Real world filters and economic models

1 Nov, 2014 at 18:10 | Posted in Economics, Theory of Science & Methodology | 4 Comments

chameleon-ipad-backgroundChameleons arise and are often nurtured by the following dynamic. First a bookshelf model is constructed that involves terms and elements that seem to have some relation to the real world and assumptions that are not so unrealistic that they would be dismissed out of hand. The intention of the author, let’s call him or her “Q,” in developing the model may be to say something about the real world or the goal may simply be to explore the implications of making a certain set of assumptions. Once Q’s model and results become known, references are made to it, with statements such as “Q shows that X.” This should be taken as short-hand way of saying “Q shows that under a certain set of assumptions it follows (deductively) that X,” but some people start taking X as a plausible statement about the real world. If someone skeptical about X challenges the assumptions made by Q, some will say that a model shouldn’t be judged by the realism of its assumptions, since all models have assumptions that are unrealistic. Another rejoinder made by those supporting X as something plausibly applying to the real world might be that the truth or falsity of X is an empirical matter and until the appropriate empirical tests or analyses have been conducted and have rejected X, X must be taken seriously. In other words, X is innocent until proven guilty … Because there is a model for X, because questioning the assumptions behind X is not appropriate, and because the testable implications of the model supporting X have not been empirically rejected, we must take X seriously. Q’s model (with X as a result) becomes a chameleon that avoids the real world filters …

cherry-pickOne can generally develop a theoretical model to produce any result within a wide range. Do you want a model that produces the result that banks should be 100% funded by deposits? Here is a set of assumptions and an argument that will give you that result. That such a model exists tells us very little. By claiming relevance without running it through the filter it becomes a chameleon …

Whereas some theoretical models can be immensely useful in developing intuitions, in essence a theoretical model is nothing more than an argument that a set of conclusions follows from a given set of assumptions. Being logically correct may earn a place for a theoretical model on the bookshelf, but when a theoretical model is taken off the shelf and applied to the real world, it is important to question whether the model’s assumptions are in accord with what we know about the world. Is the story behind the model one that captures what is important or is it a fiction that has little connection to what we see in practice? Have important factors been omitted? Are economic agents assumed to be doing things that we have serious doubts they are able to do? These questions and others like them allow us to filter out models that are ill suited to give us genuine insights. To be taken seriously models should pass through the real world filter.

Chameleons are models that are offered up as saying something significant about the real world even though they do not pass through the filter. When the assumptions of a chameleon are challenged, various defenses are made (e.g., one shouldn’t judge a model by its assumptions, any model has equal standing with all other models until the proper empirical tests have been run, etc.). In many cases the chameleon will change colors as necessary, taking on the colors of a bookshelf model when challenged, but reverting back to the colors of a model that claims to apply the real world when not challenged.

Paul Pfleiderer

Pfleiderer’s absolute gem of an article reminds me of what H. L. Mencken once famously said:

There is always an easy solution to every problem – neat, plausible and wrong.

Pfleiderer’s perspective may be applied to many of the issues involved when modeling complex and dynamic economic phenomena. Let me take just one example — simplicity.

When it comes to modeling I do see the point often emphatically made for simplicity among economists and econometricians — but only as long as it doesn’t impinge on our truth-seeking. “Simple” macroeconom(etr)ic models may of course be an informative heuristic tool for research. But if practitioners of modern macroeconom(etr)ics do not investigate and make an effort of providing a justification for the credibility of the simplicity-assumptions on which they erect their building, it will not fulfill its tasks. Maintaining that economics is a science in the “true knowledge” business, I remain a skeptic of the pretences and aspirations of  “simple” macroeconom(etr)ic models and theories. So far, I can’t really see that e. g. “simple” microfounded models have yielded very much in terms of realistic and relevant economic knowledge.

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.

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 — as Pfleiderer acknowledges — 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.

Explanation, understanding and prediction of real world phenomena, relations and mechanisms therefore cannot be grounded on simpliciter assuming simplicity. 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 – considered “simple” or not – 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 ontological shortcoming of a basically epistemic – rather than ontological – approach, 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 simplifications made do not result in models similar to reality in the appropriate respects (such as structure, isomorphism etc), the surrogate system becomes a substitute system that does not bridge to the world but rather misses its target.

Constructing simple macroeconomic models somehow seen as “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 – simplicity being one of them – are restrictive rather than harmless and could a fortiori anyway not in any sensible meaning be considered approximations at all.

If economists aren’t able to show that the mechanisms or causes that they isolate and handle in their “simple” models are stable in the sense that they do not change when exported to their “target systems”, they do only hold under ceteris paribus conditions and are a fortiori of limited value to our understanding, explanations or predictions of real economic systems.

That Newton’s theory in most regards is simpler than Einstein’s is of no avail. Today Einstein has replaced Newton. The ultimate arbiter of the scientific value of models cannot be simplicity.

As scientists we have to get our priorities right. Ontological under-labouring has to precede epistemology.

4 Comments

  1. As I have been stating for years now — all mainstream economic theory– including Old and New Keynesianism has three fundamental axioms that Keynes specifically rejected in writing his more general theory. [A general theory has fewer restrictive axioms that the alternative — as Keynes pointed out in the preface to the German edition of THE GENERAL THEORY. He says that is why he specifically called his theory The GENERAL Theory.

    What are these three assumptions? (1) the neutral money assumption, (2) the gross substitution assumption — where he specifically notes that producible capital durables are not a good substitute for liquid assets, i.e., in his chapter on the essential properties of money and interest, and (3) the ergodic axiom.
    believe it or not, Samuelson and Friedman still have these same three axioms in their models

    Paul Davidson

  2. “Do you want a model that produces the result that banks should be 100% funded by deposits? Here is a set of assumptions and an argument that will give you that result.”

    I wonder if that was a reference to Cochrane’s “Toward a run-free financial system” paper. It’s one of my favorite mainstream papers because it fits in so many faulty assumptions. There is a whole book to be written in a critique of it.

  3. Lacking the Midas touch of science
    Comment on ‘Real world filters and economic models’

    .

    The characteristic capability of science — to turn whatever it might touch into knowledge — obviously has eluded economics. Currently, economists do not understand how the economy works. And there is no real difference between Orthodoxy and Heterodoxy despite much discussion about secondary points. The differences between the schools only demonstrate that there are many ways to get it wrong.

    J. S. Mill excused economics in the inescapable benchmark comparison with physics as separate and inexact science. Indeed, when one compares the respective starting points — Newton and Smith — and the actual state of the fields then one is driven to the conclusion that in the course of time economics has fallen behind even farther.

    Economics has always taken its inspirations from the real sciences. This includes methodology and theory design (Mirowski, 1995). It did not escape economists that the simplicity argument played a great role in physics.

    “… in my opinion there is the correct path and, moreover, that it is in our power to find it. Our experience up to date justifies us in feeling sure that in Nature is actualized the ideal of mathematical simplicity.” (Einstein, 1934, p. 167)

    As untalented plagiarists economists used this argument and abused it for the justification of their cartoon science.

    This is the correct way of simplification, abstraction and idealization:

    The Principia begins with an idealized world, a simple mental construct, a “system” of a single mathematical particle and a centrally directed force in a mathematical space. Under these idealized conditions, Newton freely develops the mathematical consequences of the laws of motion that are the axioms of the Principia. At a later stage, after contrasting this ideal world with the world of physics, he will add further conditions to his intellectual construct – for example, by introducing a second body that will interact with the first one and then exploring further mathematical consequences. … In this way he can approach by stages nearer and nearer to the condition of the world of experiment and observation, introducing bodies of different shapes and composition and finally bodies moving in variant types of resistant mediums rather than in free space. (Cohen, 1994, p. 77)

    Standard economics, too, starts with an idealized world but then it does not move nearer and nearer to the world of experiment and observation but in the opposite direction in order to rationalize an unsuccessful initial idealization. Thus idealization, which is indispensable, becomes counterproductive. There is only a thin line between fruitful abstraction and barren absurdity. To assume that the moon is a mass point is unrealistic but fruitful, to assume that it is made of green cheese is unrealistic but nothing else. Most assumptions of conventional microeconomics fall into the green cheese category.

    While science turns the junk of ignorance into the gold of knowledge, economics merely turns common sense junk into rigorous junk. Newton’s most important methodological message was: hypotheses non fingo. Economists have done the opposite with much alacrity but little success.

    Now, what is the fundamental error that unites Orthodoxy and Heterodoxy? It is psychologism:

    “Psychologism is the view that in any explanation (individualist or otherwise) the only exogenous givens other than natural constraints allowed are those representing psychological states of either individuals or groups.” (Boland, 1992, pp. 147-148)

    To paraphrase H. L. Mencken: Psychologism is commonsensical, convincing, and wrong.

    “The notion that microeconomics is a branch of applied mathematics does economists more credit than several possible alternative explanations for its empirical weakness. … It isolates the limitations of the theory in a factual supposition about the determinants of human behavior, one that economists share with all of us. But the supposition we all share is false, and so economics rests on a purely contingent, though nevertheless central, mistaken belief ….” (Rosenberg, 1992, p. 247)

    As a matter of fact, no way leads from psychologism of any sort to the understanding of how the actual economy works. The solution does not consist in replacing the unrealistic homo economicus by the realistic homo socialis. The solution consists in replacing behavioral axioms by objective structural axioms.

    It is as simple as that:

    “The basic concepts and laws which are not logically further reducible constitute the indispensable and not rationally deducible part of the theory. It can scarcely be denied that the supreme goal of all theory is to make the irreducible basic elements as simple and as few as possible without having to surrender the adequate representation of a single datum of experience.” (Einstein, 1934, p. 165)

    There is only one scientific method. And, in its present state, economics is not a separate and inexact science but a failed science.

    .

    Egmont Kakarot-Handtke
    .
    References
    Boland, L. A. (1992). The Principles of Economics. Some Lies my Teacher Told Me. London, New York, NY: Routledge.

    Cohen, I. B. (1994). Natural Images in Economic Thought, chapter Newton and
    the Social Sciences, With Special Reference to Economics, or, the Case of the
    Missing Paradigm, pages 55–90. Cambridge: Cambridge University Press.

    Einstein, A. (1934). On the Method of Theoretical Physics. Philosophy of Science,
    1(2): 163–169. URL http://www.jstor.org/stable/184387.

    Mirowski, P. (1995). More Heat than Light. Cambridge: Cambridge University
    Press.

    Rosenberg, A. (1992). Economics – Mathematical Politics or Science of Diminishing
    Returns? Chicago, IL: University of Chicago Press.

  4. there is a good podcast interview with him on Russ Roberts Econtalk


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