Abstract
The paper explores how, in economics and biology, theoretical models are used as explanatory devices. It focuses on a modelling strategy by which, instead of starting with an unexplained regularity in the world, the modeller begins by creating a credible model world. The model world exhibits a regularity, induced by a mechanism in that world. The modeller concludes that there may be a part of the real world in which a similar regularity occurs and that, were that the case, the model would offer an explanation. Little concrete guidance is given about where such a regularity might be found. Three modelling exercises in evolutionary game theory—one from economics and two from biology—are used as case studies. Two of these (one from each discipline) exemplify ‘explanation in search of observation’. The third goes a step further, analysing a regularity in a model world and treating it as informative about the real world, but without saying anything about real phenomena. The paper argues that if the relation between the model and real worlds is understood in terms of similarity, and if modelling is understood as an ongoing discovery process rather than as the demonstration of empirical truths, there can be value in creating explanations before finding the regularities that are to be explained.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Notes
One strand in my work has been concerned with the emergence and stability of conventions and norms. When I began work on this topic in the early 1980s, the game theory used in economics assumed ideally rational players. Needing a way of modelling processes of social evolution, I adapted an evolutionary game-theoretic approach that had recently been developed by theoretical biologists (Sugden 2004).
I was unaware of Giere’s work when I first wrote about models in economics. In Sugden (2009) I try to make up for this omission.
Page references are to the reprint in Schelling (2006).
Several commentators (e.g. Aydinonat 2007; Grüne-Yanoff 2009; Mäki 2009) have contested this reading, arguing that Schelling presents this mechanism only as a potential explanation of real phenomena. I stand by (but do not repeat here) the argument of my 2000 paper that, despite some passages in MM which suggest the ‘potential explanation’ interpretation, Schelling’s extensive discussions of real-world evidence would be out of place if he were not claiming that his model tells us something, however speculative, about the real world.
As well as modelling spatial patterns of segregation, Schelling develops a very different ‘bounded-neighborhood model’. This is presented in considerable detail in JMS, but only in highly abbreviated form in MM. I shall focus on spatial models.
This property of ESS-based analysis is explained and justified in a later book by Maynard Smith (1982, pp. 4, 20–22). He argues that the assumption of asexual reproduction is just a convenient way of formulating a principle that evolutionary biologists know to be a close approximation to the truth in most applications, namely that ‘like begets like’. To use a more detailed genetic model in explaining broad features of animal behaviour would be ‘out of place’.
From now on, I will follow the conventions of game theory in treating differences in RHP as implying differences in the (expected) payoffs of strategy combinations.
This definition of ‘common-sense ESS’ is imprecise, but it is the one given by MSP.
Here isolation is being treated as the basis for a model’s claim to be informative about the world: because the model has been constructed by isolating the workings of ‘accepted principles’, we can be confident that its implications are true, albeit in the very special circumstances the model specifies. In this sense, ‘isolation’ is opposed to ‘similarity’, as implied by the title of this Section. In a weaker sense, exemplified by Mäki’s (2009) recent account of ‘models as isolations and surrogate systems’, a model can isolate a fictional mechanism simply by describing a fictional world where that mechanism is at work and where other potential causal factors are absent. If such a model turned out to exhibit similarities with the real world, one might come to believe that the mechanism it exhibited was not merely fictional; but that belief would not be justified by an isolation argument in Cartwright’s sense.
References
Aydinonat NE (2007) Models, conjectures and exploration: an analysis of Schelling’s checkerboard model of residential segregation. J Econ Methodol 14:429–454
Barton NH (1979) The dynamics of hybrid zones. Heredity 43:341–359
Cartwright N (1998) Capacities. In: Davis J, Hands W, Mäki U (eds) The handbook of economic methodology. Edward Elgar, Cheltenham, pp 45–48
Cartwright N (2002) The limits of causal order, from economics to physics. In: Mäki U (ed) Fact and fiction in economics. Cambridge University Press, Cambridge, pp 137–151
Cartwright N (2009) If no capacities, then no credible worlds. But can models reveal capacities? Erkenntnis 70:45–58
Giere R (1988) Explaining science. University of Chicago Press, Chicago
Grüne-Yanoff T (2009) Learning from minimal economic models. Erkenntnis 70:81–99
Karlin S, McGregor J (1972) Application of the method of small parameters to multi-niche population genetics. Theor Popul Biol 3:186–209
Mäki U (2009) MISSing the world: models as isolations and credible surrogate systems. Erkenntnis 70:29–43
Maynard Smith J, Parker G (1976) The logic of asymmetric contests. Anim Behav 24:59–175
Maynard Smith J, Price G (1973) The logic of animal conflicts. Nature 246:15–18
Maynard Smith J (1982) Evolution and the theory of games. Cambridge University Press, Cambridge
Schelling TC (1978) Micromotives and macrobehavior. Norton, New York
Schelling TC (2006) Dynamic models of segregation. In: Schelling TC (ed) Strategies of commitment and other essays. Harvard University Press, Cambridge, pp 249–310. First published in Journal of Mathematical Sociology 1 (1971)
Sugden R (1995) The coexistence of conventions. J Econ Behav Organ 28:241–256
Sugden R (2000) Credible worlds: the status of theoretical models in economics. J Econ Methodol 7:1–31
Sugden R (2004) The economics of rights, cooperation and welfare, 2nd edn. Palgrave Macmillan, Basingstoke. First edition 1986
Sugden R (2009) Credible worlds, capacities and mechanisms. Erkenntnis 70:3–27
Acknowledgments
A previous version of this paper was presented at a conference on ‘Modelling the world: perspectives from biology and economics’ held at the University of Helsinki in May 2009. I thank participants at that conference and two anonymous referees for comments.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Sugden, R. Explanations in search of observations. Biol Philos 26, 717–736 (2011). https://doi.org/10.1007/s10539-011-9280-4
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10539-011-9280-4