Chameleon economics

5 June, 2015 at 14:50 | Posted in Economics | 8 Comments

Chameleons 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. monocle_chameleon_2The 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 …

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

Reading Pfleiderer’s 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 come to modeling I do see the point emphatically made time after time by e. g. Paul Krugman in simplicity — as long as it doesn’t impinge on our truth-seeking. “Simple” macroeconomic models may of course be an informative heuristic tool for research. But if practitioners of modern macroeconomics 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” macroeconomic 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.




  1. Apropos Newton and Einstein, I know that (for reasons mysterious to me) Popper’s taken a beating for about a half-century now, but he supplied, as an example of asymmetric power of falsification, that prediction about some kind of planetary motion (I think it was Mercury or something) that would be distinctly different if you went by Newton or Einstein’s theory. Popper wrote that what made him admire the Einstein argument was precisely that it was willing to leave itself open to such a yes-no test.
    Cf. neoclassicals.

    Come to think of it a good parody would be to write a neoclassical refutation of quantum mechanics. Paraphrasing Krugman on one of his anti-Lars blog posts, “I’ve seen what happens when you accept that something can be both a particle and a wave–and it ain’t pretty.” Ergo, dare to be silly.

  2. All empirical sciences use simplifying or unrealistic assumptions in their modeling activities. That is not the issue…

    I see the above claim made all the time. Covhrane recently had some nonsense about elephants and frictionless surfaces. Freshwater like him of heterodox like Syll, there is never any support for the claim.
    It is so obviously false that it makes one wonder how university professors could be so utterly ignorant of how science works? I think a big part of the answer is that the economics term “model” has the same letters and pronunciation as the scientific term “model” but they are quite different words with unrelated etymologies.

  3. “That is not the issue – as long as the assumptions made are not unrealistic in the wrong way or for the wrong reasons. . . . 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.”
    I have been reading your blog regularly for some time now, and find it cordial. Though I have seen you make the above quoted assertion several times, I have almost no idea what you mean by it. I stare at it uncomprehending, I’m afraid, as at a word salad.
    I have a broadly similar view of the epistemic status of neoclassical macroeconomics and what appears to me to be its degenerative research program, so it’s not that I’m inclined to contradict you in any broad way, from the standpoint of my own prior notions, nor do I intend any disrespect.
    I simply do not see how I am to reconcile two assertions, so closely juxtaposed: all theories are false due to their simplicity; theories cannot serve us if they are false in any way. How do you intend a humble reader to resolve this paradox?

  4. Where I agree with Krugman is that models should be simple. And sometimes we do need models, for example, we need some estimate of elasticities and multipliers for policy purposes.

    Where I disagree with the neo-classical approach is that the model should not be the main focus of analysis. The historical record should be. And this should be very thorough, drawing on interdisciplinary knowledge. We should recognise that some things you can not and should not put into a model or into mathematics. And more often than not, these are precisely the most interesting and important things.

    The other thing I disagree with with Krugman is simply taking old models off the shelf. True, you might think that these explain the facts. But perhaps a lot of other things explain those facts as well.

    You simply have to do the history, from the bottom up, and consult widely.

    • Krugman had a revealing blogpost about his preference for too simple analysis that you might find illuminating. It had to do with a famous paper by Evsey Domar on the feudal institution of serfdom, which sought to understand why it was instituted in Russia in the 16th century, after it had faded in Western Europe. Domar’s thesis, which Krugman praised as “a simple yet powerful insight” (in Krugman’s telling, at least) was that all depended upon the relative abundance of land and labor: scarce labor relative to land made it worthwhile to tie labor to land as a way of suppressing wage demands. The problem with this story is that just the opposite circumstance seemed, historically, to doom serfdom and feudalism in Western Europe: the Black Death reduced the population, wages rose and the institution of serfdom came apart.

      It is a great illustration, because none of our present politics is entangled with the effort to justify an explanation one way or another. We can witness a pure style in action.

      The ratio of land to labor recalls the traditional focus of economics upon problems allocating resources. But, the argument just hangs in mid-air, with no grounding. It is in serious danger of being transmuted directly from insight to “just so” story without ever touching ground. What is “abundant” land relative to labor? Where are the political problems — the need for population to staff armies, the struggles among monarchs and between monarchs and their aristocrats? the claims of villains upon seigneurs? Where are specialization and trade and the rise of cities against the autarky of the manor? And, what are we to make of Krugman’s insistence that serfdom had collapsed in the increasingly overpopulated decades prior to the Black Death? Are the documented facts of history to be denied? There were still serfs to be freed by the French Revolution (primarily in the ironically named province known as the Free County, Franche Comte) and there were colliery serfs freed in Scotland in the early 19th century.

      The original Krugman piece is archived here:

  5. Lars, Bruce should have an answer. Mine would be that Newton was true to the scientific method, including being true to the data. But his model did not absolutely correspond to reality and it was not true that it was the final theory of its subject. No theory can properly claim more. It is the extravagant claims for their models that mark some economists out as being deeply flawed.

    It seems to me that a part of the problem is that humans have a psychological need for ‘facts’ and certainty that some so-called experts satisfy, for a variety of reasons. Keynes argues against this.

  6. “If economists aren’t able to show that the mechanisms or causes … in their “simple” models are stable in the sense that they do not change when exported to their “target systems”, they … are … of limited value to our understanding, explanations or predictions of real economic systems.”

    If I read this right, then presumably ‘models with emergent properties are of limited value …’. But if real economies have emergent properties, wouldn’t it be helpful to have appropriate models? And if emergent properties are ‘an elephant in the room’, wouldn’t a model be the most essential kind of model, before we can make progress?

  7. Reblogged this on Forwardeconomics.

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