Empirical Legal Studies

Data on Testacy and Intestacy in Florida

Filtered by my admitted soft spot for scholars who engage in the hard, unglamorous, and often under-appreciated tasks incident to data creation/collection, a recent paper taking an initial descriptive cut at some archival probate data caught my eye. In The Demographics of Intergenerational Transmission of Wealth: An Empirical Study of Testacy and Intestacy on Family Property, Danaya Wright (Florida), recognizing that "[e]veryone dies eventually, and the vast majority of us will die owning at least some property," digs into probate record archives to assess various trends. Exploiting all (N=408) estates that went through court-supervised probate in Alachua County (FL) in 2013, the paper focuses on such variables as wealth, age, number of children, race, sex and marital status, with an eye toward potential systematic differences between testate (293) and intestate (115) decedents. The paper reports "clear differences between testate and intestate decedents on the basis of race, sex, wealth, marital status, age, and even children, with testacy correlating to significantly more wealth than intestacy."

Appropriately mindful of data and research design limitations, the paper also conveys a welcome level of cautiousness and modesty in terms of its ability to scaffold firm conclusions. After all, the data used in the paper draw from one year (2013) in a single county in one state (FL). As well, while the paper benefits from all of estates submitted to probate, most (77.3%) of the deaths in Alachua County in 2013 did not trigger probate or were probated elsewhere. While important external validity and selection effects' questions linger, the paper nonetheless illustrates the scholarly potential of exploiting data that too often remain "hidden in plain sight." The paper's abstract follows.

“In this article, I analyze many of the differences between testate and intestate decedents and suggest areas of concern for law- and policy-makers, as well as practicing lawyers and financial planners. Identifying the right demographic at risk for wealth deterioration may allow for interventions that can slow or reverse the widening wealth gap and ultimately help the next few generations build economically stable lives. To that end, I discuss how a number of demographic differences (wealth, age, race, sex, and marital status) affect the downward trajectory of certain groups and the upward trajectory of others.”

Recent Update for User-Writen "stripplot"

"Longer-time" Stata users may recall (and have used) a user-written graphics command, stripplot. Old and new Stata users, however, should be aware that the stripplot command was recently updated and expanded to allow users to "compare distributions and a variety of displays is possible, including linear and stacked dot and strip plots, with in conjunction box plots or confidence intervals." To illustrate some possibilities, consider, e.g.,:

This facilitates, e.g., a side-by-side display of quantile plots combined with horizontal reference lines for means. For those interested, install with the ssc command. For more information, and examples, click here.

Data on Police Conduct and Civilian Oversight

Among the myriad of ideas for reforming police currently under debate, many call for greater oversight of police conduct in ways that increase civilian participation. Whether increased civilian oversight will generate the desired reductions in police misconduct without chilling effective policing, however, remains under-studied.

A recent paper by Kyle Rozema (Wash U) and Max Schanzenbch (Northwestern), Does Discipline Decrease Police Misconduct? Evidence from Chicago Civilian Allegations, makes a helpful contribution to the empirical void. Exploiting 1990-2015 officer-level data from Chicago, the paper implements "an officer-level event study to investigate how officer misconduct changes after a civilian allegation of misconduct is sustained." To this end the paper, presented at the 2019 CELS, implements a stacked event study approach to investigate how "officer misconduct changes after a civilian allegation of misconduct is sustained" and considers three possible mechanisms: (police) incapacitation, shirking, and improved conduct. What the authors find is that: "In terms of mechanisms, we found no evidence that this effect results from incapacitation, such as desk duty assignment, and no evidence that it results from chilling effective policing. Even though sustained allegations result in negligible suspensions, we found evidence that a sustained allegation has a detrimental impact on promotion and pay. We interpret the results as most consistent with improved officer conduct driven by specific or marginal deterrence. Consequently, our findings suggest that sustaining the marginal allegation will improve police conduct without affecting overall police effectiveness." The paper's abstract follows.

“Reformers are calling for greater oversight of police behavior, in part through enhanced use of civilian complaints. However, others counter that greater oversight could chill effective policing. We assess police officer response to administrative determinations of misconduct. Using Chicago data, we find strong evidence that a sustained allegation reduces that officer’s future misconduct. We find no evidence that this effect is driven by incapacitation, such as assignment to desk duty, or by officer disengagement with policing. We conclude that our findings are consistent with improved officer conduct, in part due to officer concerns over promotion, salary, and desirable assignments.”

Evidence of More Revolving Doors

"Revolving doors," evidently, are everywhere. While in a few sectors (e.g., financial regulators/financial services industries) research on revolving doors is well-developed, empirical research in other sectors is less so. The latter sectors include, e.g., an individual's path from a Supreme Court clerkship, to an appellate litigation group, and then back to the Supreme Court as an advocate. While "hunches" about this "revolving door" have persisted over time, data on former clerks' efficacy arguing in front of their former bosses remain scant. A recent paper, The Influence of Personalized Knowledge at the Supreme Court: How (Some) Former Law Clerks Have the Inside Track, exploits decisions in the Supreme Court Database between the 1979 and 2018 Terms and contributes to this data void. In their paper, political scientists Ryan Black (Mich. St.) and Ryan Owens (Wisc.) find evidence of an effect as the following figure implies.

The paper's abstract, summarizing core results, follows.

"When arguing at the U.S. Supreme Court, former High Court law clerks enjoy significant influence over their former justices. Our analysis of forty years of judicial votes reveals that an attorney who formerly clerked for a justice is 16 percent more likely to capture that justice’s vote than an otherwise identical attorney who never clerked. What is more, an attorney who formerly clerked for a justice is 14 to 16 percent more likely to capture that justice’s vote than an otherwise identical attorney who previously clerked for a different justice. Former clerk influence is substantial, targeted, and appears to come from clerks’ personalized information about their justices. These results answer an important empirical question about the role of attorneys while raising normative concerns over fairness in litigation."

Evidence of a "Non-Revolving" Door

For years commentators have warned about a "revolving door" involving the SEC and the industry sector that it regulates. Much of the attention to such a revolving door, however, has overlooked one specific "side-door": namely, “[j]oining a plaintiffs’ side securities litigation firm would seem to be an appealing option for SEC attorneys looking to continue pursuing the same core mission of protecting investors and holding companies accountable for fraud and misconduct.” In a recent paper, The Non-Revolving Door, Alexander Platt (Kansas) argues that "the door between the SEC and the plaintiffs’ bar does not revolve."

To be sure, a few factors limit the results' scope. For example, the paper focuses on only a small number of leading plaintiffs' side law firms, a few SEC attorney roster years, and descriptive analyses. Any limitations notwithstanding, however, the results will likely interest securities law scholars. An excerpted abstract follows.

"This paper shows that the door between the SEC and the plaintiffs’ bar does not revolve. Among other things, I show that none of the ten leading plaintiffs’-side firms employ anyone with recent SEC experience doing plaintiffs’ side litigation; none of the enforcement attorneys I identified as working for the agency in 2015 left to do plaintiffs’ side litigation; none of the current upper- and middle-managers in the SEC’s enforcement division have any prior plaintiffs’ side experience; and only five of the enforcement attorneys I identified as working for the agency in 2019 had prior plaintiffs’ side experience.

This 'non-revolving door' between the SEC and the plaintiffs bar is an intriguing, overlooked feature of the securities enforcement in the United States. Among other things, it raises the prospect that SEC attorneys might have come to embrace the defense bar’s hostile and skeptical view of the social value of securities class action litigation, with significant consequences for the securities enforcement landscape."

Data on "Young Adult" Criminal Sentencing Experiments

As greater attention is paid to variation in cognitive development, especially across "younger" adults, criminal justice responses are almost inevitable. One such example involves an ongoing experiment in the Netherlands where, since 2014, legislation now allows courts to sentence young adults (ages 18 to 22, inclusive) under either juvenile or adult sentencing guidelines. The underling idea motivating this experiment is that some "young adult" offenders are less mature than others and, as such, may benefit more from the comparatively more "pedagogically oriented" juvenile sanctions than from adult sanctions that emphasize deterrence. In a recent paper, Characteristics of Young Adults Sentenced with Juvenile Sanctions in the Netherlands, Lise Prop (Govt. of the Netherlands) et al., exploit data on 583 criminal cases involving young adults to gain some initial empirical footing about whether and, if so, how the sub-pool of young adult criminals sentenced under juvenile guidelines differ from young adults sentenced under the adult guidelines.

Overall, results from their cross-sectional study find that characteristics indicating "maturation" problems across different domains were "more prevalent among young adults sentenced with juvenile sanctions" and, accordingly, provide some initial descriptive support for the impulse to treat young adult offenders differently when it comes to sentencing. The paper's abstract follows.

"Since 1 April 2014, young adults aged 18 up to and including 22 years can be sentenced with juvenile sanctions in the Netherlands. This legislation is referred to as ‘adolescent criminal law’ (ACL). An important reason for the special treatment of young adults is their over-representation in crime. The underlying idea of ACL is that some young adult offenders are less mature than others. These young adults may benefit more from pedagogically oriented juvenile sanctions than from the deterrent focus of adult sanctions. Little is known, however, about the characteristics of the young adults sentenced with juvenile sanctions since the implementation of ACL. The aim of this study is to gain insight into the demographic, criminogenic and criminal case characteristics of young adult offenders sentenced with juvenile sanctions in the first year after the implementation of ACL. A cross-sectional study was conducted using a juvenile sanction group and an adult sanction group. Data on 583 criminal cases of young adults, sanctioned from 1 April 2014 up to March 2015, were included. Data were obtained from the Public Prosecution Service, the Dutch Probation Service and Statistics Netherlands. The results showed that characteristics indicating problems across different domains were more prevalent among young adults sentenced with juvenile sanctions. Furthermore, these young adults committed a greater number of serious offences compared with young adults who were sentenced with adult sanctions. The findings of this study provide support for the special treatment of young adult offenders in criminal law as intended by ACL."

Comparing Coefficients in Different Regression Models

Prompted by a question (here) on Statalist relating to efforts to compare (with a TTest) whether coefficients in two separate regression models systematically differ I stumbled upon the suest command. With the suest command, one can, e.g., regress one model, store its results, regress a second model, store its results, and then compare them with the test command. "This will yield a chi2 statistic with 1 degree of freedom. You can run this for each variable." This will help one assess whether the coefficients are the same in each regression model or not. For a very helpful (and brief) video tutorial, click here.

Kicking "Problem" Cops "Down the Road"?

Recent public attention to police departments reminded me of a draft paper I saw a few months ago, The Wandering Officer, that, since then, has appeared in print in the Yale Law Journal (click here). What the paper's authors, Ben Grunwald (Duke) and John Rappaport (Chicago), mean by a "wandering" officer is an officer fired by one department, sometimes for serious misconduct, who then finds employment as a sworn law enforcement officer at another agency. While the potential problems posed by "wandering" officers are obvious, less obvious within the criminal justice community, however, is the extent, character, and magnitude of the "wandering" officer phenomenon itself.

The paper digs into this phenomenon and with the benefit of a large data set from Florida identifies some broad, basic descriptive contours. The data set draws on "128,616 full-time law-enforcement job stints that spanned at least one day between 1988 and 2016; they correspond to 98,169 unique officers." While through 1998 officers under investigation were frequently allowed to "resign" before any involuntary termination, following 1998 the data set identifies those officers who resigned “'in lieu of separation' or 'while being investigated' for misconduct." The paper's three core findings are described in the excerpted abstract, below.

"... We report three principal findings. First, in any given year during our study, an average of just under 1,100 officers who were previously fired—three percent of all officers in the State—worked for Florida agencies. Second, officers who were fired from their last job seem to face difficulty finding work. When they do, it takes them a long time, and they tend to move to smaller agencies with fewer resources in areas with slightly larger communities of color. Interestingly, though, this pattern does not hold for officers who were fired earlier in their careers. Third, wandering officers are more likely than both officers hired as rookies and those hired as veterans who have never been fired to be fired from their next job or to receive a complaint for a “moral character violation.” Although we cannot determine the precise reasons for the firings, these results suggest that wandering officers may pose serious risks, particularly given how difficult it is to fire a police officer. We consider several plausible explanations for why departments nonetheless hire wandering officers and suggest potential policy responses to each."

"Younger" Federal Judges & Executive Power

While modeling judicial decisions--especially for federal judges--is not a terribly new endeavor, a recent paper in the Journal of Law and Economics (2020), Younger Federal District Court Judges Favor Presidential Power, caught my eye. In it, the authors, Tom Campbell (Chapman) and Nathaniel Wilcox (Chapman--economics), assess how federal judges' votes on challenges to assertions of executive power evolve over a judge's life cycle. And they do so with an eye toward federal district court judges' potential appetite for judicial "promotion."

Drawing on district court opinions spanning from 1960 to 2015, what the authors find is that “The probability that district judges favor the executive (statistically) significantly increases with the hazard for elevation (and so declines with age) for all specifications with that regressor. Moreover, the estimated average marginal effects show that the estimated size of the effect is highly robust to the particular specification: in about one of every five cases, 50-year-old judges appear to rule differently than 65-year-old judges.” The paper's abstract follows.

"From 1960 to 2015, opinions of US federal district court judges (trial judges) in cases involving challenges to executive branch authority show that these judges favor executive authority less as they age. We suggest that district judges know that elevation to the federal circuit court of appeals becomes increasingly improbable, and hence have less reason to cooperate with the executive, with advancing age. Political variables, seniority of judges, and other variables introduced as extra regressors do not reverse this main result, nor does it appear to be the product of cohort effects or selection off the district court. When there are contemporaneous vacancies on their circuit courts, district judges in the 11 state circuits (but not the District of Columbia Circuit) are also more likely to favor the executive."

"Quick-and-Dirty" Codebooks

While it's difficult to over-state the importance--indeed, necessity--of an accurate, readable codebook, what is also true is that they can be a "pain" to generate (especially if one waits until the very end of a project). Stata can generate a "bare-bones," though perfectly serviceable, codebook with relatively little effort. A helpful "how-to" is included in this discussion (here).

Impacts on Firms From Joining the S&P 500 Index

For those whose financial portfolios include investments in low-cost index funds, most assume that companies benefit from inclusion in the leading indexes, such as the S&P 500. As a recent paper, Does Joining the S&P 500 Index Hurt Firms?, by Benjamin Bennett (Tulane) et al., notes, being added to the index is like "joining a prestigious club. A firm gains prestige by joining the club, but at the cost of becoming compared to other firms in the club."

To better assess the costs and benefits, the paper executes "difference-in-differences (DiD) analyses based on S&P 500 index addition. Specifically, we first identify all S&P 500 additions in our sample period. Added firms are our treated firms. For each treated firm, we search for a control firm that is never a member of the S&P 500 index in our sample period and use a propensity-score match on total assets, Tobin’s q, stock return, and 2-digit SIC industry (exact match) in the year before a treated firm is added to the index, so that the matching process is not affected by index additions." The main findings are summarized in the paper's abstract.

“We investigate the impact on firms of joining the S&P 500 index from 1997 to 2017. We find that the positive announcement effect on the stock price of index inclusion has disappeared and the long-run impact of index inclusion has become negative. Inclusion worsens stock price informativeness and some aspects of governance. Compensation, investment, and financial policies change with index inclusion. For instance, payout policies of firms joining the index become more similar to the policies of their index peers. ROA falls following inclusion. There is no evidence of an impact of inclusion on competition.”

Testing a "Ratio Problem" in Finance Scholarship

On the heels of a recent post (here) describing a Stata regression command tailored to the unique needs of a dependent variable that takes the form of a ratio/percentage/fraction, comes a recent paper that explores potential problems with finance papers that model ratios. Potentially compounding the problem is that ratios as dependents variables are certainly not uncommon in the finance literature (see, e.g., papers featuring Tobin's Q). In The Ratio Problem, Robert Bartlett (Berkeley) and Frank Partnoy (Berkeley) frame the ratio "problem" in terms of two challenges–omitted variable and measurement error bias–"that arise anytime a researcher uses linear regression to estimate a production function that has a ratio as an output." As the paper notes, "In theory, the [ratio] denominator is not necessarily problematic; in practice, however, there are statistical concerns whenever the output of a production function is a ratio." The paper's abstract follows.

“We use the term ‘ratio problem’ to describe the omitted variable and measurement error bias that can arise when a ratio is the dependent variable in an economic model. First, we show how bias can arise from the omission of two classes of variables based on a ratio’s denominator. As an example, we demonstrate that the widely-cited ‘inverse U’ relationship between managerial ownership and Tobin’s Q is reversed when these variables are included. Second, we show how measurement error in the ratio’s denominator can produce bias. We provide empirical tests and solutions, and urge caution about ratios as dependent variables.”

Modeling Rates/Fractions/Percentages

While I probably should have mentioned this when Stata's (relatively) new and quite helpful "fracreg" command was released, a recent surge of student questions about how to best model a rate (or fractional) dependent variable motivates this post.

Periodically ELS scholars will need (or want) to model a defendant variable that is bounded between zero and one (e.g., rates, fractions, percentages, etc.). Until recently few satisfactory options (at least "off-the-shelf" ones) existed as the various standard "reg" commands are inapt given the rate/fractional/percentage dependent variable's bounded structure. The "fracreg" command in Stata, however, is designed for dependent variables that range from zero to one (inclusive). Anyone intrigued should consult the user manual (here) and watch a brief introductory tutorial video (here).

Descriptive Analyses of Hidden Legal "Corners": Lone Pine Orders

While an increasingly important mass tort litigation mainstay since their creation in 1986, "Lone Pine" orders remain in relative scholarly obscurity. In Lone Pine Orders: A Critical Examination and Empirical Analysis, Nora F. Engstrom (Stanford) and Amos Espeland (Stanford-grad student) set out to "pull back the curtain." They do just that as it relates to Lone Pine orders in a brief essay and, in so doing, their paper demonstrates, once again, how the creation of new original data sets, combined with basic descriptive analyses, can add helpful information. The paper's abstract follows.

"Invented in 1986 and now a prominent feature of the mass tort landscape, Lone Pine orders require plaintiffs to provide to the court prima facie evidence of injury, exposure, and specific causation — sometimes early, and usually on pain of dismissal. Though they’ve taken root in a hazy space outside of the Federal Rules of Civil Procedure, these case management orders are frequently issued, and they play an important role in the contemporary litigation and resolution of mass torts. But although Lone Pine orders are common, potent, and increasingly controversial, they have mostly fallen under the academic radar. Even their key features are described inconsistently by commentators and courts. This Essay pulls back the curtain. Drawing on a unique hand-coded data set, this Essay describes the origin and evolution of Lone Pine orders, sketches poles of the debate surrounding their use, and offers empirical evidence regarding their entry, content, timing, and effect."

Comparing "predicted probabilities" and "odds ratios"

Those who use the logistic as well as the margin commands (and both are quite common in ELS) sometimes confront the question of whether to report out odds ratios (from the logistic command) or the predicted probabilities (from the margin command). As one commentator notes in this Stata list discussion (here), "An odds [ratio] is related but not the same as a probability. They are related in the sense that both are ways of quantifying how likely an event (success) is. They differ in that the "odds [ratio] is the average number of success per failure. The probability is the average number of successes per trial." What is the more intuitive of the two will, of course, vary across people.