What I Learnt From Superfreakonomics

Recently went for a lecture by Steven Levitt and Stephen Dubner, authors of Freakonomics and Superfreakonomics, the latter of which I’ve just finished reading.

Firstly, a little bit of context: Freakonomics was the one book that convinced me that I should be an Economics major. (Sad, I know.) In his first book, Levitt investigated weird and taboo issues using economic tools: data, models, regression analysis, correlation and causality, etc. Using economic lenses to look at difficult issues such as abortion, prostitution, etc strips away the morals of the situation and focuses on the sometimes surprising underlying causes. In Levitt’s words, “being moral isn’t bad, but it gets in the way of answering questions.”

Sadly though, I was a little disappointed by his lecture. Aside from getting my copy of Superfreakonomics signed by the authors (whoohoo!), I didn’t take away as much as I did when Levitt came to speak at Penn. (I think it was, in part, because of the inane boring questions asked by the LSE audience, which had as much quirkiness as my Financial Econometrics textbook)

Some points raised by Levitt:

Macroeconomics, often the public persona of the Economics discipline, is way too demanding and complex to be useful. Economists specializing in it often get caught up in the mathematics of the discipline to be able to provide any useful information. (Sounds a LOT like my Financial Economics class). Thankfully though, there seems to me a movement away from this in academic circles to something more descriptive.

Microeconomics, however, is much easier to understand. We intuitively understand our own individual behavior, and hence it’s easier to come up with models that would generally describe how a rational individual would behave. (However, this doesn’t mean that everyone would behave rationally) With an idea of individual behavior, it’s a natural step to aggregate behaviors in order to get an idea of how an economy might run.

I disagree slightly with that last point. In the words of Tommy Lee Jones in the first Men in Black movie: “A person is smart. People are dumb, panicky, (and) stupid.” Or conversely, James Surowieki would claim in The Wisdom of Crowds that a crowd is a lot more intelligent than the sum of its parts.

Sorry, I digress – let’s talk about the book.
Superfreakonomics, while raising some interesting perspectives on prostitutes, politicians, drunk driving vs drunk walking, and climate change, didn’t blow me away as much as the first book did. A few gems within it are worth mentioning:

1) Levitt describes a counterterrorist agent who built an algorithm to identify potential terrorists by finding patterns in their banking behavior – withdrawals, deposits, and yes – purchases of life insurance. It proved to be really effective too. Out of the millions of accounts the bank had, the algorithm zeroed in on less than 50 suspicious accounts. That’s helluva accurate for that huge a scale. And I thought algorithmic trading was hard.

2) Before germ theory was discovered, there was a suspicious pattern of high mortality rates among women in labor who were treated by doctors. The cause? Doctors weren’t washing their hands.

3) A pimp adds more value for her clients than a Realtor does.

4) The real story behind the Kitty Genovese case and the bystander effect. I always thought that was a straightforward case of how people lack altruism and our world is full of selfish, coldblooded, indifferent people. Levitt provides a different explanation of the events surrounding Genovese’s murder.

4) The best solutions to our hardest problems – car safety, global warming, mortality rates in hospitals – are usually cheap and so blindingly simple that no one would think of implementing them – until they are actually executed.

Am currently trying to come up with a trading strategy along those lines – we’ll see where that gets me.

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