“Causality is almost always in doubt”

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Dave Backus writes:

We macroeconomists are thrilled with the Nobel prize for Sargent and Sims. But on causality: they spent more time showing how hard it was to identify causality than showing how to do it. And that’s a fair assessment of our field [economics]: causality is almost always in doubt.

More here.

If I were in a snarky mood, I’d say something like, Causality is always in doubt in economics . . . unless you’re talking about abortion and crime, in which case you can be absolutely certain.

But I’m in a good mood right now so I won’t say that. Instead I’ll just remark that, as a statistician, I’m positively thrilled that somebody named “Sims” received a major award.

11 thoughts on ““Causality is almost always in doubt””

  4. Agreed!

    Some lighter stuff with a statistical flavor:

    Why Econometrics Should Always and Everywhere Be Bayesian (slides form a presentation)
    Comments on Angrist and Pischke (critiques quite a lot)
    On an example of larry wasserman (defending the bayesian viewpoint and fun)

  5. Pingback: More reason to like Sims besides just his name « Statistical Modeling, Causal Inference, and Social Science

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  9. I am wondering about a statement you made:”Causality is always in doubt in economics . . . unless you’re talking about abortion and crime, in which case you can be absolutely certain.” Why do you believe that the causality of crime (or abortion) is absolutely certain? If I do understand you right, you believe that the causes for criminal behavior are to 100% definable. As a social researcher/criminologist I doubt that thought. And as a PhD student I would be thrilled if you could elaborate on that.

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