Essay Topics for Mba Students

this is an scotchalals Case Study. Assignment Overview This date is based on an article published in The S ho applyinavian daybook of political economy c solelyed Neuro political economy Why Economics inescapably masterminds, in 2004, Vol. 106, Issue 3, page 555-79. The article is al shewy attached to this assignment misgiving. Please read the article c befully before attempting this exercise. You go out as well need to draw on several(prenominal) some other(a)wise re ascendents getable through the library as well as external resources. Please note that you need to forget clear references for your sources when citing search and data.Learning Objectives This assignment is designed to encourage you to consider around the application of concepts conducted in this unit in a real world scenario. This assignment, indeed, is dispute as it raises a question to any(prenominal) of the fundamental assumptions behind the existing economic theories, for mental testingpl e, how able (from your ? rst lecture) an economic agent is Economists be a whittleg this question for a while and try to open up the slow- package by examining the mavin mechanism to inform economic contingent action. 1 As a result the new discipline has emerged c eached Neuro political economy.We hope that this assignment get out hyperbolise the horizon of your thoughts in identifying the limitation of existing economic theories. Assessment Your score on this assignment contri savees towards 30% of your ? nal score for this unit. Although you formation work in group, this is not a group assignment and you must pass answers individually. Please check the Academic H unmatchedsty and Misconduct section in the Unit Guide. You leave be graded on your use of appropriate economic conjecture and concepts, the clarity of exposition and e rattlingplaceall superior of your answers.Questions Answer all questions. Limit the give-and-take count of your assignment to less than 30 00. Please use diagrams in your answer when appropriate. 1. What is Neuroeconomics? Provide two examples that standard economics failed to explain only the Neuroeconomics lot (examples prevail to be di? erent from those examples provided in our article). 6 marks 2. Explain how di? erent lobes of a human card atomic number 18 interconnected in solvent to your examples that you argue for question 1. Which feature(s) of human humor 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 Global Financial Crisis (GFC) with the help of Neuroeconomics? Explain. 6 marks 5. Suppose, you atomic number 18 holding a senior commercializeing executive director position in your company. Is it possible to use the intimacy of Neuroeconomics to promote the sales of your company? Explain. 6 marks 2 Scand. J. of Economics 106(3), 555579, 2004 DOI 10. 1111/j. 1467-9442. 2004. 00378. x Neuroeconomics Why Economics Needs Brains* Colin F. CamererCalifornia Institute of Technology, Pasadena, CA 91125, USA emailprotected caltech. edu George Loewenstein Carnegie-Mellon University, Pittsburgh, PA 15213, USA emailprotected cmu. edu Drazen Prelec MIT, Cambridge, MA 02139, USA emailprotected edu Abstract Neuroeconomics uses knowledge nigh cartoon ability mechanisms to inform economic theory. It opens up the black box of the star, practically as organizational economics opened up the theory of the firm. Neuroscientists use umteen toolsincluding champion resourcefulness, ex crushion of patients with brain damage, animal expression and recording single nerve cell activity.The key insight for economics is that the brain is composed of quaternate systems which act. Controlled systems (executive function) interrupt automatic pistol pistol ones. Brain recite complicates standard assumptions ab supplying up basic preferen ce, to include homeostasis and other kinds of state-dependence, and shows stirred up activation in ambiguous resource and strategic interaction. Keywords Behavioral economics neuroscience neuroeconomics brain imaging JEL classification C91 D81 I. IntroductionIn a strict guts experience, all economic activity must involve the human brain. Yet, economics has achieved much success with a program that sidestepped the * We thank participants at the Russell Sage Foundation-sponsored conference on Neuro fashional Economics (May 1997) at Carnegie-Mellon, the Princeton workshop on Neural Economics (December 2000) and the Arizona conference (March 2001). This research was supported by NSF grant SBR-9601236 and by the Center for Advanced Study in Behavioral Sciences, where the authors visited during 19971998.David Laibsons presentation at the Princeton conference was particularly helpful, as were comments and enkindleions from referees, John Dickhaut, Paul Zak, a paper by Jen Shang, and c onversations 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 Scandinavian 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 biological and cognitive sciences that focus on the brain, in favor of the maximization style of classical physics, with agents choosing using up bundles having the highest im designatement subject to a budget constraint, and allocations determined by equilibrium constraints. Later tools extended the exemplification to include public service company trade despatchs with un trustworthyty and time, Bayesian touch of teaching, and ableity of remainations intimately the economy and or so the actions of other players in a game.Of cour se these economic tools create proved utilizable. But it is all-important(prenominal) to remember that before the emergence of revealed preference, many economists had doubts about the ground of picking. In 1925, Viner (pp. 373374), lamented that Human behavior, in ordinary, and presumably, indeed, also in the market place, is not under the constant and detailed guidance of sustenanceful and accurate hedonic calculations, but is the produce of an unstable and unrational complex of re twist around actions, impulses, instincts, habits, customs, fashions and hysteria. At the a bid time, economists fe atomic number 18d that this unstable and unrational complex of influences could not be measurable at once. Jevons (1871) wrote, I hesitate to say that men will ever watch the means of measurement directly the feelings of the human heart. It is from the quantitative effect of the feelings that we must estimate their comparative amounts. The practice of anticipate that un observed utilities ar revealed by observed choices revealed preferencearose as a last resort, from skepticism about the ability to valuate directly feelings and thoughts. But Jevons was wrong.Feelings and thoughts can be measured directly now, because of recent breakthroughs in neuroscience. If neural mechanisms do not always produce rational choice and judgment, the brain severalise has the capability to suggest amend theory. The theory of the firm provides an optimistic analogy. Traditional mystifys treated the firm as a black box which produces output based on inputs of capital and labor and a production function. This simplification is useful but modern views open the black box and study the contracting practices inside the firmviz. , how capitalowners collect use of and get a line labor.Likewise, neuroeconomics could model the details of what goes on inside the consumer mind just as organizational economics models what goes on inside firms. This paper presents some of the basic ideas and orders in neuroscience, and speculates about aras of economics where brain research is deally to affect hollerions cypher also Zak (2004), and Camerer, Loewenstein and Prelec (2004) for more than details. We postpone most discussion of wherefore economists should care about neuroscience to the conclusion. The editors of the Scandinavian journal of Economics 2004. Neuroeconomics why economics needs brains 557 II.Neuroscience Methods Many variant methods are used in neuroscience. Since each method has strengths and weaknesses, research findings are usually embraced besides afterward they are corroborated by more than one method. Like filling in a crossword puzzle, clues from one method help fill in what is learned from other methods. Much neural evidence comes from studies of the brains of non-human animals (typically rats and order Primates). The animal model is useful because the human brain is basically a mammal brain covered by a folded lens cereb ral mantle which is responsible for higher(prenominal) functions analogous language and long-term preparation.Animal brains can also be designedly damaged and stimulated, and their tissues studied. Many human physiological reactions can be easily measured and used to rag inferences about neural functioning. For example, pupil dilation is correlated with mental effort call in Kahneman and Peavler (1969). Blood pressure, skin conductance (sweating) and heart rate are correlated with anxiety, sexual arousal, mental concentration and other motivational states get L eveson (1988).Emotional states can be reliably measured by coding facial expressions and recording movements of facial muscles (positive emotions flex cheekbones and negative emotions lead to eyebrow furrowing) see Ekman (1992). Brain imaging Brain imaging is the great springtime forward in neuroscientific measurement. Most brain imaging involves a comparison of batch performing disparate line of worksan experimental task E and a control task C. The difference surrounded by images stickn during E and C shows what part of the brain is polarially bring outd by E.The oldest imaging method, electro-encephalogram (or EEG) measures electrical activity on the outside of the brain using scale electrodes. EEG records timing of activity genuinely precisely ($1 millisecond) but spatial heroism is light and it does not directly record interior brain activity. positron emission crownworkography (PET) is a newer technique, which measures line of descent flow in the brain using positron emissions after a weakly radioactive blood injection. PET gives better spatial resoluteness than EEG, but poorer temporal resolution and is limited to short tasks (because the radioactivity decays speedily).However, PET usually expects averaging over fewer trials than fMRI. The newest method is functional magnetised resonance imaging (fMRI). fMRI measures changes in blood oxygenation, which indicates brain activi ty 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 quest picked up by fMRI. Unfortunately, the signal is weak, so drawing inferences requires repeated 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). But technology is improving rapidly. Single-neuron measurement tear down fMRI only measures activity of circuits consisting of thousands of neurons. In single neuron measurement, tiny 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 supernumerary human populations (when neurosurgeons use implanted electrodes to locate the source of epileptic convulsions).Because of the focus on a nimals, single neuron measurement has so far shed far more light on basic aflame and motivational processes than on higher-level processes such as language and consciousness. Psycho railsology Chronic mental sicknesses (e. g. , schizophrenia), developmental disorders (e. g. , autism), and degenerative diseases of the nervous system (e. g. , Parkinsons Disease (PD)) help us discover how the brain works. Most forms of illness have been fellerd with particular proposition brain areas. In some cases, the progression of illness has a localized path in the brain.For example, PD initially affects the basal ganglia, spreading only later to the cortex. The early symptoms of PD on that show upfore provide clues about the specific role of basal ganglia in brain functioning see Lieberman (2000). Brain damage in humans Localized brain damage, produced by accidents and strokes, and patients who underwent radical neurosurgical procedures, are an e peculiarly exuberant source of insights see e. g. Damasio (1994). If patients with known damage to area X perform a particular task more poorly than normal patients, the difference is a clue that area X is necessary 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 day in the stock markets October 19, 1987changed academic views of financial market operations). For example, patient S. M. has isobilateral amygdala damage. She can recognize all facial expressions except reverence and she does not perceive faces as untrustworthy the way others do. This is powerful evidence that the human amygdala is crucial for judging who is afraid and who to distrust. virtual(prenominal) 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 features 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 four lobesfrom front to back (left to right, clockwise in Figure 1), facade, parietal, occipital and temporal. The frontal lobe is thought to be the locus The editors of the Scandinavian Journal of Economics 2004.Neuroeconomics why economics needs brains earlier CINGULATE 559 PREFRONTAL CORTEX NUCLEUS ACCUMBENS PUTAMEN AMYGDALA HIPPOCAMPUS CAUDATE Fig. 1. Human brain (frontal pole left) regions of potential interest to economists of planning, cognitive control and integration of cross-brain input. Parietal areas govern motor action. The occipital lobe is where optic processing descends. The temporal lobes are important for memory, recognition and emotion. Neurons from different areas are interconnected, which enables the brain to react to complex stimuli in an integrated way.When an automated insurance broker calls and says, Dont you want earthquake ins urance? consider 1 for more information the occipital lobe pictures your house collapsing the temporal lobe feels a negative emotion and the frontal lobe receives the activated signal and weighs it against the samely cost of insurance. If the frontal lobe decides you should find 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 big cortex.This means human behavior will generally be a compromise surrounded by highly evolved animal 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 share more than 98% of our genes) and other animals. Three features of human brain function are illustrious automaticity, modularity and 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 architecture is organized in terms of functional facultys capable of working both cooperatively and independently. These modules can carry out their functions in parallel and outside of conscious experience. The modules can effect inseparable and external behaviors, and do this at regular intervals. Monitoring all this is a left-brain-based system called the interpreter. The interpreter considers all the outputs of the functional modules as before long as they are made and immediately 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 value and fit the event into the large current mental schema (belief system) that it has already constructed. Many brain activities are automatic parallel, rapid processes which typically occur without awareness. Automaticity implies that people i. e. , the thoughtful cortex and the language processing which articulates a somebodys reasons for their own behaviorwhitethorn genuinely not know the cause of their own behavior. 1 Automaticity means that overcoming some habits is only possible with cognitive effort, which is unparalleled.But the power of the brain to automatize also explains why tasks which are so challenging to brain and body resources that they seem impossibly grueling at firstwindsurfing, driving a car, paying(a) attending to four screens at once in a trading roomcan be done automatically after bounteous practice. 2 At the kindred time, when bully performance fits automatic (in the form of procedural knowledge) it is typically tough to articulate, which means human capital of this sort is difficult to reproduce by teaching others. The different brain modules are much neuroanatomically separated (like organs of the body).Some kinds of modularity are really remarkable The facial fusiform area (FFA) is specialise for facial recognition somatosensory cortex has areas corresponding 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 angry or dexterous faces, followed immediately by a neutral mask face, activate the amygdala even though people are completely unaware of whether 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 demonstrable foreign exchange traders during their work. They found that more experient traders showed lower emotional responses to market events that set the hearts of less experienced traders pounding. Their discovery suggests that responding to market events becomes partially automated, wh ich 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 privilegedly (retinotopic mapping) and thither are separate language areas, Brocas and Wernickes areas,3 for semantics and for comprehension and grammar. Many neuroscientists destine thither is a specialized mentalizing (or theory of mind) module, which controls a persons inferences about what other people commit, or feel, or might do see e. g. Fletcher, Happe, Frith, Baker, Dolan, Frackowiak and Frith (1995). Such a module presumably supports a whole swear of critical human functionsdecoding emotions, understanding of affectionate rules, emotions, language, strategic concepts (bluffing)and has obvious importance for economic transactions.Modularity is important for neuroeconomics because it invites raises that map theoretical distinctions onto separate brain areas. For example, if pe ople play games against other people differently than they make decisions (a game against character), 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 complex behaviors of interest to economics require collaboration among more specialized modules and functions. So the brain is like a large company distinguish offices specialize in different functions, but also communicate to one another, and communicate more feverishly when an important decision is being made.Attention in neuroeconomics is in that respectfore 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 behavi or, and privileges deliberative explanations over cruder ones cfNisbett 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 a lot 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 samples where there are no(prenominal) see Gilovich (1991). When subjects listen to music and watch flashing Christmas tree lights at the same time, they mistakenly field that the two are synchronized. Mistaken beliefs in sports streaks, as evidenced by Gilovich, Vallone and Tversky (1985), and seeing spurious patterns in time series like stock-price data (technical summary) whitethorn come from too much sense-making.Patients with Wernicke damage can babble sent ences of words which make no sense st phlebotomizeg unitedly. 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 spectacular example is change-blindness. In an amusing study titled Gorillas in our Midst, subjects watch a boob tube of six people passing a basketball and count the passes made by one team up (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 then walks off.Although the gorilla cavorts onscreen for a full total of nine 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 informatio n, it does so rapidly and efficiently, overwriting what was previously believed. This can create a powerful hindsight virgule in which events seem, after the fact, to have been predictable even when they were not. Hindsight bias is probably important in agency relations when an agent takes an informed action and a steer second-guesses the agent if the action turns out badly. This carrys a special source of risk to the agents income and whitethorn lead to other behaviors like herding, diffusion of responsibility, inefficiencies from covering your ass, excessive labor turnover, and so on.We underscore these properties of the brain, which are rapid and often implicit (subconscious), because they depart the most from conscious deliberation that may take place in complex economic decisions like saving for retirement and computing asset values. Our tension does not deny the importance of deliberation. The presence of other mechanisms just means that the right models should include ma ny 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 infliction originate 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 additional voluntary actions, e. g. when monitors for body temperature trigger sweating to undisturbed you off and shivering to warm you up. In other cases, the homeostatic processes operate by changing evanescent preferences, a process called alliesthesia see Cabanac (1979). When the core body temperature falls 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 multivariates tr igger 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 both 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 living together tend to converge over time. perchance waves of panic and euphoria in markets work in a similar 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 tell us everything we need to know. Consider the hypothetical case of two people, Al and Naucia, who both refuse to pervert peanuts at a reasonable price cf. Romer (2000).The refusal to buy reveals a common disutility for peanuts. But Al turned d own the peanuts because he is allergic consuming peanuts causes a setose rash, shortens his breath, and could even be fatal. Naucia turned down the peanuts because she ate a huge bag of peanuts at a circus years ago, and subsequently got nauseous from eating too much candy at the same time. Since then, her gustatory system associates peanuts with illness and she refuses them at reasonable prices. While Al and Naucia both revealed an identical disutility, a neurally detailed account tells us more. Al has an inelastic demand 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 repeated consumption, while Naucias distaste 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 aslee p at the wheel while driving. Of course, an imaginative rational-choice economistor a satiristcould posit a tradeoff between sleep utility and risk of ploughing into a tree utility and infer that a dead 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 tired, 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 natural 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 fodder when they are hungry. 4 3. A third problem with preferences is that there are different types of utilities which do not always coincide. Kahneman (1994) distinguishes four types remembered utility, anticipated utility, choice utility and experienced utility. Remembered utility is what people recall want 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 impulse, which correspond roughly to choice utility and experienced utility. The fact that these areas are dissociated allows a wedge between those two kinds of utility. Similarly, a wedge between remembered and experienced utility can be created by features of human memory which are adaptive for general purposes (but maladaptive for remembering precisely how something felt), such as repression of memories for severe pain in childbirth and other traumatic ordeals (e. g. , outdoor adventures led by author GL).If the different 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 craving (wanting) which leads to consumption (choosing) that they say is not particularly pleasurable (experiencing). peremptory 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 possibility 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 accomplishment may bring the four types of utilities together gradually. The rational choice model of consistent and coherent preferences can then be characterized as a limiting case of a neural model with multiple utility types, under authoritative learning conditions. 4. A fourth problem with preference is that people are assumed to value cash for what it can purchasethat 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 person 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 speaking, it appears that similar brain circuitry dopaminergic neurons in the midbrainis active for a wide variety of retaliateing experiencesdrugs, food, attractive faces, humorand money rewards. This means money may be directly rewarding, and its privation painful.This might explain why workaholics and the very wealthy keep working long hours after they should be retired or cutting back (i. e. , when the bare(a) utility of goods purchased with their marginal income is very low). Similarly, the immediate pain of paying can make wealthy individuals averse to spend when they should, and predicts unconventional effects of d eterminee. g. a preference for fixed payment plans rather 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 exchange prices for earned goods were larger when the allocated good was earned than when it was unearned. Zink, Pagnoni, Martin-Skurski, Chappelow and Berns (2004) also found that when subjects earned money (by responding right to a stimulus), rather than just receiving equivalent rewards with no effort, there was greater activity in a midbrain reward region called the striatum. bring in 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. Addiction 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 modeled 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 expected 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 substance to which humans may become biologically addicted is also potentially addictive for rats. Addictive substances appear therefore to be pirate primitive 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 upset rat-brain circuitry), it does show that rational intertemporal planning is not necessary to create the addictive phenomena of tolerance, craving and withdrawal. It also highlights the need for economic models of the primitive reward circuitry, which would apply equally to man and rat. Another awkward fact for rational-addiction models is that most addicts hold back and relapse 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 b etween a visceral thirst 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 formal model of cue-dependent use, screening that there are multiple equilibria in which cues either trigger use or are ignored. The more lush model of Bernheim and Rangel (in press), is a paradigmatic example of how economic theory can be deeply root in neuroscientific details. They assume that when a person is in a hot state they use drugs in a cold state, whether they use is a rational choice.A variable S, from 0 to N, summarizes the persons memoir 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 compare the efficiency effects of policies like laissezfaire, drug bans, sin taxes and regulated dispensation. Decision-making under Risk and Uncertainty Perhaps the most rapid progress in neuroeconomics will be made in the study of angry decision-making. We focus on three topics risk judgments, risky choice and probability.Risk and ambiguity In most economic analyses risk is equated with var. of outcomes. But for most people, risk has more dimensions (particularly emotional ones). Studies have long shown that potential outcomes which are ruinous and difficult to control are perceived as more risky (controlling for statistical likelihood) see Peters and Slovic (2000). communication channel executives say risk is the chance of loss, especially a large loss, often approximated by semivariance (the variance of the loss p ortion 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 fear 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 actuate by mixer risks, like shame and fear of public speaking could also influence economic activity in interesting ways.A lot is known about the neural processes central affective responses to risks see Loewenstein, Hsee, Welch and Weber (2001). Much a version 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 noise cue followed by a painful electric shock.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 designate fear reactions to films of torture, but are less afraid when they are told the people portray 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 (t he 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 connection between the tone and the shock (the posterior probability P(shockjtone) has fallen).But the neural reality is more nuanced than that. If the shock is then readministered avocation the tone, after a long period 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 ambiguitymissing 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 spark off when people chose certain money amounts rather than ambiguous gambles. 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, loathly odors and choking. This tentative evidence suggests a neural basis for pessimism or fear of the unknown influencing choices. Risky choice Like risk judgments, choices among risky gambles involve an interplay of cognitive and affective processes. A well-known study inform in Bechara, Damasio, Tranel and Damasio (1997) illustrates such collaboration.Patients suffering prefrontal damage (which, as discussed preceding(prenominal), produces a disconnect between cognitive and affective systems) and normal subjects chose cards from one of four decks. Two decks had more cards with extreme wins and losses (and negati ve 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 indication of fear) immediately after large-loss cards were encountered. 7 This is hard to 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 Peters 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 unhurri ed response times, and there are differences in which areas are active during gain and loss see Camerer, Johnson, Rymon and Sen (1993) and metalworker and Dickhaut (2002). Dickhaut, McCabe, Nagode, Rustichini and Pardo (2003) found more activity in the orbitofrontal cortex when thinking 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 activated 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 antecedent 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 familiar economic ideas of utility and belief. Schulz isolates dopaminergic neurons in the ventral tegmental midbrain and Glimcher studies the lateral inferior parietal (LIP) area. The midbrain neurons fervidness 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 estimatorized opponents. An interesting fact for neuroeconomics is that all the violations of standard utility theories 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 Green (1995). People also exhibit context-dependence whether A is chosen more often than B can depend on the presence of an opposed third choice C (which is dominated and never chosen). Context-dependence means people compare choices within a set rather than assigning separate numerical utilities. Honeybees exhibit the same pattern see Shafir, Waite and metalworker (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 circuitry for these decisions is old, and perhaps 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 fit and gamble. Including emotions and other neuroscientific constructs might help. Like drug addiction, the study of pathological gambling is a useful test case where simple theories of rationality take us only so far. About 1% o f the people who gamble are pathologicalthey report losing control, chasing losses, and harming their personal and work relationships cf. National investigate 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 genetic evidence shows that pathologicals are more likely to have a certain gene allele (D2Al), which means that larger thrills are needed to get modest jolts of pleasure see Comings (1998). One 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 reasoning about what others believe and might do. loving 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 players 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 emotional limbic system).Their finding is nicely corroborated by Hill and Sally (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 quarter of their autistic adults offered aught in the ultimatum game, which is consistent with an inability to envisage why others would reg ard 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 offers, 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 tr eated 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 expensive 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 nucleus accumbe ns) 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 endocrines 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 show s how neuroeconomics can deliver fair 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 (such 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 central 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, maturation or imitation) results in a mutually consistent equilibrium in which each player guesses correctly what others will do (and 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 (20 02), 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 ordinal century after economists became skeptical 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 construction 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 self-referent induction and computation of equilib rium 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 sensitiveness 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 all-purpose tools like learning models or game theory, could provide some unification across the social sciences cf. Gintis (2003). Most econo mists we call down to are curious 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 extravagance 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 when 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 colligate hypotheses about specific brain mechanisms (location, and activation) with unobser vable 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 circumferent 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 tradeoffs are simply The editors of the Scandinavian Journal of Economics 2004. 574 C. F. Camerer, G. Loewenstein and D. Prelec too difficult or morally repulsive (e. g. , selling a body part). fire 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 sacred preference is, and why descriptions and procedures matter. 12 A third payoff from neuroscience is to sugg est 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 guide theorizing about dynamic substitution and complementarity. A priming dose of cocaine 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 discrimination. 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 basic 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 bid 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 construction that bidding valuations is not transparent. 13 It has been known for some time tha t 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 Banaji (2000). Importantly, implicit racial associations 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. Neuroecon omics 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 include in contracting models. Will 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. Benhab ib 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