A Capital Idea Part 79: Life Satisfaction, Income Inequality, and Quality of Life
Denmark makes a nice example, but true knowledge requires looking at the cumulative reality, not selective cherry picking of the best examples. I realized last time that I should look at these issues across the nations of the world. If I had access to statistics programs, I could run correlations between these variables, but in the absence of these programs, I spent most of the day yesterday comparing the highest and lowest 10 nations on these variables, an informal technique which yields very similar conclusions to that of a correlation coefficient. I also found one site which had a scatterplot of the relation between income and life satisfaction (http://www.gallup.com/poll/104608/worldwide-residents-richer-nations-more-satisfied.aspx), but it didn't give the correlation coefficient and income isn't quite the variable I most wanted to look at, preferring Quality of Life instead.
What I found was mostly as I had postulated. One comparison had very weak results, in the direction I expected, and another had even stronger results than expected, but in general, they showed that income inequality goes with low quality of life and low quality of life goes with poor life satisfaction. The link between income inequality and life satisfaction is the weak one, but I will present explanations for that.
The link between per capita national income and life satisfaction seems to belie the old saying that "Money can't buy happiness." However, the situation is not that simple. Actually, as national income goes up, the relation between the two variables becomes weaker. In other words, nations where most of the people are so poor that they are destitute and have trouble meeting basic needs such as finding enough to eat, truly have poor life satisfaction, with good reason. However, nations where people generally have enough income that they don't have to worry about starving or meeting basic needs, tend to have fairly good and similar life satisfaction, whether it is a particularly rich nation, or a modestly wealthy nation. Differences among these "better off" nations are probably much more due to other factors such as income inequality, cultural factors, social harmony, etc. Overall, looking at the scatter plot graph, it looks like a fairly strong correlation between per capita income and life satisfaction, perhaps around .60. The scale for correlations ranges from -1 (complete opposites) to +1 (complete correspondence).
Next, I looked at the GINI Index (http://en.wikipedia.org/wiki/List_of_countries_by_income_equality), which measures income inequality, focusing on the ten nations with the highest GINI Index, and the ten with the lowest. These nations were compared on both Quality of Life, and the Satisfaction with Life Index. The ten nations with the lowest GINI Indices, in alphabetical order, were Croatia, Denmark, Finland, Germany, Hungary, Japan, Norway, Slovakia, Slovenia, and the Ukraine. Of course, Denmark has the lowest GINI Index. These nations have relative income equality. The ten nations with the highest GINI Indices, in alphabetical order, were Bolivia, Botswana, Chile, Columbia, Guatemala, Haiti, Honduras, Panama, Paraguay, and South Africa. Actually, some nations were left out of these lists because they did not have data on the Satisfaction with Life Index and/or the Quality of Life Index, so these are the top and bottom 10 nations on the GINI Index which have data on all 3 variables. Also, there is not a specific year for the GINI Index, as the data year varies for different nations, but in every case, it is from the past several years.
There are 111 nations with Quality of Life data as of 2005 on Wikipedia (http://en.wikipedia.org/wiki/Quality-of-life_index). I took the Quality of Life rankings of the ten nations with the lowest GINI Indices, and found that they averaged 40.25. The Quality of Life rankings of the ten nations with the higest GINI Indices averaged 77.5. Thus, Quality of Life was far worse in nations with great income disparities than in nations with small income disparities. Next, I did the same type of comparison between the GINI Index and Satisfaction with Life, which lists 178 nations on this index as of 2006 (http://en.wikipedia.org/wiki/Satisfaction_with_Life_Index). In this case, I found that the ten nations with the lowest GINI Indices averaged a rank of 72.6 on Satisfaction with Life, while the ten nations with the highest GINI Indices have only a slightly higher average, 76.3 on the Satisfaction with Life Index (lower rankings being better). Of course, as many people have pointed out, Satisfaction with Life is essentially a subjective measure. The two largest biases in this measure which I can identify are the tendency to be self-deprecating as opposed to being narcissistically egotistical, and peoples' life expectations in terms of what it takes to make them feel "happy." For example, I noticed that Satisfaction with Life ratings for Asian nations tend to be low, which I think has to do with a relative tendency to be self-deprecating by citizens of Asian nations. There was only 1 Asian nation on either GINI Index list, Japan, but it ranked 90th in Satisfaction with Life even though it is 17th on Quality of Life and has one of the world's very lowest GINI Indices. In terms of peoples' expectations, I would expect these to be relatively low among poor people with relatively little hope of social progress. Poor peoples in nations with great income disparities, in other words, may be easier to please, assuming they accept their situation and feel that there is little they can do about it. (Otherwise, with the empowerment of the people, a revolution is in the offiing.) They are essentially comparing themselves to a lower standard than other peoples.
The final comparison I did was Satisfaction with Life, compared with Quality of Life. The reason I felt this comparison was needed is that I felt, as explained in the previous post, that Quality of Life is a better measure of a nation's wealth than is per capita income. Also, if I am correct, there should be an even stronger relation between Satisfaction with Life and Quality of Life than there is between Satisfaction with Life and per capita income, because Quality of Life takes into account variables such as access to good, cheap health care or education -- things which progressive societies do for their citizens -- which contribute to life satisfaction, which per capita income does not. It is important to note that there are no measures of life satisfaction included in the Quality of Life measure. The two measures are completely independent of each other. However, Wikipedia states that the Satisfaction with Life Index correlates strongly with health, wealth, and access to basic education. The results I found were striking. The ten nations with the highest Satisfaction with Life ratings which also had Quality of Life ratings were, in order of rank, Denmark, Switzerland, Austria, Iceland, Finland, Sweden, Canada, Ireland, Luxembourg, and Costa Rica. The ten nations with the lowest Satisfaction with Life ratings which also had Quality of Life ratings were Rwanda, Bulgaria, Pakistan, Russia, Georgia, Belarus, Turkmenistan, Armenia, Ukraine, Moldava, and Zimbabwe, with Zimbabwe having the lowest rank. The average Quality of Life rank for the top 10 nations on Satisfaction with Life is 10.9, which is not that far from being the top 10 nations overall in terms of Quality of Life. In contrast, the 10 basket cases at the bottom of the life satisfaction list, have an average ranking of 93.8 out of 111 on Quality of Life, not far from being as bad as it could be. In other words, it appears that there is an extremely high correlation between Satisfaction with Life, and Quality of Life -- higher than the correlation between Satisfaction with Life and per capita income, as I had postulated.
To put these findings in context, let me reiterate from the previous post, the variables found in the Quality of Life Index. These are health, family life, community life, material well-being, political stability and security, climate and geography, job security, political freedom, and gender equality. In other words, nations which have progressive policies such as empowerment of women, inexpensive and effective health care, trade union membership (found in the community life variable), high public sector employment (job security leading to low unemployment) and so forth, also tend to have higher Quality of Life ratings (and thus good resource use and national wealth), which correlates very highly with life satisfaction.
Of course, we have a "chicken or egg" problem with all of these correlations, or to be more technical, the issue that correlation does not imply causality. Whether life satisfaction leads to a better quality of life, vice versa, or some of both is not a settled issue, although it's probably some of both. Simlarly, whether relative income equality leads to a better quality of life, vice versa, or some of both cannot be determined by the fact that the two variables are related. If I could run a sophisticated causal modeling analysis including government policies, I suspect I would most likely find that progressive government policies (including the high tax rates that these necessitate) lead to a lower GINI Index, leading in turn to better quality of life, which finally leads to better life satisfaction. High life satisfaction also should have a feedback loop to quality of life (i.e., the economy) and even to government policies.
Such conclusions of course await futher research, unless somebody has already done it. We need to be aware of what works and what doesn't work in terms of government policy, in order to have a nation of informed and politically involved citizens and voters. Presumably, a nation of informed citizens will choose by and large, policies which work. The problem is when misinformed or uninformed citizens vote for politicians who advocate policies that do not work, when only a biased minority of the population even votes, or when politicians with their own agendas fail to carry out the will of an informed electorate. The importance of sharing information which can show us that progressive policies work well and conservative ones don't work so well, cannot be overstated.