Treating Rationality as a Continuous Variable
Amitai Etzioni
Society ISSN 0147-2011 Volume 51 Number 4 Soc (2014) 51:393-400 DOI 10.1007/s12115-014-9798-6
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Author's personal copy Soc (2014) 51:393–400 DOI 10.1007/s12115-014-9798-6
SYMPOSIUM: THE ACHIEVEMENT OF AMITAI ETZIONI
Treating Rationality as a Continuous Variable Amitai Etzioni
Published online: 3 July 2014 # Springer Science+Business Media New York 2014
Abstract Granted, Behavioral Economics has demonstrated that “people” (implying all) are unable to act as strong definitions of rationality assume. Their cognitive limitations are “hard wired”. However Behavioral Economics’ own data show that important segments of the population find “the” rational answer to choices posed to them. How do these findings square with the thesis that limitations are hard wired and universal? And, more attention should be paid to the extent to which various people deviate from the rational choice, and—whether training can improve performance despite the claim that flaws are hard wired. Keywords Behavioral economics . Rationality . Training . Methodology This article argues that (a) behavioral economics (BE) has produced an unusually robust body of evidence about human deliberations and decision making (in short, choice behavior); that (b) this body of evidence requires a fundamental change in the ways one views and studies choice behavior; that (c) the same body of evidence is open to a major misperception; and that (d) closing the door that leads to this misperception—by drawing on BE’s own data—provides for additional, major steps forward in the study of choice behavior.
Behavioral Economics: Unusually Robust and Transformative The key finding of BE—that people have built-in or hardwired, major cognitive biases that prevent them from making A. Etzioni (*) The George Washington University, 1922 F St. NW, Room 413, Washington, DC 20052, USA e-mail:
[email protected]
choices rationally—has been replicated by numerous scholars from a variety of different countries and cultures (Schwartz 2008; Korobkin and Ulen 2000).1 It has furthermore been supported by experiments conducted in “the field” as well as under laboratory conditions (Hursh and Roma 2013). It thus exhibits a level of robustness not often found in the social sciences—or even in the “hard” sciences. One study of preclinical cancer research found that, of 53 studies that contributed “landmark” advances to the field, only six could be replicated—a mere 11 % (Begley and Ellis, 2012). Drawing on these findings, BE demonstrated that a key assumption of neoclassical economics, sometimes referred to as mainstream economics in the United States, and its allied fields such as law and economics and public choice theory, is unsustainable (Mueller 2004).2 BE challenges the prevailing paradigm of neoclassical economics by showing that there are “three important ‘bounds’ on human behavior, bounds that draw into question the central ideas of utility maximization, stable preferences, rational expectations, and optimal processing of information. People can be said to display bounded rationality, bounded willpower, and bounded self-interest” (Jolls et al. 1998:1471). Behavioral economics is one subdiscipline that adheres to the “complexity approach” to economics, a paradigm that is “grounded on sharply different microfoundations and methodology [than the Neoclassical/ Samuelsonian paradigm]” and represents a fundamental “shift from the neoclassical focus” (Fontana 2010). Davis asserts that behavioral economics “involve[s] significant departures 1 “There is simply too much credible experimental evidence that individuals frequently act in ways that are incompatible with the assumptions of rational choice theory.” 2 One of the two “relatively recent challenges to the neoclassical orthodoxy” that has “taken hold of a non-negligible minority of the profession” is behavioral economics. In some cases, neoclassical economics has fought back by citing evidence that behavioral economics only provides a good model for inexperienced consumers and investors.
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from the neoclassical economics as generally understood” (Davis 2006). Richard Thaler, Cass Sunstein, and Daniel Kahneman (2011) use the terms “Econ” and “Human” to stress this transformative finding. “Econ,” they write, is short for Homo economicus—“the notion that each of us thinks and chooses unfailingly well, and thus fits within the textbook picture of human beings offered by economists.” Human, on the other hand, is “the name used by the authors for homo sapiens, or ‘real people’. Real people have trouble with long division if they don’t have a calculator, sometimes forget their spouse’s birthday and have a hangover on New Year’s Day.” We are all “real people,” behavioral economists find, not the artifacts conjured by economics. Initially, BE also held that its findings reveal cognitive biases rather than emotions are the main reasons that people make poor choices (some write “are irrational”). Some still hold to this observation (Dictionary.com, 2013). However, Kahneman explains that more recently BE has come to recognize that in addition to suffering from cognitive limitations, humans are also influenced by their emotions (Personal communication, Kahneman 2011). This issue is not further explored in this article.
Cognitive Biases: Predetermined or Predispositional? The cognitive biases documented by behavioral economics are variously referred to as “hard-wired” (Powell et al. 2011)3 or “systematic”4 (Pesendorfer 2006). Behavioral economists do not devote much text to defining or studying these concepts because they are used in the same way they are employed by others sciences and defined in a standard dictionary. For instance, “hard-wired,” is understood to mean “pertaining to or being an intrinsic and relatively unmodifiable behavior pattern” (Dictionary.com, 2013), “genetically or innately determined” (Merriam-Webster Online Dictionary, 2013) or “determine[d] or put into effect by physiological or neurological mechanisms[;] automatic or innate” (The Free Online Dictionary, 2013). Vis (2011) summarizes the state of the field by writing, “An increasing amount of work drawing on evolutionary biology and neuroeconomics suggests that we, so to speak, cannot help ourselves [from displaying cognitive biases], as this behavior is hardwired.” (Seymour and Dolan (2008) report from a neurobiological perspective that the behavioral anomalies documented by behavioral economics can be traced to processes in the amygdala.) “Instead of trying to fix the hardwired errors of individual cognition, organizations should focus on managing the psychological architecture of the choice environment.” 4 Zarri (2010) holds that one of the two major groups of behavioral economists is primarily concerned with the discussion and documentation of “major cognitive limitations and systematic biases in decision making.” 3
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One may hold that behavioral economists who use these phrases mean to suggest that cognitive biases are merely predispositions rather than determinative attributes, although one is hard put to find a behavioral economist who explicitly makes this argument. However, if these are merely predispositions, the next step is clearly to identify under what conditions cognitive biases are activated, remain dormant, or are overcome, as well as to determine the strength of people’s predispositions. Can training, education, and self-awareness keep them at bay? Stanovich and West (1998) addressed this issue, but the question has since largely been ignored by the mainstream of BE scholarship, it shall be seen. The point spills over from BE’s academic publications into the more popular media. One business journal writes that “irrational decision-making under risk seems to be hardwired into our brains” (Rockford and Gray 2012). An NPR article holds that “behavioral economics [argues] that the human animal is hard-wired to make errors when it comes to decision-making,” and that “the human brain is hard-wired to make serious errors” (Spiegel, Alix 2009). An article in the Washington Post states, “The notion that we’re hard-wired to make poor decisions is a central tenet of investor psychology” (Frick, 2010). Nuclear biology distinguishes between genes or constellations of genes that determine individual attributes and those that merely predispose an individual to a particular attribute. Behavioral economics seems to imply that the strong and pervasive cognitive biases that they uncovered are determinative. The extent to which they can be corrected, if at all, is less clearly articulated, a point further explored below. However much of BE leaves itself open to the perception that because biases are hardwired, they are insurmountable.
Universal or Particularistic? The sciences differ a great deal in terms of the attributes on which they focus. Some focus on attributes of all the members of the category the given science studies (Kahneman 2003)5; other sciences focus on attributes particular to subcategories of individual members of the species. The differences between universalistic and particularistic attributes become salient if one asks—who has these cognitive biases? Behavioral economics answers clearly: humans, “people,” the whole species. This generalization, as will shortly be seen, is both validated by the evidence and open to a major misinterpretation. A review of ten of the most influential behavioral economics articles, as compiled by Mark Egan, PhD student in behavioral science, and Liam Delaney, professor at Stirling 5 “Psychology offers integrative concepts and mid-level generalizations, which gain credibility from their ability to explain ostensibly different phenomena in diverse domains.”
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University, finds that nine of the articles made generalizations that “people” (Thaler 2008), “consumers” (Schmidt and Fehr 1999), or “the average” individual (Thaler and Richard 1980) display generic or specific cognitive biases. Several scholars imply that these limitations are universalistic by stating that people “generally” (Thaler 2008) are subject to these cognitive biases, and pay little mind to exceptions—or at the very least, fail to acknowledge their importance. Thus, in a very often cited article by Tversky and Kahneman (1981) they write that “people exhibit patterns of preference which appear incompatible with expected utility theory,” and that “people generally evaluate…” In another article, they write that “decision makers systematically violate [the] basic tenets [of rational choice theory],” that “people overweight” certain probabilities, and that “people employ a variety of heuristic procedures” (Tversky and Kahneman 1992). Thaler (2008), in describing his theory of consumer behavior, writes that “people appear to…” and that “people generally will demand…” Loewenstein et al. (2001) write that “people react…” Sunstein (2013) writes that “Behavioral economists have emphasized that in important contexts, people err.” Rarely, terms such as “often” are used, implying that there are exceptions; however, when examined in the context of the article, it becomes clear that the term is used stylistically rather than to characterize, let alone study, those who do not exhibit such biases. The same universalistic pattern is evident in a second sample of articles examined—the ten most downloaded articles (since 2010) using the keyword “behavioral economics” at Social Sciences Research Network. Nine of the ten articles (most of which deal with the subfield of behavioral finance)— were kept as part of the sample; the tenth was dropped because it is a short outline of points rather than a report of findings or analysis. Of these remaining nine, all used generalizing phrases about people and cognitive biases. Sunstein (2013) writes that “people make choices that are not in their interest.” Ricciardi and Simon (2000) hold that “human beings” and “people” have a tendency to behave contrary to the tenets of rational choice. Thaler et al. (2010) report straightforwardly that “Humans make mistakes.” The strong tendency to address the species rather than particularistic differences within it is understandable given the context in which BE developed. BE is clearly in dialogue (some may argue that it is more appropriate to say it is in a clash) with neoclassical economics. Given that economists deal with “people”—assumed to be rational, able to make the necessary calculations and choices to maximize the utility they seek (Fehr and Schmidt 1999)6—it is enough for BE to show that “people” are unable to meet these requirements, to demonstrate that the core economic assumption is unsustainable. It does not matter, from this perspective, whether the 6 “Almost all economic models assume that all people are exclusively pursuing their material self-interest…”
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cognition of all people is flawed in the same measure or whether some are less biased than others. To put it differently, if rationality were a variable whose score ranges from zero to ten, economists would hold that people who score ten are rational. It is enough for behavioral economists to show that people score less than ten to disprove the economists’ assumption. It matters not if people score a nine or a two on average, or if some people score a nine while others score a two, or even if a minority of people scores a ten. However, for all purposes other than disproving neoclassical economics, such variations matter a great deal.
Behavioral Economics Data Support the Particularistic, Distribution Thesis BE own data do not support a “universalizing” conclusion, and instead show that important segments of people are either able to act rationally according to BE’s own criteria—or at least, their cognitive limitations are much less limiting than those of others. Indeed, a few scholars questioned “the magnitude and pervasiveness of many of these deviations” (Robinson and Hammitt 2011). The discussion below turns to asking what determines these differences. An early study of confirmation bias found that students confronted with fictional studies showing or disproving that capital punishment has a deterrent effect on crime were more likely to find the studies unconvincing if the “evidence” contradicted their original personal opinion. However, the same study found that people were still influenced to some degree “in the direction” of the presented evidence even if they had initially disagreed (Lord et al. 1979). Confounding factors that might lead people both to adopt their original opinion and to agree with evidence in support of that original position—say, normative commitments to particular values, or perspectives about what constitutes a strong argument—are not considered, even though the issue under consideration is one highly charged with ethical considerations. An experiment by Darley and Latané that proposed the concept of bystander apathy found that 31 % of individuals who thought that they were one of six participants did respond to a fellow participant’s apparent seizure, while 85 % of those who thought that they were the only one capable of responding did so. (These figures, however, should not be taken to mean that all of the participants responded at the same time. Some responded more rapidly than others).) Nisbett and Borgida (1975) found in their study that only four of fifteen participants immediately responded to their comrade’s distress. Neither experiment explains the behavior of those who responded in spite of the chance to act as a bystander—27 % in the latter study and 31 % in the former. In a study at Harvard, Princeton, and MIT, behavioral economists asked students to answer the following simple math question:
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A bat and a ball cost $1.10. The bat costs one dollar more than the ball. How much does the ball cost? The study found that “more than 50 %” of students at toptier universities—and more than 80 % at less prestigious institutions—gave the incorrect answer (Kahneman 2003).7 Neither the authors nor many who cite their work note that nearly 50 % of the students at top universities and nearly 20 % of students elsewhere answered correctly. In Chabris’ and Simons’ famous “invisible gorilla” experiment, approximately 50 % of people— with no apparent pattern as to age, gender, or education level— tasked with counting the number of basketball passes in a video didn’t remember seeing a woman in a gorilla costume who appears on screen for 9 seconds (Young 2011). However, this means that about 50 % did see the “invisible gorilla.” Another study examining the oft-cited phenomenon of preference reversals found that preference reversal occurred at an overall rate of 46 % (Tversky et al. 1990)—which of course means that over half of the time, the study participants displayed consistent preferences and thus did not reveal their cognitive bias. In the often-cited “Linda” study, the majority—64 %—of study participants correctly concluded that the likelihood of Linda being a bank teller was greater than the likelihood of Linda being a bank teller and a feminist (Kahneman 2011). Even more stunningly, Cosmides and Tooby (1996) found that between 76 and 92 % of study participants displayed proper Bayesian reasoning (answered “correctly”) when the statistical problem at hand was framed in terms of frequencies rather than probabilities, suggesting that the “cognitive bias” documented by behavioral economics may in fact be an artifact of BE’s experimental methods. None of these behavioral economics articles calls attention to or studies those who get the right answers, even when they comprise the majority of the participants. BE has been criticized on the grounds that many of its studies rely on experiments that use highly contrived conditions, trivial stimuli, and draw conclusions from very small samples. A survey of psychological studies found that psychologists have persistently selected “samples so small that they exposed themselves to a 50 % risk of failing to confirm their true hypotheses!” (Kahneman 2011) Kahneman (2011) notes that many behavioral economists, himself included, similarly failed to use standard methods of selecting sample sizes, thus leading to inappropriately small samples. For example, Tversky and Kahneman’s (1992) often-cited study that proposed a two-phase model of decision making was based on a survey of 25 students. The finding that memories are shaped most strongly by the end of the event– is based on a study of two colonoscopy patients (Kahneman, Daniel 2010). Hence the importance of the Investment Company Institute’s 2006 study of 401(k) participation, which is based on “real” field 7 47 of 93 students in the Princeton sample and 164/293 in the University of Michigan sample gave the wrong answer.
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conditions and uses a very large population (Holden et al. 2006). (Sizes of studies in the paper ranged from 1.1 million to 3.5 million.) The ICI study (and similar studies) is often cited to show that “people” do not act rationally—because they do not put money into their 401(k) accounts in spite of the fact that they provide significant tax deductions or deferments. Sunstein and Thaler (2008), for example, in their acclaimed book, Nudge, argue that “people” need paternalistic libertarian “nudges” to make the correct decision to contribute to 401(k) plans. However, the ICI study by Holden et al. (2006) found that approximately 70 % of eligible employees participated in 401(k) plans in 2003—only 30 % did not. (Nor is it obvious that all these people should have enrolled given their economic circumstances.) In another study, cited by Thaler and Sunstein (2008), the authors stress that almost 50 % of eligible employees fail to participate in 401(k) plans. Note should be taken that over 50 % of eligible employees did participate. In short, both experiments and “field” studies show that important segments of “the people” act rationally even by BE standards because they got the correct answers on the various questions or tests administered by behavioral economists or acted as a rational person is expected to. This contrasts with the way behavioral economists state their findings, which leaves them open to the misperception that they mean that nobody, or almost nobody, is able to think or act rationally because they are hardwired to make systematic mistakes.
Knowing Should Be Treated as a Continuous Variable Many of BE’s experiments and much of the reporting of its findings is cast in terms that suggest that rationality is a dichotomous variable: either one is rational or not. (What is rational, though, is somewhat pliable, as indicated for instance by the term “bounded rationality.”) This further reflects the fact that for a behavioral economist to show that people are not rational suffices to falsify the key assumption of neoclassical economics; it matters not how many and to what extent people err—or at least, if the errors are more than trivial, which neoclassical economists cannot absorb by referring to ‘imperfect knowledge” as if the errors are a rounding error that can be ignored. In contrast to the assumptions of BE, it should be assumed that rationality and cognitive biases—and their application in choice behavior—are continuous variables (Korobkin and Ulen 2000).8 The term “knowing” is next used to refer to the 8
Russell B. Korobkin and Thomas S. Ulen acknowledge the fallaciousness of this dichotomy. “To claim that rational choice theory is an insufficient behavioral model on which to base legal policy is not to argue that individuals behave irrationally (although they certainly do in some circumstances). Rather, it is to assert that legal scholars seeking to understand the incentive effects of law in order to propose efficacious legal policy should not be limited to rational choice theory.”
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result of collecting and processing information and subsequently drawing conclusions. The term “knowledge” is used rather than “information,” because information is the raw material from which knowledge might be made. However, one may have the wrong kind or wrong amounts (e.g. excessive) of information, or may process it poorly; this is the merit of keeping the two concepts distinct. The merit of viewing rationality as a continuous variable is demonstrated by one of Kahneman, Tversky, and Slovic’s own early experiments about preference reversal. In the experiment, people ranked two options and were later asked to price similar options without being given specific prices from which to choose. The study showed that people priced the options in ways that were inconsistent with the way that they had earlier ranked their preferences. Because price is a continuous variable in this experiment, it is theoretically possible to show that some people price the options “worse” (more inconsistently) than others do and therefore display more severe preference reversal than others. Heberlein and Bishop conducted an experiment in which people were asked to give the amount that they would pay to obtain a hunting permit, and then asked to state for how much they would sell the same permit assuming they possessed one. They found that on average people would pay $31 to buy and would sell for $143 (Bishop and Heberlein 1979). How much, then, is the permit actually “worth?” Using the continuous variable of price here makes it possible to see just how “poor” subjects are at making decisions. Those who would buy at the same price at which they would sell the permit—say, they would buy it at $31 and sell it for $31—would score high on the rationality variable. Those who would buy at $31 and sell at $50 are not rational, but are better knowers than those who would buy at $31 and sell for $143. Similarly, Thaler and Sunstein (2008) speak about the number of people who participated in a 401(k) plan in a particular year as evidence of cognitive biases. However, surely there is a difference in the level of rationality displayed by someone who enrolls in a 401(k) plan immediately upon becoming eligible—the “perfectly rational” choice, given that benefits begin accruing immediately, chosen by less than 20 % of people—and someone who procrastinates up to 36 months before eventually making the “correct” choice—a path taken by the remaining 45 % of those who participated in a 401(k) according to a study by Madrian and Shea (2000). Thus, the 65 % of people who participate in a 401(k) are not all equally limited by their cognitive biases. Some manage to overcome their biases in order to make a decision that is close to the one expected from rational actors—others, meanwhile, are much worse knowers and score much lower on the rationality variable. One may accept that generally humans are poor knowers— that is, many make serious mistakes—and nonetheless recognize that on some subjects important segments of the public do get it right, and above all that people vary a great deal in the
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extent to which they err—or know. This raises two questions behavioral economists have yet to address much more than they have done so far: given the findings just cited, it seems that the biases are not hardwired. But what drives them? What accounts for the differences? And above all, to what extent can the biases be corrected through education, training, structural arrangements, or in some other way?
What is Responsible for the Differences? What accounts for the differences in cognitive performance is a key question for those who view limitations as a distribution, but an irrelevant consideration for those who view them as universal attributes of all humans. Given that the evidence mustered by BE and other disciplines strongly indicates that there are significant differences in the degree to which individuals are “poor knowers,” much more attention must be paid to the variables that influence cognitive abilities. That people at “top tier” universities made many fewer errors—a difference of 30 percentage points—while solving a simple math question than did other students (Kahneman 2003) suggests that education or selection may be two such variables. Others seem to include emotions (Kahneman 2011),9 social norms and cultural factors may affect levels of self-control or ability to defer gratification which in turn may affect the level of poor knowing. The same may hold for age and structural factors (Forbes 2005)—all deserve more attention within the BE context.
Hard-wired or Therapeutic? Apart from contributing to a better understanding of the causes of human cognitive flaws, identification of the said variables is relevant to determining the extent to which these flaws can be overcome. True, BE seems correct to conclude that in spite of training, education, and other provisions, most people will remain incapable of acting in ways neoclassical economists would consider “rational”—that is, score the maximum on the knowing variable. However, if it is possible to improve people’s knowing from a very poor level to a significantly higher one, it is surely worth knowing. Behavioral economists have not dedicated much attention to this question, which is understandable because if one can overcome biases they are not hardwired. Indeed, Kahneman (2011) writes that some of his research “supports the uncomfortable conclusion that teaching psychology is mostly a waste of time” because knowledge of one’s cognitive biases does little to ameliorate them. He writes in that it may be possible to 9 47 of 93 students in the Princeton sample and 164/293 in the University of Michigan sample gave the wrong answer. With payoffs.
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“discipline” one’s intuition, but he admits that even he, one of the foremost scholars of behavioral science, still “finds it unnatural to [implement them].” Trout (2005) finds that biases “are virtually as stable, durable, and universal as reflexes” and are “extremely difficult for individuals to correct, and so are, for practical purposes, psychologically incorrigible.” He thus recommends “institutional prosthetics” to mitigate their effects. Thaler and Sunstein (2008) write in Nudge that although education is the “obvious” answer to the question of how to correct cognitive bias, “the evidence does not suggest that education is, in and of itself, an adequate solution.” Casscells, Schoenberger, and Grayboys found, in a study of sixty medical students and faculty, that only 18 % answered a simple statistical problem involving false positive rates correctly (Kaplan and Du 2009)—suggesting that even those who are scientifically trained are subject to cognitive bias. A study by British scientists Rabipour and Raz (2012), using the “largest sample size ever used in cognitive research,” found “no significant increase in general cognitive performance following 6-weeks of online training.”10 An article by Jolls and Sunstein (2004) suggests that it is possible to reduce or even “eliminate” the effects of cognitive bias through the law, but this approach emphasizes correcting for cognitive biases rather than training individuals to overcome them. Indeed, the concept of libertarian paternalism is predicated on the idea that rather than attempting to teach people to overcome their biases, one should work around them by changing their choice architecture and by using other methods that ensure favorable outcomes without relying upon individuals’ deliberations (Thaler and Sunstein 2008). However, the more one notes the BE own data show significant differences in poverty of decision making—no one is rich but some are more less poor than others—the more one must wonder what role education and training play in these differences. BE has established, through a very robust set of data, that a key assumption of neoclassical economics—namely, that people are rational actors—is untenable. BE did so by showing that “people” have multiple, systematic, hard-wired major cognitive biases. However, in the process, BE greatly overstated its case by a) largely ignoring those significant parts of the population that by its own data did act “rationally,” and b) ignoring significant differences in the magnitude of the participants’ deviations from that which BE considers “rational.” The article led to the following exchange with the editor of the Review of Behavioral Economics, Barkley Rosser, which helps much in clarifying the issues at hand. He wrote: “While it is true that many behavioral economists sloppily talk about average behaviors, most fully recognize that there 10
The study had several limitations, but the general findings of the report were widely circulated in the British media.
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are considerable variations of this, and there is a considerable literature in which efforts are made to measure these degrees of rationality or intelligence in connection with various behaviors. The other is that I think this matter of what “rationality” is is more complicated than you have let on and is in fact multidimensional, although it may be continuous on most of these. It would seem that you focus on basic ability to calculate, obviously highly correlated with math IQ, but there are many other sources of “irrationality” than just this, although it is an important one and one that can be measured better than others.” I responded by “could you share with me who measures degrees of rationality. of course only someone completely clueless would treat rationality as equivalent to intelligence. “ Barkley Rosser responded: “The idea that rationality in various forms varies continuously, or at least varies systematically in various ways across individuals, was present from the very beginning of behavioral economics as a self-conscious approach initiated by my late friend whom I imagine you also knew, Herb Simon. It is present even in his 1947 Administrative Behavior. He posed bounded rationality as reflecting both access to information and computational ability as determining how far boundedly rational behavior would deviate from full rationality. So, in his classic 1955 article, 69(1), “A behavioral model of rational choice,” he states “Broadly stated, the task is to replace the global rationality of economic man with a kind of rational behavior that is compatible with the access to information and the computational capacities that are actually possessed by organisms, including man, in the kinds of environments these organisms exist.” This clearly implies variations of these “computational capacities.,” with no reason to assume they are not reasonably continuous (and IQ certainly is continuous, which is correlated with “computational capacity,” if imperfectly so). Another area where this comes up is in discussions of rational expectations. Thus in a classic paper testing rational expectations that also cites Simon’s Nobel Prize address (AER, Sept. 1979), Michael C. Lovell finds that the hypothesis fails, but he notes that there are many competing alternatives that people use, with some coming closer to the hypothesis than others, clearing implying variations in the degree of rationality, “Tests of the Rational Expectations Hypothesis,” AER, March 1986, 76, 110–124. This a much cited paper, with others following it. Somewhat related to that is a large and ongoing literature that allows for heterogeneous agents who vary in their willingness to switch strategies in financial markets based on the relative performance of those strategies, with an instantaneous such willingness identified with “Chicago-style full rationality,” but with this measure varying continuously and crucial to the dynamic patterns observed in markets. A classic that underlay the widely studied Santa Fe stock market model is
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William A. Brock and Cars Hommes, “Heterogeneous beliefs and routes to chaos in a simple asset pricing model,” Journal of Economic Dynamics and Control, 1998, 22, 1236–1274. Finally, we have the massive literature on the ultimatum game, where the discussion becomes entangled with whether deviations from Nash equilibrium “rational” strategies are done or not for reasons of a “taste for fairness,” with these now observed to vary widely across societies. An early study that criticized the ultimatum game results and argued that making it into a two-stage game would lead to much more behavior that was rational a la Nash, “gamesman rational” rather than “fairnessman irrational,” with this varying across individuals is Ken Binmore, Avner Shaked, and J. Sutton, “Testing noncooperative bargaining theory: A preliminary study,” AER, Dec. 1985, with discussions in terms of degrees of rationality on p. 1180. The literature on this is also enormous and ongoing, with the more complicated arguments about “what is rational” involved, quite aside from recognizing that there are degrees of such rationality across individuals, however “rationality” is defined.” I suggested that : “The fact that various scholars defined rationality differently, and that same definitions set the bar lower than others, does not address the question of measuring the degree of rationality of any particular kind. This is like when one suggests that now that we know that oranges are acidic, one should measure differences in degree of acidity and what causes them—one is told that there are differences in acidity among oranges, tangerines, and grapefruits. Well put, but not to the point. Thus Herb Simon may talk about bounded rationality as distinct from optimal rationality—but does not tell us who has less vs more bounded rationality and so on and on. Ultimately the reason to know why some people are somewhat more rational than others—is to help people become less irrational. However, to proceed it is not enough to show that training and education do not come easily, but to make for more effective measures, given that none of them are very potent.” Barkley Rosser should have the last word “I completely agree that ”rationality“ is multi-dimensional, and from Simon on various people have indeed identified different forms of rationality. Different aspects can be measured in different ways, and those who have sought to be more specific about doing so in a continuous manner, as some have, have had to be specific about the specific instrument used to make that measurement.”
Further Reading Begley, C. G. & Ellis, L. M. 2012. Drug development: Raise standards for preclinical cancer research. Nature, 483, 531–533.
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Amitai Etzioni is a University Professor at the George Washington University and author of The Active Society and New Common Grounds, among other books.
