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" 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. "

― Abhijit V. Banerjee , Good Economics for Hard Times: Better Answers to Our Biggest Problems

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Abhijit V. Banerjee quote : 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.
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