We examine a controversial process, known as expungement, which allows brokers to remove evidence of financial misconduct from public records. From 2007 to 2016, we identify 6660 expungement requests, suggesting that brokers attempt to expunge 12% of the allegations of misconduct reported by customers and firms. When these requests are adjudicated on the merits, arbitrators approve expungement 84% of the time. We show that expungements significantly predict future misconduct; brokers with prior expungements are 3.3 times as likely to engage in new misconduct as the average broker. Further, using an instrumental variable based on the random assignment of arbitrators, we present evidence that brokers who receive expungement are more likely to reoffend than brokers who are denied expungement. We also show that successful expungements improve long-term career prospects.
This paper studies the design of education policy in an optimal non-linear tax model with asymmetric information. It shows that both heterogeneity in ability and risky human capital investment (or the combination of the two) can provide a theoretical justification for government intervention in education. The sign of the optimal policy is exclusively determined by the Hicksian coefficient of complementarity. Specifically, when education increases (decreases) exposure to risk, or equivalently, when the wage elasticity of education is increasing (decreasing) in ability, the optimal policy is to tax (subsidise) education. But when heterogeneity and risk are combined, the sign of the optimal policy is indeterminate. Numerical results suggest that the magnitude of the optimal policy will depend on the strength of the insurance and redistributive motives. Income-contingent loans or educationdependent taxes and subsidies can implement the optimum.