Data Science & Psychology Data Science applied to Values, Morals, Politics, & things that matter.

I recently read this blog post by Justin Wolfers defending the use of United States gross domestic product rather than measures of subjective well being (e.g. gross national happiness) to measure how well our country is doing.  For those of you who are unfamiliar with this debate, you can see this below video or this link to the Sarkozy Commission Report which prompted the French president to similarly question whether the French are using the right indicators to measure societal progress in their country.

Personally, I think this ends up being a subjective rather than an objective question and I think it's likely that people who are productivity oriented will never be convinced to use happiness measures primarily and that those who are care oriented will never be convinced to use GDP.  I'm currently working on a paper detailing why I think that this question of the 'right indicators' is a subjective rather than an objective question that depends on one's goals, warmth or competence.

Using more objective criteria, Wolfer's argument is that perhaps gross domestic product and measures of subjective well being are so highly correlated that there is no need to use new measures of psychological well being.  If they are so highly correlated, maybe there is no need to measure both.  I disagree for 2 reasons:

1.  The correlations he uses are with log transformed values of income and most people care about actual dollar values rather than log transformed values.  Consider this excerpt from the paper referenced:

Most early studies considered the relationship between the level of absolute income and the level of happiness, and thus often found a curvilinear relationship.In some cases the lack of evidence of a clear linear relationship between GDP per capita and happiness led to theories of a satiation point, beyond which more income would not increase happiness. A more natural starting point might be to represent well-being as a function of the logarithm of income rather than absolute income. And indeed, recent research has shown that within countries "the supposed attenuation at higher income levels of the happiness-income relation does not occur when happiness is regressed on log income, rather than absolute income." However, if happiness is linearly related to log income in the within-country cross section,then cross-country studies should also examine the relationship between average levels of subjective well-being and average levels of log income.

This is a very good academic point about satiation points, and it may be true that doubling the income of someone who makes a million dollars a year produces the same increase in happiness that doubling the income of someone who makes $20,000 a year.  But for the same million dollars that it takes to double a rich person's salary, we can create the same amount of subjective well being in 50 people who make $20,000 per year (50*20,000=1 million).  That fact is lost in a log transformed graph.  Real world allocation decisions are made with actual dollars, not log transformed dollars, which removes the skew that represents the United States' actual distribution of wealth.  (ps. feel free to correct me if anyone reading this knows more about log transformation than I and I'll edit this)

2.  Life Satisfaction, Happiness, and Smiling/Laughing are different things and the fault may be in the measurement of subjective well being failing to tap what Kennedy was talking about in his speech.  If I ask you how satisfied you are with your life, a large part of your answer may have to do with your current economic circumstances.  Wolfers and Stevenson do a good job in their paper of examining questions about life satisfaction and happiness separately and conclude reasonably that the measures are similar if we throw out outliers.  However, when we look at a question like "Did you smile or laugh a lot yesterday?", the correlation goes down to .27 from .82 (which was the correlation between log GDP/capita and life satisfaction).  

Try answering this question-> "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?"  What did you base your answer on?  Was it somewhat about your economic circumstances or work goals?  

Now ask yourself if you smiled or laughed a lot lately.  What was your answer based on? 

If you are like me, these questions tap very different parts of my life.  My thoughts naturally go to my progress with goals in question 1, whereas when asked about smiling/laughing, I tend to think of my day-to-day experiences.  There is a big difference between remembered happiness and experienced happiness.  General global assessments may indeed be related to economic well being, but perhaps the fault lies in the blunt ways we measure happiness where we don't really know whether the person is talking about being satisfied, joyous, lacking anxiety, feeling engaged, etc...  When asked about things which tap these more discrete constructs, GDP doesn't seem to capture them very well at all.   According to the Gallup World Poll data reported by Wolfers, having learned something interesting was uncorrelated with log GDP.  Feeling love is correlated .14.  Smiling/laughing, with a correlation of .27 with log GDP/capita, leaves a lot of unexplained variance that ought to be considered in policy making. 

To be fair, Wolfers himself acknowledges that "we can do a lot better" in measuring well being in previous posts and his defense of GDP is more to play devil's advocate as he states that he agrees with criticisms of the over-use of United States Gross Domestic Product to measure our country's progress.  I learned a lot in writing this post and will be following his well written blog and research closely in the hopes that it spurs more thought elaboration.