Prob[G succeeds while B fails] = 0.6 * (1 - 0.4) = 0.36
Prob[B succeeds while G fails] = 0.4 * (1 - 0.6) = 0.16
Prob[G and B both succeed] = 0.6 * 0.4 = 0.24
Prob[G and B both fail] = (1 - 0.6) * (1 - 0.4) = 0.24
In other words, it is more likely that G will do at least as well as B than the other way around—just as one would expect. But it is also the case that only one time in three, roughly, will G succeed while B fails. Almost half the time, in fact, both strategies perform equally well—or poorly—and one time out of six, it will even be the case that B will succeed while G fails. With almost two-thirds probability, it follows that when the good and bad processes are run side by side, the outcomes will not accurately reflect their differences.
8. See Brill (2009) for the original quote.
9. The distinction is important because it is often argued that for any sufficiently large population of fund managers, someone will be successful for many years in a row, even if success in any given year is determined by a coin toss. But as Mauboussin (2006, 2010) shows, coin tossing is actually a misleading metaphor. Because the performance of managed funds is assessed after fees, and because the overall portfolio of managed funds does not necessarily mirror the S&P 500, there is no reason to think that 50 percent of funds should “beat the market” in any given year. In fact the actual percentage varied from 7.9 percent (in 1997) to 67.1 percent (in 2005) over the fifteen-year interval of Miller’s streak. When these empirical success rates are taken into account, the probability of observing a streak like Miller’s is closer to one in 2.3 million (Mauboussin 2006, p. 50).
10. For DiMaggio’s statistics see http://www.baseball-almanac.com/fur: DiMaggio’s Statistics.
11. Arbesman and Strogatz (2008), using simulations, find that the likelihood of a fifty-six-game streak is somewhere between 20 percent and 50 percent. Interestingly, they also find that DiMaggio was not the most likely player to have attained this distinction; thus his streak was some mixture of skill and luck. See also McCotter (2008), who shows that long streaks happen more frequently than they should if batting average is constant, as Arbesman and Strogatz assume, suggesting that batters in the midst of a streak may be more likely to score a subsequent hit than their season average would suggest. Although they disagree with respect to the likelihood of streaks, however, both models are consistent in the idea that the correct measure of performance is the batting average, not the streak itself.
12. Of course, it’s not always easy to agree on what constitutes a reliable measure of talent in sports either: whereas for a 100-meter sprinter it is very clear, in baseball it is much less so, and fans argue endlessly over which statistics—batting average, strikeout rate, runs batted in, slugging percentage—ought to count for more. Mauboussin (2010), for example, argues that strikeout rate is a more reliable measure of performance than batting average. Whatever the right measure is, however, the main point is that sports afford relatively large numbers of “trials” that are conducted under relatively comparable conditions.
13. See Lewis (2009) for an example of measuring performance in terms of a player’s effect on the team’s win-loss record.
14. Of course, we could artificially increase the number of data points by looking at their daily or weekly performance rather than their annual one; but these measures are also correspondingly noisier than annual measures, so it probably wouldn’t help.
15. See Merton for the original paper. See also Denrell (2004) for a related argument about how random processes can account for persistent differences in profitability among businesses.
16. See Rigney (2010). See also DiPrete and Eirich (2006) for a more technical review of the cumulative advantage and inequality literature. See Kahn (2010) for detail on college graduates’ earnings.
17. See McDonald (2005) for the Miller quote.
18. Mauboussin (2010) makes this point in considerably more detail.
19. Ironically, the further removed a measure of success is from a direct measure of talent, the more powerful the Halo Effect becomes. As long as your claim to talent is based on your personally having performed a particular thing well, someone can always question how well it was actually done, or how worthwhile a thing it was to do in the first place. But as soon as one’s accomplishments become abstracted from their substance—as happens, for example, when a person wins important prizes, achieves great recognition, or makes fabulous amounts of money—concrete, individual metrics for assessing performance are gradually displaced by the Halo. A successful person, like a bestselling book or popular idea, is simply assumed to have displayed the appropriate merit, at which point the success effectively becomes a substitute for merit itself. But even more than that, it is merit that cannot be easily questioned. If one believes that the Mona Lisa is a great piece of art because of X, Y, and Z, a knowledgeable disputant can immediately counter with his or her own criteria, or point out other examples that ought to be considered superior. But if one believes instead that the Mona Lisa is a great piece of art simply because it is famous, our pesky disputant can come up with all the objections she desires and we can insist quite reasonably that she must be missing the point. No matter how knowledgably she argues that properties of the Mona Lisa aren’t uniquely special, we cannot help but suspect that something must have been overlooked, because surely if the artwork was not really special, then it wouldn’t be, well, special.
20. See http://www.forbes.com/lists/2009/12/best-boss-09_Steven-P-Jobs_HEDB.html.
21. Sometimes even the leaders themselves concede this point—but interestingly they tend to do so only when things are going badly. For example, when the leaders of the four largest investment banks testified before Congress in early 2010, they did not take personal responsibility for the performance of their firms, claiming instead that to have been victims of a “financial tsunami” that had wreaked havoc on the economy. Yet in the years leading up to the crisis, when their firms were making money hand over fist, these same leaders were not turning down their bonuses on the grounds that everyone in their industry was making money, and therefore they shouldn’t be credited with doing anything special. See Khurana (2002) for details, and Wasserman, Anand, and Nohira (2010) for the empirical results on when leadership matters.
22. To quote Khurana directly: “strong social, cultural, and psychological forces lead people to believe in cause-and-effect relationships such as that between corporate leadership and corporate performance. In the United States, the cultural bias towards individualism largely discounts the influence of social, economic, and political forces in human affairs so that accounts of complicated events such as wars and economic cycles reduce the forces behind them to personifications.… This process of exaggerating the ability of individuals to influence immensely complex events is strongly abetted by the media, which fixate the public’s attention on the personal characteristics of leaders at the expense of serious analysis of events” (Khurana 2002, p. 23).
23. As Khurana and other critics are quick to acknowledge, their research does not mean that anyone can be an effective CEO, or that CEO performance is irrelevant. It is certainly possible, for example, for a CEO to destroy tremendous value by making awful or irresponsible decisions. And because avoiding bad decisions can be difficult, even satisfactory performance requires a certain amount of experience, intellect, and leadership ability. Certainly not everyone has the wherewithal to qualify for the job, or the discipline and energy to perform it. Many CEOs are impressive people who work long hours under stressful conditions and carry heavy burdens of responsibility. It’s therefore perfectly reasonable for corporate boards to choose candidates selectively and to compensate them appropriately for their talent and their time. The argument is just that they shouldn’t be selected or compensated on the grounds that their individual performance will have more than a weak influence on the future performance of their firm.
24. For a summary of Rawls’s and Nozick’s arguments, see Sa
ndel (2009). For the original arguments, see Rawls (1971) and Nozick (1974).
25. See DiPrete (2002) for empirical evidence on intergenerational social mobility.
26. See, for example, Herszenhorn (2009) and Kocieniewski (2010).
27. See, for example, Watts (2009).
28. See Watts (2003, Chapter 1) for a detailed discussion of one such cascading failure—the 1996 failure in the western United States.
29. See Perrow (1984) for examples of what he calls normal accidents in complex organizations. See also Carlson and Doyle (2002) for a more technical treatment of the “robust yet fragile” nature of complex systems.
30. See Tabibi (2009) for an example of how Goldman Sachs profited from multiple forms of government assistance.
31. See Sandel (2009).
32. See Granovetter (1985).
33. See Berger and Luckman (1966). The deliberative democracy literature mentioned in Chapter 1, note 25, is also relevant to Sandel’s argument.
CHAPTER 10: THE PROPER STUDY OF MANKIND
1. The full text of Pope’s “Essay on Man” is available online at Project Gutenberg http://www.gutenberg.org/etext/2428.
2. Parsons’s notion of rationality was inspired by Max Weber, who interestingly was not a functionalist, or even a positivist, espousing instead what has become known as an interpretive school of sociology, manifest in his claim that rational action was that which was understandable (verstehen) to an analyst. Nevertheless, Weber’s work was quickly seconded by strongly positivistic theories, of which rational choice theory is the most obvious; thus illustrating how deeply the positivistic urge runs in all forms of science, including social science. Parsons also is sometimes cast as an anti-positivist, but once again, his ideas have been incorporated into positivist theories of social action.
3. For critiques of Parsons, see Mayhew (1980, p. 353), Harsanyi (1969, p. 514), and Coleman and Fararo (1992, p. xvii).
4. Many sociologists—both before Merton and since—have been critical of what they have viewed as facile attempts to replicate the success of natural science by imitating its form rather than its methods As early as the 1940s, for example, Parsons’s contemporary Huntington Cairns wrote that “We possess no such synoptic view of social sciences which encourages us to believe that we are now at a stage of analysis where we can with any certainty select the basic concepts upon which an integrated structure of knowledge can be erected” (Cairns 1945, p. 13). More recently, a steady drumbeat of criticism has been directed at rational choice theory, for much the same reasons (Quadagno and Knapp 1992; Somers 1998).
5. Quotes are from Merton (1968a).
6. See Merton (1968a) for his description of theories of the middle range, including the theory of relative deprivation and the theory of the role set.
7. Harsanyi (1969, p. 514) and Diermeier (1996) both reference Newton, while the political scientists Donald Green and Ian Shapiro have called rational choice theory “an ever-expanding tent in which to house every plausible proposition advanced by anthropology, sociology, or social psychology” (Green and Shapiro 2005).
8. The “success” or “failure” of rational choice theory, it should be noted, is highly controversial, with rational choice advocates claiming that it is unfair to evaluate rational choice theory as a “theory” in the first place, when really it should be regarded rather more as a family of theories unified only by their emphasis on purposive action as the cause of social outcomes over accident, blind conformity, or habit (Farmer 1992; Kiser and Hechter 1998; Cox 1999). Perhaps this is an accurate statement of what rational choice theory has become (although interestingly some rational choice theorists include even habit within the gambit of rational incentives [Becker and Murphy 2000]), but it’s certainly not what early proponents like Harsanyi intended it to be. Harsanyi in fact criticized Parsons’s theory explicitly for not being a “theory” at all, lacking the ability to derive conclusions logically from a set of axioms—or as he put it, “the very concept of social function in a collectivist sense gives rise to insoluble problems of definition and of empirical identification” (1969, p. 533). Whether or not it has subsequently metamorphosed into something more realistic should therefore not distract from the point that its original mission was to be a theory, and that in that sense it has been no more successful than any of its predecessors.
9. Indeed, as Becker (1945, p. 84) noted long ago, natural scientists are every bit as prone as social scientists to overestimate their ability to construct predictive models of human behavior.
10. Stouffer (1947).
11. It should be noted that not all sociologists agree that measurement is really the problem that I’m making it out to be. According to at least one school of thought, sociological theories should help us to make sense of the world, and give us a language with which to argue about it; but they shouldn’t aim to make predictions or to solve problems, and so shouldn’t be judged by the pragmatic test in the first place. If this “interpretive” view of sociology is correct, the whole positivist enterprise that began with Comte is based on a fundamental misunderstanding about the nature of social science, starting with assumption that it ought to be considered a branch of science at all (Boudon, 1988b). Sociologists, therefore, would do better to focus on developing “approaches” and “frameworks”—ways of thinking about the world that allow them to see what they might otherwise miss, and question what other people take for granted—and forget all about trying to build theories of the kind that are familiar to us from physics. It was essentially this kind of approach to sociology, in fact, that Howard Becker was advocating in his book Tricks of the Trade, the review of which I encountered back in 1998, and that John Gribbin—the reviewer, who, remember, is a physicist—evidently found infuriating.
12. See, for example, Paolacci et al. (2010).
13. The privacy debate is an important one, and raises a number of unresolved questions. First, when asked, people say they care deeply about maintaining their privacy (Turow et al. 2009); however, their actions frequently belie their responses to survey questions. Not only do many people post a great deal of highly personal information about themselves in public but they also decline to pay for services that would guarantee them a higher than default level of privacy. Possibly this disconnect between espoused and revealed preferences implies only that people do not understand the consequences of their actions; but it may also imply that abstract questions about “privacy” are less meaningful than concrete tradeoffs in specific situations. A second, more troubling problem is that regardless of how people “really” feel about revealing particular pieces of information about themselves, they are almost certainly unable to appreciate the ability of third parties to construct information profiles about them, and thereby infer other information that they would not feel comfortable revealing.
14. See Sherif (1937) and Asch (1953) for details of their pioneering experiments. See Zelditch (1969) for his discussion of small-group versus large-group studies. See Adar and Adamic (2005), Sun et al. (2009), and Bakshy and Adamic (2009) for other examples of tracking information diffusion in online networks.
15. Now that they’ve proven the concept, Reiley and Lewis are embarking on a whole array of similar experiments—for department stores, phone providers, financial services companies, and so on—with the aim of measuring differences across domains (do ads work differently for phones than for credit cards?), across demographics (are older people more susceptible than younger?), and even across specific ad layouts and designs (blue background versus white?).
16. See Lazarsfeld and Merton (1954) for the original definition of “homophily,” and McPherson et al. (2001) for a recent survey of the literature. See Feld (1981) and McPherson and Smith-Lovin (1987) for discussion of the importance of structural opportunities.
17. The reason is that social structure not only shapes our choices but is also shaped by them. It is true, for example, that whom we are likely to meet in the immediate future is determined
to some degree by our existing social circles and activities. But on a slightly longer timescale it is also true that we may choose to do certain things over others precisely because of the people we expect to meet in the course of doing them. The whole point of “social networking” events in the business world, for example, is to put yourself in a situation where you might meet interesting people. Likewise, the determination of some parents to get their children into the “right” schools has less to do with the quality of education they will receive than the classmates they will have. That said, of course, it is not equally easy for everyone to get into Harvard, or to get invited to the most desirable social gatherings. On a longer timescale again, therefore, your position in the social structure constrains not only whom you can get to know now but also the choices that will determine your future position in the social structure. Arguments about the relative importance of individual preferences and social structure invariably get bogged down in this chicken-and-egg tangle, and so tend to get resolved by ideology rather than by data. Those who believe in the power of individual choice can always contend that structure is simply the consequence of choices that individuals have made, while those who believe in the power of structure can always contend that the appearance of choice is illusory.
18. A similar finding has subsequently been reported in another study of homophily using data collected from Facebook (Wimmer and Lewis, 2010).
19. Some studies have found that polarization is increasing (Abramowitz and Saunders 2008; Bishop 2008), whereas others have found that Americans agree more than they disagree, and that views on one issue, say abortion, turn out to be surprisingly uncorrelated with views on other matters, like gun ownership, or immigration (Baldassari and Gelman 2008; Gelman et al. 2008; DiMaggio et al. 1996; Fiorina et al. 2005).
20. See Baldassari and Bearman (2007) for a discussion of real versus perceived agreement. In spite of the practical difficulties, some pioneering studies of precisely this kind have been conducted, first by Laumann (1969) and later by Huckfeldt and colleagues (Huckfeldt et al. 2004; Huckfeldt and Sprague 1987).
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