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Machine Learning Could Solve Economists' Math Problem
An anonymous reader writes: Noah Smith argues that the field of economics frequently uses math in an unhealthy way. He says many economists don't use math as a tool to describe reality, but rather as an abstract foundation for whatever theory they've come up with. A possible solution to this, he says, is machine learning: "In other words, econ is now a rogue branch of applied math. Developed without access to good data, it evolved different scientific values and conventions. But this is changing fast, as information technology and the computer revolution have furnished economists with mountains of data. As a result, empirical analysis is coming to dominate econ. ... [Two economists pushing this change] stated that machine learning techniques emphasized causality less than traditional economic statistical techniques, or what's usually known as econometrics. In other words, machine learning is more about forecasting than about understanding the effects of policy. That would make the techniques less interesting to many economists, who are usually more concerned about giving policy recommendations than in making forecasts."
Let's be clear: how you think economics is defined by your ideology, and most economics is bad math with unfounded assumptions arriving at un-supportable conclusions.
So, if you're the Chinese government and think you can manipulate markets to suit your beliefs, you'll be horribly mistaken. Likewise, if you subscribe to the ridiculous Austrian School of economics (which refuses to have empirical evidence), then you likewise believe your theory is so perfect it doesn't need to be validated.
Nobody has ever had any proof for "trickle down economics" other than they think it should work and it suits their ideology, but 30 years of actual real world data mostly shows it's utterly failed to work as planned.
Economics is useful to look at what came before, and understand some limited problems ... but in general many people believe once you try to use that to predict things, or influence outcomes you get into a level of complete bullshit and voodoo. Time and time again when people try to take action or set policy based on economics, it fails utterly.
And until economics is based on anything other than sketchy math and ideology, it can never be a real science or have much more meaning than something people use to defend their ideology. But since people never look at economics separated from their ideology, it will never happen.
Economics is mostly a tool to make it look like the things you believe should happen, based on how you want the system to behave, have any actual relationship with the outcomes you expect to achieve with policy. The problem is that is a lie.
But it sure as hell can't be called an objective science. First you have to believe in the ideology and then you believe in the methodology.
The problem is people like to believe that the ideology is objective reality, and that their observations are in fact rules. And that simply isn't true.
Lost at C:>. Found at C.
My understanding of the difference is that this produces somewhat testable results WITHOUT requiring a theory of how and why those effects occur.
To give an extremely simplified example, assume that a certain coin is flipped every day. For the past 20,000 days, it has always come up heads. (Obviously not a fair coin). The machine will predict that it will probably come up heads tomorrow. Traditional economic theory will try to understand WHY it keeps coming up heads before making predictions. That's the first difference.
The requirement for a theory that explains how and why economic effects occur also means that the theory is subject to subject to be supported or decried based on political considerations or other irrelevant factors. A system which accurately predicts what will happen without comment on politically sensitive policy questions may be useful.
It takes no account of the irrational human animal.
Quite the contrary; there are a few economic think tanks around that take plenty account of that and "tailor" (is "completely fabricate" too judgemental?) data to totally agree with the political stance of their primary benefactors.