Economics is Not a Science
I’ve always held that economics is not a science. I don’t mean that in a
derogatory way. I say that only in an apples-are-not-oranges kind of way.
The latest Nobel prize for economics just
proved that (let’s set aside the stupidity of the Nobel committee at times,
that’s a topic for another day). This year’s winners for Economics are Eugene
Fama and Robert Shiller. In case you
haven’t heard of either (and so don’t get the absurdity), let John
Kay explain the ridiculousness of giving them the prize jointly:
“Prof Fama made his name by developing
the efficient market hypothesis, long the cornerstone of finance theory. Prof
Shiller is the most prominent critic of that hypothesis. It is like awarding
the physics prize jointly to Ptolemy for his theory that the Earth is the
centre of the universe, and to Copernicus for showing it is not.”
Kay says that people are neither
hyper-rational (as Fama says) nor “slaves to our psychological weaknesses” (the
Shiller model). Rather, he says that:
“There is a middle course, which
understands that the economists’ use of the term “rationality” lacks relevance
in a world characterised by imperfect information; that rational expectations
are impossible in the face of radical uncertainty; and that it is implausible
that constantly changing securities prices represent an equilibrium.”
Ok, you say, all this just proves the
absurdity of the Nobel choice. But what’s that got to do with economics not
being a science, you wonder? Well, here’s the key difference this choice brings
up:
“There was no scope for compromise on the
nature of the physical world: Copernicus was right and Ptolemy was wrong. There
are not, and will not be, equivalent certainties in economics.”
(The closest physics has to such a
scenario is the clash between two of its most successful theories, general
relativity and quantum mechanics. But then again, Einstein never won the prize
for relativity; so there you go).
Many people tend to make evaluations of sciences, in relative terms. In doing that, one also tends to benchmark sciences with a fuzzy mix of mathematics and physics as the benchmark. I myself have done this earlier in my life, but I learnt with pain and unease that the 'maths-physics' bench mark is detrimental to proper evaluation.
ReplyDeleteI suppose most people would at least agree to consider that 'science' is the method of expressing and explaining what is happening with proper cause-effect correlation, having repeatability and predictability. (A few more points may also be agreed upon in this regard.) One other thing (i.e. NOT acceptable points) is that one should not bring in weird ideas (gods, horoscopy, prejudices, superstitions etc. and many such faith or feelings stuff, without foundation in reality and without scope for objectivity.
We then are necessarily having only this scenario. Different sciences have to have different settings and backgrounds, to produce good explanations. We can 'sort-of' say this: sciences in different domains have different levels of deviations, while dealing with explanations of reality or happenings, if we consider maths and physics as being 'exact' or 'having a tendency for exactness' sciences.
In that sense I am not really bothered about declaration of "some subject not to be taken as science". With some level of sympathy (knowing the difficulty of people trying to work out good explanations against odds), I would consider subjects as good "explainers" of phenomena in their domain, if we can't make the reality conform to the level of exactness of our heart's desire, i.e., in the way maths and physics deal with Nature or Reality. Reality doesn't take orders from us - even worse - has no desire to please us, no?! :-)
While many people may not be willing for fuzziness as a necessary ingredient of those sciences who have the compulsion to be less exact then the 'bench mark' sciences (maths, for example), I am convinced that we might as well develop our faculty for fuzziness, if we wish to progress in less-exact sciences. If we do, we may move towards better understanding in many domains of knowledge. Why limit ourselves?