Institute For The Future

The Challenges of Measuring Wellbeing

 

If you knew that you could work an extra ten hours a week for the next year and make 20 percent more money, would you? Your answer, whatever it is, probably depends on a whole host of factors including what sorts of family obligations you have, how much you like your job, and how much you, personally, value money. You and your spouse, to say nothing of you and your coworkers or you and your neighbors, all have at least slightly different perspectives on this question. In effect, what this example, and other similar questions point to, is that, as a recent article by Koen Decancq and Maria Ana Lugo highlights, wellbeing has as much to do with individual preferences as clearly quantifiable measures and require putting statistical weights on personal preferences. Both are factors that further complicate the important but tricky challenge of understanding how to measure wellbeing, and, as a practical matter, also underscore what I think we'll begin to see as an equally important challenge: How do we, at large scales, develop systems that take into consideration variables that we can't accurately measure?

 

Last month, my colleague Mani Pande noted a recent report by the French government aimed at moving beyond GDP toward broader measures of wellbeing including sustainability, quality of life, and other critically important measures. What's interesting to note, however, is that GDP was never supposed to be a measure of welfare or anything like it. Simon Kuznets, who developed the GDP measure in 1934, said about GDP that "the welfare of a nation can scarcely be inferred from a measure of national income."

 

Fast forward 75 years and shifts in GDP are some of the most important data in the world. As Joseph Stiglitz, one of the leaders of France's efforts to develop new measures, wrote when several months ago: "In our performance-oriented world, measurement issues have taken on increased importance: what we measure affects what we do."

 

Hence the calls to measure happiness, sustainability and other variables beyond economic output. The challenge is that while economic output is a pretty straightforward variable, things like quality of life are far messier, and involve far more complicated tradeoffs.

 

To take an extreme example, The Atlantic rounds up some recent criticism of the new book (which I haven't yet read) The Politics of Happiness. The Atlantic notes that critics of the book have pointed out that while Bhutan, by improving happiness, might be a model for integrating wellbeing measures into policy, it also happens to be "extremely poor and authoritarian." In much the same way you can ask yourself if you'd trade a raise for less free time, you can ask yourself: Would you live in a poor dictatorship if it made you happier?

 

In the realm of more realistic tradeoffs, I've been playing around lately with Facebook's Gross National Happiness measure and seen that Monday and Tuesday are almost always have the lowest Gross National Happiness scores. Most people also happen to believe that Tuesday, followed by Monday are the most productive days of the work week.

 

My point is not to discount new measures of wellbeing or growth--I think growth for growth's sake is a fairly asinine goal. As Stiglitz has argued:

 

 

 

If we have poor measures, what we strive to do (say, increase GDP) may actually contribute to a worsening of living standards. We may also be confronted with false choices, seeing trade-offs between output and environmental protection that don't exist. By contrast, a better measure of economic performance might show that steps taken to improve the environment are good for the economy.

 

 

 

 

Which is to say, I think it's pretty clear that GDP, by itself, is at best a suboptimal way to measure social wellbeing and hope (and expect) to see projects like Stiglitz's gain traction in the coming years.

 

But I also think we need to recognize the limits of any measure we have. Decancq and Lugo make a related, but slightly different point, which is that "As long as there is no widely accepted theoretical framework on how to set these trade-offs, the researcher has no choice than to rely on her common sense and to be very cautious in interpreting" which metrics of wellbeing matter the most.

 

I think this point--that we need to be "very cautious in interpreting" metrics--is their most important. While some researchers and policymakers might be able to develop more holistic, macro-level measures of well-being and sustainability to some degree of reasonable consensus, it seems unlikely to me that we'll ever have a "widely accepted theoretical framework" for how individuals determine their own definitions, goals and ideas behind wellbeing.

 

More generally, I think there's a broader lesson from the history of GDP that's instructive here. As Stiglitz put it, "what we measure affects what we do." As important as it will be to move beyond GDP, I think it will be equally important to recognize that we can't measure all of the important things in the world. We need better metrics, in other words, but we also need to get better at accepting the limits of those metrics.