(Back to the overview post)
Income growth is not a neat story, but technology pessimists would like you to think it is. Robert Gordon provides the following neat picture of ‘Growth in real GDP-per-capita, 1300-2100’ (here or unpaywalled summary, here).
The end-date alone should be enough to make us realise that this is a stylised representation, at best (and the 2008 onwards data is purely imagined, a ‘provocative fantasy’ in Gordon’s words). But even with that caveat it is a highly selective and misleading representation of growth.
I believe strongly in simple models and straightforward measures. But even the simplest measures can hide complexity and strong assumptions. This was brought home to me by two stories that have been in the news in the last fortnight, relating to two of the most common numbers you will come across in social science research and reporting: the unemployment rate and life expectancy. Both news stories raised questions about how these numbers were interpreted.
This is the first of what may become a series of posts, and focuses on life expectancy.
Trending #8 on BBC News recently was “How in a single year did life expectancy in the US drop by 12 years?”, a clickbait title for a story about the Spanish flu of 1918, which swept across the world in the wake of the First World War.
The 12 year drop caught my attention, so I dug around, and – confusingly – this statistic is both true and highly misleading. Like the “interest rate”, there is no single thing called “life expectancy”. Media reports rarely explain which version of life expectancy they mean – in this case the BBC links to a US National Archives webpage which is no more specific, and doesn’t cite a source. That’s frustrating, because there are important assumptions embedded in the ‘standard’ quoted life expectancy measure, which, spelt out, is ‘period life expectancy at birth’.
Q&A is a live panel discussion show, filmed before a studio audience, produced by Australia’s ABC. It is virtually identical to BBC’s Question Time for British readers. A few months ago I noticed that all the transcripts are posted online, and I thought this would be an interesting way to analyse the political bias, and representativeness, of the show.