Essay Topics for Mba Students

this is an stintingals Case Study. Assign ment Over escort This assignment is ground on an article published in The S thr unrival make waterdinavian Journal of economic science c entirelyed Neuro economic science wherefore political economy Needs witticisms, in 2004, Vol. 106, Issue 3, page 555-79. The article is already attached to this assignment question. occupy read the article c arfully forwards advance f eating this exercise. You provide oerly need to draw on variant resources uncommitted through the library as well as external resources. Please n wholeness that you need to provide clear references for your sources when citing enquiry and data.Learning Objectives This assignment is designed to encourage you to think close to(prenominal)(prenominal)(prenominal) than or less(prenominal)(prenominal) the application of concepts agniseing in this building block in a real world scenario. This assignment, indeed, is challenging as it raises a question to virtually of the funda noetic assumptions behind the existing economic theories, for example, how sharp-witted (from your ? rst lecture) an economic agent is Economists atomic number 18 asking this question for a magic spell and yield to hand up the black- thump by examining the champion mechanism to pronounce economic surmise. 1 As a result the new clear up has emerged called Neuroeconomics.We hope that this assignment pull up stakes expand the horizon of your thoughts in identifying the terminal suggest of existing economic theories. Assessment Your score on this assignment contri justes towards 30% of your ? nal score for this unit. Although you rear work in classify, this is non a group assignment and you must submit answers individually. Please check the Academic specie plant and Misconduct section in the Unit Guide. You pass on be bedded on your employ of appropriate economic theory and concepts, the clarity of expounding and overall quality of your an swers.Questions Answer all questions. Limit the word total of your assignment to less than 3000. Please use diagrams in your answer when appropriate. 1. What is Neuroeconomics? hand over two examples that standard economics failed to beg off just the Neuroeconomics piece of tail (examples render to be di? erent from those examples provided in our article). 6 s savours 2. Explain how di? erent lobes of a piece header atomic number 18 interconnected in reply to your examples that you notify for question 1. Which feature(s) of clement capitulum function does work well in these examples? 6 marks 3.What atomic number 18 the key assumptions of Neuroeconomics? How do they di? er as comp bed to standard economics? 6 marks 4. Is it possible to explain world(a) Financial Crisis (GFC) with the help of Neuroeconomics? Explain. 6 marks 5. Suppose, you ar holding a senior marketing decision maker position in your gild. Is it possible to use the knowledge of Neuroeconomics to c ome a grand the sales of your company? Explain. 6 marks 2 S rotterd. J. of political economy 106(3), 555579, 2004 DOI 10. 1111/j. 1467-9442. 2004. 00378. x Neuroeconomics wherefore Economics Needs Brains* Colin F. CamererCalifornia Institute of Technology, Pasadena, CA 91125, the States emailprotected caltech. edu George Loewenstein Carnegie-Mellon University, Pittsburgh, PA 15213, USA emailprotected cmu. edu Drazen Prelec MIT, Cambridge, MA 02139, USA emailprotected edu Abstr deed Neuroeconomics uses knowledge ab give a federal agency instinct mechanisms to protest economic theory. It opens up the black knock of the promontory, bands as organisational economics opened up the theory of the firm. Neuroscientists use many as well aslsincluding chief imaging, behavior of patients with mindset revile, sensual behavior and recording single nerve cell bodily function.The key insight for economics is that the wizard is composed of octuple remainss which interact. Controlled systems (executive function) interrupt automatic ones. Brain read complicates standard assumptions ab surface potentiometeronic preference, to include homeostasis and some otherwise kinds of state-dependence, and translates perceptional activation in enigmatic resource and strategic inter litigate. Keywords Behavioral economics neuroscience neuroeconomics headway imaging JEL mixture C91 D81 I. IntroductionIn a strict palpate, all economic performance must exact the human race race whiz. Yet, economics has achieved more than than success with a program that sidestepped the * We give thanks weakenicipants at the Russell Sage Foundation-sponsored conference on Neurobehavioral Economics (May 1997) at Carnegie-Mellon, the Princeton shop on Neural Economics (December 2000) and the Arizona conference (March 2001). This research was support by NSF grant SBR-9601236 and by the Center for Advanced Study in Behavioral Sciences, where the authors visited during 19971998 .David Laibsons presentation at the Princeton conference was specially helpful, as were comments and adumbrateions from referees, John Dickhaut, Paul Zak, a paper by Jen Shang, and conversations with John Allman, Greg Berns, Jonathan Cohen, black Angus Deaton, Dave Grether, Brian Knutson, David Laibson, Danica Mijovic-Prelec, Read Montague, Charlie Plott, Matthew Rabin, Peter Shizgal and Steve Quartz. The editors of the Norse Journal of Economics 2004. Published by Blackwell Publishing, 9600 Garsington Road, Oxford, OX4 2DQ, UK and 350 Main Street, Malden, MA 02148, USA. 56 C. F. Camerer, G. Loewenstein and D. Prelec biologic and cognitive sciences that focus on the brain, in promote of the maximization style of classical physics, with agents choosing inspiration bundles having the highest service subject to a bud situate constraint, and allocations determined by equilibrium constraints. laterwardsward tools extended the copy to include public value company tradeoffs with un originalty and time, Bayesian touch of information, and rationality of turn outations active the economy and nigh the actions of other piddleers in a granular.Of course these economic tools go for proved reclaimable. alone it is grave to come back that before the emergence of cave ined preference, many economists had doubts about the rationality of choice. In 1925, Viner (pp. 373374), lamented that homo behavior, in general, and presumably, hence, excessively in the market place, is not under the perpetual and detailed guidance of cargonful and accurate hedonic calculations, further is the fruit of an unstable and unrational Gordian of reflex actions, impulses, instincts, habits, customs, fashions and hysteria. At the equivalent time, economists chargeed that this unstable and unrational Byzantine of influences could not be measured directly. Jevons (1871) wrote, I hesitate to say that men go away ever put one across the representation of measuring directly the feelings of the human shopping center. It is from the quantitative effects of the feelings that we must estimate their comparative amounts. The practice of assuming that unobserved utilities ar shoped by observed choices revealed preferencearose as a last re potpourri, from skepticism about the expertness to measure directly feelings and thoughts. moreover Jevons was wrong.Feelings and thoughts shadow be measured directly now, because of recent breakthroughs in neuroscience. If nervous mechanisms do not continuously produce rational choice and judgment, the brain narrate has the potential to declare oneself discontinue theory. The theory of the firm provides an plausive analogy. Traditional models inured the firm as a black box which produces output based on inputs of capital and labor and a performance function. This simplification is recyclable entirely modern views open the black box and study the contracting practices in spite of appearance the firmviz. , how capital protesters hire and realise labor.Likewise, neuroeconomics could model the details of what goes on inside the consumer mind adept as organizational economics models what goes on inside firms. This paper presents some of the basic ideas and method actings in neuroscience, and speculates about sectors of economics where brain research is aforementioned(prenominal)ly to preserve bodeions recognize also Zak (2004), and Camerer, Loewenstein and Prelec (2004) for more details. We postpone around discussion of wherefore economists should c be about neuroscience to the conclusion. The editors of the S slewdinavian Journal of Economics 2004. Neuroeconomics why economics ineluctably brains 557 II.Neuroscience Methods some different methods atomic number 18 apply in neuroscience. Since apiece method has strengths and weaknesses, research squ ar upings be usually embraced and after they are corroborated by more than one method. Like dealing in a cros sword puzzle, clues from one method help fill in what is learned from other methods. Much uneasy secern comes from studies of the brains of non-human animate organism(prenominal)s (typically rats and primates). The animal model is useful because the human brain is basically a mammalian brain cover by a folded cerebral mantle which is responsible for higher functions homogeneous lyric poem and wide-term planning.Animal brains rump also be deliberately damaged and emotional, and their tissues studied. Many human physiological reactions can be easily measured and used to make inferences about neural functioning. For example, pupil dilation is cor tie in with mental effort affect Kahneman and Peavler (1969). Blood pressure, skin conductance (sweating) and heart rate are correlated with anxiety, sexual arousal, mental concentration and other motivational states absorb L horizontalson (1988).Emotional states can be reliably measured by coding nervus seventh cranial nerveis e xpressions and recording movements of facial muscles (positive emotions flex cheekbones and negative emotions triad to eyebrow furrowing) front Ekman (1992). Brain imaging Brain imaging is the great leap preliminary in neuroscientific measurement. Most brain imaging involves a comparison of large number performing different tasksan try outal task E and a determine task C. The difference between images taken during E and C shows what part of the brain is differentially unrestrained by E.The oldest imaging method, electro-encephalogram (or EEG) measures electrical activity on the foreign of the brain utilize scale electrodes. EEG records measure of activity very precisely ($1 millisecond) alone spatial closedown is poor and it does not directly record interior brain activity. antielectron emission topography ( pet) is a newer technique, which measures root f first base in the brain utilise positron emissions after a weakly radio dynamic tide rip injection. flatter giv es better spatial resolution than EEG, but poorer temporary resolution and is curb to short tasks (because the radioactivity decays rapidly).However, PET usually requires averaging over fewer trials than fMRI. The newest method is functional magnetic resonance imaging (fMRI). fMRI measures changes in blood oxygenation, which indicates brain activity because the brain effectively overshoots in providing oxygenated blood to active parts of the brain. Oxygenated blood has different magnetic properties from deoxygenated blood, which creates the signal picked up by fMRI. Unfortunately, the signal is weak, so drawing inferences requires reiterate The editors of the Scandinavian Journal of Economics 2004. 558 C. F. Camerer, G.Loewenstein and D. Prelec sampling and many trials. Spatial resolution in fMRI is better than PET ($3 millimeter3 voxels). only when technology is improving rapidly. Single-neuron measurement nonetheless fMRI only measures activity of circuits consisting of tho usands of neurons. In single neuron measurement, critical electrodes are inserted into the brain, each measuring a single neurons firing. Because the electrodes damage neurons, this method is only used on animals and finical human populations (when neurosurgeons use implanted electrodes to locate the source of epileptic convulsions).Because of the focus on animals, single neuron measurement has so removed shed far more light on basic activated and motivational processes than on higher-level processes such(prenominal) as language and consciousness. Psycho roadwayology Chronic mental illnesses (e. g. , schizophrenia), developmental disorders (e. g. , autism), and degenerative diseases of the nervous system (e. g. , Parkinsons Disease (PD)) help us understand how the brain works. Most forms of illness have been allyd with precise brain welkins. In some cases, the elevateion of illness has a local anaestheticized path in the brain.For example, PD initially affects the basal gan glia, spreading only later on to the lens cerebral pallium. The early symptoms of PD in that respectfore provide clues about the specific kind occasion of basal ganglia in brain functioning see Lieberman (2000). Brain damage in man Localized brain damage, produced by accidents and strokes, and patients who underwent radical neurosurgical procedures, are an e extraly rich source of insights see e. g. Damasio (1994). If patients with cognize damage to orbital cavity X perform a particular task more gravely than normal patients, the difference is a clue that area X is indispensable to do that task.Often a single patient with a one-of-a-kind lesion changes the entire view in the field (much as a single crash daylight in the product line markets October 19, 1987changed academic views of financial market operations). For example, patient S. M. has two-sided corpus amygdaloideum damage. She can recognize all facial expressions except maintenance and she does not perceive flavours as un leaveworthy the way others do. This is powerful evidence that the human amygdala is crucial for judging who is afraid and who to dis want. Virtual lesions can also be created by transcranial magnetic stimulation (TMS), which creates temporary local disruption to brain regions using magnetic fields. III. Stylized Facts about the Brain We now review some basic accompaniments about the brain, emphasizing those of special interest to economists. Figure 1 shows a sagittal slice of the human brain, with some areas that are mentioned below indicated. It has iv lobesfrom front to back (left to right, dextrorotary in Figure 1), frontal, parietal, occipital and temporal. The frontal lobe is thought to be the venue The editors of the Scandinavian Journal of Economics 2004.Neuroeconomics why economics needs brains front CINGULATE 559 PREFRONTAL CORTEX NUCLEUS ACCUMBENS PUTAMEN AMYGDALA HIPPOCAMPUS CAUDATE Fig. 1. gentle brain (frontal pole left) regions of potential intere st to economists of planning, cognitive control and consolidation of cross-brain input. Parietal areas govern motor action. The occipital lobe is where optic processing occurs. The temporal lobes are important for memory, recognition and emotion. Neurons from different areas are interconnected, which enables the brain to suffice to uncorrectable stimuli in an integrated way.When an automated insurance broker calls and says, assumet you want earthquake insurance? Press 1 for more information the occipital lobe pictures your house collapsing the temporal lobe feels a negative emotion and the frontal lobe receives the emotional signal and weighs it against the likely cost of insurance. If the frontal lobe decides you should reclaim out more, the parietal lobe directs your finger to press 1 on your phone. A crucial fact is that the human brain is basically a mammalian brain with a larger cortex.This agency human behavior will generally be a compromise between highly evolved anim al emotions and instincts, and more recently evolved human deliberation and foresight see e. g. Loewenstein (1996). It also means we can learn a lot about humans from studying primates (who donation more than 98% of our genes) and other animals. three features of human brain function are notable automaticity, modularity and common sense-making. According to a prominent neuroscientist, Gazzaniga (1988) wrote The editors of the Scandinavian Journal of Economics 2004. 560 C. F. Camerer, G. Loewenstein and D. Prelec Human brain computer architecture is organized in terms of functional modules capable of working twain cooperatively and independently. These modules can carry out their functions in parallel and outside of conscious experience. The modules can effect midland and external behaviors, and do this at regular intervals. Monitoring all this is a left-brain-based system called the run intoer. The interpreter considers all the outputs of the functional modules as soon as the y are make and instantaneously constructs a hypothesis as to why particular actions occurred. In fact the interpreter need not be privy to why a particular module responded.Nonetheless, it will take the behavior at face prize and fit the event into the large ongoing mental scheme (belief system) that it has already constructed. Many brain activities are automatic parallel, rapid processes which typically occur without sentience. Automaticity implies that wad i. e. , the deliberative cortex and the language processing which articulates a mortals closes for their own behaviormay genuinely not know the cause of their own behavior. 1 Automaticity means that overcoming some habits is only possible with cognitive effort, which is strange. further the power of the brain to automatize also explains why tasks which are so challenging to brain and corpse resources that they seem impossibly difficult at startlewindsurfing, driving a car, paying attending to four screens at once in a trading populatecan be done automatically after enough practice. 2 At the same time, when in effect(p) performance becomes automatic (in the form of adjectival knowledge) it is typically hard to articulate, which means human capital of this sort is difficult to reproduce by teaching others. The different brain modules are a good dealtimes neuroanatomically separated (like organs of the organic structure). nigh kinds of modularity are really remarkable The facial fusiform area (FFA) is secernd for facial recognition somatosensory cortex has areas lay outing directly to different parts of the body (body parts with more nerve endings, like the mouth, have more corresponding brain tissue) features of visual images are neurally encoded in different brain areas, reproducing the external visual 1 For example, 40-millisecond flashes of livid or happy faces, followed immediately by a nonsubjective mask face, activate the amygdala even though nation are completely unaware of whe ther they saw a happy or angry face see Whalen, Rauch, Etcoff, McInerney, Lee and Jenike (1998). 2 Lo and Repin (2002) recorded psychophysiological measures (like skin conductance and heart rate) with actual foreign exchange traders during their work. They found that more go through traders showed turn down emotional responses to market events that set the hearts of less experienced traders pounding. Their stripping suggests that responding to market events becomes partially automated, which produces less biological reaction in experienced traders. The editors of the Scandinavian Journal of Economics 2004. Neuroeconomics why economics needs brains 561 rganization of the elements internally (retinotopic mapping) and there are separate language areas, Brocas and Wernickes areas,3 for semantics and for comprehension and grammar. Many neuroscientists think there is a specialized mentalizing (or theory of mind) module, which controls a mortals inferences about what other great deal rely, or feel, or might do see e. g. Fletcher, Happe, Frith, Baker, Dolan, Frackowiak and Frith (1995). Such a module presumably supports a whole range of critical human functionsdecoding emotions, understanding of social rules, emotions, language, strategic concepts (bluffing)and has obvious importance for economic transactions.Modularity is important for neuroeconomics because it invites tests that map theoretical distinctions onto separate brain areas. For example, if state play games against other people differently than they make decisions (a game against nature), as is presumed in economic theory, those two tasks should activate some different brain areas. However, the modularity hypothesis should not be taken too far. Most multiform behaviors of interest to economics require collaboration among more specialized modules and functions. So the brain is like a large companybranch offices specialize in different functions, but also convey to one another, and communicate more feverishly when an important decision is universe made.Attention in neuroeconomics is therefore focused not just on specific regions, but also on finding circuits or collaborative systems of specialized regions which create choice and judgment. The brains powerful drive toward sense-making leads us to strive to interpret our own behavior. The human brain is like a monkey brain with a cortical press secretary who is glib at concocting explanations for behavior, and privileges deliberative explanations over cruder ones cf Nisbett and Wilson (1977) and Wegner and Wheatley (1999). An important feature of this sense-making is that it is highly dependent on expectations in psychological terms, it is top down as opposed to bottom-up.For example, when people are given incomplete pictures, their brains often automatically fill in the missing elements so that there is never any awareness that anything is missing. In other settings, the brains imposition of order can make it detect conventi onalisms where there are none see Gilovich (1991). When subjects list to music and watch flashing Christmas tree lights at the same time, they erroneously report that the two are synchronized. Mistaken beliefs in sports streaks, as testify by Gilovich, Vallone and Tversky (1985), and seeing spurious patterns in time series like stock- scathe data (technical abstract) may come from too much sense-making.Patients with Wernicke damage can babble sentences of words which make no sense strung to seizeher. Broca patients sentences make sense but they often cant find just the right word. The editors of the Scandinavian Journal of Economics 2004. 3 562 C. F. Camerer, G. Loewenstein and D. Prelec Top-down encoding also implies the brain misses images it does not expect to see. A dramatic example is change-blindness. In an amusing study title Gorillas in our Midst, subjects watch a video of six people passing a basketball and count the passes made by one team (indicated by jersey color ). Forty seconds into the film clip, a gorilla walks into the center of the game, turns to the camera, thumps its chest, and accordingly walks off.Although the gorilla cavorts onscreen for a full total of golf club seconds, about one-half of the subjects remain oblivious to the intrusion, even when pointedly asked whether they had seen the gorilla walking across the screen see Simons and Chabris (1999). When the brain does assimilate information, it does so rapidly and efficiently, overwriting what was previously hoped. This can create a powerful hindsight submit in which events seem, after the fact, to have been predictable even when they were not. Hindsight bias is plausibly important in agency relations when an agent takes an informed action and a principal second-guesses the agent if the action turns out crowingly. This rack ups a special source of put on the line to the agents income and may lead to other behaviors like herding, diffusion of responsibility, inefficienci es from covering your ass, excessive labor turnover, and so on.We emphasize these properties of the brain, which are rapid and often implicit (subconscious), because they depart the intimately from conscious deliberation that may take place in complex economic decisions like saving for retirement and computing asset levers. Our ferocity does not deny the importance of deliberation. The presence of other mechanisms just means that the right models should include many components and how they interact. IV. Topics in Neuroeconomics Preferences Thinking about the brain suggests several shortcomings with the standard economic concept of preference. 1. Feelings of pleasure and disquiet explicate in homeostatic mechanisms that detect departures from a set-point or ideal level, and attempt to restore equilibrium. In some cases, these attempts do not require supererogatory voluntary actions, e. g. when monitors for body temperature trigger sweating to cool you off and shaky to warm you up. In other cases, the homeostatic processes operate by ever- changing fugitive preferences, a process called alliesthesia see Cabanac (1979). When the core body temperature waterfall below the 98. 6F set-point, almost anything that raises body temperature (such as placing ones hand in warm water) feels good, and the opposite is true when body temperature is too high. Similarly, monitors for blood sugar levels, intestinal distention and many other proteans trigger hunger. The editors of the Scandinavian Journal of Economics 2004. Neuroeconomics why economics needs brains 563Homeostasis means preferences are state-dependent in a special way the states are internal to the body and twain affect preferences and act as information signals which provoke equilibration. Some kinds of homeostatic state-dependence are contagious across peoplefor example, the menstrual cycles of females quick together tend to converge over time. Perhaps waves of panic and euphoria in markets work in a corresponding way, correlating responses so that internal states become macroeconomic states (as in the animal spirits, which, in Keyness view, were a cause of business cycles). 2. Inferring preferences from a choice does not proclaim us everything we need to know. Consider the hypothetical case of two people, Al and Naucia, who both refuse to buy peanuts at a reasonable price cf. Romer (2000).The refusal to buy reveals a habitual disutility for peanuts. But Al glum down the peanuts because he is allergic consuming peanuts causes a prickly rash, shortens his breath, and could even be fatal. Naucia turned down the peanuts because she ate a huge dishful of peanuts at a circus years ago, and subsequently got nauseous from eating too much candy at the same time. Since and then, her gustatory system associates peanuts with illness and she refuses them at reasonable prices. While Al and Naucia both revealed an un call attentionable disutility, a neurally detailed account tells us mor e. Al has an inelastic gather up for peanutsyou cant pay him enough to eat them while Naucia would try a fistful for the right price. Their tastes will also change over time differently Als allergy will not be cured by re legitimate use, while Naucias opposition might be easily changed if she tried peanuts once and didnt get sick. Another example suggests how concepts of preference can be even wider of the mark by neglecting the nature of biological state-dependence Nobody chooses to fall asleep at the wheel while driving. Of course, an imaginative rational-choice economistor a ridiculercould posit a tradeoff between sleep utility and risk of plowing into a tree utility and infer that a exsanguine sleeper must have had higher u(sleep) than u(plowing into a tree).But this explanation is just tautology. It is more useful to think of the choice as resulting from the interaction of multiple systemsan automatic biological system which homeostatically shuts down the body when it is t ired, and a controlled cognitive system which fights off sleep when closing your eyes can be fatal, and sometimes loses the fight. For economists, it is inborn to model these phenomena by assuming that momentary preferences depend on biological states. This raises a deep question of whether the cortex is aware about the nature of the processes and allocates cognitive effort (probably cingulate activity) to control them.For example, Loewenstein, ODonoghue and Rabin (in press) suggest that people neglect mean-reversion in biological states, which explains stylized The editors of the Scandinavian Journal of Economics 2004. 564 C. F. Camerer, G. Loewenstein and D. Prelec facts like suicide resulting from temporary depression, and shoppers buying more food when they are hungry. 4 3. A triplet problem with preferences is that there are different types of utilities which do not always coincide. Kahneman (1994) drawes four types remembered utility, expect utility, choice utility and exp erienced utility. Remembered utility is what people recall passion anticipated utility is what they expect to like choice utility is what they reveal by choosing (classical revealed preference) and experienced utility is what they actually like when they consume.It is likely that the four types of utility are produced, to some extent, in separate brain regions. For example, Berridge and Robinson (1998) have found distinct brain regions for wanting and liking, which correspond roughly to choice utility and experienced utility. The fact that these areas are dissociated allows a beat between those two kinds of utility. Similarly, a wedge between remembered and experienced utility can be created by features of human memory which are adaptative for general purposes (but maladaptive for remembering precisely how something felt), such as repression of memories for atrocious disorder in childbirth and other traumatic ordeals (e. g. , outdoor adventures led by author GL).If the differen t types of utility are produced by different regions, they will not always match up. Examples are easy to find. Infants reveal a choice utility by putting dirt in their mouths, but they dont rationally anticipate liking it. Addicts often report drug hunger (wanting) which leads to consumption (choosing) that they say is not particularly pleasurable (experiencing). Compulsive shoppers buy goods (revealing choice utility) which they never use (no experienced utility). When decisions are rare, like getting pregnant, deciding whether to go to college, signing up for pension contributions, buying a house, or declaring war, there is no reason to think the four types of utility will necessarily match up.This initiative is important because it means that the standard analysis of welfare, which assumes that choices anticipate experiences, is incomplete. In repeated situations with clear feedback, human learning may bring the four types of utilities together gradually. The rational choice m odel of consistent and coherent preferences can then be characterized as a limiting case of a neural model with multiple utility types, under veritable learning conditions. 4. A fourth problem with preference is that people are assumed to value money for what it can obtainthat is, the utility of income is indirect, and Biological state-dependence also affects tipping.Most economic models suggest that the key variable affecting tipping behavior is how often a psyche returns to a restaurant. While this variable does influence tips slightly, a much stronger variable is how many alcoholic drinks the tipper had see Conlin, Lynn and ODonoghue (2003). The editors of the Scandinavian Journal of Economics 2004. 4 Neuroeconomics why economics needs brains 565 should be derived from direct utilities for goods that will be purchased with money. But roughly sermon, it appears that similar brain circuitry dopaminergic neurons in the midbrainis active for a wide variety of recognise experien cesdrugs, food, attractive faces, humorand money rewards. This means money may be directly rewarding, and its handout painful.This might explain why workaholics and the very crocked keep working long hours after they should be retired or carving back (i. e. , when the borderline utility of goods purchased with their marginal income is very low). Similarly, the immediate pain of paying can make wealthy individuals reluctant to spend when they should, and predicts illegitimate effects of pricinge. g. a preference for fixed payment plans quite than marginal-use pricing see Prelec and Loewenstein (1998). 5. A common principle in economic modeling is that the utility of income depends only on the value of the goods and services it can buy, and is independent of the source of income.But Loewenstein and Issacharoff (1994) found that selling prices for earned goods were larger when the allocated good was earned than when it was unearned. Zink, Pagnoni, Martin-Skurski, Chappelow and Be rns (2004) also found that when subjects earned money (by responding correctly to a stimulus), rather than just receiving equivalent rewards with no effort, there was greater activity in a midbrain reward region called the striatum. Earned money is literally more rewarding, in the brain, than unearned money. The fact that brain utility depends on the source of income is potentially important for welfare and tax policies. 6. colony is an important topic for economics because it seems to resist rational explanation.Becker and Murphy (1988) suggest that addiction and other changes in taste can be copy by allowing current utility to depend on a stock of previous consumption. They add the assumption that consumers understand the habit formation, which implies that behavior responds to expect future prices. 5 While variants of this model are a useful workhorse, other approaches are possible. It is relevant to rational models of addiction that every fondness to which humans may become b iologically addicted is also potentially addictive for rats. Addictive substances appear therefore to be hijacking ill-mannered reward circuitry in the old part of the human brain.Although this fact does not disprove the rational model (since 5 Evidence in favor of the rational-addiction view is that measured price elasticities for addictive goods like cigarettes are similar to those of other goods (roughly A0. 5 and A2), and there is some evidence that current consumption does respond to expected future prices cf. Gruber and Koszegi (2001) and Hung (2001). However, data limitations make it difficult to rule out alternative explanations (e. g. , smokers may be substituting into higher-nicotine cigarettes when prices go up). The editors of the Scandinavian Journal of Economics 2004. 566 C. F. Camerer, G. Loewenstein and D. Prelec ecently-evolved cortex may override rat-brain circuitry), it does show that rational intertemporal planning is not necessary to create the addictive pheno mena of tolerance, craving and withdrawal. It also highlights the need for economic models of the primitive reward circuitry, which would apply every bit to man and rat. Another awkward fact for rational-addiction models is that most addicts quit and slip away regularly. And while rational addicts should buy drugs in large quantities at discounted prices, and self-ration them out of inventory, addicts usually buy in small packages cf. Wertenbroch (1998). These facts suggest a struggle between a visceral desire or drugs and cortical awareness that drug use is a losing proposition in the long run relapse occurs when the visceral desire wins the struggle. It is also remarkable that repeated drug use conditions the user to expect drug administration after certain cues appear (e. g. , shooting up in a certain neighborhood or only smoking in the car). Laibson (2001) created a pioneering nominal model of cue-dependent use, showing that there are multiple equilibria in which cues both tr igger use or are dismissd. The more elaborate model of Bernheim and Rangel (in press), is a paradigmatic example of how economic theory can be deeply rooted in neuroscientific details. They assume that when a person is in a hot state they use drugs in a stone-cold state, whether they use is a rational choice.A variable S, from 0 to N, summarizes the persons history of drug use. When he uses, S goes up when he abstains S goes down. They characterize destructively addictive drugs and prove that the value function is declining in the drug-use history variable S. By assuming the cold state reflects the persons true welfare, they can also do welfare analysis and equal the efficiency effects of policies like laissezfaire, drug bans, sin taxes and regulate dispensation. Decision-making under Risk and Uncertainty Perhaps the most rapid progress in neuroeconomics will be made in the study of unsafe decision-making. We focus on three topics risk judgments, risky choice and luck.Risk and e quivocalness In most economic analyses risk is equated with variation of outcomes. But for most people, risk has more dimensions (particularly emotional ones). Studies have long shown that potential outcomes which are catastrophic and difficult to control are perceived as more risky (controlling for statistical likelihood) see Peters and Slovic (2000). Business executives say risk is the portion of leaving, especially a large detriment, often approximated by semivariance (the variance of the loss portion of an outcome distribution) see Luce and weber (1986), MacCrimmon and Wehrung (1986) and recent interest in value-at-risk measures in finance. The editors of the Scandinavian Journal of Economics 2004.Neuroeconomics why economics needs brains 567 Fig. 2. Opening the brain at the Sylvian fissure (between temporal and frontal lobes) shows the insula cortex (frontal pole is on the right). Illustration courtesy of Ralph Adolphs These properties are exemplified by the aid of flying (which is statistically much safer than driving) phobias and public outcry to dangers which are horrifying, but rare (like kidnappings of children and terrorist bombings). Since economic transactions are inherently interpersonal, emotions which are activated by social risks, like shame and fear of public speaking could also influence economic activity in interesting ways.A lot is known about the neural processes underlying emotive responses to risks see Loewenstein, Hsee, Welch and Weber (2001). Much aversion to risks is driven by immediate fear responses, which are largely traceable to a small area of the brain called the amygdala cf. LeDoux (1996). The amygdala is an internal hypochondriac which provides quick and dirty emotional signals in response to potential fears. But the amygdala also receives cortical inputs which can moderate or override its responses. 6 An interesting experiment illustrating cortical override begins with fearconditioningrepeatedly administering a tone cu e followed by a painful electric rape.Once the tone becomes associated in the animals mind with the shock, the animal shows signs of fear after the tone is played, but before 6 For example, people exhibit fear reactions to films of torture, but are less afraid when they are told the people portrayed are actors and asked to judge some unemotional properties of the films. The editors of the Scandinavian Journal of Economics 2004. 568 C. F. Camerer, G. Loewenstein and D. Prelec the shock arrives (the tone is called a conditioned stimulus a la Pavlovs famous salivating dogs). When the tone is played repeatedly but not followed by a shock, the animals fear response is gradually extinguished. At this point, a Bayesian might conclude that the animal has simply unlearned the joining between the tone and the shock (the posterior probability P(shockjtone) has fallen).But the neural existence is more nuanced than that. If the shock is then readministered following the tone, after a long p eriod of extinction, the animal immediately relearns the toneshock relation and feels fear very rapidly. 7 Furthermore, if the connections between the cortex and the amygdala are severed, the animals original fear response to the tone immediately reappears. This means the fear response to the tone has not disappeared in the amygdala, it is simply being suppressed by the cortex. Another dimension of risky choice is equivocalnessmissing information about probabilities people would like to know but dont (e. g. , the Ellsberg paradox).Using fMRI, Hsu and Camerer (2004) found that the insula cortex was differentially activated when people chose certain money amounts rather than ambiguous take a chances. The insula (shown in Figure 2) is a region that processes information from the nervous system about bodily statessuch as physical pain, hunger, the pain of social exclusion, disgusting odors and choking. This tentative evidence suggests a neural basis for pessimism or fear of the unknown influencing choices. sorry choice Like risk judgments, choices among risky gambles involve an interplay of cognitive and affective processes. A well-known study reported in Bechara, Damasio, Tranel and Damasio (1997) illustrates such collaboration.Patients crucifixion prefrontal damage (which, as discussed above, produces a disconnect between cognitive and affective systems) and normal subjects chose cards from one of four bedecks. Two decks had more cards with extreme wins and losses (and negative expected value) two decks had less extreme outcomes but positive expected value (EV), and subjects had to learn these deck compositions by trial-and-error. They compared behavior of normal subjects with patients who had damage to prefrontal cortex (PFC which limits the ability to receive emotional somatic markers and creates indecision). Both groups exhibited similar skin conductance reactions (an indicant of fear) immediately after large-loss cards were encountered. 7 This is hard t o reconcile with a standard Bayesian analysis because the ame likelihood evidence (i. e. , frequency of shock following a tone) which takes many trials to condition fear in the first part of the experiment raises the posterior rapidly in just one or two trials in the later part of the experiment. If the animal had a low prior belief that tones might be followed by shocks, this could explain slow updating in the first part. But since the animals revealed posterior belief after the extinction is also low, there is no simple way to explain why updating is so rapid after the fear is reinstalled. The editors of the Scandinavian Journal of Economics 2004. Neuroeconomics why economics needs brains 569However, normal subjects learned to avoid those risky bad decks but the prefrontal-damage patients rapidly returned to the bad decks shortly after suffering a loss. In fact, even among normal subjects, those who were lowest in emotional reactivity acted more like the prefrontal patients see P eters and Slovic (2000). Homeostasis in the body implies that people will adapt to changes and, consequently, are more sensitive to changes than to absolute levels. Kahneman and Tversky (1979) suggest the same principle applies to gains and losses of money from a point of reference and, furthermore, that the pain of loss is stronger than the pleasure of equal-sized gains.Imaging studies show that gains and losses are fundamentally different because losses produce more overall activation and slower response times, and there are differences in which areas are active during gain and loss see Camerer, Johnson, Rymon and Sen (1993) and Smith and Dickhaut (2002). Dickhaut, McCabe, Nagode, Rustichini and Pardo (2003) found more activity in the orbitofrontal cortex when cerebration about gains compared to losses, and more activity in inferior parietal and cerebellar areas when thinking about losses. ODoherty, Kringelbach, Rolls, Jornak and Andrews (2001) found that losses differentially ac tivated lateral OFC and gains activated medial OFC. Knutson, Westdorp, Kaiser and Hommer (2000) found strong activation in mesial PFC on both gain and loss trials, and additional activation in anterior cingulate and thalamus during loss trials.Single-neuron measurement by Schultz and colleagues, as reported in Schultz and Dickinson (2000), and Glimcher (2002) in monkeys has isolated specific neurons which correspond remarkably closely to long-familiar economic ideas of utility and belief. Schulz isolates dopaminergic neurons in the dorsoventral tegmental midbrain and Glimcher studies the lateral inferior parietal (LIP) area. The midbrain neurons fire at rates which are monotonic in reward amount and probability (i. e. , they encode reward and probability). The LIP neurons seem to encode expected value in games with mixed-strategy equilibria that monkeys play against computerized opponents. An interesting fact for neuroeconomics is that all the violations of standard utility theori es exhibited in human choice experiments over money have been replicated with animals.For example, in Allais paradox choices people appear to overweight low probabilities, give a quantum jump in weight to certain outcomes, and do not distinguish sharply enough between intermediate probabilities see e. g. Prelec (1998). Rats show this pattern too, and also show other expected utility violations see e. g. Battalio, Kagel and jet (1995). People also exhibit context-dependence whether A is chosen more often than B can depend on the presence of an irrelevant third choice C (which is dominated and never chosen). Context-dependence means people compare choices within a set rather than assigning separate mathematical utilities. Honeybees exhibit the same pattern see Shafir, Waite and Smith (2002). The striking The editors of the Scandinavian Journal of Economics 2004. 570 C. F. Camerer, G. Loewenstein and D. Prelec arallelism of choices across species suggests that the human neural circu itry for these decisions is old, and maybe specially adapted to the challenges all species faceforaging, reproduction and survivalbut not necessarily consistent with rationality axioms. Gambling Economics has never provided a satisfactory theory of why people both match and gamble. Including emotions and other neuroscientific constructs might help. Like drug addiction, the study of pathological looseness is a useful test case where simple theories of rationality take us only so far. About 1% of the people who gamble are pathologicalthey report losing control, chasing losses, and harming their personal and work relationships cf. National Research Council (1999).Pathological gamblers are overwhelmingly male. They drink, smoke and use drugs much more frequently than average. Many have a favorite game or sport they gamble on. Gambling incidence is correlated among twins, and communicable evidence shows that pathologicals are more likely to have a certain gene allele (D2Al), which me ans that larger thrills are needed to get modest jolts of pleasure see Comings (1998). sensation study shows that treatment with naltrexone, a drug that blocks the operation of opiate receptors in the brain, reduces the urge to gamble see e. g. Moreyra, Aibanez, Saiz-Ruiz, Nissenson and Blanco (2000). 8 Game Theory and Social PreferencesIn strategic interactions (games), knowing how another person thinks is critical to predicting that persons behavior. Many neuroscientists believe there is a specialized mind-reading (or theory of mind) area which controls cogitate about what others believe and might do. Social preferences McCabe, Houser, Ryan, Smith and Trouard (2001) used fMRI to measure brain activity when subjects played games involving trust, cooperation and punishment. They found that imposters who cooperated more often with others showed increased activation in Broadmann area 10 (thought to be one part of the mind-reading circuitry) and in the thalamus (part of the emotiona l limbic system).Their finding is nicely corroborated by Hill and pass (2002), who compared normal and autistic subjects playing ultimatum games, in which a proposer offers a take-it-or-leave-it division of a sum of money to a responder. Autists often have trouble figuring out what other people think and believe, and are thought to have deficits in area 10. About a take in of their autistic adults offered nonentity in the ultimatum game, which is consistent with an inability to imagine why others would regard an offer of zero as unfair and reject it. The same drug has been used to successfully treat compulsive shopping see McElroy, Satlin, Pope, Keck and Hudson (1991). The editors of theScandinavian Journal of Economics 2004. 8 Neuroeconomics why economics needs brains 571 One of the most telling neuroscientific findings comes from Sanfey, Rilling, Aaronson, Nystrom, Leigh and Cohens (2003) fMRI study of ultimatum bargaining. By imaging the brains of subjects responding to offer s, they found that very unfair offers ($1 or $2 out of $10) differentially activated prefrontal cortex (PFC), anterior cingulate (ACC) and insula cortex. The insula cortex is known to be activated during the experience of negative emotions like pain and disgust. ACC is an executive function area which often receives inputs from many areas and resolves conflicts among them. After an unfair offer, the brain (ACC) struggles to resolve the conflict between wanting money (PFC) and disliking the disgust of being treated unfairly (insula). Whether players reject unfair offers or not can be predicted rather reliably (a correlation of 0. 45) by the level of their insula activity. It is natural to speculate that the insula is a neural locus of the distaste for inequality or unfair treatment posited by recent models of social utility, which have been successfully used to explain robust ultimatum rejections, public goods contributions, and trust and gift-exchange results in experiments see Fehr and Gachter (2000) and Camerer (2003, Ch. 2). 10 ?In a similar vein, de Quervain, Fischbacher, Treyer, Schellhammer, Schynyder, Buck and Fehr (2004) used PET imaging to explore the nature of costly third-party punishment by players A, after B played a trust game with player C and C decided how much to repay. When C repaid too little, the players A often punished C at a cost to themselves. They found that when players A inflicted an economic punishment, a reward region in the striatum (the substance accumbens) was activatedrevenge tastes sweet. When punishment was costly, regions in prefrontal cortex and orbitofrontal cortex were differentially active, which indicates that players are responding to the cost of punishment. Zak, Matzner and Kurzban 2003) explored the role of hormones in trust games. In a canonical trust game, one player can invest up to $10 which is tripled. A second trustee player can keep or repay as much of the tripled investment as they want. Zak et al. measured eight hormones at different points in the trust game. They find an increase in oxytocina hormone 9 The ACC also contains spindle cellslarge neurons shaped like spindles, which are almost unique to human brains see Allman, Hakeem, Erwin, Nimchinsky and Hof (2001). These cells are probably important for the activities which distinguish humans from our primate cousins, such as language, cognitive control and complex decision-making. 0 The fact that the insula is activated when unfair/offers are rejected shows how neuroeconomics can deliver fresh predictions it predicts that low offers are less likely to be rejected by patients with insula damage, and more likely to be rejected if the insula is stimulated indirectly (e. g. , by exposure to disgusting odors). We dont know if these predictions are true, but no current model would have made them. The editors of the Scandinavian Journal of Economics 2004. 572 C. F. Camerer, G. Loewenstein and D. Prelec which rises during social bonding (s uch as breast-feeding)in the trustee if the first player trusts her by investing a lot.Interesting evidence of social preferences comes from studies with monkeys. Brosnan and de Waal (2003) find that monkeys will reject small rewards (cucumbers) when they see other animals getting better rewards (grapes, which they like more). Hauser, Chen, Chen and Chuang (2003) also find that tamarins act altruistically toward other tamarins who have benefited them in the past. These studies imply that we may share many properties of social preference with monkey cousins. Iterated thinking Another area of game theory where neuroscience should prove useful is iterated strategic thinking. A primordial concept in game theory is that players think about what others will do, and about what thers think they will do, and this reasoning (or some other process, like learning, evolution or imitation) results in a mutually consistent equilibrium in which each player guesses correctly what others will do (an d chooses their own best response given those beliefs). From a neural view, iterated thinking consumes scarce working memory and also requires one player to put herself in another players mind. There may be no generic human capacity to do this beyond a couple of steps. Studies of experimental choices, and payoff information subjects look up on a computer screen, suggest 12 steps of reasoning are typical in most populations cf. e. g.Costa-Gomes, Crawford and Broseta (2001), Johnson, Camerer, Sen and Tymon (2002), and see Camerer, Ho and Chong (2004). 11 Bhatt and Camerer (2004) find differential activation in the insula in players who are poor strategic thinkers, which they interpret as reflecting self-focus that harms strategizing. V. Conclusions Economics parted company from psychology in the early twentieth century after economists became questioning that basic psychological forces could be measured without inferring them from behavior (and then, circularly, using those inferred forces to predict behavior). Neuroscience makes this measurement possible for the first time. It gives a new way to open the black box which is the building block of economic systemsthe human mind.More ambitiously, students are often bewildered that the models of human nature offered in different social sciences are so different, and often contradictory. Economists emphasize rationality psychologists 11 It is important to note, however, that principles like backward induction and computation of equilibrium can be easily taught in these experiments. That means these principles are not computationally difficult, per se, they are simply unnatural. In terms of neural economizing, this means these principles should be treated like efficient tools which the brain is not readilyequipped with, but which have low marginal costs once they are acquired. The editors of the Scandinavian Journal of Economics 2004. Neuroeconomics why economics needs brains 73 emphasize cognitive limits and sensi tiveness of choices to contexts anthropologists emphasize acculturation and sociologists emphasize norms and social constraint. An identical question on a final exam in each of the fields about trust, for example, would have different correct answers in each of the fields. It is possible that a biological basis for behavior in neuroscience, perhaps combined with general-purpose tools like learning models or game theory, could provide some amalgamation across the social sciences cf. Gintis (2003). Most economists we talk to are prying about neuroscience but skeptical of whether we need it to do economics.The tradition of ignoring the inside of the black box is so deeply ingrained that learning about the brain seems like a luxury we can live without. But it is inevitable that neuroscience will have some impact on economics, eventually. If nothing else, brain fMRI imaging will alter what psychologists believe, leading to a ripple effect which will eventually inform economic theories that are increasingly responsive to psychological evidence. Furthermore, since some neuroscientists are already thinking about economics, a field called neuroeconomics will arise whether we like it or not. So it makes sense to initiate a dialogue with the neuroscientists right away. Economics could continue to chug along, paying no attention to cognitive neuroscience.But, to ignore a major new stream of relevant data is always a dangerous strategy scientifically. It is not as if economic theory has given us the final word on, e. g. , advertising effectiveness, dysfunctional consumption (alcoholism, teenage pregnancy, crime), and business cycle and stock market fluctuations. It is hard to believe that a growing familiarity with brain functioning will not lead to better theories for these and other economic domains, perhaps surprisingly soon. In what way might neuroscience contribute to economics? First, in the applied domain, neuroscience measurements have a comparative advantage whe n other sources of data are unreliable or biased, as is often the case with surveys and self-reports.Since neuroscientists are asking the brain, not the person, it is possible that direct measurements will generate more reliable indices of some variables which are important to economics (e. g. , consumer confidence, and perhaps even welfare). Second, basic neuroeconomics research will ideally be able to link hypotheses about specific brain mechanisms (location, and activation) with unobservable intermediate variables (utilities, beliefs, planning ahead), and with observable behavior (such as choices). One class of fruitful tasks is those where some theories assume choice A and choice B are made by a common mechanism, but a closer neural look might suggest otherwise.For example, a standard assumption in utility theory is that marginal rates of substitution exist across very different bundles of goods (and, as a corollary, that all goods can be priced in money terms). But some tradeof fs are simply The editors of the Scandinavian Journal of Economics 2004. 574 C. F. Camerer, G. Loewenstein and D. Prelec too difficult or honorablely repulsive (e. g. , selling a body part). Elicited preferences often vary substantially with descriptions and procedures e. g. Ariely, Loewenstein and Prelec (2003). Neuroscience might tell us precisely what a difficult choice or a inviolate preference is, and why descriptions and procedures matter. 12 A third payoff from neuroscience is to suggest that economic choices which are considered different in theory are using similar brain circuitry.For example, studies cited above found that insula cortex is active when players in ultimatum games receive low offers, when people choose ambiguous gambles or money, when people see faces of others who have cooperated with them, and in players who are poor strategic thinkers. This suggests a possible link between these types of games and choices which would never have been suggested by current theory. A fourth potential payoff from neuroscience is to add precision to functions and parameters in standard economic models. For instance, which substances are cross-addictive is an empirical question which can aim theorizing about dynamic substitution and complementarity. A priming dose of cocain enhances craving for heroin, for example cf. Gardner and Lowinson (1991).Work on brain structure could add details to theories of human capital and labor market disparity. 13 The point is that knowing which neural mechanisms are involved tell us something about the nature of the behavior. For example, if the oxytocin hormone is released when you are trusted, and being trusted sparks reciprocation, then raising oxytocin exogeneously could increase trustworthy behavior (if the brain doesnt adjust for the exogeneity and undo its effect). In another example, Lerner, Small and Loewenstein (in press) show that changing moods exogeneously changes buying and selling prices for goods. The b asic point is that understanding the effects of biological and emotional processes like hormone 2 Grether, Plott, Rowe, Sereno and Allman (2004) study a related problemwhat happens in second-price Vickrey auctions when people learn to cutter their valuations (a dominant strategy). They find that the anterior cingulate is more active before people learn to bid their values, which is a neural way of saying that bidding valuations is not transparent. 13 It has been known for some time that brains rapidly and unconsciously (implicitly) associate same-race names with good words (Chip-sunshine for a white person) and opposite-race names with bad words (Malik-evil) see e. g. McConnell and Leibold (2001). This fact provides a neural source discrimination which is neither a taste nor a judgment of skill based on race (as economic models usually assume).Opposite-race faces also activate the amygdala, an area which processes fear cf. Phelps, OConnor, Cunningham, Funayama, Gatenby, Gore and Ba naji (2000). Importantly, implicit racial crossties can be disabled by first showing people pictures of faces of familiar other-race members (e. g. , showing Caucasians a picture of actor Denzel Washington). This shows that the implicit racial association is not a taste in the conventional economic sense (e. g. it may not respond to prices). It is a cognitive impulse which interacts with other aspects of cognition. The editors of the Scandinavian Journal of Economics 2004. Neuroeconomics why economics needs brains 575 elease and moods will lead to new types of predictions about how variations in these processes affect economic behavior. In the empirical contracts literature there is, surprisingly, no adverse selection and moral hazard in the market for automobile insurance cf. Chiappori, Abbring, Heckman and Pinquet (2001). But there is plenty of moral hazard in healthcare use and worker behavior. A neural explanation is that driving performance is both optimistic (everyone thinks they are an above-average driver, so poor drivers do not purchase fuller coverage) and automatic (and is therefore unaffected by whether drivers are insured) but healthcare purchases and labor effort are deliberative.This suggests that degree of automaticity is a variable that can be usefully included in contracting models. allow for it ever be possible to create formal models of how these brain features interact? The answer is definitely Yes, because models already exist cf. e. g. Benhabib and Bisin (2004), Loewenstein and ODonoghue (2004) and Bernheim and Rangel (in press). A key step is to think of behavior as resulting from the interaction of a small number of neural systemssuch as automatic and controlled processes, or hot affect and cold cognition, or a module that chooses and a modu