Mainstream economics — nothing but pseudo-scientific cheating
from Lars Syll
A common idea among mainstream — neoclassical — economists is the idea of science advancing through the use of ‘as if’ modeling assumptions and ‘successive approximations’. But is this really a feasible methodology? I think not.
Most models in science are representations of something else. Models “stand for” or “depict” specific parts of a “target system” (usually the real world). All theories and models have to use sign vehicles to convey some kind of content that may be used for saying something of the target system. But purpose-built assumptions — like “rational expectations” or “representative actors” — made solely to secure a way of reaching deductively validated results in mathematical models, are of little value if they cannot be validated outside of the model.
All empirical sciences use simplifying or unrealistic assumptions in their modeling activities. That is not the issue – as long as the assumptions made are not unrealistic in the wrong way or for the wrong reasons.
The implications that follow from the kind of models that mainstream economists construct are always conditional on the simplifying assumptions used — assumptions predominantly of a rather far-reaching and non-empirical character with little resemblance to features of the real world. From a descriptive point of view there is a fortiori usually very little resemblance between the models used and the empirical world. *As if’ explanations building on such foundations are not really any explanations at all, since they always conditionally build on hypothesized law-like theorems and situation-specific restrictive assumptions. The empirical-descriptive inaccuracy of the models makes it more or less miraculous if they should — in any substantive way — be able to be considered explanative at all. If the assumptions that are made are known to be descriptively totally unrealistic (think of e.g. “rational expectations”) they are of course likewise totally worthless for making empirical inductions. Assuming that people behave ‘as if’ they were rational FORTRAN programmed computers doesn’t take us far when we know that the ‘if’ is false.
Theories are difficult to directly confront with reality. Economists therefore build models of their theories. Those models are representations that are directly examined and manipulated to indirectly say something about the target systems.
But models do not only face theory. They also have to look to the world. Being able to model a “credible world,” a world that somehow could be considered real or similar to the real world, is not the same as investigating the real world. Even though all theories are false, since they simplify, they may still possibly serve our pursuit of truth. But then they cannot be unrealistic or false in any way. The falsehood or unrealisticness has to be qualified.
One could of course also ask for robustness, but the “as if worlds,” even after having tested it for robustness, can still be a far way from reality – and unfortunately often in ways we know are important. Robustness of claims in a model does not per se give a warrant for exporting the claims to real world target systems.
Anyway, robust theorems are exceedingly rare or non-existent in macroeconomics. Explanation, understanding and prediction of real world phenomena, relations and mechanisms therefore cannot be grounded (solely) on robustness analysis. Some of the standard assumptions made in neoclassical economic theory – on rationality, information handling and types of uncertainty – are not possible to make more realistic by de-idealization or successive approximations without altering the theory and its models fundamentally.
If we cannot show that the mechanisms or causes we isolate and handle in our models are stable, in the sense that what when we export them from are models to our target systems they do not change from one situation to another, then they only hold under ceteris paribus conditions and a fortiori are of limited value for our understanding, explanation and prediction of our real world target system.
The obvious shortcoming of a basically epistemic — rather than ontological — approach such as “successive approximations” and ‘as if’ modeling assumptions, is that “similarity” or “resemblance” tout court do not guarantee that the correspondence between model and target is interesting, relevant, revealing or somehow adequate in terms of mechanisms, causal powers, capacities or tendencies. No matter how many convoluted refinements of concepts made in the model, if the successive ‘as if’ approximations do not result in models similar to reality in the appropriate respects (such as structure, isomorphism, etc), they are nothing more than ‘substitute systems’ that do not bridge to the world but rather misses its target.
So, I have to conclude that constructing minimal macroeconomic ‘as if’ models or using microfounded macroeconomic models as “stylized facts” somehow “successively approximating” macroeconomic reality, is a rather unimpressive attempt at legitimizing using fictitious idealizations for reasons more to do with model tractability than with a genuine interest of understanding and explaining features of real economies. Many of the model assumptions standardly made by neoclassical macroeconomics are restrictive rather than harmless and could a fortiori anyway not in any sensible meaning be considered approximations at all.
Mainstream economics building on such a modeling strategy does not produce science.
It’s nothing but pseudo-scientific cheating.
The thrust of this realist rhetoric is the same both at the scientific and at the meta-scientific levels. It is that explanatory virtues need not be evidential virtues. It is that you should feel cheated by “The world is as if T were true”, in the same way as you should feel cheated by “The stars move as if they were fixed on a rotating sphere”. Realists do feel cheated in both cases.