get obsessed by economic indices like per capita GDP.  I’m hoping 2018 report builds on these earlier observation and makes a strong case for policy changes.