Biologists and economists use models to study complex systems. This similarity between these disciplines has led to an interesting development: the borrowing of various components of model-based theorizing between the two domains. A major recent example of this strategy is economists’ utilization of the resources of evolutionary biology in order to construct models of economic systems. This general strategy has come to be called “evolutionary economics” and has been a source of much debate among economists. Although philosophers have developed literatures on the nature of models and modeling, the unique issues surrounding this kind of interdisciplinary model building have yet to be independently investigated. In this paper, we utilize evolutionary economics as a case study in the investigation of more general issues concerning interdisciplinary modeling. We begin by critiquing the distinctions currently used within the evolutionary economics literature and propose an alternative carving of the conceptual terrain. We then argue that the three types of evolutionary economics we distinguish capture distinctions that will be important whenever resources of model-based theorizing are borrowed across distinct scientific domains. Our analysis of these model-building strategies identifies several of the unique methodological and philosophical issues that confront interdisciplinary modeling.
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By “borrowing” we merely mean making use of an element of model based theorizing in the construction of a model in a domain other than the one in which it was originally developed.
Indeed, Witt’s paper is aimed at elucidating what various economists within the literature have taken to be an “evolutionary” approach to economics. The influence of Witt’s analysis of evolutionary economics can be seen, for example, in Aldrich et al. (2008).
We use the term interdisciplinary modeling to refer to any type of model building in which two or more scientific disciplines are involved in the construction of a scientific model. This is to be distinguished from constructing a model that applies within two or more disciplines or is somehow involved with a topic at the intersection of two or more scientific domains.
Witt’s example of such an influence is the influence of human genetic endowment on economic behavior.
In addition, Witt causes some confusion by calling the distinction between monism and dualism an ontological one. Both camps agree on how the world is, but disagree about the import of biological evolution for economic inquiry. As such the distinction is a heuristic one not an ontological one. Recognizing this difference is important because ontological claims and heuristic strategies require very different methods of evaluation.
An important part of Darwin’s view is the claim that everything, including intentionality, must be explained within a naturalistic causal framework. This belief is similar to that held by Veblen (Witt’s paradigmatic monist), who suggested that human intentionality must be explained in causal terms and these causes would inevitably include reference to biological systems.
Dennett never actually uses the phrase “Universal Darwinism”, but it is clear that the core of his view is the same as those defended by Dawkins and Campbell.
This is not intended to imply that all evolutionary systems will have to be Darwinian in this sense. For example, Hodgson (2002) has argued that some systems in economics are Darwinian while others are Lamarckian. The Universal Darwinist only claims that the principles of Darwinian evolution are not domain-specific, but are substrate neutral.
Dennett gives the example of long division, which works equally well with pencil and paper as with skywriting (Dennett 1995, p. 50).
An account of the relationship between metaphors and analogies in science is beyond the scope of the paper.
It is true that such an identity entails an analogy between all systems in which it holds. However, Universal Darwinists are interested in the operation of the principles themselves, not in the analogy between two similar systems.
Of course one is employing biological concepts in some sense, but only insofar as the results of biological evolution are important for the study of economic systems. The concepts themselves are not borrowed in the sense of being used to describe anything about the economic system.
It is important to note that the common use of the term analogy would suggest that one could certainly draw an analogy with a system without using that similarity to aid in the construction of a model. Indeed, analogies can play other important roles in science, such as aiding in description or suggesting novel ways to test, describe, or explain a model or theory. Our focus here, however, is the use of analogy in the construction of models since this is where biology actually shapes the economic model or theory. Other uses of analogy (e.g. description) are primarily cognitive aids.
Our term “theoretical modeling”, though not unrelated, should not be confused with Achinstein’s use of the term (Achinstein 1964, 1965, 1968). Achinstein uses the term within the context of the debate over scientific realism. We intend only to make a claim concerning whether a modeler believes their model is true of some target system.
Precisely what it means for a model to be true is a matter of debate that is beyond the scope of this paper. For a further discussion of this complicated issue see (Mäki 2009).
This distinction is similar to Michael Ruse’s distinction between the heuristic and justificatory roles of analogies (Ruse 1986, pp. 32–35). An analogy-as-heuristic employs an analogy without implying the same kinds of causal relationships within the two contexts. An analogy-as-justification, however, involves the transfer of claims of truth from one domain to the other.
Although these authors discuss four Darwinian principles, the struggle for scarce resources is almost always subsumed by the principle of selection. Indeed, this struggle is usually precisely why selection occurs. Later on, Aldrich and Ruef actually ignore this fourth principle when applying Darwinian principles at the level of organizations.
For example, agent-based economic modeling incorporates assumptions concerning the decision-making limitations of economic agents. These limits on agents’ rationality are often informed by biology.
Holding to the theory of Universal Darwinism does not commit one thinking economics in particular is a place where the Darwinian algorithm applies. Our focus here, however, is on those who do endorse this claim.
For instance, Cordes (2006) argues that in order for Darwinism to apply within other domains it will have to be watered down to the point where it is in danger of being explanatorily powerless.
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We would like to thank André Ariew and Randall Westgren for helpful discussion and comments on earlier drafts of this paper. This research was partially funded by the Al and Mary Agnes McQuinn Chair of Entrepreneurial Leadership.
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Rice, C., Smart, J. Interdisciplinary modeling: a case study of evolutionary economics. Biol Philos 26, 655–675 (2011). https://doi.org/10.1007/s10539-011-9274-2
- Evolutionary economics
- Universal Darwinism