Suicide ain’t painless III: Equality will make you happy (not)!

After my last post, some social justice minded readers asked about the relationship between unhappiness (as measured by suicide rates) and inequality, as measured by the GINI index (recall that the GINI index ranges from 0 to 100, the former corresponding to communist paradise, and the later to ancient Egypt). Luckily, the World Bank, in its munificence, has the requisite data, and so the results were not long in coming.

Suicide rate vs GINI index

The reader can see that the least egalitarian countries have the lowest suicide rates. Before we yield to temptation of using this study to yet again condemn socialism, we should note, as before, that correlation does not imply causation, and the countries with the higher GINI all tend to be in South America, and the ones with the lowest in central Europe, so there are many factors. Still, the numbers are what they are. What is particularly interesting is that the GINI index is negatively correlated with the GDP per capita, since the countries with the highest GINI index are essentially feudal, so what we have here are three quantities which are pairwise negatively correlated (not a mathematical surprise, exactly, but still fairly unusual).

Gini vs GDP

Suicide ain’t painless II: Does money buy happiness?

We continue our study of the Kaggle.com suicide data. The next question we ask is whether the level of per capita income affects the suicide rates. It should be noted that the GDP data in the suicides database is not the right data – it is not adjusted for inflation, which makes it less than useful. Instead, we merged the Kaggle data with the World Bank Data on GDP per capita Purchasing Power Parity in constant 2011 US Dollars. Without any further ado, here is the graph:

Suicide rate per 100000 vs GDP (in constant 2011 USD)

We see that while money might not be able to buy happiness, it does seem to alleviate the misery considerably. We should give the usual warning that correlation does not imply causation, since, for example, suicide rates in sub-Saharan Africa (represented here mostly by South Africa) are low, as are the incomes, while suicide rates in East Asia (Korea, Japan) are relatively high, as are the incomes, so there are underlying cultural reasons responsible for both x- and y- coordinates. Still, the relationship could not be clearer. An interesting companion graph is one where only the women’s suicides are counted (since the suicide rates among men are much higher, the similar graph for me is essentially identical to that for general population):

Womoen’s suicide rates

It seems that the situation for women is much more “binary”. There is high “unhappiness” rates until around $50K, but once that boundary is crossed all is well. This author will leave it to the sociologists to explain this phenomenon.