I’ve made a promise to myself not to blog anything until I get some more data processing tips written up on my website. But ‘ll break it just for a quick couple of links. One rocks, the other sucks.
Second, a graph spotted at Atlantic Cities which worried them because it looked like the whole world wants smaller households fast, and that’s going to cause environmental havoc. It worried me, on the other hand, because it just looked implausible. It’s amazing how complacent analysts* become as soon as they can switch on their stats software and do some fancy stuff. The common sense part of the brain powers down. Mmmm, breakpoints regression. Ooooh, bootstrapped starting values. Here’s a graph! What does it mean? Never mind that, let’s just publish the damn thing!
If you look at the slopes, the developed countries’ breakpoint is about 1893, which makes sense with industrialisation. The devloping countries have 1987, which doesn’t make so much sense. It’s not clear from the paper, but it looks like the breakpoint regression was done at country level, without weighting them by population. I’m happy to be corrected on that, but that’s what it looks like. That gives China and Swaziland exactly the same weight in pushing and pulling the line. And, most importantly, look over at the far right of the developing countries – there’s not many there with data since 1990 (they acknowledge this in the paper), and the ones who are there have smaller household sizes. Is it a trend or is it information bias? Smaller household <– healthier economy –> regular official statistics. This is not rocket science, it’s common sense. Think about what your data might mean! Aaargh.
* – by “analysts”, I mean the authors of the paper, not Emily Badger whose writing and keen eye for interesting stats I have admired for some time