For various reasons, I have not yet fully read Steven Levitt and Stephen Dubner’s Freakonomics. Partly because of my wariness of the book’s outset – economists as a whole do a lousy job of describing, modelling and predicting the economy, so why the hell would we let them loose on the rest of life? Additionally, the cover art for the paperback (left) is lousy. So even though I bought the book nearly a year ago it’s taken me this long to burrow through the ennui . I am now about halfway through and I should really finish the book before reviewing it, but with a hiatus coming up (see next post) I thought I best write my thoughts now before I forget them. They could all be invalidated though once I’ve read the second half of the book so don’t bite me too much if I have got it wrong.
So, here goes. Freakonomics is written very much like Malcolm Gladwell – in fact, it could almost be a parody of Malcolm Gladwell; the way the story is pitched; the scene and dramatis personae spelled out at the very start; the sentences tumble out one after the other, interjected with the odd insight that turns out to be blindingly obvious; there is an overuse of rhetorical questions, and an obsession with the bright young thing making a bold and staggering breakthrough in a field previously obscured by traditionalism. The end result is something like this:
“Of course, other people had counted the average number of paper clips per box, but what Threepwod J. Butterkist, the 15-year-old prodigy economist from Harvard, was to take the data from across the United States, across all time, across different dimensions, and crunch it through a really big computer, which can do this much faster than an ordinary human being.
The results of Butterkist’s analysis were nothing short of astonishing. In fact, they were a challenge to the established orthodoxy about stationery distribution – it turns out that it can be accounted for by the clip counters’ incentives. What does this have in common with how higher education should be funded in the 21st Century and establishing a consensus on tackling global warming? As it turns out, they share a lot more than you might think.
This sounds harsh; actually I quite like Gladwell/Levitt and Dubner’s writing and means of storytelling and painting a vivid mental picture, and the tidbits of information are useful anecdotes for dinner party conversation, etc. But having read three chapters, there’s not much meat, no real philosophy that unifies the whole book and makes it a genuinely enlightening whole, just some chance observations about how some situations are in some ways similar to other very different-looking ones.
In their defence, the authors do try to draw some more overarching conclusions but in doing so have to make ridiculous simplifications. Real estate agents and doctors are both summed up as “experts” who (ab)use their position of knowledge, but there is no meaningful discussion on the differences – training a doctor is considerably more effort than training an estate agent; doctors deal with considerably more difficult ethical issues than estate agents; doctors are more strictly governed by professional bodies in what they can and cannot do, etc. etc. Equating both doesn’t really cut it.
Oh, and the obsession with incentives. Everything is reduced to incentive or disincentive – even the factors surrounding a moral judgement can be framed as “moral incentives”, with the implication these incentives can be quantified and even monetised; a roundabout way of saying “everyone has a price” . The end result is rather hollow and paints a rather depressing picture of the human being as an incentives-processing machine. Of course, monetary incentives are real, important and inform people’s decisions, but they’re not the complete picture. Rather than look at them in the context of other systems of information and human judgement, by making everything fit the incentives framework and be subject to the same means of analysis, the view is somewhat obscured.
Reading Freaknomics is a bit like reading Wikipedia – the trivia is brilliant, you can spend hours getting lost in the details and marvel at the dedication that some people have made into first producing and then analysing the vast amounts of data involved. However, the end result is pretty thin. You learn that systems can be tricked, hacked and gamed, and that some people will do it – but not really why, or for that matter why others don’t. Levitt’s endless fascination with the detective process, while uplifting and engaging, puts the things he is actually investigating, and the deeper reasons underlying them, into the shade. As a result, you’re lefting feeling hungry for more – the feeling there must be more to it than these anecdotes surely? Which is a pity. Perhaps someone from a less narrow background will be able to fill in the gaps a lot more effectively, but this book isn’t quite doing it for me yet.
As I say, this is based on the first three chapters alone – it could well be the start of chapter four contains some startling revelation that makes all the above moot. If so then please don’t bite my head off.