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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."
Marx was a drunken idiot whose economic "theories" didn't have so much as a means to correctly communicate value.
His value theory is totally bonkers but much of his diagnosis of the ils of the capitalistic system is fairly good. Where people go wrong, is in looking for the solution in his works. There is a lot arm waving but hardly any coherent solutions.
TCAP-Abort
Economics is not scientific in the mathematical sense. It takes no account of the irrational human animal.
That's entirely and demonstrably untrue. In 2002 the Nobel prize was awarded to Daniel Kahneman "for having integrated insights from psychological research into economic science, especially concerning human judgment and decision-making under uncertainty". Much recent economic study has been explicitly examining the irrationality of people and their economic decisions. Economics is a science but it is one where it is challenging to design experiments and so much of the data comes from empirical analysis.
That is why it is more like the weather than mathematics.
Mathematics is a language to describe things. Economics isn't a branch of mathematics any more or less than any other science. It is however a bit like studying the weather in that the forecasting models are trying to make predictions about a very complex and chaotic system. The models get their data from historical real world events but perfect accuracy in the models is nigh unacheivable.
Putting that stuff near "science" or "maths" is an insult to those fields of endeeavour.
Not any more than meteorology or ecology or geology or any other field that gets its data from complex and chaotic empirical sources.
Which economists predicted 2007/2008?
Quite a few of them. Some didn't get their timing right but I can introduce you to economists and financial analysts that I know personally that were warning about a likely crash in the housing market and knock on effects as far back as 2003. They obviously couldn't predict the exact outcome because that is basically impossible in a large chaotic system. (especially when you cannot perfectly model the initial state)
People have this naive idea that economists ought to be able to predict the future perfectly or it isn't a science. Predicting the recession of 2008 was something akin to a geologist trying to predict exactly when and where an earthquake will hit. There are too many unknowns to make anything better than a probabilistic analysis. They can tell you there is an X% chance of an event happening within time period Y. Asking for something more accurate than that is simply unrealistic expectations.
The difference seems to be that while physicists are aware that their models are incomplete, economists (or, more likely, journalists, politicians, and the people who actually apply these models) etc. disregard these caveats and claim that this model describes the entire financial system in a few differential equations.
Economists don't disregard the limitations of their models at all. If you would spend some time speaking with actual economists (I have) you'd quickly find out that they are exquisitely aware of the limitations of their models.
Where things tend to go off the rails is when financial analysts with a profit motive try to stretch the economists models beyond what they can actually explain. A great example of this is Long Term Capital Management which was described in the book When Genius Failed. They took some models with a long list of assumptions and limitations and tried to apply the models to areas well beyond the limitations of the model. Early success begat hubris which led to greed and ultimately their downfall.
What do you mean? Keynes modeled stagflation; he didn't use that term, but it's clear that Keynes, and those who studied his work, were aware of the effect of a supply shock on an economy.
The issue with Keynesian policy and stagflation is, given two problems with conflicting resolutions, how do you address both of them?
We now know that tackling them one at a time works. First you address inflation, then you address stagnation. This isn't a weakness of Keynesian theory -- it's validation.
"Trolls they were, but filled with the evil will of their master: a fell race..." -- J.R.R. Tolkien on Olog-hai