Computing the perfect model: Why do economists Shun simulation?

Philosophy of Science 74 (3):304-329 (2007)
Abstract
Like other mathematically intensive sciences, economics is becoming increasingly computerized. Despite the extent of the computation, however, there is very little true simulation. Simple computation is a form of theory articulation, whereas true simulation is analogous to an experimental procedure. Successful computation is faithful to an underlying mathematical model, whereas successful simulation directly mimics a process or a system. The computer is seen as a legitimate tool in economics only when traditional analytical solutions cannot be derived, i.e., only as a purely computational aid. We argue that true simulation is seldom practiced because it does not fit the conception of understanding inherent in mainstream economics. According to this conception, understanding is constituted by analytical derivation from a set of fundamental economic axioms. We articulate this conception using the concept of economists' perfect model. Since the deductive links between the assumptions and the consequences are not transparent in ‘bottom‐up’ generative microsimulations, microsimulations cannot correspond to the perfect model and economists do not therefore consider them viable candidates for generating theories that enhance economic understanding.
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References found in this work BETA
James H. Fetzer (1988). Program Verification: The Very Idea. Communications of the ACM 31 (9):1048--1063.
William V. Gehrlein (1983). Condorcet's Paradox. Theory and Decision 15 (2):161-197.

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Citations of this work BETA
Julian Reiss (2012). The Explanation Paradox. Journal of Economic Methodology 19 (1):43-62.
J. Kuorikoski, A. Lehtinen & C. Marchionni (2010). Economic Modelling as Robustness Analysis. British Journal for the Philosophy of Science 61 (3):541-567.
Igor Douven (2010). Simulating Peer Disagreements. Studies in History and Philosophy of Science Part A 41 (2):148-157.
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