Saturday, September 12, 2009

Pretence and Economic Knowledge

Paul Krugman critiques the economics profession for widely shared views that failed to anticipate and ill prepared us for an economic crisis that promises to be the worst since WWII.

Hayek made a similar charge in his Nobel Lecture of December 11, 1974, The Pretence of Knowledge: “… the economists are at this moment called upon to say how to extricate the free world from the serious threat of accelerating inflation which, it must be admitted, has been brought about by policies which the majority of economists recommended and even urged governments to pursue. We have indeed at the moment little cause for pride: as a profession we have made a mess of things.” Although Hayek saw the problem as stemming from an inappropriate "scientistic" attitude, he explicitly wanted “…to avoid giving the impression that I generally reject the mathematical method in economics.” Rather, his main message was that “If man is not to do more harm than good in his efforts to improve the social order, he will have to learn that in this, as in all other fields where essential complexity of an organized kind prevails, he cannot acquire the full knowledge which would make mastery of the events possible…The recognition of the insuperable limits to his knowledge ought indeed to teach the student of society a lesson of humility which should guard him against becoming an accomplice in men's fatal striving to control society - a striving which makes him not only a tyrant over his fellows, but which may well make him the destroyer of a civilization which no brain has designed but which has grown from the free efforts of millions of individuals.”

Economic scientists have precious little understanding of this rule governed complex order, and how to keep it on its demonstrated long term path of growth and human betterment without suffering too irreparably from the kind of unpredictable reverses that we are now mired in. Less pretence and a commitment to learn from the new data being generated as I write, will be both humbling and informative, after the inevitable human political impulse to blame one’s long standing political adversaries has run its course.

What is most impressive in the current crisis is that even those who find bubbles unsurprising, and who had warned of the housing bubble debacle, did not anticipate its ability to undermine the financial system so decisively and thereby to devastate a good performing economy. This is revealed in a fairly crisp timeline: residential home prices started their decline in 2006; mortgage market collapse in July-August, 2007 (which kick-started the Fed into taking “enhanced liquidity” measures); the fourth quarter 2008 events—the Treasury, Fed, FDIC joint announcement of crisis action, unprecedented extensions of FRB credit to holders of all varieties of underwater assets in implicit recognition that the financial system was under reserved and insolvent, not just illiquid.

Economists and policy makers have been learning as we go, and no one can be sure how long that process has yet to go.

2 comments:

michael webster said...

A limits of knowledge thesis is almost always unsatisfactory: the clearer or more formal the thesis, the easier it is to see what axiom has to be changed to avoid the result.

Nice overview here:

http://rjlipton.wordpress.com/2009/09/13/are-impossibility-proofs-possible/

My own sense, being an attorney and PhD in choice theory, is that economists routinely ignore or dismiss systemic fraud as possibility.

See William Black on control fraud.

http://www.youtube.com/watch?v=Rz1b__MdtHY

Finally, it might be helpful if economists distinguished between two senses of solution: a) a recommendation to a problem, and b) a mathematical calculation. Sense b) almost never gives you a solution in sense a).

The model which allowed you to make a calculation, on the other hand, might show distinct economic processes, A and B, have something, unexpectedly, in common.

That commonality might allow you to make a recommendation for a B problem based upon past success in dealing with A problems.

hou said...

Less pretence and a commitment to learn from the new data being generated as I write.
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