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NEUROECONOMICS: A CRITICAL RECONSIDERATION

Published online by Cambridge University Press:  01 November 2008

Glenn W. Harrison
Glenn W. Harrison*
Affiliation:
University of Central Florida
*
*Department of Economics, College of Business Administration, University of Central Florida, USA, and Durham Business School, Durham University, UK (part-time). Email contact: [email protected].
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Abstract

Understanding more about how the brain functions should help us understand economic behaviour. But some would have us believe that it has done this already, and that insights from neuroscience have already provided insights in economics that we would not otherwise have. Much of this is just academic marketing hype, and to get down to substantive issues we need to identify that fluff for what it is. After we clear away the distractions, what is left? The answer is that a lot is left, but it is still all potential. That is not a bad thing, or a reason to stop the effort, but it does point to the need for a serious reconsideration of what neuroeconomics is and what passes for explanation in this literature. I argue that neuroeconomics can be a valuable field, but not the way it is being developed and “sold” now. The same is true more generally of behavioural economics, which shares many of the methodological flaws of neuroeconomics.

Type
Essay
Information
Economics & Philosophy , Volume 24 , Issue 3: Neuroeconomics , November 2008 , pp. 303 - 344
Copyright
Copyright © Cambridge University Press 2008

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References

REFERENCES

Allgower, E. L. and Georg, K.. 2003. Introduction to numerical continuation methods. Phildaelphia: Society for Industrial and Applied Mathematics.CrossRefGoogle Scholar
Andersen, S., Harrison, G. W., Lau, M. I. and Rutström, E. E.. 2007. Behavioral econometrics for psychologists. Working Paper 07-04. Department of Economics, College of Business Administration, University of Central Florida; Journal of Economic Psychology, forthcoming.Google Scholar
Andersen, S., Harrison, G. W., Lau, M. I. and Rutström, E. E.. 2008a. Eliciting risk and time preferences. Econometrica 76: 583–618.CrossRefGoogle Scholar
Andersen, S., Harrison, G. W., Lau, M. I. and Rutström, E. E.. 2008b. Lost in state space: are preferences stable? International Economic Review 49: 1091–1112.CrossRefGoogle Scholar
Anderson, J. R. 2000. Cognitive psychology and its implications, 5th edn. New York: Worth.Google Scholar
Andreasen, N. C., Arndt, S., Swayze, V., Cizadlo, T., Flaum, M., O'Leary, D., Ehrhardt, J. C. and Yuh, W. T. C.. 1994. Thalamic abnormalities in schizophrenia visualized through magnetic resonance image averaging. Science 266: 294–8.Google Scholar
Bacharach, M. 2006. Beyond individual choices: teams and frames in game theory. Princeton, NJ: Princeton University Press.Google Scholar
Barrett, L. F., Tugade, M. M. and Engle, R. W.. 2004. Individual differences in working memory capacity and dual-process theories of the mind. Psychological Bulletin 130: 553–73.CrossRefGoogle ScholarPubMed
Benhabib, J. and Bisin, A.. 2005. Modeling internal commitment mechanisms and self-control: A neuroeconomics approach to consumption-saving decisions. Games and Economic Behavior 52: 460–92.Google Scholar
Becker, G. M., DeGroot, M. H., Morris, H. and Marschak, J.. 1963. Stochastic models of choice behavior. Behavioral Science 8: 41–55.CrossRefGoogle Scholar
Berridge, K. C. 1996. Food reward: brain substrates of wanting and liking. Neuroscience and Biobehavioral Reviews 20: 1–25.CrossRefGoogle ScholarPubMed
Bhatt, M. and Camerer, C. F.. 2005. Self-referential thinking and equilibrium as states of mind in games: fMRI evidence. Games and Economic Behavior 52: 424–59.CrossRefGoogle Scholar
Binmore, K. 2007a. Playing for real. A text on game theory. New York: Oxford University Press.CrossRefGoogle Scholar
Binmore, K. 2007b. Does game theory work? The bargaining challenge. Cambridge, MA: MIT Press.Google Scholar
Bolton, P. and Dewatripont, M.. 2005. Contract Theory. Cambridge, MA: MIT Press.Google Scholar
Bowman, F. D., Caffo, B., Bassett, S. S. and Kilts, C.. 2008. A Bayesian hierarchical framework for spatial modeling of fMRI data. NeuroImage 39: 146–56.Google Scholar
Bronars, S. G. 1987. The power of nonparametric tests of preference maximization. Econometrica 55: 693–8.Google Scholar
Bullmore, E., Brammer, M., Williams, S. C. R., Rabe-Hesketh, S., Janot, N., David, A., Mellers, J., Howard, R. and Sham, P.. 1995. Statistical methods of estimation and inference for functional MR image analysis. Magnetic Resonance in Medicine 35: 261–77.CrossRefGoogle Scholar
Camerer, C. F. and Ho, T.-H.. 1994. Violations of the betweeness axiom and nonlinearity in probability. Journal of Risk and Uncertainty 8: 167–96.Google Scholar
Camerer, C. 2003. Behavioral game theory: Experiments in strategic interaction. Princeton, NJ: Princeton University Press.Google Scholar
Camerer, C. 2008. The case for mindful economics. In Foundations of positive and normative economics, ed. Caplin, A. and Schotter, A.. New York: Oxford University Press.Google Scholar
Camerer, C., Loewenstein, G. and Prelec, D.. 2004. Neuroeconomics: why economics needs brains. Scandinavian Journal of Economics 106: 555–79.Google Scholar
Camerer, C., Loewenstein, G. and Prelec, D.. 2005. Neuroeconomics: how neuroscience can inform economics. Journal of Economic Literature 43: 9–64.CrossRefGoogle Scholar
Caplin, A. and Schotter, A., Andrew, , eds. 2008. Foundations of positive and normative economics. New York: Oxford University Press.CrossRefGoogle Scholar
Chambers, R. G. and Quiggin, J.. 2000. Uncertainty, production, choice, and agency: The state-contingent approach. New York: Cambridge University Press.Google Scholar
Chandrasekhar, P. V. S., Capra, C. M., Moore, S., Noussair, C. and Berns, G.. 2008. Neurobiological regret and rejoice functions for aversive outcomes. NeuroImage 39: 1472–84.Google Scholar
Cohen, J. D. 2005. The vulcanization of the human brain: A neural perspective on interactions between cognition and emotion. Journal of Economic Perspectives 19 (4): 3–24.Google Scholar
Coller, M. and Williams, M. B.. 1999. Eliciting individual discount rates. Experimental Economics 2: 107–27.CrossRefGoogle Scholar
Cox, J. C. 2004. How to identify trust and reciprocity. Games and Economic Behavior 46: 260–81.Google Scholar
Crum, W. R., Griffin, L. D., Hill, D. L. G. and Hawkes, D. J.. 2003. Zen and the art of medical image registration: correspondence, homology, and quality. NeuroImage 20: 1425–37.CrossRefGoogle ScholarPubMed
Deaton, A. S. 1974. The analysis of consumer demand in the United Kingdom, 1900–1970. Econometrica 42: 341–67.CrossRefGoogle Scholar
Dehaene, S. and Changeux, J.-P.. 1997. A hierarchical neuronal network for planning behavior. Proceedings of the National Academy of Sciences USA 94: 13293–13298.CrossRefGoogle Scholar
Dehaene, S., E. Spelke, P. Pinel, R. Stanescu and Tsivkin, S.. 1999. Sources of mathematical thinking: Behavioral and brain-imaging evidence. Science 284: 970–974.Google Scholar
Delgado, M. R., Nystrom, L. E., Fissell, C., Noll, D. C. and Fiez, J. A.. 2000. Tracking the hemodynamic responses to reward and punishment in the striatum. Journal of Neurophysiology 84: 3072–7.CrossRefGoogle ScholarPubMed
DeQuervain, D., Fischbacher, U., Treyer, V., Schellhammer, M., Schnyder, U., Buck, A. and Fehr, E.. 2004. The neural basis of altruistic punishment. Science 305: 1254–8.Google Scholar
Dickhaut, J., McCabe, K., Nagode, J. C., Rustichini, A., Smith, K. and Pardo, J. V.. 2003. The impact of the certainty context on the process of choice. Proceedings of the National Academy of Sciences, USA 100 (6): 3536–41.Google Scholar
Elliott, R., Friston, K. J. and Dolan, R. J.. 2000. Dissociable neural responses in human reward systems. Journal of Neuroscience 20 (16): 6159–65.CrossRefGoogle ScholarPubMed
Friedman, D., Harrison, G. W. and Salmon, J.. 1984. The Informational Efficiency of Experimental Asset Markets. Journal of Political Economy 92: 349–408.Google Scholar
Friston, K. J., Ashburner, J., Frith, C. D., Poline, J. B., Heather, J. D. and Frackowiak, R. S. J.. 1995. Spatial registration and normalization of images. Human Brain Mapping 2: 165–89.CrossRefGoogle Scholar
Gallagher, H. L. and Frith, C. D.. 2003. Functional imaging of ‘Theory of Mind’. Trends in Cognitive Sciences 7: 77–83.Google Scholar
Garcia, C. B. and Zangwill, W. I.. 1981. Pathways to solutions, fixed points, and equilibria. Englewood Cliffs, NJ: Prentice-Hall.Google Scholar
Gigerenzer, G. 1996. On narrow norms and vague heuristics: A reply to Kahneman and Tversky (1996). Psychological Review 103: 592–6.CrossRefGoogle Scholar
Gilhooly, K. J. and Falconer, W. A.. 1974. Concrete and abstract terms and relations in testing a rule. Quarterly Journal of Experimental Psychology 26: 355–9.Google Scholar
Glimcher, P. W. 2003. Decisions, uncertainty, and the brain: The science of neuroeconomics. Cambridge, MA: MIT Press.CrossRefGoogle Scholar
Goeree, J. K., Holt, C. A. and Palfrey, T. R.. 2005. Regular quantal response equilibrium. Experimental Economics 8: 347–67.Google Scholar
Grether, D. M., Plott, C. R., Rowe, D. B., Sereno, M. and Allman, J. M.. 2007. Mental processes and strategic equilibration: An fMRI study of selling strategies in second price auctions. Experimental Economics 10: 105–22.Google Scholar
Gul, F. and Pesendorfer, W.. 2006. Random expected utility. Econometrica 74: 121–46.CrossRefGoogle Scholar
Gul, F. and Pesendorfer, W.. 2008. The case for mindless economics. In Foundations of positive and normative economics, ed. Caplin, A. and Schotter, A.. New York: Oxford University Press.Google Scholar
Haile, P. A., Hortaçsu, A. and Kosenok, G.. 2008. On the empirical content of quantal response equilibria. American Economic Review 98: 180–200.Google Scholar
Harbaugh, W. T., Mayr, U. and Burghart, D. R.. 2007. Neural responses to taxation and voluntary giving reveal motives for charitable donations. Science 316: 1622–5.CrossRefGoogle ScholarPubMed
Harrison, G. W. 1989. Theory and misbehavior of first-price auctions. American Economic Review 79: 749–62.Google Scholar
Harrison, G. W. 1992. Theory and misbehavior of first-price auctions: Reply. American Economic Review 82: 1426–43.Google Scholar
Harrison, G. W. and List, J. A.. 2004. Field experiments. Journal of Economic Literature 42: 1013–59.CrossRefGoogle Scholar
Harrison, G. W. and Rutström, E. E.. 2005. Expected utility theory and prospect theory: one wedding and a decent funeral. Working Paper 05-18. Department of Economics, College of Business Administration, University of Central Florida; Experimental Economics, forthcoming.Google Scholar
Harrison, G. W. and Rutström, E. E.. 2008. Risk aversion in the laboratory. In Risk aversion in experiments, ed. Cox, J. C. and Harrison, G. W.. Bingley, UK: Emerald.Google Scholar
Harsanyi, J. C. 1975. The tracing procedure: A Bayesian approach to defining a solution for n-person non-cooperative games. International Journal of Game Theory 4: 61–94.CrossRefGoogle Scholar
Hayes, J. R. and Simon, H. A.. 1974. Understanding written problem instructions. In Knowledge and cognition, ed. Gregg, L. W.. Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
Hey, J. D. 2005. Why we should not be silent about noise. Experimental Economics 8: 325–45.Google Scholar
Hey, J. D. and Orme, C.. 1994. Investigating generalizations of expected utility theory using experimental data. Econometrica 62: 1291–326.CrossRefGoogle Scholar
Hirshleifer, J. and Riley, J. G.. 1992. The analytics of uncertainty and information. New York: Cambridge University Press.CrossRefGoogle Scholar
Hsu, M., Bhatt, M., Adolphs, R., Tranel, D. and Camerer, C. F.. 2005. Neural systems responding to degrees of uncertainty in human decision-making. Science 310: 1680–3.Google Scholar
Johnson, E. J., Camerer, C. F., Sankar, S. and Tymon, T. T.. 2002. Detecting failures of backward induction: monitoring information search in sequential bargaining. Journal of Economic Theory 104: 16–47.Google Scholar
Johnson-Laird, P. N., Legrenzi, P. and Sonino Legrenzi, M.. 1972. Reasoning and sense of reality. British Journal of Psychology 63: 394–400.Google Scholar
Jones, L. S. 2007. The ethics of transcranial magnetic stimulation. Science 315: 1663.Google Scholar
Judd, K. L. 1998. Numerical methods in economics. Cambridge, MA: MIT Press.Google Scholar
Kahneman, D. and Tversky, A.. 1979. Prospect theory: An analysis of decision under risk. Econometrica 47: 263–91.Google Scholar
Kahneman, D. and Tversky, A.. 1996. On the reality of cognitive illusions. Psychological Review 103: 582–91.Google Scholar
Keller, L., ed. 1999. Levels of selection in evolution. Princeton, NJ: Princeton University Press.Google Scholar
Knoch, D., Pascual-Leone, A., Meyer, K., Treyer, V. and Fehr, E.. 2006. Diminishing reciprocal fairness by disrupting the right prefontal cortex. Science 314: 829–32.Google Scholar
Knoch, D., Pascual-Leone, A. and Fehr, E.. 2007. The ethics of transcranial magnetic stimulation: Response. Science 315: 1663–4.Google Scholar
Knutson, B., Westdorp, A., Kaiser, E. and Hommer, D.. 2000. FMRI visualization of brain activity during a monetary incentive delay task. NeuroImage 12: 20–7.Google Scholar
Kosfeld, M., Heinrichs, M., Zak, P., Fischbacher, U. and Fehr, E.. 2005. Oxytocin increases trust in humans. Nature 435: 673–6.CrossRefGoogle ScholarPubMed
Leland, W. J. 1994. Generalized similarity judgements: An alternative explanation for choice anomalies. Journal of Risk and Uncertainty 9: 151–72.Google Scholar
Linden, D. J. 2007. The accidental mind. Cambridge, MA: Harvard University Press.Google Scholar
Lohrenz, T., McCabe, K., Camerer, C. F. and Montague, P. R.. 2007. Neural signature of fictive learning signals in a sequential investment task. Proceedings of the National Academy of Sciences, USA 104: 9494–8.CrossRefGoogle Scholar
Loomes, G. 2005. Modelling the stochastic component of behavior in experiments: some issues for the interpretation of data. Experimental Economics 8: 301–23.Google Scholar
Loomes, G. and Sugden, R.. 1998. Testing different stochastic specifications of risky choice. Economica 65: 581–98.CrossRefGoogle Scholar
Lopes, L. L. 1995. Algebra and process in the modeling of risky choice. In Decision Making from a Cognitive Perspective, ed. Busemeyer, J. R., Hastie, R. and Medin, D. L.. San Diego: Academic Press.Google Scholar
Luce, R. D. 1986. Response times: Their role in inferring elementary mental organization. New York: Oxford University Press.Google Scholar
Marr, D. 1982. Vision: A computational investigation into the human representation and processing of visual information. New York: W. H. Freeman & Company.Google Scholar
Marr, D. and Poggio, T.. 1976. Cooperative computation of stereo disparity. Science 194: 283–7.CrossRefGoogle ScholarPubMed
McCabe, K., Houser, D., Ryan, L., Smith, V. L. and Trouard, T.. 2001. A functional imaging study of cooperation in two-person reciprocal exchange. Proceedings of the National Academy of Sciences, USA 98: 11832–5.CrossRefGoogle ScholarPubMed
McClure, S. M., Laibson, D. I., Loewenstein, G. and Cohen, J. D.. 2004. Separate neural systems value immediate and delayed monetary rewards. Science 306: 503–7.Google Scholar
McClure, S. M., Ericson, K. M., Laibson, D. I., Loewenstein, G. and Cohen, J. D.. 2007. Time discounting for primary rewards. Journal of Neuroscience 27: 5796–804.CrossRefGoogle ScholarPubMed
McDaniel, T. M. and Rutström, E. E.. 2001. Decision making costs and problem solving performance. Experimental Economics 4: 145–61.Google Scholar
Mehta, J., Starmer, C. and Sugden, R.. 1994. The nature of salience: An experimental investigation of pure coordination games. American Economic Review 84: 658–673.Google Scholar
Merlo, A. and Schotter, A.. 1992. Experimentation and learning in laboratory experiments: Harrison's criticism revisited. American Economic Review 82: 1413–25.Google Scholar
Montague, P. R. and Berns, G. S.. 2002. Neural economics and the biological substrates of valuation. Neuron 36: 265–85.Google Scholar
Paris, Q. and Caputo, M. R.. 2002. Comparative statics of money-goods specifications of the utility function. Journal of Economics (Zeitschrift für Nationalökonomie) 77: 53–71.Google Scholar
Pratt, J. W. 1964. Risk aversion in the small and in the large. Econometrica 32: 122–36.CrossRefGoogle Scholar
Rabe-Hesketh, S., Bullmore, E. T. and Brammer, M. J.. 1997. The analysis of functional magnetic resonance images. Statistical Methods in Medical Research 6: 215–37.Google Scholar
Rabin, M. 1998. Psychology and economics. Journal of Economic Literature 36: 11–46.Google Scholar
Rilling, J. K., Sanfey, A. G., Aronson, J. A., Nystrom, L. E. and Cohen, J. D.. 2004. The neural correlates of theory of mind within interpersonal interactions. NeuroImage 22: 1694–703.Google Scholar
Ross, D. 2005. Economic Theory and Cognitive Science: Microexplanation. Cambridge, MA: MIT Press.Google Scholar
Rubinstein, A. 1988. Similarity and decision-making under risk (is there a utility theory resolution to the Allais paradox?) Journal of Economic Theory 46: 145–53.Google Scholar
Rubinstein, A. 2006. Discussion of ‘Behavioral Economics’. In Advances in Economics and Econometric Theory, ed. Blundell, R., Newey, W. K. and Persson, T., vol II, 246–54. New York: Cambridge University Press.Google Scholar
Rubinstein, A. 2007. Instinctive and cognitive reasoning: a study of response times. Economic Journal 117: 1243–59.Google Scholar
Samuelson, L. 2005. Foundations of human sociality: a review essay. Journal of Economic Literature 43: 488–97.Google Scholar
Samuelson, P. 1938. A note on the pure theory of consumer's behaviour. Economica 5: 61–71.CrossRefGoogle Scholar
Sanfey, A. G., Rilling, J. K., Aronson, J. A., Nystrom, L. E. and Cohen, J. D.. 2003. The neural basis of economic decision-making in the ultimatum game. Science 300: 1755–8.CrossRefGoogle ScholarPubMed
Simon, H. A. 1996. The sciences of the artificial, 3rd edn. Cambridge, MA: MIT Press.Google Scholar
Smith, V. L. 1991. Rational choice: the contrast between economics and psychology. Journal of Political Economy 99: 877–97.Google Scholar
Smith, V. L. 2003. Constructivist and ecological rationality in economics. American Economic Review 93: 465–508.Google Scholar
Smith, V. L. 2007. Rationality in economics: Constructivist and ecological forms. New York: Cambridge University Press.Google Scholar
Sorenson, R. A. 1992. Thought experiments. New York: Oxford University Press.Google Scholar
Starmer, C. 2000. Developments in non-expected utility theory: The hunt for a descriptive theory of choice under risk. Journal of Economic Literature 38: 332–82.CrossRefGoogle Scholar
Stigler, G. J. and Becker, G. S.. 1977. De Gustibus Non Est Disputandum. American Economic Review 67: 76–90.Google Scholar
Sugden, R. 2003. The logic of team reasoning. Philosophical Explorations 6: 165–81.CrossRefGoogle Scholar
Sunder, S. 2006. Economic theory: structural abstraction or behavioral reduction? History of Political Economy 38: 322–42.Google Scholar
Tisserand, D. J., Pruessner, J. C., Sanz Arigita, E. J., Boxtel, M. P. J., Evans, A. C., Jolles, J. and Uylings, H. B. M.. 2002. Regional frontal cortical volumes decrease differentially in aging: an MRI study to compare volumetric approaches and voxel-based morphometry. NeuroImage 17: 657–9.Google Scholar
Tversky, A. 1969. Intransitivity of preferences. Psychological Review 76: 31–48.Google Scholar
Tversky, A. 1977. Features of similarity. Psychological Review 84: 327–52.CrossRefGoogle Scholar
Varian, H. R. 1985. Non-parametric analysis of optimizing behavior with measurement error. Journal of Econometrics 30: 445–58.Google Scholar
Varian, H. R. 1988. Revealed preference with a subset of goods. Journal of Economic Theory 46: 179–85.Google Scholar
von Winterfeldt, D. and Edwards, W.. 1982. Costs and payoffs in perceptual research. Psychological Bulletin 19: 609–22.Google Scholar
von Winterfeldt, D. and Edwards, W.. 1986. Decision analysis and behavioral research. New York: Cambridge University Press.Google Scholar
Wason, P. C. and Johnson-Laird, P. N.. 1972. Psychology of reasoning: structure and content. Cambridge, MA: Harvard University Press.Google Scholar
Wason, P. C. and Shapiro, D.. 1971. Natural and contrived experience in a reasoning problem. Quarterly Journal of Experimental Psychology 23: 63–71.Google Scholar
White, N. M. and Gaskin, S.. 2006. Dorsal hippocampus function in learning and expressing a spatial discrimination. Learning and Memory 13: 119–22.Google Scholar
Wilcox, N. T. 1993. Lottery choice: incentives, complexity and decision time. Economic Journal 103: 1397–417.Google Scholar
Wilcox, N. T. 2006. Theories of learning in games and heterogeneity bias. Econometrica 74: 1271–92.Google Scholar
Wilcox, N. T. 2008a. Stochastic models for binary discrete choice under risk: a critical primer and econometric comparison. In Risk Aversion in Experiments, ed. Cox, J. and Harrison, G. W.. Bingley, UK: Emerald.Google Scholar
Wilcox, N. T. 2008b. Stochastically more risk averse: a contextual theory of stochastic discrete choice under risk. Journal of Econometrics 142: forthcoming.Google Scholar
Wong, D. K., Grosenick, L., Uy, E. T., Guimaraes, M. P., Carvalhaes, C. G., Desain, P. and Suppes, P.. 2008. Quantifying inter-subject agreement in brain-imaging analyses. NeuroImage 39: 1051–63.Google Scholar
Zak, P. J., Kurzban, R. and Matzner, W. T.. 2005. Oxytocin is associated with human trustworthiness. Hormones and Behavior 48: 522–7.Google Scholar
Zak, P. J., Stanton, A. A. and Ahmadi, S.. 2007. Oxytocin increases generosity in humans. PloS ONE, 11: e1128, 1–5.Google Scholar