David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
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Journal of Economic Methodology 17 (2):171-183 (2010)
Contrary to what is claimed by Gul and Pesendorfer (2008), in this paper I argue that neuroscience and economics can meet in ways that speak to the interests of economists. As Bernheim (2009) argues, economists seem to be primarily interested in novel models that link ?traditional? environmental variables (such as prices and taxes) to choice behavior in a more accurate way than existing models. Neuroscience might be helpful here, since especially computational neuroscience is also in the business of mapping environmental variables on to behavior. Given that experimental findings seem to show that choice behavior displays great context-sensitivity, I discuss two tentative ways in which neuroscience might be helpful. Neuroscience might be able to identify a multitude of environmental variables and the choice algorithms in the brain that they activate. Going this way might lead to novel models that differ markedly from standard economic models. Alternatively, neuroscience might be able to provide more theoretical guidance as to how individuals model the situations they are in. In principle, this route might leave standard economic models largely intact while improving their predictive record.
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References found in this work BETA
Gerd Gigerenzer (1999). Simple Heuristics That Make Us Smart. Oxford University Press.
Elizabeth A. Hoffman, M. Ida Gobbini & James V. Haxby (2000). The Distributed Human Neural System for Face Perception. Trends in Cognitive Sciences 4 (6):223-233.
Vernon L. Smith (2008). Rationality in Economics: Constructivist and Ecological Forms. Cambridge University Press.
Terence C. Burnham & Brian Hare (2007). Engineering Human Cooperation. Human Nature 18 (2):88-108.
Jack Vromen (2010). On the Surprising Finding That Expected Utility is Literally Computed in the Brain. Journal of Economic Methodology 17 (1):17-36.
Citations of this work BETA
Roberto Fumagalli (forthcoming). Five Theses on Neuroeconomics. Journal of Economic Methodology:1-20.
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