by Tony Lawson and the nature of heterodox economics Lawson believes that there is a ‘coherent core’ of heterodox economists who employ methods that are consistent with the social ontology they implicitly advance. However, Lawson also acknowledges that many also use mathematical modelling, a method that presupposes a social ontology that is in severe tension with it. Therefore, I repeat, Lawson proposes that heterodox economists in fact exist in two groups, those who use methods consistent with the social ontology they are committed to, and those who do not. But all are heterodox economists. Lawson’s hope is that by making the kind of social ontology presupposed by mathematical modelling clear, heterodox economists will increasingly review the legitimacy
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Lars Pålsson Syll considers the following as important: Economics
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Tony Lawson and the nature of heterodox economics
Lawson believes that there is a ‘coherent core’ of heterodox economists who employ methods that are consistent with the social ontology they implicitly advance. However, Lawson also acknowledges that many also use mathematical modelling, a method that presupposes a social ontology that is in severe tension with it. Therefore, I repeat, Lawson proposes that heterodox economists in fact exist in two groups, those who use methods consistent with the social ontology they are committed to, and those who do not. But all are heterodox economists.
Lawson’s hope is that by making the kind of social ontology presupposed by mathematical modelling clear, heterodox economists will increasingly review the legitimacy of the modelling approach. However, Lawson still considers those who make such a methodological mistake to be heterodox economists. For they still, he argues, are committed to the social ontology he defends and always reveal it in some way in their analyses or pronouncements …
In recent years, Lawson has been increasingly frustrated by the continued use of mathematical modelling by heterodox economists, as well as by movements towards its increased usage. An argument made by such heterodox economists is that the problem identified by Lawson lies not with mathematical modelling per se but with the sort of mathematical methods used. They argue that poor mathematical modelling has been the problem and that better, more complex, models will be able to capture the reality of human existence.
Lawson clearly regards that methodological argument to be mistaken. For, as stated above, he finds that even complex mathematical models presuppose a closed system. However, he maintains that the social reality that such researchers reveal themselves to implicitly accept is at least quite similar to that which he defends. Their concern with being realistic, for one, speaks volumes. Therefore, these researchers should, he believes, still be distinguished from the mainstream …
Lawson does not argue for excluding mathematical models. Rather, as with all other methods, they should only be applied in conditions in which their use is appropriate, though admittedly Lawson does, as an empirical matter, assess the occurrence of the latter to be relatively rare. His stance is not anti-mathematical method but anti-mismatch of method and context of application … What Lawson does argue for regarding practice is an explicit, systematic and sustained ontological awareness, which he believes can only improve the methodological choices of heterodox economists.
If scientific progress in economics lies in our ability to tell ‘better and better stories’ one would, of course, expect economics journals being filled with articles supporting the stories with empirical evidence confirming the predictions. However, the journals still show a striking and embarrassing paucity of empirical studies that (try to) substantiate these predictive claims. Equally amazing is how little one has to say about the relationship between the model and real-world target systems. It is as though explicit discussion, argumentation and justification on the subject aren’t considered to be required.
In mathematics, the deductive-axiomatic method has worked just fine. But science is not mathematics. Conflating those two domains of knowledge has been one of the most fundamental mistakes made in modern — and as Lawson argues, both in mainstream and heterodox — economics. Applying it to real-world open systems immediately proves it to be excessively narrow and hopelessly irrelevant. Both the confirmatory and explanatory ilk of hypothetico-deductive reasoning fails since there is no way you can relevantly analyse confirmation or explanation as a purely logical relation between hypothesis and evidence or between law-like rules and explananda. In science, we argue and try to substantiate our beliefs and hypotheses with reliable evidence. Propositional and predicate deductive logic, on the other hand, is not about reliability, but the validity of the conclusions given that the premises are true.