Good Economics for Hard Times

by Abhijit V. Banerjee

  This phenomenon predated 2016, but Trump’s election made it that much easier to talk about openly. In a clever experiment highlighting this, researchers recruited online respondents in eight deep-red states: Alabama, Arkansas, Idaho, Nebraska, Oklahoma, Mississippi, West Virginia, and Wyoming.26 Just before the 2016 election, they offered respondents a financial incentive to give money to an anti-immigration charity. Specifically, they asked respondents to authorize them to make a $1 donation to the organization on their behalf, and offered to pay them an extra fifty cents if they agreed. For some people the choice was purely private. For some randomly selected others the offer was presented in a way that implied a small chance they would be personally called by a member of the research team to verify their decision—so at least one person would observe their decision and discuss it with them. Before the election, people in this second group were less likely to agree to donate than people who could do it purely privately (34 percent versus 54 percent). But when the same experiment was conducted right after the election, that difference entirely disappeared! The victory of someone who expressed overt anti-immigration views had freed respondents up to openly give money to an anti-immigrant group.

  It is perhaps reassuring that previous waves of migrants to the United States experienced similar rejection before they were ultimately accepted. Benjamin Franklin hated the Germans: “Those who come hither are generally of the most ignorant Stupid Sort of their own Nation.… Not being used to Liberty, they know not how to make a modest use of it.” Jefferson thought the Germans were unable to integrate. “As to other foreigners it is thought better to discourage their settling together in large masses,” he wrote, “wherein, as in our German settlements, they preserve for a long time their own languages, habits, and principles of government.”27 America tried to limit Chinese immigration as early as the nineteenth century and it was eventually banned. In 1924, quotas were introduced with the aim of limiting immigration of Eastern and Southern Europeans (Italians and Greeks).28

  And yet each wave of immigrants eventually was accepted and assimilated. The first names they chose for their children, the occupations they ended up in, the way they voted, and what they bought and ate converged with those of the local population. In turns, the locals adopted the once-foreign first names and foods: Rocky is an American hero and pizza is one of the five basic food groups.

  The same phenomenon happened in France. French people rejected the Italians. Then they rejected the Poles. Then they rejected the Spaniards and the Portuguese. Every wave of migrants eventually became integrated, but in each case at first the French believed it was “different this time.” By 2016, it was the Muslims’ turn to be rejected.

  Where do these preferences and attitudes come from? Why do we seem to look for a new enemy even as we become reconciled to the previous one?

  STATISTICAL DISCRIMINATION

  There are potentially some simple economic explanations for bigoted behavior toward other groups, very much in the spirit of Becker and Stigler’s standard model. Intimidation sometimes serves an economic purpose. Between 1950 and 2000, Hindu Muslim riots in India were much more likely to occur in a particular city in a particular year if the Muslim community happened to be relatively well off. And they were less likely to occur if the Hindu community happened to be doing well.29 This is consistent with detailed accounts of some of the large riots, where Muslim businesses were specifically targeted in the midst of what may have seemed like random violence. Violence is often a convenient camouflage for theft.

  It is also true that sometimes individuals feel the need to express intolerance and prejudice (including sentiments they do not actually share) in order to signal fealty to their group. For example, during the Indonesian economic crisis, membership in Koran reading groups increased. The display of intense religiosity was a sign of loyalty to earn a place in a mutual assistance circle.30 In other contexts, sometimes people keep quiet about racism (and/or sexism), or even echo what they hear because they do not want to lose their jobs or valuable social connections.

  And, finally, there is what economists call statistical discrimination. We met an Uber driver in Paris who was very enthusiastic about his job. He said that in the old (pre-Uber) days, if a North African man like him was seen driving a nice car, everyone assumed he was either a drug dealer or had stolen the car. Most people believed, correctly, that most normal North Africans tended to be relatively poor and therefore unlikely to be able to afford a new car, and on the basis of that statistical association their presumption was that the individual North African driver of a nice car was a criminal. Now they assume he is an Uber driver, which is clear progress.

  Statistical discrimination explains why the police in the United States justify stopping black drivers more often. And how the Hindu majoritarian government of the state of Uttar Pradesh recently explained why so many of the people “accidentally” killed by the state police (in what are called “encounter deaths”) are Muslim. There are more blacks and Muslims among criminals. In other words, what looks like naked racism does not have to be that; it can be the result of targeting some characteristic (drug dealing, criminality) that happens to be correlated with race or religion. So statistical discrimination, rather than old-fashioned prejudice—what economists call taste-based discrimination—may be the cause. The end result is the same if you are black or Muslim, though.

  A recent study on the impact of “ban the box” (BTB) policies on the rate of unemployment of young black men provides a compelling demonstration of statistical discrimination. BTB policies restrict employers from using application forms where there is a box that needs to be checked if you have a criminal conviction. Twenty-three states have adopted these policies in the hope of raising employment among young black men, who are much more likely to have a conviction than others and whose unemployment rate is double the national average.31

  To test the effect of these policies, two researchers sent fifteen thousand fictitious online job applications to employers in New Jersey and New York City, just before and right after the states of New York and New Jersey implemented the BTB policy.32 They manipulated the perception of race by using typically white or typically African American first names on the résumés. Whenever a job posting required indicating whether or not the applicant had a prior felony conviction, they also randomized whether he or she had one.

  They found, as many others before them, clear discrimination against blacks in general: white “applicants” received about 23 percent more callbacks than black applicants with the same résumé. Unsurprisingly, among employers who asked about criminal convictions before the ban, there was a very large effect of having a felony conviction: applicants without a felony conviction were 62 percent more likely to be called back than those with a conviction but an otherwise identical résumé, an effect similar for whites and blacks.

  The most surprising finding, however, was that the BTB policy substantially increased racial disparities in callbacks. White applicants to BTB-affected employers received 7 percent more callbacks than similar black applicants before BTB. After BTB, this gap grew to 43 percent. The reason was that without the actual information about convictions, the employers assumed all black applicants were more likely to have a conviction. In other words, the BTB policy led employers to rely on race to predict criminality, which is of course statistical discrimination.

  That people are using statistical logic does not, of course, mean they are always drawing the right inferences from it. In one study, researchers asked Ashkenazi Jews (European or American Jews and their descendants) in Israel to play a trust game with Eastern Jews (Asian and African immigrants and their descendants). The trust game is one of the mainstays of experimental economics. It is played by two people, one of whom, the sender, is given a certain amount of money and asked to share some part of it with the other person, the receiver. The amount could be zero and is entirely left to the sender’s discretion. However, they are both told that if the sender s
hares any of it, that shared amount will be tripled and given to the receiver, who then has full control over the money. The receiver has the option of sharing some of his gains with his benefactor but can opt not to do so. The point of this game is to infer what the sender thinks about the receiver; the less selfish the sender believes the receiver to be, the more he should share.

  The trust game has been played thousands of times in laboratory settings. Typically, the sender shares half or more of the original amount and gets back more than was sent. Senders are trusting and receivers are trustworthy. This is also what the researchers found when the two players were both Ashkenazi. But things fell apart when the receiver was an Eastern Jew. In that case, the sender shared about half of what would have been sent to an Ashkenazi. As a result, both senders and receivers got less.

  It could be that this happens because the Eastern receivers are not trusted to return the gift. Or it could be because they are disliked, and Ashkenazi senders are willing to hurt themselves just to hurt Eastern receivers as well. But when players were asked to just voluntarily give some of their money to a partner with no expectation any of it would come back, they gave about as much to Eastern partners as they did to the Ashkenazi; the source of the different behaviors in the trust game seems to be suspicion rather than animosity.

  Interestingly, the suspicion extends to Eastern senders in the trust game. They were no more trusting of their co-ethnics than the others. There seems to be a stereotype of Eastern Jews that everyone has bought into. But the twist is that the stereotype is entirely unfair. There is absolutely no evidence the Eastern players in this game act in a less trustworthy way; their pattern of returning the money is exactly the same as that of the Ashkenazis. The participants in the experiment thought they behaved rationally, but they were being led astray by imaginary suspicions.

  SELF-REINFORCING DISCRIMINATION

  The ubiquity of self-discrimination, or discrimination against one’s own group, was powerfully brought to light by a well-known experiment by the American psychologist Claude Steele, which demonstrated the power of what he called a “stereotype threat.” In his original experiment, he found that black students performed comparably with white students when told a test they were taking was “a laboratory problem-solving task.”33 However, black students scored much lower than whites when test takers were told the test was meant to measure their intellectual ability.

  Minorities aren’t the only ones vulnerable to stereotype threat. Female college students performed better on a hard mathematics test when it included at the beginning the statement “You may have heard that women typically do less well at math tests than men, but this is not true for this particular test.”34 Conversely, white male math and engineering majors who received high scores on the math portion of the SAT (a group of people quite confident about their mathematical abilities) did worse on a math test when told the experiment was intended to investigate “why Asians appear to outperform other students on tests of math ability.”35 These types of experiments have been repeated many times in different contexts to test different types of self-discriminatory prejudice.

  Self-discrimination is often self-reinforcing; people perform differently when they are reminded of their group identity, which makes them doubt themselves even more. The same goes for discrimination against other groups. In a now infamous (once famous) experiment in psychology from the 1960s, teachers were tricked into believing one group of their students (a fifth of the class) was gifted and therefore expected to develop much faster than the rest in terms of IQ. In reality, this group was randomly selected and roughly identical to the rest.36 The students for whom teachers had higher expectations gained twelve IQ points over the course of the year, while the rest gained only eight. The original experiment was criticized for a variety of reasons, including the morality of such interventions, but numerous other experiments have shown the power of self-fulfilling prophecies.

  In France, a study of young cashiers in a French grocery store chain, a sizable share of whom were minorities of North African and Sub-Saharan African origin, showed that biased supervisors invested less in the workers they managed.37 The cashiers worked with different supervisors on different days and had virtually no control over their schedule. The study showed that assignment to a supervisor more or less biased against a minority affected the performance of minority and nonminority workers differently. On days when they were scheduled to work with biased supervisors, minority cashiers were more likely to be absent. When they did come to work, they spent less time working; they also scanned items more slowly and took longer to serve the next customer. Such effects were completely absent for nonminority workers. The reason for the lower performance of minority workers when assigned to a biased manager seemed to be not so much overt hostility (minority workers did not report disliking working with biased supervisors more, or that biased supervisors disliked them) as less-effective management. Minority workers reported, for example, that biased supervisors were less likely to come over to their cashier stations and encourage them to perform better.

  Discrimination against women in leadership positions often carries the same flavor of self-fulfilling prophecy. In villages in Malawi, male or female farmers were randomly selected to learn a new technology and teach it to other farmers.38 Women retained more information from the training, and those who were trained by them and listened to them did in fact learn more. But most farmers did not listen. They assumed women were less able, and therefore paid less attention to them. Along the same lines, when women in Bangladesh were trained to become line managers, they were just as good as men based on an objective assessment of their leadership and technical qualities, but they were perceived as less good by their line workers. And, presumably as a result, the performance of their lines also suffered, perversely confirming the prejudice that they were worse managers.39 What started as an unjustified preference against women resulted in women actually doing worse through no fault of their own, and this reinforced their inferior status.

  CAN AFRICAN AMERICANS PLAY GOLF?

  What is strange about these self-fulfilling prophecies is just how predictable they are. It is always a traditionally disadvantaged person who ends up as the victim of a biased, but self-fulfilling prediction; you never hear about white males being systematically underestimated in anything except sports. The bias stems from a stereotype rooted in the social context.

  A study of African American and white Princeton undergraduates shows how deep this runs.40 The students, who had no prior experience of golf, were asked to perform a series of golf exercises of increasing difficulty. In a first experiment, half of them were asked to indicate their race in a questionnaire before they played (the standard way to “prime” race; that is, to bring group identity to the top of the mind), and half were not. All students were then presented the golf exercises as a test of “general sports performance.” When race was not primed, white and black students performed very similarly. But once race was made salient, the fact that golf is a “white” sport (this was before Tiger Woods) made the African Americans worsen their performance and the white students improve theirs, creating a large gap between the two.

  In a second experiment, researchers did not prime race, but instead the students were randomly assigned to one of two treatments.41 In both groups, the instructions said the exercises would become increasingly challenging. In one group, the instructions said the test was designed to measure personal factors correlated with natural athletic ability. Natural athletic ability was defined as “one’s natural ability to perform complex tasks that require hand-eye coordination, such as shooting, throwing, or hitting a ball or other moving objects.” In the other, the same test was presented as measuring “sports intelligence,” or “personal factors correlated with the ability to think strategically during an athletic performance.” In the “natural ability” condition, the African Americans did much better than the whites. In the “sports intelligence” condition, the whi
tes did much better than the African Americans. Everyone, including the blacks themselves, had bought into the stereotype of the African American natural athlete and the white natural strategic player. And this was at Princeton…

  It is hard to square this evidence with the Becker-Stigler construct of coherent and stable preferences. It seems clear that the way the groups thought about themselves (and others) was a product of these largely ephemeral social constructs of “sports intelligence” and “natural ability” and their supposed connection to race.

  ACTING WHITE

  Becker and Stigler want us to stay away from the social context behind preferences, but the social context keeps creeping back in. We have preferences not only about what to eat or where to live, but also about who we should spend time with.

  We avoid people we are suspicious of, move to neighborhoods where there are more of us. In turn, this segregation affects life chances and breeds inequality. When a neighborhood is mostly poor and black it also gets fewer resources, and all of this has lasting influences on the lives of the children who grow up there. When black people moved to white towns in the north between 1915 and 1970, during what is known as the Great Migration, whites moved away, often leaving behind worse schools, declining infrastructure, and fewer job opportunities.42

  These neighborhoods became poorer and more derelict, more crime prone, and less and less conducive to economic success. The chance for a black kid to move from the bottom quintile to the top quintile of the distribution of income is much lower in neighborhoods abandoned by the whites during the Great Migration than in others.43 There are obviously many factors at play, but one of them is that people consciously and unconsciously end up playing by the rules of their neighborhoods. Violence becomes the norm in a neighborhood where it is expected, just as taking five courses when four are required is the norm for MIT undergraduate students.