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UCSD ECON 264 - Neuroeconomics

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Neuroeconomics: How neuroscience can inform economics Colin Camerer Division HSS 228-77 Caltech Pasadena CA 91125 [email protected] George Loewenstein Dept Social & Decision Sciences Carnegie-Mellon University Pittsburgh PA 15213 [email protected] Drazen Prelec Sloan School of Management MIT Cambridge, MA 02138 [email protected] August 2, 2004. 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, Greg Berns, Meghana Bhatt, Jonathan Cohen, Angus Deaton, John Dickhaut, Dave Grether, Ming Hsu, David Laibson, Danica Mijovic-Prelec, Read Montague, Charlie Plott, Matthew Rabin, Peter Shizgal, Steve Quartz, and Paul Zak. Albert Bollard, Esther Hwang and Karen Kerbs provided editorial assistance.1Who knows what I want to do? Who knows what anyone wants to do? How can you be sure about something like that? Isn't it all a question of brain chemistry, signals going back and forth, electrical energy in the cortex? How do you know whether something is really what you want to do or just some kind of nerve impulse in the brain. Some minor little activity takes place somewhere in this unimportant place in one of the brain hemispheres and suddenly I want to go to Montana or I don't want to go to Montana. (White Noise, Don DeLillo) 1. Introduction In the last two decades, following almost a century of separation, economics has begun to import insights from psychology. “Behavioral economics” is now a prominent fixture on the intellectual landscape, and has spawned applications to topics in economics, such as finance, game theory, labor economics, public finance, law and macroeconomics (see Colin Camerer and George Loewenstein, 2004). Behavioral economics has mostly been informed by a branch of psychology called "behavioral decision research," but other cognitive sciences are ripe for harvest. Some important insights will surely come from neuroscience, either directly, or because neuroscience will reshape what is believed about psychology which in turn informs economics. Neuroscience uses imaging of brain activity and other techniques to infer details about how the brain works. The brain is the ultimate ‘black box’. The foundations of economic theory were constructed assuming that details about the functioning of the brain’s black box would not be known. This pessimism was expressed by William Jevons in 1871: I hesitate to say that men will ever have the means of measuring directly the feelings of the human heart. It is from the quantitative effects of the feelings that we must estimate their comparative amounts. Since feelings were meant to predict behavior, but could only be assessed from behavior, economists realized that without direct measurement, feelings were useless intervening constructs. In the 1940s, the concepts of ordinal utility and revealed preference eliminated the superfluous intermediate step of positing immeasurable feelings. Revealed preference theory simply equates unobserved preferences with observed choices. Circularity is avoided by assuming that people behave consistently, which makes the theory falsifiable; once they have revealed that they prefer A to B, people should not subsequently choose B over A. Later extensions — discounted, expected, and subjective expected utility, and Bayesian updating — provided similar “as if” tools which sidestepped psychological detail. The ‘as if’ approach made good sense, as long as the brain2remained substantially a black box. The development of economics could not be held hostage to progress in other human sciences. But now neuroscience has proved Jevons’ pessimistic prediction wrong; the study of the brain and nervous system is beginning to allow direct measurement of thoughts and feelings. These measurements are, in turn, challenging our understanding of the relation between mind and action, leading to new theoretical constructs and calling old ones into question. How can the new findings of neuroscience, and the theories they have spawned, inform an economic theory that developed so impressively in their absence? In thinking about the ways that neuroscience can inform economics, it is useful to distinguish two types of contributions, which we term incremental and radical approaches. In the incremental approach, neuroscience adds variables to conventional accounts of decision making or suggests specific functional forms to replace “as if” assumptions that have never been well-supported empirically. For example, research on the neurobiology of addiction suggests how drug consumption limits pleasure from future consumption of other goods (dynamic cross-partial effects in utility for commodity bundles) and how environmental cues trigger unpleasant craving and increase demand. These effects can be approximated by extending standard theory and then applying conventional tools (see Douglas Bernheim and Antonio Rangel, forthcoming; David Laibson, 2001; Ted O'Donoghue and Matthew Rabin, 1997). The radical approach involves turning back the hands of time and asking how economics might have evolved differently if it had been informed from the start by insights and findings now available from neuroscience. Neuroscience, we will argue, points to an entirely new set of constructs to underlie economic decision making. The standard economic theory of constrained utility maximization is most naturally interpreted either as the result of learning based on consumption experiences (which is of little help when prices, income and opportunity sets change), or careful deliberation– a balancing of the costs and benefits of different options -- as might characterize complex decisions like planning for retirement, buying a house, or hammering out a contract. Although economists may privately acknowledge that actual flesh-and-blood human beings often choose without much deliberation, the economic models as written invariably represent decisions in a ‘deliberative


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