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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."
Oh, look .. ideology pulled out of your ass and passed off as facts.
Blah blah blah.
Sorry, this is exactly my point. Show us some empirical proof, or STFU. What's that? Don't have empirical proof? Then you don't have facts. You have ideology.
Lost at C:>. Found at C.
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.