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Notes
It may seem particularly pressing in economics, because economic models seem to lack at least part of the heuristic value or some of the representational features their counterparts in the natural sciences apparently exhibit (cf. Rosenberg 1978; Reiss 2012; for a radically different viewpoint: Sugden 2013, Mäki 2009a, 2011).
Most of those who discuss the puzzle in the special issue of the Journal of Economic Methodology (2013) suggest that we should relax the notion of explanation, or reconsider its relation to truth, in order to solve the puzzle, which is, on the view defended here, besides the point, for the “puzzle” these relaxations are supposed to solve is not a genuine puzzle. A notable exception is to be found in a paper by Alexandrova and Northcott (2013), who take the puzzle at face value and argue, for reasons not touched upon here, that false models just do not explain anything. The intermediate conclusion to be drawn here is the same.
Explanatory “how”-statements can be defined in terms of “because”-statements, so that the results should generalize to “how”-explanations (Schnieder 2009).
There is no consensus as to what models actually are. Some hold that they are abstract types of objects (Psillos 2011), or that they are kin to fictions (Godfrey-Smith 2006, Frigg 2010, Toon 2010); some have argued that they are mere possibilities (Sugden 2000) or that they are descriptions (Achinstein 1968).
The locution “according to” is a hyper-intensional, sentence-forming operator. This operator is hyper-intensional in the sense that substitution of co-intensional expressions within its scope is not always possible salva veritate. A nice side effect of the hyper-intensionality of this operator is that, intuitively, “according to” cancels ontological commitment—a fact some philosophers have tried to exploit in the context of literary fiction (cf. Künne 1983). Just like we are not committed to the assumption that Sherlock Holmes exists when embracing the claim that that according to Doyle’s novels, Sherlock Holmes lives on Baker Street, we are not committed to the assumption that, say, ether exists when claiming that according to the classical ether model, there is ether. The beauty of this move consists in the fact that thereby, we do not commit us to the existence of “fictional” entities, or objects postulated by models. Recent fictionalist interpretations of scientific modeling, such as those proposed by Frigg (2010) and Toon (2010), incorporate similar locutions, such as “It is fictional in _ that _.” These accounts remain silent about the exact logical behavior of such locutions, focusing instead of the truth conditions for sentences that employ such operators, based on a theory of props and games of make believe (Walton 1990). See also (van Riel 2015) for an elaboration.
Conceive of the quantification as substitutional, quantifying into the position of sentences.
One exception is worth mentioning: If models are propositions, there is a straightforward answer to how they can be related to truth and falsehood.
The idea is that the problem is particularly pressing in economics, because economic models, according to Reiss, seem to lack the explanatory value or some of the representational features their counterparts in the natural sciences apparently exhibit (a view also defended by Rosenberg 1978; for a radically different viewpoint: Sugden 2013, Mäki 2009, 2011).
Of course, not everybody who believes that some false models are explanatory, even when and insofar as they provide false explanations, believes that there is a genuine puzzle or paradox surrounding the explanatory power of false models. Some would say, for instance, that these models provide “how-possibly”-explanations (for a discussion, see van Riel 2015). Yet, by combining the strong interpretation of 1 with the idea that some models are explanatory, i.e., premise 2, we focus on precisely this idea: That false models, even when and insofar as they provide false explanantia, may be explanatory.
Reiss himself seems to be aware of this fact, claiming that one “strategy to resolve the paradox is to claim that a model can be true despite, or even in virtue of, containing many falsehoods. More accurately, a model can misrepresent its target in some (presumably, inessential) respects to correctly (“truthfully”) represent other (presumably, essential) respects.” (Reiss 2012, 50) And he suggests that “[t]his line of defense is perfectly legitimate for a variety of false modelling assumptions in science.” (ibid.) The point is that not all models succeed in this respect, and he suggests that the paradox arises for models when no such faithful representation based on, or involving falsehoods is involved.
This also sheds light on the mechanism underlying the generation of true explanations based on false models: It is not at all miraculous how truths can be true according to a given falsehood.
Here, I follow the suggestion of an anonymous referee to include discussion of this case. I am very grateful—I agree with the referee that in most cases, no puzzle will arise because models that provide falsehoods also provide true explanantia, in this sense.
Mere models may provide true explanantia in various ways. More complex models may involve true representations and falsehoods alike (complex scale models, for instance, may be faithful to spatial relations without being faithful to actual size), others may be entirely false but imply, or suggest, when appropriately embedded, relevant truths (as, for instance, a harmonic oscillator model does when used to model the behavior of a spring—it succeeds for small replacements of the spring).
The idea that there are two such notions of explanation is extremely demanding and as far as I can see not backed up by any evidence; Salmon (1984), to whom Alexandrova and Northcott (2013) refer, just correctly observed that explanations are related to ontic dependencies and can play an epistemic role. From these observations, it does not follow that there are two notions of explanation.
References
Achinstein, P. (1968). Concepts of science. A philosophical analysis. Baltimore: Johns Hopkins Press.
Alexandrova, A. (2008). Making models count. Philosophy of Science, 75, 383–404.
Alexandrova, A., & Northcott, R. (2009). Progress in economics: lessons from the spectrum auctions. In H. Kincaid & D. Ross (Eds.), The Oxford handbook of philosophy of economics (pp. 306–336). Oxford, NY: Oxford University Press.
Alexandrova, A., & Northcott, R. (2013). It’s just a feeling. Why economic models do not explain. Journal of Economic Methodology, 20, 262–267.
Craver, C. (2006). When mechanistic models explain. Synthese, 153, 355–376.
Elgin, C. (2009). Is understanding factive? In A. Haddock, A. Millar, & D. Pritchard (Eds.), Epistemic Value (pp. 322–330). Oxford: Oxford University Press.
Frigg, R. (2010). Models and fiction. Synthese, 172(2), 251–268.
Godfrey-Smith, P. (2006). The strategy of model-based science. Biology and Philosophy, 21, 725–740.
Grimm, S. (2006). Is understanding a species of knowledge? British Journal for the Philosophy of Science, 57, 515–535.
Grimm, S. (2014). Understanding as knowledge of causes. In A. Fairweather (Ed.), Virtue epistemology naturalized (pp. 329–345). Dordrecht: Springer International Publishing.
Grüne-Yanoff, T. (2013). Genuineness resolved: a reply to Reiss’ purported paradox. Journal of Economic Methodology, 20, 255–261.
Hausmann, D. (2013). Paradox postponed. Journal of Economic Methodology, 20, 250–254.
Jones, M. R. (2005). Idealization and abstraction: a framework. In M. R. Jones & N. Cartwright (Eds.), Idealization XII: correcting the model. Poznan studies in the philosophy of sciences and the humanities 86 (pp. 173–217). Amsterdam: Rodopi.
Khalifa, K. (2012). Inaugurating understanding or repackaging explanation? Philosophy of Science, 79, 15–37.
Künne, W. (1983). Abstrakte Gegenstände. Semantik und Ontologie. Frankfurt/M: Suhrkamp.
Kvanvig, J. (2003). The value of knowledge and the pursuit of understanding. Cambridge: Cambridge University Press.
Mäki, U. (2009). Missing the world: models as isolations and credible surrogate systems. Erkenntnis, 70, 29–43.
Mäki, U. (2011). Models and the locus of their truth. Synthese, 180, 47–63.
Mäki, U. (2013). On a paradox of truth, or how not to obscure the issue of whether explanatory models can be true. Journal of Economic Methodology, 20, 268–279.
Pritchard, D. (2008). Knowing the answer, understanding and epistemic value. Grazer Philosophische Studien, 77, 325–339.
Psillos, S. (2011). Living with the abstract: realism and models. Synthese, 180, 3–17.
Reiss, J. (2012). The explanation paradox. Journal of Economic Methodology, 19, 43–62.
Rosenberg, A. (1978). The puzzle of economic modeling. The Journal of Philosophy, 75, 679–683.
Salmon, W. (1984). Scientific explanation and the causal structure of the world. Princeton: Princeton University Press.
Schnieder, B. (2009). A refutation of the Anscombe thesis. Linguist Philos, 31, 649–669.
Strevens, M. (2013). No understanding without explanation. Studies in History and Philosophy of Science, 44, 510–515.
Sugden, R. (2000). Credible worlds: the status of theoretical models in economics. Journal of Economic Methodology, 7, 169–201.
Sugden, R. (2013). How fictional accounts can explain. Journal of Economic Methodology, 20, 237–243.
Toon, A. (2010). Models as make-believe. In R. Frigg & M. C. Hunter (Eds.), Beyond mimesis and convention: representation in art and science (pp. 71–96). Berlin: Springer.
van Riel, R. (2015). The content of model-based information. Synthese, 192, 3839–3858.
van Riel, R. (2016). If you understand, you won’t be lucky. Grazer Philosophische Studien, 93, 196–211.
Walton, K. (1990). Mimesis as make-believe. Cambridge, MA: Harvard.
Wimsatt, W. W. (1987). False models as means to truer theories. In M. Nitecki & A. Hoffman (Eds.), Neutral models in biology (pp. 23–55). Oxford: Oxford University Press.
Woodward, J. (2003). Making things happen: a theory of causal explanation. Oxford: Oxford University Press.
Acknowledgments
I would like to thank the audience at the “Explanatory Power II”-Workshop in Bochum in Spring 2013, the audiences at colloquia in Belgrade, Bochum and Hannover, the guests at Thomas Spitzley’s discussion group at the University Duisburg-Essen and, especially, an anonymous referee for extremely helpful comments on earlier drafts of this paper. Generous funding for this work was provided by the Volkswagen Foundation as part of the Dilthey-Fellowship “A Study in Explanatory Power,” based at the University Duisburg-Essen.
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van Riel, R. What is the Problem of Explanation and Modeling?. Acta Anal 32, 263–275 (2017). https://doi.org/10.1007/s12136-016-0307-y
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DOI: https://doi.org/10.1007/s12136-016-0307-y