I went to a talk a few weeks ago by Richard Wilkinson and Kate Pickett, global health researchers who have written a book called The Spirit Level. They were quick to explain that, while the name makes perfect sense in British English, it has been a source of continuing confusion in American English. What is a “spirit level”? It’s a building tool, a type of ruler with little bubbles in it to show when it is parallel to the ground. Maybe it’s called a carpenter level in the states, or just a level when the context is clear.
I would have called it “Inequality vs Stuff”, or at least that’s my description of the talk: a vast array of scatterplots showing the relationship between income inequality and different measurements of population health. Here is one that is typical for their case:
When they told the story, they started with a composite health index scattered against inequality, since that has much less noise, and then use the noisy plots like this one as supporting evidence when they show that the relationship holds for everything.
The slide that stuck with me the most is one that diverged from their story a little:
Not population health this time, but still interesting. Something to share with your entrepreneur friends.
These plots seem like enough fun that I made my own, based on a question from the question and answer portion of the talk. I’ve forgotten who, but someone in the audience asked “How is inequality related to total fertility rate?” and the answer from Wilkinson and Pickett was along the lines of “We never thought to check, how do you think it might be related?”
Since I had the data lying around from my attempts to learn about model selection last summer, I made myself the plot. Turns out there is not much of an association.
The only example of a non-association the speakers mentioned was a surprise to them: suicide rates are not correlated with income inequality.
Healthy Algorithms 
Fascinating!
I’ve heard that Fertility is more correlated with how “macho” a society is.
This explains Japan, Italy, Spain being low and Sweden, Finland, Denmark and Norway being high.
Not sure how the USA fits into this … maybe immigration.
Ah, good old armchair sociology.
Imagining for a moment that patents are actually a good measure of innovation:
Country A and Country A’ both consist of 1M scientifically trained, well-educated workers. They spent their time inventing great stuff to make the world better, and also cleaning their houses, gardening, plumbing, and paving roads. Country A has a strict anti-immigration policy. Country A’ allows in a million less educated workers from B, a poor country. In A’, the B workers take on low-paid jobs like cleaning houses, gardening, plumbing and paving roads. The B workers are better off than in their home country. The A’ workers have more leisure time, and they also spend more time time working and inventing, because they’re good at inventing and those B workers need to be paid.
Which country is better off? Which country will have more patents per million inhabitants? Which country would you rather live in?
The problem with a lot of these analogies is that you’re comparing a small culturally and racially homogenous population with a large nonhomogenous one. Of course violence will be higher in the US in states that include large populations of poor, disenfranchised people with poor prospect. Of course life expectancy will be lower there. But what does that tell us? That these states should improve their statistics by kicking out poor nonwhite people?
It would be interesting to see the relative rate of innovation between more comparable populations — say those in Japan, Finland and the US who have technical degrees. I’d expect innovation to be *higher* in the US because of its greater economic openness, but I’m not sure.
Mugizi: It seems like fertility rates are a great mystery in their own right. I’ve heard a good story for their relationship with “development”, which is probably as hard to define and measure well as the macho index.
Rif: You’ve zeroed in on the big concern I have with this sort of work. I think there is great evidence that high income inequality is associated with all sorts of bad things, and I’m open to the idea that there are some causal pathways, through stress hormones, for example. But if you believe this evidence, and you want to improve health, you have some highly divergent options. Wilkinson and Pickett said it doesn’t matter how a country does it, be it government mandated redistribution or voluntary salary caps, but they didn’t mention the less friendly ways of reducing inequality, like closing the borders and deporting the poor.
Through happy chance, I read a paper today for our journal club that tries to resolve this issue, promoting the “neo-material interpretation” over the “psychosocial interpretation”. It is 10 years old, so I’m interested to know how this side of the debate has evolved since then.