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Chapter 3
Identity, Structure, and Causal Representation
in Scientific Models
Kevin D. Hoover
Abstract Recent debates over the nature of causation, casual inference, and the uses
of causal models in counterfactual analysis, involving
inter alia
Nancy Cartwright
(
Hunting Causes and Using Them
), James Woodward (
Making Things Happen
), and
Judea Pearl (
Causation
), hinge on how causality is represented in models.
Economists' indigenous approach to causal representation goes back to the work of
Herbert Simonwith the Cowles Commission in the early 1950s. The paper explicates a
scheme for the representation of causal structure, inspired by Simon, and shows
how this representation sheds light on some important debates in the philosophy of
causation. This structural account is compared to Woodward's manipulability
account. It is used to evaluate the recent debates - particularly, with respect to the
nature of causal structure, the identity of causes, causal independence, and modularity.
Special attention is given to modeling issues that arise in empirical economics.
1 Models and Causes
Formal scientific models possess some distinct advantages over verbal accounts.
(There are, to be sure, disadvantages as well.) All representations (formal or verbal)
are partial: they omit, simplify, approximate, and idealize; they fall short of saying
Prepared for the
International Conference on the Philosophy of Economics and Biology
at the
National Tsing Hua University, Hsinchu, Taiwan, 24-25 March 2011; it is a substantial revision of
a paper first presented at the conference on
Modeling the World: Perspectives from Biology and
Economics
, Helsinki, 28-30 May 2009. I am grateful to Fran¸ois Claveau and two anonymous
referees for comments on an earlier draft. I acknowledge the support of the US National Science
Foundation (grant no. NSF SES-1026983).
K.D. Hoover (
*
)
Departments of Economics and Philosophy, Duke University,
213 Social Sciences Building, Box 90097, Durham, NC 27708-0097, USA
e-mail:
kd.hoover@duke.edu
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