As any student of policy analysis knows, when we analyze the impact of a real policy on real people, we must look for “unintended consequences,” a kind of backfiring where for some unforeseen reason, the policy hurts those it’s trying to help.
This came up recently in a couple of research papers evaluating the impact of “ban the box,” or BTB, an initiative intended to meet an extremely venerable goal: to help those with criminal records make their way back into the workforce. BTB does so by moving background checks from the beginning of the application process to the end, often after a conditional offer of employment has been extended.
The problem, according to some critics of the policy, is that while BTB might help those with criminal records get their feet in the door, employers without criminal record information will engage in “statistical discrimination.” That is, they’ll discriminate against applicants they believe most likely to have criminal records: young black and Latino men. Based on this dynamic, one author of a critical analysis of BTB concluded that the policy “does more harm than good.”
Not so, and here’s where policy analysts need to be a lot more careful. Are they identifying a problem with the policy or with employer behavior more generally? Especially if it is the latter, are there better ways to address that behavior than policy repeal? Do the policy’s beneficiaries outweigh anyone hurt by unintended consequences?
That’s why a new policy brief from Maurice Emsellem and Beth Avery (E&A) of the National Employment Law Project (disclosure: I chair NELP’s board) is so important. Media reports haven’t done enough to contextualize those studies’ findings and have been too quick to dismiss a policy that, while only a limited part of what’s needed to help disadvantaged individuals get a fair shake in the job market, generally appears to be having its intended effects.
As E&A note, evidence from cities across the United States – from Durham, North Carolina to Washington, DC to Atlanta, Georgia – indicates that ban the box is increasing employment among people with criminal records. The critical studies don’t challenge that claim directly, but, as noted above, argue that employers respond to ban-the-box policies by discriminating broadly against all young black and/or Latino men. But while employer discrimination surely exists, the studies fail to make the case that this is due to BTB.
One study, by Amanda Agan and Sonja Starr, relies on fictitious job applications for young men ages 21-22 submitted to New Jersey and New York employers both “shortly before and after the New York City and New Jersey private sector ban-the-box laws took effect in 2015.” The study found that the gap in callbacks between white applicants and black applicants (whom were given distinctively racial-sounding names) increased following the introduction of ban the box.
But does this prove unintended consequences? For firms that used and then banned the box, black callback rates were about 11 percent before and after the policy change, while white callback rates went up, from around 11 percent to 15 percent. It appears that these results were driven by increased callbacks for applicants with criminal records of both races, as black applicants with records had only an 8.4 percent callback rate and white applicants with records had only an 8.8 percent callback rate prior to the change.
In other words, there were increased callbacks for applicants of both races with records (though more so for whites): a good example of an intended consequence. The NYT also got this wrong, asserting that the paper found that “employers became much less likely to call back any apparently black applicant.”
The other study, from Jennifer Doleac and Benjamin Hanson, compared employment across the United States between metropolitan areas that did and didn’t enact ban the box laws. While the authors found reduced employment for black men without college degrees between the ages of 25 and 34, they also found increased employment for other black workers.
There are also some potentially serious modelling problems with this study. First, the authors consider every worker in an entire metropolitan statistical area (MSA) to be covered by a ban-the-box law “if any jurisdiction in their MSA has a BTB policy.” A BTB law passed in East Palo Alto, CA in January of 2005, for example – a city with around 30,000 people – looks to me like it would have caused the entire San Francisco-Oakland-Hayward, CA MSA, which has a population of closer to 4.7 million, to be considered covered, despite no other jurisdiction within that MSA adopting ban the box until San Francisco did so in October of that year.
What’s more, public-sector-only BTB laws count, and they’re all that’s in place in nearly 80 percent of months the authors examine in MSAs covered in this way (including in the aforementioned California MSA until July of 2013). It’s not clear why we’d expect public-sector BTB laws to affect the hiring behavior of private employers, or the behavior of both public and private employers in neighboring cities and counties that don’t have BTB laws. The authors also neglect to control for local unemployment, which I’d guess matters in a model that predicts employment outcomes.
My conclusion from the studies and the NELP report is that it’s not clear that employer responses to ban-the-box laws are the problem. What is clear, from these and many other studies, is that there are serious discrepancies in job opportunities for people of different races. Those discrepancies have nothing to do with BTB and must be addressed. And if the critics are right—if some employers are actually responding to ban-the-box laws by ramping up statistical discrimination—then they’re doing so in violation of federal civil rights law.
E&A conclude correctly that “a comprehensive policy response is necessary to fundamentally increase job opportunities for people with records and reduce race discrimination in hiring.” That policy response must include ban the box, enforcement of federal civil rights law, policing reforms, prison reforms, education about implicit bias, and a suite of other policies. It takes a village of such policies to achieve economic justice.