Traditional income-based metrics that measure economic growth are necessary, but they do not tell us enough on their own. Metrics such as GDP do not explain, for example, why life expectancies in the U.S. are falling even as the stock market is booming and unemployment is dropping to new lows. Nor do they tell us why suicides are up in India when extreme poverty has fallen a lot.
On top of that, these traditional income-based metrics do not guarantee growth that is inclusive and sustainable.
This is where, as my colleagues and I argued recently in a paper published in , well-being metrics, at the very least, could provide some much-needed help in filling in the blanks -- and yield insight into sustainable policies.
Well-being metrics, including those derived from large-sale surveys and questionnaires such as , are considered "soft metrics" compared with GDP and other income-based metrics. However, they add a dose of personal reality to these "hard numbers" because they monitor what is actually happening in people's daily lives. The science of measuring well-being, meanwhile, has become increasingly robust.
These surveys measure three distinct dimensions of well-being: Hedonic metrics capture people's affective states -- enjoyment, stress or anger -- while evaluative metrics assess people's satisfaction with their lives, and eudaimonic metrics find out whether people have purpose or meaning in their lives.
Each of these metrics can potentially play a role in policy design, monitoring and evaluation in a number of important areas:
Well-being metrics can inform policy on social issues. There is a consistent "U-shaped" relationship between age and life satisfaction, with most dissatisfaction (and stress) happening in middle age. In the U.S., this coincides with the ages with the highest rates of overdose and suicide -- which are depressing the country's overall life expectancy rates.
Well-being metrics can also influence environmental sustainability. Existing research shows airport noise, air pollution, and irregular events such as flooding and drought bear high life-satisfaction costs. At the same time, people living in greener, urban areas and on coasts report higher satisfaction and less stress. Pro-environmental behaviors such as recycling are also associated with higher levels of well-being.
Policies based solely on income-based cost benefit analysis can fail to capture important side effects. For example, closing a remote, rural post office that does not manage much mail and is expensive to reach may make fiscal sense. However, well-being surveys in the United Kingdom show that daily visits to the post office are important to residents in isolated areas, particularly older Britons, and a decision like this would have high costs to their welfare.
Implications
Measures of economic growth and well-being each come with their own set of limitations, and the question of whether well-being metrics should have a central or secondary role in policy objectives is far from settled. At the very least, both need to coexist in the public and policy debate.
Well-being metrics provide important complements to income-based indicators of progress such as GDP and fill in the blanks where those measures fall short. In a complex and changing global economy like ours, these metrics can provide the early signs of populations at risk of failure, or highlight new ones that are ready to prosper.
This blog is based on the new paper, "Well-Being in Metrics and Policy," by Carol Graham, Kate Laffan and Sergio Pinto published recently in Science.
Carol Graham is a Senior Scientist for Â鶹´«Ã½AV and a Senior Fellow at the Brookings Institution.
Kate Laffan is a Fellow at the London School of Economics.
Sergio Pinto is a doctoral student at the University of Maryland.
Read the full paper here:
