Abstract
Robert Sugden argues that robustness analysis cannot play an epistemic role in grounding model-world relationships because the procedure is only a matter of comparing models with each other. We posit that this argument is based on a view of models as being surrogate systems in too literal a sense. In contrast, the epistemic importance of robustness analysis is easy to explicate if modelling is viewed as extended cognition, as inference from assumptions to conclusions. Robustness analysis is about assessing the reliability of our extended inferences, and when our confidence in these inferences changes, so does our confidence in the results. Furthermore, we argue that Sugden’s inductive account relies tacitly on robustness considerations.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Notes
As one referee pointed out, models could be seen as thought experiments of the extended cognitive system.
Much of the recent philosophical literature on models underscores this point. For example, Marion Vorms (2008) uses the example of the harmonic oscillator (simple pendulum) to show how the material means or the format of representation may matter in subtle ways to what kind of inferences can be made with it.
Whether a public and a material thing can be used to make inferences about something else naturally depends on the intrinsic properties of the thing in question. Thus the contextual nature of representation does not mean that it is completely arbitrary whether something can be a representation of a particular system. We believe that this is the intuition behind the idea that there has to be a substantial account of representation that explains the epistemic properties of models (see e.g. Contessa 2007). However, noting that the intrinsic properties of things matter to what can be done with them does not yet imply that it is the concept of representation that accounts for the inferential properties of a model, rather than the other way round (cf. Brandom 1994).
This does not mean that the model outcome would be empirically supported in the sense that it should straightforwardly agree with the observations. Modelling results are often claims about tendencies or capacities of the modelled systems, and the manifestations of these tendencies can be blocked by factors not included in the models.
Uskali Mäki has argued (e.g., in 2009) that Sugden’s claim about the constructive nature of modelling is implicitly based on isolation: when we have constructed the model, we have already made the necessary isolations.
References
Akerlof, G. A. (1970). The market for “lemons”: Quality uncertainty and the market mechanism. Quarterly Journal of Economics, 84(3), 488–500.
Alexandrova, A. (2006). Connecting economic models to the real world: Game theory and the FCC spectrum auctions. Philosophy of the Social Sciences, 36(2), 173–192.
Arrow, K. J. (1986). Rationality of self and others in an economic system. Journal of Business, 59(4), 385–399.
Aydinonat, N. E. (2007). Models, conjectures and exploration: An analysis of Schelling’s checkerboard model of residential segregation. Journal of Economic Methodology, 14(4), 429–454.
Aydinonat, N. E. (2008). The invisible hand in economics: How economists explain unintended social consequences. London: Routledge.
Brandom, R. B. (1994). Making it explicit: Reasoning, representing and discursive commitment. Cambridge, MA: Harvard University Press.
Callender, C., & Cohen, J. (2006). There is no special problem about scientific representation. Theoria, 21(55), 7–25.
Cartwright, N. (2009). If no capacities then no credible worlds. But can models reveal capacities? Erkenntnis, this issue. doi:10.1007/s10670-008-9136-8.
Contessa, G. (2007). Scientific representation, interpretation, and surrogative reasoning. Philosophy of Science, 74(1), 48–68.
da Costa, N. C. A., & French, S. (2003). Science and partial truth: A unitary approach to models and scientific reasoning. New York: Oxford University Press.
de Donato Rodríguez, X., & Zamora Bonilla, J. (2009). Credibility, idealisation, and model building: An inferential approach. Erkenntnis, this issue. doi:10.1007/s10670-008-9139-5.
Giere, R. N. (1988). Explaining science: A cognitive approach. Chicago: University of Chicago Press.
Giere, R. (2002a). Models as parts of distributed cognitive systems. In N. J. Nersessian & L. Magnani (Eds.), Model based reasoning: Science, technology, values (pp. 227–241). New York: Kluwer/Plenum.
Giere, R. (2002b). Scientific cognition as distributed cognition. In P. Carruthers, S. Stich, & M. Siegal (Eds.), The cognitive basis of science (pp. 285–299). Cambridge, UK: Cambridge University Press.
Godfrey-Smith, P. (2006). The strategy of model-based science. Biology and Philosophy, 21, 725–740.
Hindriks, F. A. (2006). Tractability assumptions and the Musgrave-Mäki typology. Journal of Economic Methodology, 13(4), 401–423.
Knuuttila, T. (2005). Models, representation, and mediation. Philosophy of Science, 72(5), 1260–1271.
Knuuttila, T. (2009). Isolating representations vs. credible constructions? Economic modelling in theory and practice. Erkenntnis, this issue. doi:10.1007/s10670-008-9137-7.
Kuorikoski, J., Lehtinen, A., & Marchionni, C. (2007). Economics as robustness analysis. Homepage of PhilSci Archive: http://philsci-archive.pitt.edu/archive/00003550/econrobu.pdf.
Mäki, U. (1992). On the method of isolation in economics. In C. Dilworth (Ed.), Intelligibility in science (pp. 319–354). Atlanta and Amsterdam: Rodopi.
Mäki, U. (1994). Isolation, idealization and truth in economics. In B. Hamminga & N.·B. De Marchi (Eds.), Idealization VI: Idealization in economics (pp. 147–168). Amsterdam and Atlanta: Rodopi.
Mäki, U. (2000). Kinds of assumptions and their truth: Shaking an untwisted F-twist. Kyklos, 53(3), 317–335.
Mäki, U. (2005). Models are experiments, experiments are models. Journal of Economic Methodology, 12(2), 303–315.
Mäki, U. (2009). MISSing the world. Models as isolations and credible surrogate systems. Erkenntnis, this issue. doi:10.1007/s10670-008-9135-9.
Morgan, M. S. (2001). Models, stories and the economic world. Journal of Economic Methodology, 8(3), 361–397.
Morgan, M. S. (2003). Experiments without material intervention: Model experiments, virtual experiments and virtually experiments. In H. Radder (Ed.), The philosophy of scientific experimentation (pp. 236–254). Pittsburgh: University of Pittsburgh Press.
Morgan, M. S., & Morrison, M. (1999). Models as mediators: Perspectives on natural and social science. Cambridge: Cambridge University Press.
Musgrave, A. (1981). “Unreal assumptions” in economic theory: The F-twist untwisted. Kyklos, 34(3), 377–387.
Norton, J. D. (2004a). Why thought experiments do not transcend empiricism. In C. Hitchcock (Ed.), Contemporary debates in philosophy of science (pp. 44–66). Oxford, UK: Blackwell Publishing.
Norton, J. D. (2004b). On thought experiments: Is there more to the argument? Philosophy of Science, 71(5), 1139–1151.
Schelling, T. C. (1978). Micromotives and macrobehavior (1st ed.). New York: Norton.
Suárez, M. (2003). Scientific representation: Against similarity and isomorphism. International Studies in the Philosophy of Science, 17(3), 225–244.
Suárez, M. (2004). An inferential conception of scientific representation. Philosophy of Science, 71(5), 767–779.
Sugden, R. (2000). Credible worlds: The status of theoretical models in economics. Journal of Economic Methodology, 7(1), 169–201.
Sugden, R. (2009). Credible worlds, capacities and mechanisms. Erkenntnis, this issue. doi:10.1007/s10670-008-9134-x.
Van Fraassen, B. C. (1980). The scientific image. Oxford: Clarendon Press.
Vorms, M. (2008). Models and formats of representation. Homepage of PhilSci Archive: http://philsci-archive.pitt.edu/archive/00003900/01/models_and_formats_of_representation.pdf.
Weisberg, M. (2006). Robustness analysis. Philosophy of Science, 73(5), 730–742.
Weisberg, M. (2007). Who is a modeler? British Journal for the Philosophy of Science, 58(2), 207–233.
Wimsatt, W. C. (1981). Robustness, reliability and overdetermination. In M. B. Brewer & B. E. Collins (Eds.), Scientific inquiry and the social sciences (pp. 124–163). San Francisco: Jossey-Bass.
Woodward, J. (2006). Some varieties of robustness. Journal of Economic Methodology, 13(2), 219–240.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Kuorikoski, J., Lehtinen, A. Incredible Worlds, Credible Results. Erkenn 70, 119–131 (2009). https://doi.org/10.1007/s10670-008-9140-z
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10670-008-9140-z