Abstract
It is argued that one can learn from minimal economic models. Minimal models are models that are not similar to the real world, do not resemble some of its features, and do not adhere to accepted regularities. One learns from a model if constructing and analysing the model affects one’s confidence in hypotheses about the world. Economic models, I argue, are often assessed for their credibility. If a model is judged credible, it is considered to be a relevant possibility. Considering such relevant possibilities may affect one’s confidence in necessity or impossibility hypotheses. Thus, one can learn from minimal economic models.
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Notes
Suarez defends a ‘deflationary or minimalist attitude and strategy towards the concept of scientific representation’ that is related to the minimal model presented here (Suárez 2004, p. 770). However, he suggests that representational force and allowing inferences are necessary conditions for scientific representations. It seems to me that both conditions are rather matters of degree, and thus only function as comparative but not exclusionary criteria. The minimal-model account presented here does not lay claim to any necessary criteria.
Cf. Hausman (1992, p. 75).
Giere has since proposed an alternative, pragmatic account that does not rely to this extent on similarity (Giere 2004). His previous account, however, still attracts attention, particularly among scientists. It therefore seems worthwhile discussing it here.
These differences were documented for some of the main economic journals during the period from 1972 to 1986. About 45% of all economic research articles analysed mathematical models without making use of or even referring to any form of data, while the respective figures were 18% in political science, 1%in sociology, 0% in chemistry and 12% in physics (Leontief 1982; Morgan 1988). It is my impression that these proportions have not significantly changed in economics (although they may, as part of the methodological aspect of economics imperialism, have increased in the other social sciences).
I should add that Cartwright (2007; this issue) arrives at a similar conclusion. Yet for her this conclusion is bad news for economics—while I would consider it bad news for the ‘stronger model requirements’ position.
By induction Sugden presumably means the broad category of non-deductive inferences (i.e. all those in which the premises of an argument are believed to support the conclusion but do not entail it), and not the narrower inference from empirically confirmed tokens to other tokens of the same type.
Sugden also mentions credibility in a different way, as a quality of the inferences themselves. He writes, ‘Since the same effects are found in both real and imaginary cities, it is at least credible to suppose that the same causes are responsible’ (Sugden 2000, p. 24, my emphasis). Here ‘credible’ is used in the sense of ‘more probable’. This is incompatible with the notion of credibility as depicting a parallel—i.e. counterfactual—reality: the descriptions of counterfactual worlds are necessarily false, and hence cannot be probable. In personal communication with the author, Bob Sugden has suggested that the above use of ‘credible’ is spurious, and that replacing ‘credible’ with ‘reasonable’ or ‘defensible’ would be a way to avoid possible confusion.
I therefore disagree with the claim that model credibility implies robustness of the results (cf. Kuorikoski and Lehtinen, this issue, section 5).
As further supported by his reference to ‘the general laws governing events in the real world’ (Sugden 2000, p. 25, my emphasis).
For example, Russell (1948) uses ‘credibility’ in the same way as ‘confidence in’ or ‘degree of belief in’ the truth of that proposition.
The exception here is Behavioural Economics, which often refers to experimental results as a way of justifying certain constraining model assumptions.
For an overview, see Frigg (2009, p. 6).
It is sometimes claimed that folk economics has predictable biases, focusing on wealth and its distribution, and neglecting the production and allocation of goods and their efficiency (cf. Rubin 2003).
Economic theory, as well as folk economics, also proposes impossibility hypotheses. Significant examples include the claim that a firm’s investment is totally independent of its liquidity position (Modigliani-Miller Theorem), and that the stability of the economy is neutral with respect to the systematic reaction of monetary policy to the business cycle (Rational Expectations Hypothesis).
Tobin’s ultra-Keynesian model is another good example (Knuuttila, this issue, section 6).
This irrelevancy problem does not arise in the cases Schlimm discusses. The impossibility claims these models dispute concern the construction of entities that display intelligent behaviour without a ‘vitalistic’ element. The impossibility hypothesis is about the very possibility of modelling. Thus, the existence of any entity that exhibits such behaviour without incorporating the vitalistic element contradicts the impossibility hypothesis. This feature makes Schlimm’s cases special, and prevents their generalisation to other situations.
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Grüne-Yanoff, T. Learning from Minimal Economic Models. Erkenn 70, 81–99 (2009). https://doi.org/10.1007/s10670-008-9138-6
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DOI: https://doi.org/10.1007/s10670-008-9138-6