December 5th: life satisfaction ranges are revealing

As I’ve argued before, measuring and understanding individuals’ life satisfaction is a valuable complement to looking at GDP. The latter is an economic variable, but since money only buys an amount of happiness (in diminishing quantities as one gets richer), it is useful to understand what other factors contribute to people’s evaluation of their lives.

There are several reasons, however, why analysing variations in life satisfaction can be quite tricky. There are several different metrics for life satisfaction (depending on questionnaire methodology) which, while compatible, need to be manupulated to ensure one is comparing apples to apples. Perhaps more importantly, much of the variation in life satisfaction between individuals cannot be explained by easily observable variables, such as gender, age, income, marital status, health conditions, etc. This suggests that a significant proportion of someone’s life satisfaction could be genetic.

Nevertheless, it seems clear that improving satisfaction, where we can, could be a meaningful public policy goal — just as much as (or sometimes more than) improving GDP per capita. If so, it is not surprising that I’m coming in with my usual refrain: let’s make sure we look at distributions and not just averages. [I’ll return to this, by the way, later in the coming week, in the context of “levelling up”.]

Today’s chart illustrates this point for regions around the world. (It should be taken with a pinch of salt. Since it is a Sunday, I have not had a chance to fully reconcile some of the differences in the data from the World Values Survey — which I have used here because it provides a distribution in addition to averages — and the World Happiness Report, which is perhaps better-known, but uses a slightly different metric, has slightly different results and only provides a distribution for 2014–16).

Based on the World Values Survey data, and perhaps somewhat surprisingly, people tend to be the most satisfied with their lives in Latin America and the Carribbean. While there are plenty of less-satisfied people in these countries, too, almost a third of the population indicate that they are “completely satisfied” with their lives [large yellow block in top right hand corner of chart]. This illustrates how looking beyond averages helps understand what might be going on in more detail.

At the other extreme, and less surprisingly, people are least satisfied with their lives in Sub-Saharan Africa. Here, the average is dragged down by a particularly large proportion of people who are “completely dissatisfied” with their lives. In general, as well, the countries and regions with the lowest average scores tend to be those where the spread of responses (as measured by standard deviation) is the highest. In other words, life satisfaction inequality is higher in less satisfied countries.

No doubt the story is much more complicated than this. But what the chart visually reminds us (or at least me) of is that, first, by comparing averages we might read into them quite spurious differences. The regions in the middle — Western Europe to North America — look in fact pretty similar on this distribution chart. Second, it also illustrates how somewhere that’s on average quite good (e.g., Latin America and Southeast Asia) can be a home to hugely diverging experiences between different cohorts in the population.



I help complex organisations make the right strategic decisions through innovative, insightful and incisive analysis and recommendations.

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Tera Allas

I help complex organisations make the right strategic decisions through innovative, insightful and incisive analysis and recommendations.