asked 15 Apr '12, 09:40
I am always amazed to see a complicated looking mathematical derivation starting from a fundamentally flawed assumption (all too common in the social sciences IMNSHO, I think this technique is used to intimidate those who are impressed by complicated math). Bryan Caplan's model is a classic example of this. He starts off by assuming "Intelligence is uniformly distributed between A and 100+A" which is ridiculous. IQ is roughly a Gaussian distribution with mean 100 and SD ~15. (even if one doesn't grant that intelligence ~= IQ I think it is hard to argue that intelligence is not something close to a Gaussian) It is possible this makes no difference to the analysis, but a uniform distribution and a Gaussian distribution are very different. For reference, direct link to his original post: http://econlog.econlib.org/archives/2012/04/is_rising_educa.html
@robrambusch I upvoted you because I thought some of the discussion in your link was good (and appreciated being pointed to the conversation), but given Caplan's assumption I'm not even willing to spend the time trying to follow his analysis. Sometimes overly simplistic models can be helpful understanding the world (the Model Thinking class makes this point repeatedly, and it is a good one), but discerning whether or not this is the case can be hard work. Sometimes overly simplistic models are unhelpful (or even detract from understanding by leading to incorrect conclusions).
answered 15 Apr '12, 12:33