vwfwerwetqwerqw

Pointing out flaws in other analysis doesn't actually justify your own preferred explanations. See creationism.

Well, I've certainly learned a lot from this discussion. Although, I find myself agreeing with the guy who called them weirdos, the Austrian school, as it has been explained, does seem really weird to me.

Non-predictive analysis can't be used to make decisions, and therefore can't have any effect on the real world unless it is being used incorrectly. By their own argument, Austrian economics is a waste of time.

A dislike of stochastic models (however understandable in historical context) should not be taken seriously in the modern world. Complex chaotic systems are modelled through intensive probabilistic simulation all the time.

Algorithmic analysis is absolutely scientific. Asymptotic analysis is based on models of computer behaviour that are testable (and people do test them and do improve on them). Moreover, the asymptotic models make predictions and those predictions are testable (and people do test them and do improve on them).

The asymptotic analysis of algorithms would not be useful if it didn't make accurate predictions about real world phenomenon. I've written peer reviewed computer science papers where I have devised an algorithm, predicted its asymptotic behaviour and then validated through empirical testing.

What you're describing sounds completely different. If the major idea is that human economies cannot be scientifically analysed, then surely all analysis is a waste of time? An analysis that isn't based on the scientific method isn't more likely to be correct.

You probably know more about economics than me (I'm just a mathematician), so I won't argue against you, but if I understand your two posts correctly, it seems like what you're describing is completely useless. If a model doesn't have predictive power then what is it good for?

I understand from your other post that the justification of Austrian "models"/"explanations" comes from their simplicity. Which I guess is some application of Occam's razor? But that makes no sense - the simplicity of a model on it's own is no indication of correctness. You always need some notion of the likelihood of the observed evidence under that given model. Otherwise, you can just say "all people make all decisions completely randomly" and that's the simplest model of all.

A completely non-predictive model has no real-world meaning, because it can't be used to effect reality. I suspect that Austrian models do effectively have some small predictive power - there is an implicit causal analysis that comes from the small element of qualitative evaluation of uncertainty, no doubt used instinctively by practitioners to decide whether an argument sounds plausible.

Anyway, it all sounds completely ridiculous. How is their method of choosing explanations any better than a witchdoctor deciding that thunder is a sign of the gods being angry?