Considering Taking Micro And Macro Econ..How Much Math Involved?

[Foucaulf]

Okay, this is getting out of hand.

1.Economics is not a science.  I think your claiming otherwise (unless you just used the language sloppily yourself and did not mean to state that) is the very heart of our disagreement.

This is not "the very heart of our disagreement." I actually have done some reading on this; you can start with the first salvo, Friedman (1966). Whether economics "is a science" has to do with its predictive accuracy, or its standards for rejecting hypotheses, or at least its culture with interpreting new facts - the usage of mathematical tools is neither necessary nor sufficient for any of the above.

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Let's stop for a moment and define "calculus" again. Calculus is simply the quantitative analysis of change. Go back to everything you have said and replace every usage of "the use of calculus" with "analyzing change." Do your statements sound as deep and insightful as you thought they were?

Yes, there are theorems that must be proved with calculus (e.g. proof via moment generating functions of the Central Limit Theorem, perhaps the most fundamental result in statistics). But your bone is not with the theorems here - it's with the models that abuse the theorems.

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As far as I know, string theory isn't criticized because it "makes no sense" but because it is unverifiable and unfalsifiable. This is a possible criticism to economics - but, again, it does not necessarily deal with the usage of math in econ.

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What are some examples of this?

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But doesn't that make it all the more important to understand the math clearly? You have this idea of economists in a shadowy room talking to each other by reading out loud hundreds of equations. That's not how they talk to each other; they use English all the time.

Keep in mind I don't even really buy the idea that math is "more precise" than English, which is something theorists like to say but doesn't jive with me as an empirical person. But you are not separating two effects here: the effect of using mathematics to model some phenomenon, and specific inaccurate mathematical models which stay beyond their shelf life.

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Please look at any college curriculum and see what the prerequisites are for a probability theory or statistics course. You'll find calculus on there eventually.

[Foucaulf]

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Do you mean the many-worlds interpretation of quantum mechanics?

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Look, the reason why I seem frustrated about this argument is that what you're saying is not far off from the usual critique in economics, maybe of most social sciences. It is fair game to criticize a model of human behaviour, formalized or not, by either dispelling its assumptions or show it is empirically falsifiable.

I don't have time to listen to the whole podcast you linked to, but I read one of the articles written by this Dr. Denniss, on the solvency of Australia's social security system:

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Read: “The purpose of the report is to get you worried about rising costs. If the report pointed out that budget revenue was likely to rise faster than budget outlays, people wouldn’t be scared.”

This is a valid critique, and I think accuses the model of the "Ricardian equivalence" assumption too often sneaked into a macro model for tractability. I don't know if it's any good, but it is valid.

Similarly, from the paper you linked to about the Becker-Murphy model of rational addiction:

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Let me make another analogy. Assume someone invented a machine that is used in surgeries and can automate some precise procedures doctors cannot follow perfectly. Then, while the machine is successful in some trials, in others an unknown bug will mess up the procedure and almost kill patients.

The range of common-sense solutions span a regulatory agency not allowing the machine to be used until it is more successful, the company creating the machine getting sued for malpractice, up to banning the machine's production altogether.

If orthodox economics is the machine, what you're arguing isn't analogous to any of those "common-sense solutions." What you're arguing is "this machine should not be for sale, but because medicine is not a science like physics this incident should have us reconsider using leeches."

Methodology is hard. It seems easy at first because there are people who make it sound easy, but nine times out of ten they don't understand it either. If you cannot argue methodology correctly, all you're doing is throwing non sequiturs and crowding out legitimate arguments.

For the record, the cost-benefit/welfare analysis style of thinking, so often mentioned in the articles you linked to, isn't very popular in economics these days: for the past two decades most work has been on causal inference, and that kind of analysis has seeped into the policy world (the World Bank funds a lot of randomized controlled trials, for example). There are serious problems with how slow dissemination can be, and how practitioners are not communicating with academics. Why not focus on this instead of "calculus in economics?"