Advantages of crude models

One advantage of crude models is that we know they are crude and will not try to read too much from them. With more sophisticated models,

… there is an awful temptation to squeeze the lemon until it is dry and to present a picture of the future which through its very precision and verisimilitude carries conviction. Yet a man who uses an imaginary map, thinking it is a true one, is like to be worse off than someone with no map at all; for he will fail to inquire whenever he can, to observe every detail on his way, and to search continuously with all his senses and all his intelligence for indications of where he should go.

From Small is Beautiful by E. F. Schumacher.

Crude models are easier to implement. They may also be more robust and better descriptions of reality.

Obviously crude models are not always better. But I like to have some evidence that a complex model is worthwhile before I invest too much effort in it. And I’m well aware of forces that reward complexity for its own sake.

7 thoughts on “Advantages of crude models

  1. “All models are wrong; some are useful.” Albert Einstein

    The advantage of technology is that we can create and solve more and more complicated models. The problem is that people forget that the models are still wrong. I’ve seen greybeard engineers disprove months of computer work using a pencil and paper.

    When we train new apprentices (structural analysis of critical airplane components) we require that they come up with some crude models to put an upper and lower bound on the answer before reviewing their computer solution.

  2. I think it is the same in quantitative finance: better use Black Scholes and have a working risk management which plans for the worst than having a super sophisticated model which nobody understands and betting your last shirt on it.

  3. In my experience people forget really quickly that the models are crude and do start to read too much from them. I found that once I developed quick and dirty models (thinking ‘they should be used only this year until we get something better’) they are still being used almost ten years later. Scary.

  4. I’ve thought about this particularly with regard to Kaggle, Netflix Competition, etc. Pragmatic Chaos & BellKor squeezed the lemon nearly dry, but did they provide real insight into the problem of movie recommendations?

    If you look at the leaderboards on Kaggle, you’ll usually see that all the top scores are razor thin margins on each other. Rarely do you see a jump-like improvement.

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