Empirical Legal Studies

An Updated Database of State Tort Law Reforms (7th)

Ronen Avraham (Tel Aviv Univ./Texas) recently alerted me to an update of one of the more helpful resources around for those who study torts and tort reform. Specifically, the Database of State Tort Law Reforms (7.0), seeks to create "one 'canonized' dataset will increase our understanding of tort reform’s impacts on our lives." A fuller (though excerpted) description follows.

"This This manuscript of the DSTLR (7th) updates the DSTLR (6th) and contains the most detailed, complete and comprehensive legal dataset of the most prevalent tort reforms in the United States between 1980 and 2020.... The dataset records state laws in all fifty states and the District of Columbia over the last several decades. For each reform we record the effective date, a short description of the reform, whether or not the jury is allowed to know about the reform, whether the reform was upheld or struck down by the states’ courts, as well as whether it was amended by the state legislator. "

Pretrial Detention and Release Experiments

As I have an admitted soft-spot for (even quasi-) randomized control trials as a research design, a recent paper by Javier Osorio (Arizona-Govt. & Pub Pol’y) et al., Reducing Pretrial Detention: A Randomized Intervention with Public Defenders in El Salvador, caught my eye. In it, the authors exploit a "randomized intervention in El Salvador designed to improve public defenders’ capacities to secure pretrial release for defendants.”

To note that pretrial detention is a problem is to note merely the obvious. And in countries facing acute security challenges, such as El Salvador, there exists enormous pressure on criminal justice authorities to limit pretrial release. The authors contend that the overreliance on pretrial detention is driven in part by lack of information about defendants’ flight risks and the prospect of their committing further crimes while awaiting trial. And this information deficit is “the consequence of deficiencies in the public defender system, upon which economically disadvantaged citizens rely to ensure legal representation.”

To assess their hypothesis, the authors exploit an unusual (by U.S. standards, anyway) experiment involving a randomly assigned treatment to public defenders in four municipalities in El Salvador. “The treatment included specialized legal training, an improved interview protocol, and enhanced communication channels with the defendants, their relatives, and other institutions. These components sought to improve public defenders’ ability to gather evidence that would support pretrial release.”

The authors found that the treatment “increased public defenders’ requests for pretrial release by nearly 10%. The intervention also helped public defenders to secure pretrial release of their clients by 4.4%, although these results are weaker and sensitive to model specification.” The paper's abstract follows.

"Approximately one third of the global prison population is in pretrial detention, waiting for trial. Overreliance on pretrial detention exposes defendants to harsh conditions, exacerbates jail overcrowding, increases recidivism, and favors criminal governance. What policies can resource strapped countries implement to effectively address excessive pretrial detention? Based on a theoretical model focused on institutional-level efforts, we evaluate an experimental intervention implemented in El Salvador intended to increase pretrial release requests and reduce pretrial detention. The intervention randomly assigned public defenders to receive specialized legal training, an improved interview protocol, material resources, and increased communication channels. We find that this inexpensive, scalable program increased pretrial release requests from public defenders by nearly 10% (0.228 standard deviations) and increased the success in securing pretrial release by 4.4% (0.114 standard deviations). Heterogeneous treatment effect analyses suggest that the program increased strategic litigation among the most experienced public defenders and has distinct effects for those accused of minor and severe crimes. We find no evidence that the mechanism explaining our results involves changes in public defenders’ attitudes or perceptions about their work environments. Criminal justice programs focusing on pretrial detention may help reduce prison overcrowding in high crime countries."

Visual Displays of Uncertainty

A recent post on Gelman's Stats blog (by Jessica Hullman) nicely merges a few critical threads. One involves Tufte's classic push to display data in creative and informative ways (see, e.g., Tufte's classic). Another relates to a detectable nudge towards emphasizing results' "uncertainty" rather than a "false" sense of "precision" through, say, point estimates. While Jessica's discussion dwells on election forecast uncertainty--and interesting ways to visually convey it--the basic point includes obvious spill-over implications. As well, even if one is persuaded that visually conveying uncertainty is a worthwhile objective, the question about whether withholding point estimates a good idea is not easily answered.

Ways to Approach (and "Interpret") Null Results

"Null" results are a species of output that remains comparatively under-explored. Or, more accurately, how much analytic weight null results can plausibly bear (and/or how to "interpret" null findings) quickly invite complex questions that frequently derail into other, related lines of inquiry (the very concept of "yes/no" statistical "significance", power testing, etc.) As is often the case, at bottom some level of judgment and discernment is required. This general topic was the subject of a recent StataList discussion (here).

Bringing Data to Firm Successions

It was perhaps inevitable that the popular success of the HBO series, Succession, might, in turn, help stimulate scholarly attention to related associated questions. As it relates to critical questions germane to "family firms'" stock and accounting performances, the general thrust in the academic literature, while mixed, trends in a negative direction. In Do Family Successions (Really) Reduce Firm Performance? Evidence from Large US Firms, Murali Jagannathan (SUNY Binghamton-, management) et al., take a fresh look with the benefit of a large dataset that includes "48,613 firm-years in 3,745 unique firms. Within our dataset, there are 683 total founder or founder-family successions, including 124 instances where the founder was succeeded by a family member.”

Two research design challenges complicate such "family firm" studies. First, the decision to appoint a founding family member as CEO is not random. To address this selection challenge, the paper adopts "an instrumental variables approach using two instruments: whether someone with the same last name as the founder serves on the board within the three-year period preceding the succession, and whether or not the firm has a long history.” Second, systematic firm differences distinguish "founder, founder family, and non-family firms." To adjust, the authors adopt a propensity match strategy to compare "founder family firms with non-founder firms and examine the change in performance around founder successions relative to the matched firms.”

Notably, the paper finds "no significant decreases in either accounting performance or firm value, and instead find evidence that both are improved.” The authors lean on evidence that "family successions are associated with higher levels of employee trust" to help account for their findings. The paper's abstract follows.

"This paper examines whether founder family successions lower performance in large US firms. We find no significant decreases in either accounting performance or firm value, and instead find evidence that both are improved. Consistent with this, we present evidence that family successions are associated with higher levels of employee trust, and that employee’s human capital is not as easily transferable at family firms. Consistent with the literature, we find that the decision to appoint a founder family member as a successor CEO is not random, and occurs in low-growth, yet profitable firms. To mitigate these endogeneity problems, we first propensity match founder family firms with non-founder firms and examine the change in performance around founder successions relative to the matched firms. We also use two instruments of founder family successions in our analysis."