by ‘Approximate truth’ in economics According to this line of defence, all models are false but to some extent ‘approximately true’ – and approximately true models are harmless from the point of view of the realist’s aims … This argument is to a large extent confused. It is correct that there are cases in which a false assumption can indeed be regarded as ‘approximately true’, namely when the assumption concerns the value of a quantitative causal factor … However, economics’ idealizations are seldom of that kind. Typically, economics models ascribe properties to actors and institutions that these don’t have and explain outcomes by way of causal processes that don’t exist. Consider Friedman’s own economic and non-economic examples. Models assuming that
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‘Approximate truth’ in economics
According to this line of defence, all models are false but to some extent ‘approximately true’ – and approximately true models are harmless from the point of view of the realist’s aims … This argument is to a large extent confused. It is correct that there are cases in which a false assumption can indeed be regarded as ‘approximately true’, namely when the assumption concerns the value of a quantitative causal factor …
However, economics’ idealizations are seldom of that kind. Typically, economics models ascribe properties to actors and institutions that these don’t have and explain outcomes by way of causal processes that don’t exist. Consider Friedman’s own economic and non-economic examples. Models assuming that firms maximize their expected returns … or that billiard players know ‘the complicated mathematical formulas that would give the optimum directions of travel’ portray outcomes as having radically different generative mechanisms than they in fact have … A billiard player who ‘just figures it out’ does not use complicated mathematical formulas, not even approximately. Most theoretical models in economics contain idealizations of this and not the ‘extreme value of a real quantity’ type. It may of course be the case that the outcomes of the actual generating mechanisms exactly or approximately coincide with the outcomes that would have been generated by the supposed mechanisms … According to creationists, God created the world 5000 years ago as if it had been a product of the laws of nature including Darwinian evolution. Few people would say that (supposing Darwin’s story is in fact correct) the creationists’ ‘model’ is ‘approximately true’ because the outcome is the same as that of Darwinian evolution.
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 about the target system. But purpose-built assumptions made solely to secure a way of reaching deductively validated results in mathematical models – like ‘rational expectations’ or ‘representative actors’ — are of little value if they cannot be validated outside of the model.
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.
The obvious ontological shortcoming of a basically epistemic — rather than ontological — approach such as ‘successive approximations’ is that ‘similarity’ or ‘resemblance’ tout court does 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. A good model is a model that works and helps us explain and understand the problems we want to research. No matter how many convoluted refinements of concepts made in the model, if the ‘successive approximations’ 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 and makes our understanding of why things work the way they do in the real world into an inexplicable mystery. Dramatically simplified and distorted models building on known to be significantly wrong/false assumptions do not deliver much in terms of genuine explanation. If models build on critical assumptions that are contradicted by what we know to be true they should be rejected tout court.
Asserting that a model is a good one if it “approximates “truth is totally useless since we are never presented with a standard against which we can judge the veracity of the approximation. Many of the model assumptions standardly made in mainstream economics are harmfully restrictive and misrepresentative — rather than incomplete and harmless — and can not in any sensible meaning be considered approximations at all.
Yours truly has to conclude that constructing ‘minimal’ economic models — or using microfounded macroeconomic models as ‘stylized facts’ or ‘stylized pictures’ 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.