Critical Review has started a new blog “Causes of the Crisis” featuring contributors to the journal's stellar issue on the topic. The papers in CRs special issue add up to the best and most comprehensive autopsy of the financial collapse available anywhere. The blog looks terrific too. Some excerpts…
Using models within economics or within any other social science, is especially treacherous. That’s because social science involves a higher degree of complexity than the natural sciences. The reason why social science is so complex is that the basic unit in social science, which economists call agents, are strategic, whereas the basic unit of the natural sciences are not. Economics can be thought of the physics with strategic atoms, who keep trying to foil any efforts to understand them and bring them under control. Strategic agents complicate modeling enormously; they make it impossible to have a perfect model since they increase the number of calculations one would have to make in order to solve the model beyond the calculations the fastest computer one can hypothesize could process in a finite amount of time.
This recognition that the economy is complex is not a new discovery. Earlier economists, such as John Stuart Mill, recognized the economy’s complexity and were very modest in their claims about the usefulness of their models. They carefully presented their models as aids to a broader informed common sense. They built this modesty into their policy advice and told policy makers that the most we can expect from models is half-truths. To make sure that they did not claim too much for their scientific models, they divided the field of economics into two branches—one a scientific branch, which worked on formal models, and the other political economy, which was the branch of economics that addressed policy. Political economy was seen as an art which did not have the backing of science, but instead relied on the insights from models developed in the scientific branch supplemented by educated common sense to guide policy prescriptions.
In the early 1900s that two-part division broke down, and economists became a bit less modest in their claims for models, and more aggressive in their application of models directly to policy questions. The two branches were merged, and the result was a tragedy for both the science of economics and for the applied policy branch of economics.
Hayek made a similar charge [to Krugman's in his long NYT piece] 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.
I look forward to posts from the other contributors.