by Do unrealistic economic models explain real-world phenomena? When applying deductivist thinking to economics, neoclassical economists usually set up “as if” models based on a set of tight axiomatic assumptions from which consistent and precise inferences are made. The beauty of this procedure is of course that if the axiomatic premises are true, the conclusions necessarily follow. The snag is that if the models are to be relevant, we also have to argue that their precision and rigour still holds when they are applied to real-world situations. They often don’t. When addressing real economies, the idealizations and abstractions necessary for the deductivist machinery to work simply don’t hold. 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, in which concepts and entities are without clear boundaries and continually interact and overlap.
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Lars Pålsson Syll considers the following as important: Economics
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Do unrealistic economic models explain real-world phenomena?
When applying deductivist thinking to economics, neoclassical economists usually set up “as if” models based on a set of tight axiomatic assumptions from which consistent and precise inferences are made. The beauty of this procedure is of course that if the axiomatic premises are true, the conclusions necessarily follow. 
The snag is that if the models are to be relevant, we also have to argue that their precision and rigour still holds when they are applied to real-world situations. They often don’t. When addressing real economies, the idealizations and abstractions necessary for the deductivist machinery to work simply don’t hold.
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, in which concepts and entities are without clear boundaries and continually interact and overlap.
Or as Hans Albert has it on the neoclassical style of thought:
In everyday situations, if, in answer to an inquiry about the weather forecast, one is told that the weather will remain the same as long as it does not change, then one does not normally go away with the impression of having been particularly well informed, although it cannot be denied that the answer refers to an interesting aspect of reality, and, beyond that, it is undoubtedly true …
We are not normally interested merely in the truth of a statement, nor merely in its relation to reality; we are fundamentally interested in what it says, that is, in the information that it contains …
Information can only be obtained by limiting logical possibilities; and this in principle entails the risk that the respective statement may be exposed as false. It is even possible to say that the risk of failure increases with the informational content, so that precisely those statements that are in some respects most interesting, the nomological statements of the theoretical hard sciences, are most subject to this risk. The certainty of statements is best obtained at the cost of informational content, for only an absolutely empty and thus uninformative statement can achieve the maximal logical probability …
The neoclassical style of thought – with its emphasis on thought experiments, reflection on the basis of illustrative examples and logically possible extreme cases, its use of model construction as the basis of plausible assumptions, as well as its tendency to decrease the level of abstraction, and similar procedures – appears to have had such a strong influence on economic methodology that even theoreticians who strongly value experience can only free themselves from this methodology with difficulty …
Science progresses through the gradual elimination of errors from a large offering of rivalling ideas, the truth of which no one can know from the outset. The question of which of the many theoretical schemes will finally prove to be especially productive and will be maintained after empirical investigation cannot be decided a priori. Yet to be useful at all, it is necessary that they are initially formulated so as to be subject to the risk of being revealed as errors. Thus one cannot attempt to preserve them from failure at every price. A theory is scientifically relevant first of all because of its possible explanatory power, its performance, which is coupled with its informational content …
The connections sketched out above are part of the general logic of the sciences and can thus be applied to the social sciences. Above all, with their help, it appears to be possible to illuminate a methodological peculiarity of neoclassical thought in economics, which probably stands in a certain relation to the isolation from sociological and social-psychological knowledge that has been cultivated in this discipline for some time: the model Platonism of pure economics, which comes to expression in attempts to immunize economic statements and sets of statements (models) from experience through the application of conventionalist strategies …
Clearly, it is possible to interpret the ‘presuppositions’ of a theoretical system … not as hypotheses, but simply as limitations to the area of application of the system in question. Since a relationship to reality is usually ensured by the language used in economic statements, in this case the impression is generated that a content-laden statement about reality is being made, although the system is fully immunized and thus without content. In my view that is often a source of self-deception in pure economic thought …
A further possibility for immunizing theories consists in simply leaving open the area of application of the constructed model so that it is impossible to refute it with counter examples. This of course is usually done without a complete knowledge of the fatal consequences of such methodological strategies for the usefulness of the theoretical conception in question, but with the view that this is a characteristic of especially highly developed economic procedures: the thinking in models, which, however, among those theoreticians who cultivate neoclassical thought, in essence amounts to a new form of Platonism.
Seen from a deductive-nomological perspective, typical economic models (M) usually consist of a theory (T) – a set of more or less general (typically universal) law-like hypotheses (H) – and a set of (typically spatio-temporal) auxiliary conditions (A). The auxiliary conditions (assumptions) give “boundary” descriptions such that it is possible to deduce logically (meeting the standard of validity) a conclusion (explanandum) from the premises T & A. Using this kind of model economists are (portrayed as) trying to explain (predict) facts by subsuming them under T given A.
This account of theories, models, explanations and predictions does not — of course — give a realistic account of actual scientific practices, but rather aspires to give an idealized account of them.
An obvious problem with the formal-logical requirements of what counts as H is the often severely restricted reach of the “law”. In the worst case it may not be applicable to any real, empirical, relevant situation at all. And if A is not true, then M doesn’t really explain (although it may predict) at all. Deductive arguments should be sound – valid and with true premises – so that we are assured of having true conclusions. Constructing, e.g., models assuming ‘rational’ expectations, says nothing of situations where expectations are ‘non-rational.’
Most mainstream economic models are abstract, unrealistic and presenting mostly non-testable hypotheses. How then are they supposed to tell us anything about the world we live in?
When confronted with the massive empirical refutations of almost every theory and model they have set up, mainstream economists usually react by saying that these refutations only hit A (the Lakatosian “protective belt”), and that by “successive approximations” it is possible to make the theories and models less abstract and more realistic, and – eventually — more readily testable and predictably accurate. Even if T & A1 doesn’t have much of empirical content, if by successive approximation we reach, say, T & A25, we are to believe that we can finally reach robust and true predictions and explanations.
There are grave problems with this modeling view. What Hans Albert most forcefully is arguing with his “Model Platonism” critique of mainstream economics, is that there is a tendency for modelers to use the method of successive approximations as a kind of “immunization,” taking for granted that there can never be any faults with the theory. Explanatory and predictive failures hinge solely on the auxiliary assumptions. That the kind of theories and models used by mainstream economics should all be held non-defeasibly corrobated, seems, however — to say the least — rather unwarranted.
Confronted with the massive empirical failures of their models and theories, mainstream economists often retreat into looking upon their models and theories as some kind of “conceptual exploration,” and give up any hopes/pretenses whatsoever of relating their theories and models to the real world. Instead of trying to bridge the gap between models and the world, one decides to look the other way.
To me this kind of scientific defeatism is equivalent to surrendering our search for understanding the world we live in. It can’t be enough to prove or deduce things in a model world. If theories and models do not directly or indirectly tell us anything of the world we live in – then why should we waste any of our precious time on them?