Mainstream economics — nothing but pseudo-scientific cheating

10 November, 2015 at 17:24 | Posted in Economics | 4 Comments

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.

60088455All 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.

Alan Musgrave



  1. Idén om individen är falsk. Människan kan inte förstås som individer och detta kan visas tämligen enkelt.

    När vi försöker förstå något så använder vi ”den vetenskapliga metoden”, numera betyder det nästan alltid matematik och matematisk reduktionism. Hur beskrivs då samhället eller sociala fenomen matematiskt om vi accepterar antagandet att människor är individer? Matematiskt och reduktionistiskt beskrivs då människan i samhället eller andra sociala fenomen som en enda person. Det är som allmänna gaslagen, den tar inte hänsyn till varje atoms olika förutsättningar, den betraktar alla atomer som lika. Det är en grå soppa som trycker ut emot en omgivning, så blir då samhället beskrivet med vetenskap. Antagandet om att människan kan förstås som individen medför ett antagande om samhället när vi gör ”vetenskap” på det, när vi behandlar flera individer matematiskt, antar vi ett fullständigt jämlikt samhälle, där alla individer matematiskt betraktas som en och samma. Det är antagandet att vi lever i en utopi där alla människor är exakt jämlika och jämställda.

    Det säger sig självt att antagandet om individen inte kan förstå samhället som det ser ut, för vi lever inte i en utopi. Antagandet om individen gör också att vi inte kan utveckla samhället till en utopi, eftersom alla människor vetenskapligt betraktas som exakt jämlika redan, alla teorier baserade på det grundantagandet kan därför inte utveckla samhället alls.

    Du har här två val, antingen erkänner du att vi lever i en utopi eller så betraktar du idén om individen som falsifierad. Om individen är falsifierad så blir alla vetenskapsgrenar som baseras på en idé om individen, pseudovetenskap.

    Suck on that Popper!

  2. Analysis (as opposed to synthesis) is wrongly treated in economics as if it is descriptive, as if the functional relationships identified in a priori reasoning can be interpreted as being factually true, because they are logically valid. The auxiliary assumptions, like the hoary Law of Diminishing Returns, used to bridge from the fundamental indeterminacy of analysis to the target system, as you phrase it, are most oft as casual and ill-considered as they are dogmatic. The first lesson is that analysis is not about creating analogues; analysis should be about sorting out the necessary and sufficient functional relationships in a conceptual system. Sorting out the necessary and sufficient relationships doesn’t tell you about the world, anymore than proving the Pythagorean Theorem tells you the height of a particular flagpole or mountain. But, proving the theorem does inform us about relationships that make easier or more practical to do those measurements. Still knowing about the world entails doing the observation and measurement. Geometry, by itself, is no map.
    It may be that geometry seems to provide something like analogues to objects in the world — concepts like rectangles and triangles that correspond with aspects of objects in the real world, like boxes or flagpoles. It is easy to see why that is a natural way to think about the methods we use when we use concepts and theorems from geometry to observe and manipulate the world.
    The great obstacle to this easy correspondence between the shapes of things posited in the analytic geometry of economic theory and the objective institutions of the real economic world is uncertainty. Coping with uncertainty — the real facts of how people struggle to decide and to cooperate in a world of variability, risk and surprise (aka ignorance) — involves a factor that deductive reasoning can only skirt. As simple a behavioral assumption as profit maximization runs aground on uncertainty: “maximize” cannot be defined for a genuinely uncertain context.
    The observant economist may recognize the rent-seeking firm as the spiritual analogue of theory’s profit maximizer, but this is no simple correspondence. The actual, rent-seeking firm is pre-occupied with power and insurance, with problems of cybernetic control of production processes and so on.
    Analytic theory is not without uses in constructing an operational model of an actual institutionalized situation in the economy, but the dominating importance of uncertainty in shaping actual arrangements means that there can be no simple correspondence with the abstract “shapes” posited by a theory that must put uncertainty aside in order to preserve a calculable, “tractable” chain of reasoning. Uncertainty is the auxiliary hypothesis that turns economic analysis upside down, when describing how the real world of the economy works. The theory’s system of markets seeking stasis in an optimal allocation of resources must yield to a reality of bureaucratic firms pursuing managerial and technical efficiency by means of sunk-cost investments, subject to financial discipline and dependent on the political power to earns rents, in order to realize a return on investment.
    Resistance to knowing any thing about the actual economy is very high among economists, as reality seems to contradict the convenient homilies of high theory.

    • ICYMI Bruce Wilder Nov 12

      ‘Uncertainty’ has become the shibboleth of Post-Keynesianism and the mantra is ‘We simply do not know.’ This raises the question: why do Post-Keynesians still waste their time with economics instead of making long and healthy walks in the lovely countryside?

      That much is sure, the flight path of a down feather is uncertain. All that can be said after countless meticulous empirical observations is that it eventually falls to the ground. This is why physicists ignored the uncertainty of the down feather entirely and took another route to figure out the Law of Falling Bodies.

      In any case, physicists have not made a habit out of telling the world what they do not know or what is unknowable. They are famous for telling the world what is known and what can be known.

      So the answer to Post-Keynesian know-nothings is to get out of the way, or as G. B. Shaw put it ‘People who say it cannot be done should not interrupt those who are doing it.’

  3. This is a great comment Bruce. Even relatively less dogmatic economists such as Krugman (no where near as extreme as someone like Sargent for example) assert that an explanation for things like liquidity traps lies in algebraic and geometric gadgets like ISLM, even though there is absolutely nothing in there that explains how it actually happens – let alone draw on actual evidence to explain the causation. People need to trawl through things like company reports, psychological, household and business surveys and documentation from lenders to really identify what has happened. The problem is mainstream economists won’t like it because not all of it will fit into a neo-classical/mathematical model – and its gruelling, time consuming work.

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