Modeling and Economics
By Ian
Interesting post up at Simulation: The Weblog. David Upton notes an article from the Mises Institute that does a rather usual (for the MI) routine on the limitations of data and econometrics.
Upton notes:
The problem is that sometimes the assumptions do work. Mathematical models and simulations can be used with amazing effectiveness to predict reality, to help us modify or improve it, and so on. At the moment, this is mostly in fields like engineering where the 'physical laws' are well known and the effects can be readily quantified.
Of course, it's the uncertainty around just those "physical laws" that makes a good deal of assumptions about economic activity so...well, fuzzy. But if I understand Upton's point, I think I side with him. My version is much shorter: "The reliance on data and math is bad compared to what?" I'm not convinced that the vast majority of economics education is laboring under a false idea of the usefulness of mathematics. By contrast, it doesn't sound like the Austrian School is winning converts based on the obvious superiority of their approach either.
The rest of Upton's post is also interesting as it talks about the iterative process of refining modeling techniques. Though I will say it reads like a shorthand version of Kuhn. As the theory keeps requiring more and more special exceptions the model that used to fit reality pretty well loses applicability, making room for the next step forward.
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