Why we don't need so much copper any more

A couple of weeks ago I posted about demographics being possibly the most important influencer of social change in today’s world. Then the other day, Arts and Letters Daily directed me to this review by Bill Gates, of a book by Matt Ridley called The Rational Optimist.

The book is about the concept that prosperity has grown and evolved throughout human history through the mechanism of trade – not a new idea by any means but he’s quite radical about it, suggesting that trade was a significant factor in our lives even during humanity’s very earliest existence. He also (according to the review) takes the view that apparently major social problems tend to sort themselves out of their own accord, citing fears from last century of overpopulation and mass starvation that have subsequently abated due to falling fertility rates in developing countries and huge advances in the efficiency of agriculture. How he expects climate change to sort itself out I’m not sure; Gates takes him to task on it and also on his optimism about African development.

There are a few other good things in there: the quotation that Bill Gates likes from John Stuart Mill – “I have observed that not the man who hopes when others despair, but the man who despairs when others hope, is admired by a large class of persons as a sage.”

I also like the idea that we should be optimistic because humans have so often innovated their way out of tricky situations: people used to worry that we would run out of copper, but now a lot of the work that used to be done by copper cables is done much more efficiently by fibre optics (and wirelessly?).

Finally, providing me an excuse to post about something I have been meaning to for ages, the article mentions Hans Rosling’s Gapminder website. I’ve probably said this about several other things already by now, but still: this is the coolest thing on the internet. You can educate yourself about everything to do with economic and demographic trends, globally, by choosing what variables you’re interested in and seeing them evolve over half a century or more in awesome animations. For instance, this animation shows GDP/capita against life expectancy, in hundreds of countries, from 1800 to 2008 (life expectancy in Afghanistan in 2008 was only four years more than it was in the UK in 1800. GDP/capita in most of the African countries shown is still lower than it was in the UK in 1800 – when inflation adjusted). I could play with that all day: this one and this one are a great contrast – the first is GDP/capita against % of population aged 20-39, which evolves quite radically over time but ends up in a sort of bow shape, with the top and bottom of the GDP scale having similar proportions of the population in that age cohort, and the middle having substantially more. The second is GDP/capita against proportion of population aged 40-59, and it’s much more linear: the older the population, the richer. Although the causality probably runs in the opposite direction: rich countries are able to keep their populations alive and healthy (economically productive) for longer.