In this short note I speculate about the various ways in which the study of neurological aspects of decision making could be fruitful for economic modelling

Spiegler, R

English

UCL Discovery

http://journals.cambridge.org Downloaded: 08 Sep 2009 IP address: 144.82.107.23Economics and Philosophy, 24 (2008) 515–521 Copyright C  Cambridge University Pressdoi:10.1017/S0266267108002125COMMENTS ON THE POTENTIALSIGNIFICANCE OF NEUROECONOMICSFOR ECONOMIC THEORYRAN SPIEGLERUniversity College, LondonIn this short note I speculate about the various ways in which the studyof neurological aspects of decision making could be fruitful for economicmodelling.In the numerous discussions on neuroeconomics, commentators reactnot only to the substance of neuroeconomics but also to the hype thatsurrounds it. The hype reﬂects a genuine excitement. Neuroscience is afrontier ﬁeld which is at least as interesting as economics. Moreover, it hasthe scientiﬁc and high-tech cachet that economists ﬁnd irresistible. Still, itis a hype and as such it tends to trigger critical responses.I agree with many of the criticisms. Like Harrison (2008), I am takenaback by the small samples that characterize neuroeconomics studies,the methodology of pooling subjects, and the heavy statistical machineryrequired to make raw fMRI data amenable to analysis. Like Rubinstein(2006), I observe that so far, neuroeconomics has consisted of attemptsto ﬁnd neural correlates to existing behavioural concepts (for instance,Sanfey et al. (2003) correlate subjects’ reaction to insolently low offers inthe Ultimatum Game with activity in a brain area which researchers havelearned to associate with a sense of disgust), and as such may be greatnews for neuroscience but is hardly newsworthy for economics.AndlikeGulandPesendorfer(2005),Iamnotconvincedthatthemerefactthatdecisionmakingtakesplaceinthebrainimpliesthatneuroscienceis necessarily relevant for economic analysis. For example, Roth (2006)emphasizestheroleofrepugnanceinlimitingmarkettransactions.Clearly,repugnance has its brain-level correlate. But as Roth points out, the515http://journals.cambridge.org Downloaded: 08 Sep 2009 IP address: 144.82.107.23516 RAN SPIEGLERclassiﬁcation of market transactions as repugnant has changed a lotin history and across cultures. Thus, the brain level is perhaps notthe interesting one when it comes to understanding the determinantsof repugnance in economic contexts. A historical and anthropologicalresearch perspective seems more suitable.However, in this short note I do not wish to engage in criticismsof neuroeconomics or the hype surrounding it. Instead, I will try to“think positive” and speculate about some ways in which research inneuroeconomics might contribute to economic theory. There are otherways in which neuroeconomics may prove inﬂuential. For example,Benhabib and Bisin (2008) suggest that neuroeconomics can change theway economists confront decision models with data, by viewing decisionmodels not only as theories of choice behaviour but also as theories of thedecision process. Benhabib and Bisin propose an empirical methodologythat tests decision models against joint choice and brain-level data.In what follows, I restrict attention to pure economic theory, assumingthat the tradition of economic modelling as a primary activity foreconomists will continue unabated, and I wonder how neuroeconomicsmight contribute to this activity. This speculative exploration of thepossibilities of neuroeconomics for economic theory borders on scienceﬁction. One could also argue that speculating about future models is idle.If one thinks a certain model might be interesting, then one should tryactually constructing one rather than speculating about it. Nevertheless,this kind of speculation is in its way a kind of constructive criticism. I havespent some time thinking about how neuroeconomics could contribute toeconomic modelling, and this is what I have been able to come up with. Ifthereaderdoesnotﬁndthisexciting,thenthiswillhavesuggestedthatthecase for the relevance of neuroscience for economic theory is not a trivialone to make.Correlations between personality traitsEconomic theory compartmentalizes personal characteristics according tothe domains of choice behaviour to which they pertain. Risk attitudesare deﬁned in terms of preferences over lotteries, patience in terms ofpreferences over dated prizes, social preferences in terms of choicesbetween asset allocations, etc. As neuroeconomists gather non-choice datain experiments, they may stumble upon correlations between personalcharacteristics that are independent a priori. For example, risk aversionmay becorrelated with social preferences, patience may becorrelated withIQ, and so forth.In principle, one can discover such correlations without looking atnon-choice data, since these personal characteristics are deﬁned purelyin terms of choice behaviour. However, when looking at the non-choicehttp://journals.cambridge.org Downloaded: 08 Sep 2009 IP address: 144.82.107.23COMMENTS ON THE POTENTIAL SIGNIFICANCE 517data that accompany risk aversion or social preferences, the researchermay be struck by similar patterns, and this may give the researcher themotivation to look for correlations in the corresponding choice data. Thus,although neuroscience is not necessary for discovering such correlations,doingneuroeconomicresearchmaybeagoodheuristicforstumblinguponthem.Theimplicationofsuchcorrelationsforeconomictheoryisthatwecanimpose them as a constraint on models that incorporate several personalcharacteristics. In particular, such restrictions on the domain of personalcharacteristics may be relevant for mechanism design problems. Thereis also a possibility that economists will be led to doubt the existingcompartmentalization of personal characteristics into risk attitudes, socialpreferences, time preferences, etc. For example, if patience is highlycorrelated with IQ and risk attitudes are highly correlated with socialpreferences, then perhaps our current categories miss something essentialabout decision making. This is an admittedly far-fetched thought. Giventhat so far neuroeconomics has mostly consisted of looking for neuralcorrelates of existing economic concepts, it is hard to see how such aradical prospect could ever materialize. Speculating about it, however, iseasy.Motivating process-based models of decision makingThe standard economic approach to modelling decision making is basedon utility maximization. It does not exclude aspects of psychology suchas ambiguity aversion, altruism or self-control problems. However, astandard model always ends up representing choice behaviour withsome kind of utility maximization. Thus, the implied decision processis invariably a cost–beneﬁt analysis. Gul and Pesendorfer (2005) arguethat the implied decision process is only a metaphor, a rhetorical device.The utility-maximization model is not meant to serve as a “model ofthe brain”. Still, why should we restrict ourselves to the cost–beneﬁtmetaphor? As Salant and Rubinstein (2007) argue, there is no reasonwhy we cannot conduct similar decision-theoretic exercises, in whichobservable behaviour (in a general sense that includes sensitivity of choicetoframing,aswellasnon-choicebehavioursuchasthetimeittakesagentsto reach a decision) is shown to be the possible result of some decisionprocess other than a cost–beneﬁt analysis.And yet, after so many years of applying the cost–beneﬁt metaphor,howresourcefulcanweexpecteconomiststobeatinventingoriginalones?Thisiswhereneuroeconomics canproveusefulasaheuristicforhittingongood ideas about the decision process, precisely because neuroeconomicsis mostly preoccupied with physiological mechanisms behind decisionmaking.http://journals.cambridge.org Downloaded: 08 Sep 2009 IP address: 144.82.107.23518 RAN SPIEGLERTo illustrate my point, consider an important aspect of decisionmaking which has nevertheless been virtually neglected by economists.Indecisiveness seems to be a personal trait that characterizes an individualat least as well as his time preferences. Reaching decisions is easy for somepeople, a torment for others. We can try to deﬁne indecision purely interms of observed choice correspondences, as in Eliaz and Ok (2006). Wecould also try to deﬁne it in terms of other choice behaviour, such as theamount of irrelevant information the decision maker seeks before makingadecision,ortheextenttowhichheprefersdefaultoptions,ortheextenttowhichtheframingofdecisionproblemsreﬁneshischoicecorrespondence.We could also try to deﬁne indecision in terms of observable non-choicebehaviour, such as the time it takes for the individual to make a decision,or the amount of ﬂip-ﬂopping and head scratching he goes through beforehe reaches the ﬁnal decision.Still, if the end point of our decision-theoretic analysis is going tobe a utility-maximization representation theorem (capturing some trade-off between material payoffs and the mental cost of thinking about thedecision), then we have restricted ourselves to a very thin reservoir ofmetaphors. Is cost–beneﬁt analysis the most convincing metaphor forindecision? By thinking hard about the mechanisms behind the decisionprocess, we can try to conceptualize indecision as a “bottleneck” in alinear processing mechanism, or as a “stalemate” between several parallelprocesses, which may be more convincing metaphors for indecision.Legitimizing other non-choice dataOne of the main claims of neuroeconomists is that non-choice dataare relevant for economic analysis. While this claim is often employedto justify gathering expensive fMRI data, it also justiﬁes looking atadditional, cheaper non-choice data such as response times, look-ups, etc.For psychologists, these types of data may be old hat, but for economiststhe idea that looking at these things might be interesting is quite new.Ironically, the high-tech cachet of neuroscience has the side beneﬁt ofdrawing economists’ attention to lower-tech non-choice data. Economictheorists, who are accustomed to the exercise of mapping properties ofchoice behaviour to mental constructs such as utility or beliefs, can extendtheir techniques to this richer set of non-choice data.Modelling the implications of neuroscience-driventechnological innovationsMajor technological innovations inspire new classes of models, evenif they do not cause changes in fundamental economic concepts. Forhttp://journals.cambridge.org Downloaded: 08 Sep 2009 IP address: 144.82.107.23COMMENTS ON THE POTENTIAL SIGNIFICANCE 519example, the internet has given rise to new classes of models oftwo-sided markets, position auctions and keyword-based search (seeEllison and Fisher-Ellison 2005; Athey and Ellison 2007; Eliaz andSpiegler 2007), where modelling assumptions gain their motivation andfocus from real-life features of internet technology. The impact of newtechnologyoneconomicthinkingcanbepurelymetaphorical.Forinstance,the E-mail Game (Rubinstein 1989) would be perfectly interpretableeven if e-mail technology never existed, but the technology may haveprovided the inspiration and probably helped attracting attention to thepaper.Advances in neuroscience may have similar impact. Imagine thatsome day, scientists discover some rough mapping between a set ofchemicals and a set of personality traits (risk attitudes, time preferences,social preferences, optimism, truthfulness, indecisiveness, etc.). Supposefurther that these chemicals become pervasive tradable commodities. Thismay inspire an interesting class of economic market models, becausecertain traits which are currently assumed to be immutable will nowbe an outcome of agents’ choices in the market for character-modifyingchemicals.At some level, we already have some experience with such models.There is a sizeable economic literature on the demand for addictivesubstances (Becker and Murphy 1988; Bernheim and Rangel 2004;Gul and Pesendorfer 2007). This literature treats the consumption ofaddictive substances as a specialized topic, without integrating it intolarger economic models. However, character-modifying chemicals maybecome so pervasive and related to other aspects of economic behaviourthat economists will be impelled to develop entirely new classes ofmarket models, even if these will not call for new basic modellingtools.None of the above seems to necessitate neuroscientiﬁc knowledge,but such knowledge can certainly inspire new economic assumptionsand models. The reader may have observed that I have emphasized therole of advances in neuroeconomics as a potential source of inspirationfor economic theorists, thus perhaps underplaying its promise to yieldempirical foundations for economic models. I would like to conclude with acomment on this distinction.Two of the biggest success stories in behavioural economics so farare Prospect theory and hyperbolic discounting. Even in these successfulmodels, there is a substantial gap between the assumptions solidly basedon experimental psychology and the way the models are actually applied.InordertoapplyProspecttheory,oneneedstospecifywhatdeterminesthereference point. It is a crucial component of any application of the model,and yet it is hard to justify any particular speciﬁcation with empiricalhttp://journals.cambridge.org Downloaded: 08 Sep 2009 IP address: 144.82.107.23520 RAN SPIEGLERpsychological knowledge. One has no choice but to complement themodel with assumptions based on introspection and anecdotal evidence.Similarly, since time preferences with hyperbolic discounting implydynamically inconsistent preferences, economists use the multi-selvesapproach when applying hyperbolic discounting. As Rubinstein (2006)remarks, in order to “solve” the resulting intra-personal game, economistsresort to some game-theoretic solution concept (backward induction withsophisticatedornaivebeliefsaboutfuturepreferences).Thejustiﬁcationofthis modelling procedure is not based on empirical evidence, but on othercriteria that economists ﬁnd persuasive.In both cases, there is a substantial gap between the empiricallyfounded assumptions and the assumptions one needs to make the modeltick. The most one can claim is that empirical knowledge has motivatedsomeofthecrucialassumptions.Idonotexpectneuroeconomicstochangethis practice. But my preference to view neuroeconomics as a source ofinspiration is not meant to belittle the ﬁeld. On the contrary; inspirationis a scarce resource, and if neuroeconomics ends up being successful ingiving economic theorists the motivation, focus and minimal empiricalknowledge they need to come up with new, interesting and insightfulmodels, that will be a wonderful achievement.REFERENCESAthey, S. and G. Ellison. 2007. Position auctions with consumer search. Mimeo. Cambridge,MA: MIT, Press.Becker, G. and K. Murphy. 1988. A theory of rational addiction. Journal of Political Economy96: 675–700.Benhabib, J. and A. Bisin. 2008. Choice and process: theory ahead of measurement. InPerspectives on the future of economics: Positive and normative foundations. Handbook ofeconomic methodology, Vol. 1, ed. A. Caplin and A. Schotter. New York: Oxford UniversityPress.Bernheim, D. and A. Rangel. 2004. Addiction and cue-triggered decision processes. AmericanEconomic Review 94: 1558–90.Eliaz, K. and E. Ok. 2006. Indifference or indecisiveness? Choice theoretic foundations ofincomplete preferences. Games and Economic Behavior 56: 61–86.Eliaz, K. and R. Spiegler. 2007. Consideration sets and competition marketing. Mimeo.London: UCL and Brown University.Ellison, G. and S. Fisher-Ellison. 2005. Lessons about markets from the internet. Journal ofEconomic Perspectives 19: 139–58.Gul,F.andW.Pesendorfer.2005.Thecaseformindlesseconomics.InPerspectivesonthefutureof economics: Positive and normative foundations. Handbook of economic methodology,V o l .1 ,ed. A. Caplin and A. Schotter. New York: Oxford University Press.Gul, F. and W. Pesendorfer. 2007. Harmful addiction. Review of Economic Studies 74:147–72.Harrison, G. 2008. Neuroeconomics: a critical reconsideration. Economics and Philosophy 24.Roth, A. 2006. Repugnance as a constraint on markets. Journal of Economic Perspectives 21:37–58.http://journals.cambridge.org Downloaded: 08 Sep 2009 IP address: 144.82.107.23COMMENTS ON THE POTENTIAL SIGNIFICANCE 521Rubinstein, A. 1989. The Electronic Mail Game: A Game with Almost Common Knowledge.American Economic Review 79: 385–91.Rubinstein,A.2006.Commentsonbehavioraleconomics.InAdvancesineconomic theory(2005World Congress of the Econometric Society), Vol. II, ed. R. Blundell, W. K. Newey and T.Persson, 246–54. New York: Cambridge University Press.Salant, Y. and A. Rubinstein. 2007. Some thoughts on the principle of revealed preferences.In Perspectives on the future of economics: Positive and normative foundations. Handbookof economic methodology, Vol. 1, ed. A. Caplin and A. Schotter. New York: OxfordUniversity Press.Sanfey, A., J. Rilling, J. Aronson, L. Nystrom and J. Cohen. 2003. The neural basis of economicdecision-making in the ultimatum game. Science 300: 1755–8.

A theory of rational addiction.

COMMENTS ON THE POTENTIAL SIGNIFICANCE OF NEUROECONOMICS FOR ECONOMIC THEORY

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