Every Monday, the National Bureau of Economic Research, a nonprofit organization made up of some of North America’s most respected economists, releases its latest batch of working papers. The papers aren’t peer-reviewed, so their conclusions are preliminary (and occasionally flat-out wrong). But they offer an early peek into some of the research that will shape economic thinking in the years ahead. Here are a few of this week’s most interesting papers.
Title: “Leveling Up: Early Results from a Randomized Evaluation of Post-Secondary Aid”
Authors: Joshua Angrist, David Autor, Sally Hudson, Amanda Pallais
What they found: Financial aid increased college attendance and completion for students from disadvantaged groups, including the non-white, those with low ACT scores and those who preferred less-selective four-year colleges.
Why it matters: The U.S. spends a lot of money on college financial aid, but researchers are unsure if or how it helps students attend and complete college. This is because of selection bias — the possibility that the students who apply for financial aid, or those who receive aid awards, might have other characteristics that play a more important role in their college success. To correct for selection bias, the researchers behind this paper were able to award more than 2,000 scholarships by random assignment. The randomized study was administered through one of the largest private aid programs in the country, the Susan Thompson Buffett Foundation’s scholarship program, which gives awards to attend public colleges in Nebraska. Overall, the financial aid packages increased the share of students matriculating at four-year colleges by nearly 8 percent. Furthermore, groups with historically low “persistence” rates (that is, those who have a hard time finishing college) saw even bigger gains when receiving aid. These groups included non-white college applicants, students with low academic achievement in high school, and students who signaled interest only in the less-selective four-year colleges.
Key quote: “We find a remarkable 20-plus point gain in four-year enrollment for nonwhite applicants and for those with ACT scores below the state median. Persistence effects were also larger for male applicants and students with low high school GPAs. On balance, STBF scholarships substantially equalized enrollment and persistence rates across groups, enabling students with low expected persistence to ‘level up’ with their traditionally college-bound peers. In contrast, applicants who targeted community colleges were largely unaffected by STBF awards.”
Data they used: Records of students applying to the Susan Thompson Buffet Foundation scholarship program, as well as their subsequent college records
Title: “The Fluidity of Race: ‘Passing’ in the United States, 1880-1940”
Authors: Emily Nix, Nancy Qian
What they found: Race “passing” was widespread: Almost 1 in 5 black men “passed” for white in the U.S. between the years after the Civil War and before World War II. In changing their self-reported race to white, they were more likely to relocate to “whiter” locations and to “pass” when the income gap between whites and blacks was large.
Why it matters: Race matters for economic outcomes. Economists know that; but often the underlying assumption is that race or ethnicity is fixed. Yet growing historical research casts doubt on such thinking. To better link the effect of race on economic outcomes, the impact of race change must be quantified. The researchers behind this paper investigate and quantify “passing” — the anecdotal notion of someone with African ancestry being identified as white. To do this, individual census records were linked over decades to track how racial identification had changed. Between 1880 and 1940, more than 19 percent of black men “passed” for white at some point in their life. But not all passing was permanent: Of those who did pass, about 10 percent “reversed passed” back to identifying as black in the following census year. The amount of passing was associated with the political and economic incentives to do so, such as a large white-black income gap.
Key quote: “Consistent with the anecdotal and historical evidence, passing was accompanied by geographic relocation to ‘whiter’ communities; reverse passing was common and accompanied by relocation to ‘blacker’ communities. The latter supports the historical evidence that many individuals crossed back and forth from black to white and white to black. Thus, race is not a fixed characteristic over an individual’s lifetime.”
Data they used: Digitized U.S. census data of men between 1880 and 1940 from the North Atlantic Population Project
Title: “Does Delay Cause Decay? The Effect of Administrative Decision Time on the Labor Force Participation and Earnings of Disability Applicants”
Authors: David H. Autor, Nicole Maestas, Kathleen J. Mullen, Alexander Strand
What they found: The reduced employment prospects (and earnings) of individuals applying for Social Security Disability Insurance (SSDI) is twice as high as previous studies suggest. That is because of an unaccounted for channel: the delayed processing of an SSDI application.
Why it matters: Lots of research has shown how receiving SSDI has negative effects on an individual’s employment prospects and lifetime earnings. But to date, these effects were examined only in the context of applicants being accepted or rejected by the Social Security Administration (SSA). This paper finds that another channel is nearly as important: the delayed processing of the SSDI application. Exploiting the fact that SSA disability examiners (who are assigned applications randomly) vary enormously in the time they take to decide on an application, researchers found a huge impact from this “delay” channel. (While their application is being processed, applicants cannot earn more than $1,000 per month.) A one standard-deviation increase in processing time (or waiting 2.1 months longer) reduced an applicant’s long-run annual earnings by 5.1 percent and lowered overall employment rates by a percentage point. Combing the “benefits receipt” channel (that is, getting SSDI) with the “delay” channel (waiting on the SSA), the overall negative impact on SSDI applicants’ economic fortunes amounts to double that of previous studies.
Key quote: “The estimated effect of SSDI receipt on employment ignoring processing time implies that the SSDI program reduces employment by 9 points in the short run and 5.5 points in the long run, among the subset of applicants on the margin of SSDI receipt. However, in this paper we estimate that this effect is closer to 22 points in the short run and 11 points in the long run accounting for processing time. That is, combining the labor supply decay effect, estimated for the first time in this paper, with new estimates of the benefit receipt effect that are purged of waiting time bias implies that the SSDI program effect on employment is 105 to 150 percent larger than previous estimates have suggested for applicants on the margin of SSDI receipt.”
Data they used: Disability Operational Data Store, an SSA workload database used to identify the varying processing speed of disability examiners