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 resumes. 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 resume.
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 resume, 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 shares 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.