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The main result is that the perception of threat makes select personality types more likely to attend to biased information and more likely to perceive threat-based messages as credible. (Lupia 321)

Catherine Eckel, Martin Johnson, and Rick K. Wilson’s “Fairness and Rejection in the Ultimatum Bargaining Game” shows how science and society can derive value from going beyond an experiment’s original design when analyzing it’s data. In this article, the most interesting findings come not from a straight comparison of treatment groups, but from interactions between the treatment and data that are often thrown away. The substantive domain is ultimatum experiments. In these experiments, one player offers a division of resources and another player is limited to accepting or rejecting the offer. If the second player rejects the offer, both get nothing. Game theoretic analyses using the Nash equilibrium suggest that the first player should offer to keep almost all of the dollar for herself and that the second player, who lacks a better option, should accept it. Like many previous researchers, these authors reveal such outcomes as infrequent (Frohlich and Oppenheimer 2000). They explain that the outcomes in their own ultimatum experiments by combining knowledge of the experimental design with data on the subjects’ gender and social orientation. More generally, the authors show that interactinv tratment, gender, and “attitudes toward” others can generate greater knowledge from the experiments than would comparisons of the treatment conditions alone.” (Lupia 321-322)

“Deliberation is the substantive focus of the issues’ final article, Adam F. Simon and Tracy Sulkin’s “Discussion’s Impact on Political Allocations: An Experimental Approach.” Inside and outside the academy, there is increasing interest in — and advocay of — more deliberative forms of social decision making (Fishkin 19995; Gutman and Thompson 1996). Among the factors driving this movement is the belief that forcing people to justify their actions publicly — as deliberative decision making institutions do — produces collective decisions that are more equiatable and, from the participants’ perspective, more legitimate. As more people advocate and implement a wider range of deliberative decision making mechanisms, claims abotu the benefits of deliberation are drawing greater empirical and theoreticla scrutiny (Heath 2001; Neblo 2001; Lupia 2002). The criticla question is, “Under what conditions are advocates’ claims true?” Simon and Sulkin address this topic directly by conducitng a laboratory experiment of the economics variety. The design is simple and clever. The experiments ofer groups of five subjects an opportunity to divide $60. The authors then vary how much subjects can communicate before making this decision, and whether subjects must allocate funds to predetermined teams or whether they can give dollars to individually directly. Althrough Simon and Sulkin find that discussion can prompt equity and perceptions of legitimacy, their experiments reveal that such happy outcomes are not automatic.” (Lupia 322-323)

While not denying that deliberation is always an option for human decision making, neuroscience research points to two generic inadequacies of this approach. First, much of the brain is constructed to support ‘automatic’ processes (Bargh, Chaiken, Raymond and Hymes 1996; Bargh and Chartrand 1999; Schneider and Shiffrin 1977; Shiffrin and Schneider 1977), which are faster than conscious deliberations and which occur with little or no awareness or feeling of effort. (Casmerer, Lowenstein, and Prelec 2003 2)

Scientific technologies are not just tools scientists use to explore areas of interest. New tools define new scientific fields, and erase old boundaries – e.g., the telescope (slipping away from speculative cosmology) created astronomy. (Casmerer, Lowenstein, and Prelec 2003 4)

Neural processes are thought to occur on a 0.1 millimeter scale in 100 milliseconds (msec), but the spatial and temporal resolution of a typical scanner is only 3 millimeters and about two seconds. Multiple trials per subject can be averaged to form composite images, but doing so constrains experimental design. (Casmerer, Lowenstein, and Prelec 2003 5)

The most common, triune division draws a distinction between the “reptilian brain,” which is responsible for basic survival functions, such as breathing, sleeping, eating, the “mammalian brain,” which encompasses neural units associated with social emotions, and the “hominid” brain, which is unique to humans and includes much of our oversized cortex — the thin, folded, layer covering the brain that is responsible for such “higher” functions as language, consciousness and long-term planning (MacLean 1990). (Casmerer, Lowenstein, and Prelec 2003 5)

Parallelism, which is a hallmark of automatic processing, facilitates rapid response and gives the brain remarkable power when it comes to certain types of tasks, such as visual identification. “Connectionist” neural network models formulated by cognitive psychologists (Rumelhart and McClelland 1986) capture this feature of the brain and have been applied to many domains, including commercial ones. Models of this type have a very different structure than the systems of equations that economists typically work with. Unlike systems of equations, they are “black-box” — it is typically impossible to make intuitive sense of what they are doing by looking, for example, at individual parameters. By the same token, parallel processes are generally not accessible to consciousness. Parallelism provides the brain with tremendous power because it allows for massive multitasking. It also provides redundancy that decreases the brain’s vulnerability to harm. As a result of this redundancy, when neurons are progressively destroyed in a region, the consequences are typically gradual rather than sudden (“graceful degradation”). (Casmerer, Lowenstein, and Prelec 2003 12)

Thus, violinists who finger violin strings with their left hand show enlarged development of cortical regions which correspond to fingers on the left hand (Elbert, Pantev, Wienbruch, rockstroh and Taub 1995), and the brain regions responsible for navigation and spatial memory (the hippocampus) of London taxi drivers are larger than comparable areas in non-taxi drivers (Maguire, Gadian, Johnsrude, Good, Ashburner, Frackowiak and Frith 2000). (Casmerer, Lowenstein, and Prelec 2003 13)

An important implication of plasticity is that information processing is unlikely to be reversible because the physiological processes that produce learning are themselves not reversible. Standard theories of information processing assume that people can ignore the effect of useless information or can undo the effect of information that is redundant or discredited. However, there are numerous demonstrations of violations of these principles. (Casmerer, Lowenstein, and Prelec 2003 13)

And, people are subject to a ‘curse of knowledge’ such that, once they know something to be true (or false) they exaggerate the degree to which others must know it (Camerer, Loewenstein and Weber 1989). (Casmerer, Lowenstein, and Prelec 2003 13)

Beyond the standard modules, such as face recognition, language and so on, research hints at the existence of some modules that are quite surprising. Thus, surgeons conducting brain surgery on an epileptic patient discovered a small region of her brain which, when stimulated, caused her to laugh (Fried 1998), hinting at the existence of a ‘humor module’. Perhaps more surprisingly, neuroscientists have located an area in the temporal lobe that, when stimulated electrically, produces intense religious feelings — e.g., the sense of a holy presence or even explicit visions of god or Christ, even in otherwise unreligious people (Persinger and Healey 2002). (Casmerer, Lowenstein, and Prelec 2003 14)

Autistic adult individuals may compensate in many ways and eventually pass such basic tests of mentalizing. However, they have difficulty appreciating more subtle social meanings (e.g., irony), and will sometimes wonder at the “uncanny ability” of non-autistic persons to “read minds” (Frith 2001b).
(Casmerer, Lowenstein, and Prelec 2003 14)

Economic theory plainly assumes that agents can ‘mentalize’, i.e., make inferences from the actions of others to their underlying preferences and beliefs. Such mentalizing inferences sustain a Bayesian equilibrium, and are not normally regarded any more or less difficult than any other types of inferences. The first, and most elementary implication of the neuroscience evidence would be to put a “flashing yellow” light above this assumption. (Casmerer, Lowenstein, and Prelec 2003 15)

Furthermore, it would not be surprising to find normal individuals differing in their mentalizing skills. Indeed, in one of the first imaging studies conducted by economists, McCabe et al. (2001) theorized that mentalizing was important in games involving trust and cooperation. They found that players who were more trusting and cooperative showed more brain activity in Brodmann area 10 (thought to be the locus of mentalizing) and more activity in the limbic system which processes emotions. (Casmerer, Lowenstein, and Prelec 2003 15)

Specialization: In a process that is not well understood, the brain figures out how to do the tasks it is assigned, efficiently, using the modules it has at its disposal. When the brain is confronted with a new problem it initially draws heavily on diverse modules, including, often, the prefrontal cortex. But over time, activity becomes more streamlined, concentrating in modules that specialized in processing relevant to the task. In one study, subjects’ brains were imaged as they played the computer game Tetris, which requires rapid hand-eye coordination and spatial reasoning. When subjects began playing, they were highly aroused and many parts of the brain were active. As they got better at the game, overall blood-flow to the brain decreased markedly, and activity became localized in only a few brain regions. Much as an economy ideally adjusts to the introduction of a new product by gradually shifting production to the firms that can produce the best goods most cheaply, with experience at a task or problem, the brain seems to gradually shift toward modules that can solve problems automatically and efficiently with low-effort. (Casmerer, Lowenstein, and Prelec 2003 16)

Specialization: In a process that is not well understood, the brain figures out how to do the tasks it is assigned, efficiently, using the modules it has at its disposal. When the brain is confronted with a new problem it initially draws heavily on diverse modules, including, often, the prefrontal cortex. But over time, activity becomes more streamlined, concentrating in modules that specialized in processing relevant to the task. In one study, subjects’ brains were imaged as they played the computer game Tetris, which requires rapid hand-eye coordination and spatial reasoning. When subjects began playing, they were highly aroused and many parts of the brain were active. As they got better at the game, overall blood-flow to the brain decreased markedly, and activity became localized in only a few brain regions. Much as an economy ideally adjusts to the introduction of a new product by gradually shifting production to the firms that can produce the best goods most cheaply, with experience at a task or problem, the brain seems to gradually shift toward modules that can solve problems automatically and efficiently with low-effort. (Casmerer, Lowenstein, and Prelec 2003 16)

As a general rule, we should expect people to be geniuses when presented with problems that can be, and are, processed by dedicated modules, but relatively obtuse when they are forced to rely on controlled processes (Casmerer, Lowenstein, and Prelec 2003 17)

But empirical evidence shows that risk-taking, time discounting and altruism are very weakly correlated (often zero) across situations. (Casmerer, Lowenstein, and Prelec 2003 17)

Framing and context effects occur when contextual or descriptive factors affect choices, even when the outcomes of those choices are the same (c.f. Camerer and Loewenstein in press). Hershey, Kunreuther, and Schoemaker (1982), for example, found that choice between the same pair of certain and risky prospects was substantially affected by whether the decision was expressed as a “gamble,” in which case people were risk-seeking, or as “insurance,” in which case they were risk averse. (Casmerer, Lowenstein, and Prelec 2003 18)

For example, parents at a day care center pick up their children later after a small fine is instituted for late pickups (see Gneezy and Rustichini in press; cfTitmuss 1970, on blood donation). When there is no fine, picking up your children promptly is construed as honoring a moral obligation to the daycare center. But when a fine is charged, parents construe their decision as whether it is worth paying a small price to be late— and many decide that it is. (Casmerer, Lowenstein, and Prelec 2003 18)

A dramatic demonstration of such sensitivity to change came from single-neuron studies of monkeys responding to juice rewards (see Schulz and Dickinson 2000). They measured the firing of dopamine neurons in the animal’s ventral striatum, which is known to play a powerful role in motivation and action. In their paradigm, a tone was sounded, and two seconds later a juice reward was squirted into the monkey’s mouth. Initially, the neurons did not fire until the juice was delivered. Once the animal learned that the tone forecasted the arrival of juice two seconds later, however, the same neurons fired at the sound of the tone, but did not fire when the juice reward arrived. These neurons are responding, not to reward or its absence, but to deviations from expectations. (When the juice was expected from the tone, but was not delivered, the neurons fired at a very low rate, as if expressing disappointment.) The same pattern can be observed at a behavioral level in animals, who will work harder (temporarily) when a reinforcement is suddenly increased and go `on strike’ when reinforcement falls. (Casmerer, Lowenstein, and Prelec 2003 20)

Neural sensitivity to change is probably important in explaining why the evaluation of risky gambles depends on a reference point which encodes whether an outcome is a gain or a loss (see section IV), why self-reported happiness (and behavioral indicators like suicide) depend on changes in income and wealth, rather than levels (Oswald 1997), and why violations of expectations trigger powerful emotional responses (Mandler 1982). (Casmerer, Lowenstein, and Prelec 2003 20)

Berridge believes that the later stages of many drug addictions presents prototypical examples of situations of what he terms “wanting” without “liking;” drug addicts often report a complete absence of pleasure from taking the drug they are addicted to, coupled with an irresistible motivation to do so. In fact, it’s hard to imagine the modern psychotherapeutic service industry being what it is if human beings never experienced the problem of ‘wanting without liking.’ Other examples of situations in which there often seems to be a disconnect between one’s motivation to obtain something and the pleasure one is likely to derive from it are sex and curiosity (seeLoewenstein 1994). Economics proceeds on the assumption that satisfying people’s wants is a good thing. While this is probably generally a safe assumption, if wanting and liking are two separate processes, then it cannot be assumed that satisfying someone’s desires necessarily makes them better off. (Casmerer, Lowenstein, and Prelec 2003 21)

Holding tissue damage constant, how much misery one experiences depends powerfully on factors such as what caused the pain (less misery if it was for a good cause), what the pain means (greater misery if it signals something significant, like cancer), and how long one expects the pain to last. (Casmerer, Lowenstein, and Prelec 2003 22)

Under the influence of intense emotions, people often report themselves as being “out of control” or “acting against their own self-interest” (Baumeister, Heatherton and Tice 1994; Bazerman, Tenbrunsel and Wade-Benzoni 1998; Hoch and Loewenstein 1991; Loewenstein 1996). As Rita Carter writes, in her superb introduction to neuroscience, Mapping the Mind, “where thought conflicts with emotion, the latter is designed by the neural circuitry in our brains to win” (1999: 54). (Casmerer, Lowenstein, and Prelec 2003 25)

Research with EEG recordings has shown (Libet 1985) that the precise moment at which we become aware of an intention to perform an action trails the initial wave of brain activity associated with that action (the EEG “readiness potential”) by about 300 msec. The overt behavioral response itself then follows the sensation of intention by another 200 msec. Hence, what is registered in consciousness is a regular pairing of the sensation of intention followed by the overt behavior. Because the neural activity antecedent to the intention is inaccessible to consciousness, we experience ‘free will’ (i.e., we cannot identify anything that is causing the feeling of intention). Because the behavior reliably follows the intention, we feel that this ‘freely willed’ intention is causing the action—but in fact, both the sensation of intention and the overt action are caused by prior neural events which are inaccessible to consciousness. (Casmerer, Lowenstein, and Prelec 2003 26)

The notion of discounting, however, gained currency not because of any supportive evidence, but based only on its convenient similarity to financial net present value calculations (Loewenstein 1992). In fact, empirical research on time discounting challenges the idea that people discount all future utilities at a constant rate. (For a review of the evidence, see Frederick, Loewenstein and O’Donoghue 2002). The notion of time discounting, it appears, neither describes the behavior of individuals nor helps us to classify individuals in a useful fashion. (Casmerer, Lowenstein, and Prelec 2003 29) (see my reaction to Punctuated Equilibria in Evolution Psychology to see how this might back up my own thoughts)

Indeed, a number of human pathologies, such as anxiety disorders, workaholism, and self-destructive miserliness, seem to be driven by an excess of futuremindedness. (Casmerer, Lowenstein, and Prelec 2003 30)

It is tempting to attribute this to the fact that self-control involves the same part of the brain – the executive prefrontal cortex – that is itself associated with feelings of mental effort. Perhaps this is why exercising willpower feels so difficult, and why exercising self-control in one domain can undermine its exercise in another, as demonstrated by a series of clever experiments conducted by Roy Baumeister and colleagues (see, e.g., Baumeister and Vohs 2003). In a typical study, subjects on diets who resisted temptation (by foregoing the chance to grab snacks from a nearby basket) later ate more ice cream in an ice-cream taste test and also quit earlier when confronted with an intellectual problem they couldn’t solve. They acted as if their ability to resist temptation was temporarily “used up” by resisting the snacks (or, alternatively, that they had “earned” a reward of ice cream by skipping the tempting snacks). (Casmerer, Lowenstein, and Prelec 2003 30-31)

Such a framework might also help to explain why people appear so inconsistent when their behavior is viewed through the lens of discounted utility. The ability to think about future consequences may not be strongly correlated with the degree to which different experiences produce visceral reactions, and these in turn might not be correlated with an individual’s level of willpower. Indeed, Frederick et al. (2002) found close to zero correlations between numerous behaviors that all had an important intertemporal component, but much higher correlations between behaviors that seemed to draw on the same dimension of intertemporal choice – e.g., which required suppression of specific emotions such as anger. (Casmerer, Lowenstein, and Prelec 2003 31)

Pathological gamblers tend to be overwhelmingly male, and tend to also drink, smoke, and use drugs much more frequently than average. Genetic evidence shows that a certain gene allele (D2A1), which causes gamblers to seek larger and larger thrills to get modest jolts of pleasure, is more likely to be present in pathological gamblers than in normal people (Comings 1998). One study shows tentatively that treatment with naltrexone, a drug that blocks the operation of opiate receptors in the brain, reduces the urge to gamble (e.g. Moreyra, AIbanez, Saiz-Ruiz, Nissenson and Blanco 2000). The same drug has been used to successfully treat “compulsive shopping” (McElroy, Satlin, Pope, Keck and al. 1991). (Casmerer, Lowenstein, and Prelec 2003 34)

When guessing probabilities, the left hemisphere of the brain is more active; but when answering logic questions, the right hemisphere is more active (Parsons and Osherson 2001). Enforcing logical coherence requires the right hemisphere to `check the work’ of the left hemisphere. (Casmerer, Lowenstein, and Prelec 2003 35)

Hill and Sally (2002) found that autistic adults were more likely than normal adults to offer nothing to the other player. The autists seem incapable of understanding what another player might believe and do; as a result, ironically, they play like selfinterested game theorists! (Casmerer, Lowenstein, and Prelec 2003 36)

Most cognitive and affective processing does not occur in the rule-like systematic fashion envisioned by standard economics, but involves automatic, massively parallel systems to which we have little or no introspective access. (Casmerer, Lowenstein, and Prelec 2003 37-38)

For instance, a past study reported that attractiveness can be ascertained from 100 ms of viewing time (Locher, Unger, Sociedade, & Wahl, 1993). (Olson and Marshuetz 2005 498).

The average rating for attractive faces was 5.79, whereas for unattractive faces it was 4.71. This difference was significant t(9) 4.90, p .01, demonstrating that attractiveness can be assessed from very brief glimpses of visual information. (Olson and Marshuetz 2005 499)

Although participants reported that they could not accurately see the faces, their ability to “guess” about the attractiveness level of the faces was surprisingly accurate. (Olson and Marshuetz 2005 501)

Why unattractive faces did not speed processing of negative words is less clear, although we speculate that unattractive faces do not induce negative emotions. (Olson and Marshuetz 2005 501)

This experiment replicated the priming effect of attractive
faces but found no priming effect for attractive houses, suggesting that attractive faces may induce emotions, whereas other attractive stimuli may not, or at least may not in the same manner. Other types of attractive stimuli, such as abstract art (Duckworth, Bargh, Garcia, & Chaiken, 2002) or animals (Halberstadt & Rhodes, 2003), have been shown to bias cognition, but such processes may be slower, requiring more time (Duckworth et al., 2002), attention, or effort, than attractiveness judgments for face stimuli, which appear to be easy and rapid. An alternative explanation for these findings is that the attractiveness of houses is not extracted as rapidly as it is from faces. (Olson and Marshuetz 2005 501)

Subjects are asked a number of standard questions regarding their socioeconomic status, political beliefs, and turnout behavior in a California primary election. They then participate in a “dictator game” (Forsythe et al. 1994), in which they are asked to divide a prize between themselves and an anonymous individual. These allocations reveal the degree to which each subject is concerend about the wellbeing of others.” (Fowler 2006 674)

For decades, scholars have tried and failed to explain high aggregate turnout as a phenomenon based purely on self-interest (Aldrich 1993; Downs 1957; Feddersen and Pesendorfer 1996; Ledyard 1982; Myerson 2000; Palfrey and Rosenthal 1985). However, there is by now a substantial literature in economics, sociology, biology, psychology, and political science yielding evidence that human beings are also motivated by the welfare of others (Fehr and Fischbacher 2003; Monroe 1998; Piliavin and Charng 1990). Specifically, people frequently engage in acts of altruism by choosing to bear costs in order to provide benefits to others. (Fowler 2006 675)

These assumptions transform the calculus of voting to P(BS + α N BO) > C. Given that P is proportional to 1/N when there is election uncertainty, the decision to vote reduces approximately to whether or not α BO > C. (Fowler 2006 675)

The civic duty model suggests that people with a strong sense of social obligation will vote in an election even if they think the alternatives in question yield identical benefits to themselves and to others. In contrast, the altruism model suggests that people who care about the welfare of others will vote only if they think one of the alternatives is superior. (Fowler 2006 675)

Unlike the ultimatum game (c.f. Hibbing and Alford 2004), the dictator game does not give player 2 an opportunity to accept or rejectthe offer—she simply pockets the money that player 1 allocates to her and the game is over. (Fowler 2006 676)

Anonymity conditions tend to decrease the mean allocation, but even in the most anonymous treatments (Hoffman et al. 1994) about 40% of the allocations are still greater than 0. (Fowler 2006 676)

In May 2004, about 350 subjects were recruited from two introductory undergraduate political science courses to participate in a study administered by computer. Subjects were offered credit towards their course grade for their participation in the study, and 249 (about 70%) of them chose to participate. (Fowler 2006 676)

Subjects are told they are eligible to win a prize of $100 and they are asked how much of the prize they would like to share with an anonymous individual. However, only one subject is randomly chosen to win the prize. Thus, in expectation the prize is only worth $100 / N ≈ $0.40 to each subject. Though economists sometimes criticize lowstakes experiments like this one, a survey of the experimental economics literature by Camerer and Hogarth (1999) shows that stake size has only a small effect on average behavior and the biggest effect of stakes on behavior is changing from zero to positive stakes. Furthermore, Carpenter, Verhoogen, and Burks (2004) show specifically for the dictator game that changing from low stakes to high stakes has no effect on mean allocations. (Fowler 2006 677)

This experiment also replicates the finding that demographic factors have little effect on dictator game allocations (see Camerer (2003) for a review). Table 1 shows that dictator game allocations do not significantly correlate with any of the socioeconomic factors or political attitudes measured in this study (see Appendix for coding descriptions). Some of the correlations are almost significant and suggest there may be weak relationships in larger sample sizes. (Fowler 2006 677)

Although we do not know whether respondents in these studies are self-interested or altruistic, the literature on economic voting shows that people generally take into account both individual (pocketbook) effects and society-level (sociotropic) effects when they vote (Clarke and Stewart 1994; Kinder and Kiewiet 1981; Mutz and Mondak 1997).(Fowler 2006 677)

Consistent with the altruism theory of turnout, partisanship is important but only in interaction with a concern for the wellbeing of others. (Fowler 2006 679)