-->

Learn about each of the loan on marketplace for business plan

Astrologers and macroeconomists

Astrologers and macroeconomists


I like to keep track of "econ diss" articles, since that's what this blog was mostly about for its first few years of existence. Most of them leave a lot to be desired. But here's one I really like, in Aeon magazine, by philosophy prof Alan Levinovitz.

Levinovitz likens modern-day macroeconomics to mathematical astrology in the early Chinese empire. And in fact, the parallel sounds pretty accurate. The article is worth reading just to learn about classical Chinese astrology, actually.

But anyway, Levinovitz draws heavily on the econ disses of Paul Romer:

‘I’ve come to the position that there should be a stronger bias against the use of math,’ Romer explained to me. ‘If somebody came and said: “Look, I have this Earth-changing insight about economics, but the only way I can express it is by making use of the quirks of the Latin language”, we’d say go to hell, unless they could convince us it was really essential. The burden of proof is on them.’
 ...and Paul Pfleiderer:
Pfleiderer called attention to the prevalence of ‘chameleons’ – economic models ‘with dubious connections to the real world’...Like Romer, Pfleiderer wants economists to be transparent about this sleight of hand. ‘Modelling,’ he told me, ‘is now elevated to the point where things have validity just because you can come up with a model.’
He also rightly (in my opinion) identifies Robert Lucas as a key figure in the turn away from empiricism in macro:
Lucas’s veneration of mathematics leads him to adopt a method that can only be described as a subversion of empirical science:
"The construction of theoretical models is our way to bring order to the way we think about the world, but the process necessarily involves ignoring some evidence or alternative theories – setting them aside. That can be hard to do – facts are facts – and sometimes my unconscious mind carries out the abstraction for me: I simply fail to see some of the data or some alternative theory."
A lot of what Levinovitz is writing is just a synthesis of things that smart economists have been complaining about in private for decades, and in public since the 2008 crisis. I think econ needs more critics like this, who are willing and able to go talk to the smart dissidents within the econ mainstream, rather than just accepting at face value the arguments of "heterodox" outsiders due to political affinity (as some econ critics sadly do).

Levinovitz, however, leaves out what I think is the most important development: the empirical revolution in econ. This has been most important in micro fields, since data is much more abundant, but it's also starting to influence macro. "Micro-focused macro" - using firm-level or area-level data to test the assumptions of macro models directly, rather than just throwing in a bunch of obviously wrong assumptions and hoping they yield aggregate results you like - is a big deal these days, and getting bigger. Soon, we may even see people insisting in seminars that DSGE models only use assumptions that have been rigorously tested on high-quality micro data! That dream is still far off, but it seems to be getting closer.

I also think Levinovitz should have given a shout-out to the successes of applied micro theory - auction theory, matching theory, discrete choice models, and the rest. He writes:
Unlike engineers and chemists, economists cannot point to concrete objects – cell phones, plastic – to justify the high valuation of their discipline.
But that's actually not right. Econ theory powers lots of useful technology, from Google's ad auctions to kidney transplant allocation systems. Economic engineering isn't a term people use, but it's a real thing, and mathematical econ theories sometimes do an excellent job of describing human behavior in ways that can be consistently applied.

But anyway, Levinovitz' article is very good (and very well-written), and is worth a read. Just remember that econ is a lot more than macro, that it has become much more data-centric, and that it has produced a number of useful engineering applications.

from Noahpinion http://ift.tt/1ViNNEG