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Wednesday, March 23, 2011

Economics and Biology

Mike the Mad Biologist explains how they differ. I can't resist commenting. The mad biologists post is brilliant and I entirely agree with it. So much so that I won't bother excerpting and just ask you to click this link.



I comment.

I am an economist and an ex biologist (BA and began PhD in Biology). I do think that Roberts has a point -- economists have to get over physics envy. It is a plain fact that the only natural science which comes to most econmists minds is physics (this is my experience basically without exception).

This means that economists identify scientifit thought with thought involving math. I'm not sure if Roberts knows enough to understand this, but he chose examples from fields of biology in which math is used. In contrast much work in molecular and cellular biology isn't mathematical at all -- the models are drawings not equations. Some economists just don't grasp how rigorous can be separate from mathematical.

Very importantly economic theory has status in the profession totally aside from its relationship with data. It is taught as math and appreciated as math. The question of whether it corresponds to reality is considered by some to be naive. "Theory" is identified with "models" and models are false by definition. A prediction is derived from a hypothesis of interest and some auxiliary hypotheses. It is tested. It is rejected by the data. This has no effect on anything. It is concluded either that the problem is with the auxiliary hypotheses (which are still regularly assumed when developing models including models used to guide policy). Or econmists just note that the alleged hypothesis of interest isn't really a hypothesis since we all were always sure it is false and so what ?

As far I as can recall, that hasn't happened in biology in centuries (that is since it was based on the four humors).

Now here I can see some good coming from Roberts's analogy. The theory which is used in spite of total empirical failure is considered necessary for rigor (meaning mathematical not scientific). The invalid reasoning is that looks sort of like physics, so economics has to be like that to be a science.

Biologists have achieved great things empirically step by step (with the occasional BS speculation about evolution, because that gives the work theoretical dignity). There are economists doing the same, with empirical work using assumptions (sometimes that an experiment is related to a real world phenomenon sometimes that a real world pheonomenon is a natural experiment) which seem obviously true to non economists (and economists including me). Their status in the profession is rapidly rising. I mean economics is getting to be a lot more like biology than it was 25 years ago. It's beginning to have the feature that you can't get published for being cleaver and you have to actually work (yes I am thinking of moving on to some less scientific field).

The stuff below is really boring.

Roberts also is very wrong as you note. Here I am ignorant too (I was a microbiologist not an ecologist or evolutionary biologist -- I used no math at work which is part of why I couldn't stand it (biological research that is-- I like math)). Also I am just agreeing with length with what you wrote.

Roberts clearly doesn't know much about research in ecology. You bet that "Darwinism" is a warning sign. He doesn't have a clue about what one can predict using the theory of evolution by natural selection, how much has been predicted, the confrontation of those predictions and data or just how utterly nonsensical to compare evolutionary biology to economics. Here a large part of the problem is that the predictions concern trivial things (hence analogous not homologous). Enough to prove that Darwin was on to something, but who cares about the sequences of introns.

Also, Gould was a rhetorical genius. The key success of punctuated equilibrium theorists was setting up straw men. They really were debating Darwin (Huxley was on their side -- I learned this from one of Gould's books). Economics hasn't failed in the sense that something written over 100 years ago is no longer believed. It has failed in the sense that things which are obviously inconsistent with the data are being published.

pulled back from comments

"Comments:
"Some economists just don't grasp how rigorous can be separate from mathematical."

Could you please expand on this?"

OK. First I explain how rigorous can be separate from mathematical.

I guess I start first with biology. I decided not to drop names in the original post, but I note that Salvador Luria was not embarrassed to say that he had forgotten all about math "except for the simplest things." He was a Nobel Laureate and MIT institute professor. Robert Weinberg (one of the leaders of one of the three or so teams which simultaneusly discovered what makes cancerous cells cancerous (somatic mutations)) did a bit of algebra (or took a derivative) in class saying "exhausting my mathematical knowledge." Look in "Science" or "Nature" you will find many articles without one equation. A model is presented. It is a drawing.

Molecular biology includes counting and measuring so it is quantitative. But it doesn't all include any sophisticated math at all. Something like RNA polymerase transcribes the lactose operon except when a repressor protein is stuck to the operator. The repressor is inactivated when lactose binds to it. There is no equation there. That is the model. It has been tested. One can doubt that model just as one can suspect that the earth is really flat. And no more. And no math.

Consider, for another example, a court of law. A rigorous examination of the evidence includes rules that no claims of fact can be made by people not under oath (unless they refer to claims made earlier by people not under oath) that witnesses are cross examined, that the claim to recognise the defendant must be based on picking him or her out of a lineup (this is not really rigorous -- the rigorous approach is to show one person after another each time asking "is this the one ?" This gives lower false positives and the same number of correct identifications). All of this sounds to me to be rigor. But none of it involves math.

OK so what about economists ? Well you wouldn't necessarily be surprised if a very cloistered mathematician defined rigor as clearly stating all definitions, axioms and other givens then making only statements which are logically implied by those definitions, axioms and givens. That is "mathematical rigor" and a mathemeticisn might be excused for not knowing that the word "rigor" is used with a quite different meaning -- one in which a photograph can be introduced rigorously in evidence even though it is not an axiom or implied by axioms.

Many economists absolutely use rigor to mean mathematical rigor. They consider the statement of givens and definitions followed by proofs of theorems rigorous economics. I would say that it is rigorous mathematics which might or might not be up to levels expected in math departments (sometimes it is, but the person doing the proving is often as not employed by a math department) but it isn't rigorous social science. In the sciences, rigor is a statement about basing claims on evidence, not about clearly stating assumptions.

Now when the mathematicians who think they are economists are asked about real world relevance, many make some sort of claim of relevance. But when arguing for real world relevance, rigor of any kind is not required. The arguments can be total BS, presented as math like reasoning but such that counterexamples can be obtained. Others say that that's not their problem.

4 comments:

Anonymous said...

"Some economists just don't grasp how rigorous can be separate from mathematical."

Could you please expand on this?

Unknown said...

Have you seen this one? I think it´s right up you ally?


Anyway, I would like to share an anecdote.

I, and some other PhD students in economics once took a class in logistic regression that was given by the biostatistics department. The book we used (don´t remember the name) was apparently written by some hot shot in statistical epidemiology, so at least these two subjects thought that this was a worthwhile approach to the analysis.

However, we economists were rather “shocked” about how it was taught (don´t get me wrong, we appreciated it). How can you openly teach people how to perform “data mining”? Shouldn’t we at least pretend that we simply stated a theoretically coherent model, used the a priori appropriate statistical technique, and then happened to get the theoretically plausible results? If you put this right there in your theoretical textbooks, won´t the collective lie be harder to uphold?

Naturally, the biosticastic professor didn’t understand what we (jokingly) asked. “But you’re supposed to find out what the data says, which factors that are important to explain it and how they relate to each other. If you already knew that in advance, what would be the point of the study.” – he answered.

...
(Started to write a lot more but it didn’t make any sense – you would have to be there to put it in context). My point is – statistics as it is used in (at least some) other sciences seem to be a completely different creature than what you know from economics.

Unknown said...

Did I forget to post the link in the last post? If so:

http://econospeak.blogspot.com/2011/03/what-kind-of-science-would-economics-be.html?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+espeak+%28EconoSpeak%29

The whole article is well worth a read.

Anonymous said...

By the way (I just submitted a comment about CS) - my undergraduate degree was a double major in math and physics, and I studied math logic (among other things) in grad school. But I've never taken a biology class... My only connection to biology is family members who are MDs - and self study. I have no idea how much of biology I don't know. Sadly, I think something similar might be true of economists where social sciences like psychology and sociology are concerned. And that thought terrifies me, considering how much of a mess these folks have caused and continue to cause.