by The problem with model-based explanations in economics One of the most important tasks of social sciences is to explain the events, processes, and structures that take place and act in society. Explanations are important within science since the choice between different theories hinges in large part on their explanatory powers. The most reasonable explanation for one theory’s having greater explanatory power than others is that the mechanisms, causal forces, structures, and processes it talks of, really do exist. All explanations of a phenomenon have preconditions that limit the number of alternative explanations. These preconditions significantly influence the ability of the different potential explanations to actually explain anything. But could one
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Lars Pålsson Syll considers the following as important: Economics
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The problem with model-based explanations in economics
One of the most important tasks of social sciences is to explain the events, processes, and structures that take place and act in society.
Explanations are important within science since the choice between different theories hinges in large part on their explanatory powers. The most reasonable explanation for one theory’s having greater explanatory power than others is that the mechanisms, causal forces, structures, and processes it talks of, really do exist.
All explanations of a phenomenon have preconditions that limit the number of alternative explanations. These preconditions significantly influence the ability of the different potential explanations to actually explain anything.
But could one not just say that different explanations are different, without a need to grade them as better or worse? I think not. That would be too relativistic.
All kinds of explanations in empirical sciences are pragmatic. Explanations have a function to fulfil, and some are better and others worse at this.
When it comes to modelling, yours truly does 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’ econom(etr)ic models may be an informative heuristic tool for research. But if practitioners of modern econom(etr)ics do not investigate and make an effort to provide a justification for the credibility of the simplicity assumptions on which they erect their building, it will not fulfil its tasks. Maintaining that economics is a science in the ‘true knowledge’ business, yours truly remains a sceptic of the pretences and aspirations of ‘simple’ econom(etr)ic models and theories building on unwarranted idealisations. So far, I can’t really see that e. g. micro-founded macro models have yielded very much in terms of realistic and relevant economic knowledge.
All empirical sciences use simplifying or unrealistic assumptions (abstractions) 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.
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.
Explanation, understanding and prediction of real-world phenomena, relations and mechanisms therefore cannot be grounded on simpliciter assuming the invoked isolations to be warranted. If we cannot show that the mechanisms or causes we isolate and handle in our models are stable, in the sense that when we export them from our 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 ontological shortcoming of a basically epistemic — rather than ontological — approach, is that the use of idealisations 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. No matter how many convoluted refinements of concepts are made in the model, if the ‘simplifying’ idealisations 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 macroeconomic models somehow seen as ‘successively approximating’ macroeconomic reality, is a rather unimpressive attempt at legitimising using fictitious idealisations for reasons more to do with model tractability than with a genuine interest in understanding and explaining features of real economies. Many of the model assumptions standardly made in mainstream macroeconomics are restrictive rather than harmless and could a fortiori anyway not in any sensible meaning be considered approximations at all.
If you — to ‘save’ your theory or model — have to invoke things that do not exist, well, then your theory or model is probably not adequate enough to give the causal explanations searched for.