Home > Uncategorized > What’s the use of economic models?

What’s the use of economic models?

from Lars Syll

chameleonOne 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 …

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. 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 … 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 modelling complex and dynamic economic phenomena. Let me take just one example — simplicity.

‘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 fullfil its tasks. Maintaining that economics is a science in the ‘true knowledge’ business, yours truly remains 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 modelling activities. That is not the issue – as long as the assumptions made are not unrealistic in the wrong way or for the wrong reasons.

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.

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. 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.

Many of the model assumptions standardly made in mainstream 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.

  1. September 27, 2020 at 11:14 pm

    The introduction starts out with question as to the viability of loans requiring 100% cash in the bank as opposed to fractional lending which many have blamed for several financial crises. The article would be far more effective if it had presented such a model and then argued why such is impractical since this idea is a perennial “wack-a-mole” particularly in international finance.

  2. Gerald Holtham
    September 28, 2020 at 4:46 pm

    Yet if I want to calculate the trajectory of an artillery shell Newton is quite good enough. I don’t need to worry about relativistic effects at such low speeds and it would be silly to burden my equations with them. Tracing a black hole, though, you need Einstein. Instinctively I agree with Lars that models should not be based on ridiculous assumptions but I find it very hard to lay down practical principles for when an assumption is legitimate. Evidently Lars is right that it should be such that model causality is not changed uncontrollably when applied to a real situation but how do you tell in advance? And the truth is a model may be informative, even adequate, in some real-world situations and not in others – just like Newton’s. Keynes’ income-expenditure model was good enough to make the case for reflation in the 1930s; it was irrelevant in the resource constrained full-employment conditions of the UK in the 1950s and it was not wrong but inadequate to the inflationary terms of trade shocks of the 1970s. Right now it is useful again. In economics the phenomena are not stable and a general model is beyond us. We need a suite of models and the wisdom to know when one of them is useful. The stupidest models can have their day. No-one is more dismissive than me of the neutrality of money as a general proposition but even that works pretty well in a hyperinflation.
    Incidentally, it’s becoming clear that general relativity is not the whole story either. To make it work we have to posit not only dark matter being 80+ per cent of all mass but there being dark energy too causing universal expansion. Seems more likely that GR is wrong – but it’s good enough for your SatNav to work.

  3. September 28, 2020 at 5:43 pm

    Holtham’s analysis makes sense when doing theory; and that it holds “approximately is good enough” when applied to the “real world”. It becomes dangerous when it is applied, as in Cinderella, when trying to force the stepsister’s foot into the glass slipper. Does this validate that Economics is not a science? We see this today in the current world where alternative models to GDP are being proposed with work to “quantify” these new “measures” such as GPI or the efforts to use quantitative measures with ESG’s and similar “metrics”. In fact, the term “metrics” creates or supports a mindset. Ecological and Behavioral Economics are in a similar situation. Capitalism is in a similar pickle in a world where there is an increasing financial divide and we ignore the “history” and the current rationalizations, particularly in a global “economy” and the needed patches to realize the goals of the SDG’s needed to support past/current trade relations.

  4. Ikonoclast
    September 29, 2020 at 5:35 am

    Here’s a working link to Paul Pfleiderer’s paper. I hope it’s okay to give the link here on RWER.

    https://onlinelibrary.wiley.com/doi/full/10.1111/ecca.12295

    I found Pfleiderer’s paper compelling and persuasive. It certainly calls into question significant aspects of “The Game of Economic Models”.

  5. September 29, 2020 at 1:35 pm

    In science there can be serious consequences for applying “models”. Medicine is a paradigmatic example whether a “bookshelf” or derivative. Economics and Social “sciences”? Yes, chameleons, creatures that change colors to avoid consequences.

  6. Gerald Holtham
    October 4, 2020 at 1:48 pm

    There is no dispute here. Models can be misused, even good ones. Models have been misused or used tendentiously and it is a particular risk in social studies like economics where the phenomena are not stationary and vested interests are involved. So do we give up and all become historians? Some people should be historians of course but is it the only approach to social phenomena?
    Do we make ourselves feel superior by repeatedly pointing out all the rubbish out there or do we try and “fail better” as Beckett put it. I’m a bit bored with being told it’s mostly a crock (I spotted that some time ago) but suggestions for much-needed improvement are always welcome. When you try to come up with them you’ll probably realise that not all errors are down to bad faith. Theorising usefully about social phenomena is objectively difficult.

  7. Ken Zimmerman
    October 25, 2020 at 9:56 am

    In 1964 in a series of lectures famed American physicist Richard Feynman described the scientific method. “Now I’m going to discuss how we would look for a new law. In general, we look for a new law by the following process. First, we guess it (audience laughter), no, don’t laugh, that’s the truth. Then we compute the consequences of the guess, to see what, if this is right, if this law we guess is right, to see what it would imply and then we compare the computation results to nature or we say compare to experiment or experience, compare it directly with observations to see if it works.

    If it disagrees with experiment, it’s WRONG. In that simple statement is the key to science. It doesn’t make any difference how beautiful your guess is, it doesn’t matter how smart you are who made the guess, or what his name is… If it disagrees with experiment, it’s wrong. That’s all there is to it.”

    Too simple in my view. But it offers one possible answer to the question, “What’s the use of economic models?” That answer is models are merely guesses that are either confirmed or dis-confirmed by experiment or experience. This answer presents two problems for the current economics discipline. First, economists perform too few experiments and often do not even compare their guesses to the experience of actual economic agents. Particularly, in the relevant historical contexts. Second, there is a question as to how clearly, if at all economists can distinguish the theoretical assumptions they have been taught and the results of observations and/or experiments.

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