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Published March 2005 | Published + Accepted Version
Journal Article Open

Neuroeconomics: How Neuroscience Can Inform Economics

Abstract

Neuroeconomics uses knowledge about brain mechanisms to inform economic analysis, and roots economics in biology. It opens up the "black box" of the brain, much as organizational economics adds detail to the theory of the firm. Neuroscientists use many tools— including brain imaging, behavior of patients with localized brain lesions, animal behavior, and recording single neuron activity. The key insight for economics is that the brain is composed of multiple systems which interact. Controlled systems ("executive function") interrupt automatic ones. Emotions and cognition both guide decisions. Just as prices and allocations emerge from the interaction of two processes—supply and demand— individual decisions can be modeled as the result of two (or more) processes interacting. Indeed, "dual-process" models of this sort are better rooted in neuroscientific fact, and more empirically accurate, than single-process models (such as utility-maximization). We discuss how brain evidence complicates standard assumptions about basic preference, to include homeostasis and other kinds of state-dependence. We also discuss applications to intertemporal choice, risk and decision making, and game theory. Intertemporal choice appears to be domain-specific and heavily influenced by emotion. The simplified ß-d of quasi-hyperbolic discounting is supported by activation in distinct regions of limbic and cortical systems. In risky decision, imaging data tentatively support the idea that gains and losses are coded separately, and that ambiguity is distinct from risk, because it activates fear and discomfort regions. (Ironically, lesion patients who do not receive fear signals in prefrontal cortex are "rationally" neutral toward ambiguity.) Game theory studies show the effect of brain regions implicated in "theory of mind", correlates of strategic skill, and effects of hormones and other biological variables. Finally, economics can contribute to neuroscience because simple rational-choice models are useful for understanding highly-evolved behavior like motor actions that earn rewards, and Bayesian integration of sensorimotor information.

Additional Information

© 2005 American Economic Association. We thank participants at the Russell Sage Foundation-sponsored conference on Neurobehavioral Economics (May 1997) at Carnegie Mellon, the Princeton workshop on Neural Economics December 8–9, 2000, and the Arizona conference in March 2001. This research was supported by NSF grant SBR-9601236 and by the Center for Advanced Study in Behavioral Sciences, where the authors visited during 1997–98. David Laibson's presentations have been particularly helpful, as were comments and suggestions from the editor and referees, and conversations and comments from Ralph Adolphs, John Allman, Warren Bickel, Greg Berns, Meghana Bhatt, Jonathan Cohen, Angus Deaton, John Dickhaut, Paul Glimcher, Dave Grether, Ming Hsu, David Laibson, Danica Mijovic-Prelec, Read Montague, Charlie Plott, Matthew Rabin, Antonio Rangel, Peter Shizgal, Steve Quartz, and Paul Zak. Albert Bollard, Esther Hwang, and Karen Kerbs provided editorial assistance.

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Accepted Version - JELfinal_1_.pdf

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August 19, 2023
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October 23, 2023