Andrew Dilnot, former head of the UK Statistics Authority and current warden (no really!) of Nuffield College, gave a talk here last week, at our annual event honouring Florence Nightingale qua statistician. The ostensible title was “Numbers and Public policy: Why statistics really matter”, but the title should have been “Why people hate statisticians”. This was one of the most extreme versions I’ve ever seen of a speaker shopping trite (mostly right-wing) political talking points by dressing them up in statistics to make the dubious assertions seem irrefutable, and to make the trivially obvious look ingenious.
I don’t have the slides from the talk, but video of a similar talk is available here. He spent quite a bit of his talk trying to debunk the Occupy Movement’s slogan that inequality has been increasing. The 90:10 ratio bounced along near 3 for a while, then rose to 4 during the 1980s (the Thatcher years… who knew?!), and hasn’t moved much since. Case closed. Oh, but wait, what about other measures of inequality, you may ask. And since you might ask, he had to set up some straw men to knock down. He showed the same pattern for five other measures of inequality. Case really closed.
Except that these five were all measuring the same thing, more or less. The argument people like Piketty have been making is not that the 90th percentile has been doing so much better than the 10th percentile, but that increases in wealth have been concentrated in ever smaller fractions of the population. None of the measures he looked was designed capture that process. The Gini coefficient, which looks like it measures the whole distribution, because it is a population average is actually extremely insensitive to extreme concentration at the high end. Suppose the top 1% has 20% of the income. Changes of distribution within the top 1% cannot shift the Gini coefficient by more than about 3% of its current value. He also showed the 95:5 ratio, and low-and-behold, that kept rising through the 90s, then stopped. All consistent with the main critique of rising income inequality.
Since he’s obviously not stupid, and obviously understands economics much better than I do, it’s hard to avoid thinking that this was all smoke and mirrors, intended to lull people to sleep about rising inequality, under the cover of technocratic expertise. It’s a well-known trick: Ignore the strongest criticism of your point of view, and give lots of details about weak arguments. Mathematical details are best. “Just do the math” is a nice slogan. Sometimes simple (or complex) calculations can really shed light on a problem that looks to be inextricably bound up with political interests and ideologies. But sometimes not. And sometimes you just have to accept that a political economic argument needs to be melded with statistical reasoning, and you have to be open about the entirety of the argument. (more…)