A large and growing literature has documented the importance of peer effects in education. However, there is relatively little evidence on the long-run educational and labor market consequences of childhood peers. We examine this question by linking administrative data on elementary school students to subsequent test scores, college attendance and completion, and earnings. To distinguish the effect of peers from confounding factors, we exploit the population variation in the proportion of children from families linked to domestic violence, who have been shown to disrupt contemporaneous behavior and learning. Results show that exposure to a disruptive peer in classes of 25 during elementary school reduces earnings at age 24 to 28 by 3 percent. We estimate that differential exposure to children linked to domestic violence explains 5 percent of the rich-poor earnings gap in our data, and that each year of exposure to a disruptive peer reduces the present discounted value of classmates’ future earnings by $80,000.

We use unique data from journal submissions to identify and unpack publication bias and p-hacking. We find initial submissions display significant bunching, suggesting the distribution among published statistics cannot be fully attributed to a publication bias in peer review. Desk-rejected manuscripts display greater heaping than those sent for review; i.e., marginally significant results are more likely to be desk rejected. Reviewer recommendations, in contrast, are positively associated with statistical significance. Overall, the peer review process has little effect on the distribution of test statistics. Lastly, we track rejected papers and present evidence that the prevalence of publication biases is perhaps not as prominent as feared.