Empirical Legal Studies

Small 'Add-Ons' to Stata Graphs

While graphics in Stata can be a pain, sometimes quick coding suggestions can help modify traditionally "standard" presentations in small ways that add clarity and, thus, value. For example, those with experience with quartile-box plots might appreciate a discussion (here) about the code needed to add marker labels indicating the value scores at the 25th, 50th, and 75th percentiles. (The example below illustrates this modification.)

Replication & (Law &) Psychology

While the current (or, candidly, any) replication crisis should give all empirical scholars pause, much of the attention (rightly or wrongly) focuses on psychology (and, by implication in the ELS world, law & psychology). While what explains the current focus on psychology is not entirely clear, in a blog post (here) Andrew Gelman (Columbia--statistics) offers a few reasons. One quick take-away, however, is that at least some of Gelman's reasons are neither necessarily nor structurally limited to psychology. Moreover, the first sentence in Gelman's post underscores another important point: The replication crisis is a "big deal" and one that warrants careful and sustained attention.

HLS's Access To Justice Lab

A while back, we posted information on a proposed idea at Harvard Law School that was seeking to "staff-up" (here). I am delighted to report that the "idea" has now launched as an up-and-running program--Harvard Law School's Access to Justice Lab. According to Research Director Chris Griffin, the Lab, affiliated with HLS's Center on the Legal Profession, is a "venture for developing evidence-based solutions to problems of court administration and legal services provision. Our goal is to understand, using randomized control trials, what methods truly enhance engagement with and efficiency in the system." The Lab's mission includes: "combat[ing] resistance among the bench and bar to rigorous empirical thinking about the U.S. legal system, and to study it using the gold standard of randomized field experiments." Those interested in learning more about the Lab and its work should visit its website, follow on Facebook or Twitter, or subscribe to the blog.

Revisiting Data on Seat Belt Laws' Efficacy

Conventional wisdom--and many legislative histories--imply that seat belt laws help to reduce automobile accident-related deaths. In a recent paper, Do Seat Belt Law Still Work? Replication and Re-Evaluation of Recent Evidence, Sam Harper (McGill) and Erin Strumpf (McGill) set out to replicate, refine, and extend existing empirical work. Drawing on US traffic fatality data from 2001-10, the authors findings' do not support conventional wisdom. The paper's abstract follows.

"Recent work suggests that mandatory seatbelt laws are associated with lower motor vehicle accident mortality, but it is unclear whether this is due to increased enforcement. We study this association using 2001-2010 US data on traffic fatalities among individuals ages 10 and over and we test the robustness of unstated assumptions by replicating and extending prior work. Using Poisson regression adjusted for state-level traffic safety policies (seat belt laws, blood alcohol laws, speed limits), miles traveled, and median income, we replicate the covariate-adjusted association seen in prior work (Rate Ratio [RR]=0.80, 95%CI 0.74,0.87). Further adjustment for state and time fixed effects showed no evidence of a causal effect (RR=1.00, 95%CI 0.95,1.06). We find little evidence that seatbelt laws reduce traffic fatalities, and prior work was confounded by general improvements in other environmental determinants of motor vehicle accident mortality. Replications studies have the potential to increase the integrity of research findings."

Publication Bias & A Call For Replications

In an interesting move, the Journal of Law and Courts is "opening its pages to most types of replications, successful or unsuccessful." In its Call For Replications, JLC's editors recognize that journals' traditional "emphasis on novelty means that a replication study has almost no chance of being published unless the replication fails and the failure can be presented as persuasive evidence for an alternative theory." While excluding "successful direct replications, employing the same data and models as the original study," the editors welcome any study that asks whether "findings in one domain extend to another domain or can be replicated using different measures or models."