The English rule prescribes that the loser of a lawsuit pays the winner's litigation costs. Previous research on the English rule finds that plaintiffs win more often at trial, receive higher awards, and receive larger settlements. Theory predicts that the English rule discourages settlement by raising the threshold payment necessary for settlement. In this paper, we reexamine the Florida experiment with the English rule by placing bounds on the selection effects. We find that the mean and median settlement amount increases. Collectively these findings are consistent with the predictions of the simplest models of the English rule's impact.

We propose methods to estimate and make inferences on conditional quantile processes for models with both nonparametric and (locally or globally) linear components. We derive their asymptotic properties, optimal bandwidths, and uniform confidence bands over quantiles allowing for robust bias correction. Our framework covers the sharp regression discontinuity design, which is used to study the effects of unemployment insurance benefits extensions, focusing on heterogeneity over quantiles and covariates. We show economically strong effects in the tails of the outcome distribution. They reduce the within-group inequality, but can be viewed as enhancing between-group inequality, although they help to bridge the gender gap.