David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
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Philosophy of Science 74 (3):304-329 (2007)
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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Citations of this work BETA
Mary S. Morgan & Till Grüne-Yanoff (2013). Modeling Practices in the Social and Human Sciences. An Interdisciplinary Exchange. Perspectives on Science 21 (2):143-156.
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.
Jaakko Kuorikoski & Caterina Marchionni (2014). Unification and Mechanistic Detail as Drivers of Model Construction: Models of Networks in Economics and Sociology. Studies in History and Philosophy of Science Part A 48:97-104.
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