From Lars Syll But I do not believe that the route to sounder economic reasoning will involve an abandonment of economists’ penchant for reasoning with the use of models. Models allow the internal consistency of a proposed argument to be checked with greater precision; they allow more finely-grained differentiation among alternative hypotheses, and they allow longer and more subtle chains of reasoning to be deployed without both author and reader becoming hopelessly tangled in them. Nor do I believe it is true that economists who are more given to the use of formal mathematical analysis are generally more dogmatic in their conclusions than those who customarily rely upon more informal styles of argument. Often, reasoning from formal models makes it easier to see how strong are the
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from Lars Syll
But I do not believe that the route to sounder economic reasoning will involve an abandonment of economists’ penchant for reasoning with the use of models. Models allow the internal consistency of a proposed argument to be checked with greater precision; they allow more finely-grained differentiation among alternative hypotheses, and they allow longer and more subtle chains of reasoning to be deployed without both author and reader becoming hopelessly tangled in them. Nor do I believe it is true that economists who are more given to the use of formal mathematical analysis are generally more dogmatic in their conclusions than those who customarily rely upon more informal styles of argument. Often, reasoning from formal models makes it easier to see how strong are the assumptions required for an argument to be valid, and how different one’s conclusions may be depending on modest changes in specific assumptions. And whether or not any given practitioner of economic modeling is inclined to honestly assess the fragility of his conclusions, the use of a model to justify those conclusions makes it easy for others to see what assumptions have been relied upon, and hence to challenge them. As a result, the resort to argumentation based on models facilitates the general project of critical inquiry that represents, in my view, our best hope for some eventual approach toward truth.
This is — sad to say — a rather typical view among mainstream economists today. Defending the use of unrealistic and unsubstantiated models with the argument that models make it “easy for others to see what assumptions have been relied upon, and hence to challenge them” is rather far-fetched. It’s like arguing: “We can’t understand what is going on in our complex and uncertain world, so let us set up ‘small-world’ models in which we assume away the complexities and reduce genuine uncertainty to calculable risk, and then let us, with precision and rigour, look at those assumptions and challenge them.” Yours truly fails to see the point.
Mainstream economic theory today is in the story-telling business whereby economic theorists create make-believe analogue models of the target system – usually conceived as the real economic system. This modeling activity is considered useful and essential. And it’s used both in micro- and macroeconomics. Since everything the economist wants to know is put in to the model, it’s a piece of cake to prove whatever in a ‘rigorous’ and valid way. Deductive certainty is achieved — in the model. Unfortunately, the price one has to pay for getting at ‘rigorous’ and precise results in this way, is making outright ridiculous assumptions that actually impair the possibility of having anything of interest to say about the real world.
Since fully-fledged experiments on a societal scale as a rule are prohibitively expensive, ethically indefensible or unmanageable, economic theorists have to go for something else. To understand and explain relations between different entities in the real economy the predominant strategy is to build models — the preferred stand-in for real experiments — and make things happen in these ‘analogue-economy models’ rather than engineering things happening in real economies.
Mainstream economics has since long given up on the real world and contents itself with proving things about thought up worlds. Empirical evidence only plays a minor role in economic theory, where models largely function as a substitute for empirical evidence. The one-sided, almost religious, insistence on axiomatic-deductivist modeling as the only scientific activity worthy of pursuing in economics, is a scientific cul-de-sac.
Avoiding logical inconsistencies is crucial in all science. But it is not enough. Just as important is avoiding factual inconsistencies. And without showing — or at least warrantedly arguing — that the assumptions and premises of their models are in fact true, mainstream economists aren’t really reasoning, but only playing games. Formalistic deductive ‘Glasperlenspiel’ can be very impressive and seductive. But in the realm of science it ought to be considered of little or no value to simply make claims about the model and lose sight of reality.
Mainstream theoretical economics is still under the spell of the Bourbaki tradition in mathematics. Theoretical rigour is everything. Studying real-world economies and empirical corrobation/falsification of theories and models nothing. Separating questions of logic and empirical validity may — of course — help economists to focus on producing rigorous and elegant mathematical theorems that Woodford et consortes consider as “progress in economic thinking.” To most other people, not being concerned with empirical evidence and model validation is a sign of social science becoming totally useless and irrelevant. Economic theories building on known to be ridiculously artificial assumptions without an explicit relationship with the real world is a dead end. That’s probably also the reason why Neo-Walrasian general equilibrium analysis today (at least outside Chicago) is considered a total waste of time. In the trade-off between relevance and rigour, priority should always be on the former when it comes to social science. The only thing followers of the Bourbaki tradition within economics — like von Neumann, Debreu, Lucas, and Sargent — has given us are irrelevant model abstractions with no bridges to real-world economies. It’s difficult to find a more poignant example of a total waste of time in science.
If the real world is fuzzy, vague and indeterminate, then why should our models build upon a desire to describe it as precise and predictable? The logic of idealization is a marvellous tool in mathematics and axiomatic-deductivist systems, but a poor guide for action in real-world systems, where concepts and entities often are without clear boundaries and continually interact and overlap.
Being told that the model is rigorous and amenable to ‘successive approximations’ to reality is of little avail, especially when the law-like (nomological) core assumptions are highly questionable. Being able to construct ‘thought-experiments’ depicting logical possibilities does not take us very far. An obvious problem with mainstream economic models is that they are formulated in such a way that they realiter is extremely difficult to empirically test and decisively ‘corroborate’ or ‘falsify.’
Contrary to Woodford, I would argue such models have — from an explanatory point of view — no value at all. The ‘thinness’ is bought at too high a price unless you decide to leave the intended area of application unspecified or immunize your model by interpreting it as nothing more than a set of assumptions making up a content-less theoretical system with no connection whatsoever to reality.