Wiley-Online-Library: Journal of Empirical Legal Studies: Table of Contents

Sentencing in the Shadow of Promotion: The Impacts of Circuit Court Nomination on Federal Judges

Nicholas Goldrosen — Sun, 07 Jun 2026 17:08:35 -0700

ABSTRACT

Judges seek to maximize their own utility, like everyone else. Their goals include job security and promotion. Federal judges lack the electoral incentives that often drive state judges, but they could audition for promotion. I test whether they audition for promotion in their criminal sentencing. Using criminal sentences imposed in the federal courts from 2006 to 2023, I find that federal judges who are eventually nominated to a higher court hand down longer sentences than their other “contender” peers, though this effect is moderated by the judicial district. This effect is a mixture of judicial behavior and a selection effect—judges are promoted for a variety of other reasons, many of which may be correlated with criminal sentencing. While there is no across-the-board evidence of judicial auditioning during vacancies, there is evidence of judicial auditioning for some judges under some presidents. This behavior, though, ends at nomination: an event-study design finds that the announcement of a nomination has no substantive effect on the nominee's sentencing. These results show that, despite the different structure of the federal judiciary from state courts, strategic rationality on the part of judges may also shape federal criminal sentencing.

A New Source of Data on Class Action Settlements: The Department of Justice's Class Action Fairness Act Log

Brian T. Fitzpatrick — Fri, 05 Jun 2026 22:04:15 -0700

ABSTRACT

Studies of class action settlements have been notoriously difficult because of the logistical burden of assembling datasets from district court orders. This is especially true for non-securities settlements. Moreover, even when they have been undertaken, they have been of unknown representativeness. Yet, since the enactment of the Class Action Fairness Act of 2005 (“CAFA”), defendants have been required to send a notice to the United States Department of Justice every time they settled a class action, lest the settlement not be binding. These notices therefore have the potential to overcome many of the challenges and limitations of past catalogs of settlements. This paper is the first to assess the efficacy of the Department's CAFA notices to study class action settlements. Using Freedom of Information Act requests, I obtained a log the Department keeps of CAFA notices. Although the log contains thousands of entries and many more settlements per year than any prior dataset, I find that the log is unpredictably incomplete. This is especially apparent for securities class actions, but appears to be true of non-securities class actions as well. As such, the log will not improve the representativeness of class action settlement studies. But the log will mitigate the logistical burden of creating datasets and therefore should improve the frequency of settlement studies.

Randomly Albright: The End of Judge Shopping in the Western District of Texas?

Christian Helmers, Bernhard Ganglmair, Brian J. Love — Mon, 01 Jun 2026 17:11:08 -0700

ABSTRACT

Because judges exercise discretion in how they handle and decide cases, heterogeneity across judges can affect case outcomes and, thus, preferences among litigants for particular judges. However, selection obscures the causal mechanisms that drive these preferences. We overcome this challenge by studying the introduction of random case assignment in a venue (the U.S. District Court for the Western District of Texas) that previously experienced a high degree of case concentration before one judge (Alan Albright), whom litigants could select with virtual certainty. To assess Albright's importance to patent enforcers, we examine how case filing patterns changed following the adoption of random case allocation and show that case filings in the Western District of Texas decreased significantly at both the intensive and extensive margins. Moreover, to shed light on why litigants prefer Judge Albright, we compare case management metrics and motions practice across randomly assigned cases and show that cases assigned to Albright received relatively early trial dates and generated fewer motions to stay pending parallel administrative invalidity proceedings and fewer motions to invalidate patents on subject matter eligibility grounds.

In Memoriam: Marc Galanter

Jeffrey Rachlinski — Sun, 31 May 2026 18:05:32 -0700

Journal of Empirical Legal Studies, EarlyView.

Issue Information

Wed, 13 May 2026 21:48:43 -0700

Journal of Empirical Legal Studies, Volume 23, Issue 2, Page 157-159, June 2026.

Sentence Variability in a Mathematical Sentencing Framework: A Statistical Analysis of Brazilian Court Data

Wed, 13 May 2026 21:48:43 -0700

ABSTRACT

This article presents the findings of a quantitative study on sentencing practices in Brazil, focusing on the presence of numerical patterns and “penal clustering” in judicial decisions. Drawing on a dataset of criminal sentences from São Paulo—the country's most populous and active judiciary—the research statistically investigates whether Brazilian judges display preferences for certain sentence lengths, such as even numbers, “round numbers,” and multiples of 6 months. The study also examines the role of numerical fractions in shaping sentence variability. Despite Brazil's civil law tradition and the absence of formal sentencing guidelines, the results reveal a significant degree of penal clustering, with judges consistently relying on a narrow set of sentencing values. These patterns suggest the influence of cognitive heuristics, particularly “anchoring effects,” in sentencing decisions. While the use of numerical fractions may enhance consistency and predictability, it may also constrain individualization—raising concerns about mechanical decision-making and reduced responsiveness to case-specific circumstances. The article discusses the implications of these findings for judicial training, institutional reform, and public policy. It argues for a more data-informed and psychologically aware approach to sentencing, capable of balancing the dual demands of consistency and individualization within both common law and civil law traditions.

Patents and Supra‐Competitive Prices: Evidence From Consumer Products

Gaétan de Rassenfosse, Ling Zhou — Wed, 13 May 2026 21:48:43 -0700

ABSTRACT

A patent system is a central tool in innovation policy. The prospect of monopolistic pricing supposedly encourages firms to innovate. However, there is scant empirical evidence supporting the existence of higher markups for patent-protected products. Using an original dataset that links consumer products to the patents that protect them, we study the impact of patent protection on product prices. Exploiting exogenous variations in patent status, we find that a loss of patent protection leads to an 8%–10% drop in product prices. The price drop is larger for more important patents and is more pronounced in more competitive product markets.

Can Disclaimers of Affiliation Dispel Trademark Confusion? Evidence From Two Randomized Experiments

Barton Beebe, Roy Germano, Joel Steckel — Wed, 13 May 2026 21:48:43 -0700

ABSTRACT

Legal scholars and courts have long viewed disclaimers of affiliation as an ineffective tool for dispelling trademark confusion. We revisit this debate with new evidence from two randomized experiments. Consistent with earlier research, we find that disclaimers alone do not dispel consumer confusion. Our experiments show, however, that simply requiring consumers to register their recognition of a disclaimer can reduce confusion to levels that most courts would consider negligible. We tested two disclaimer acknowledgment tasks in an online shopping context: a burdensome task in which participants were required to retype the text of the disclaimer before they could continue with the study and a much simpler task in which participants were required to click a box affirming that they read and understood the disclaimer in order to continue. The tasks were similarly effective in lowering the probability of confusion to levels below the threshold that would typically trigger a finding of likelihood of confusion.

A Survey of Preferences for Estate Distribution at Death

John Morley, Yair Listokin — Wed, 13 May 2026 21:48:43 -0700

ABSTRACT

What do you want to do with your property when you die? This paper presents the results of a survey in which we asked this question to a nationally representative sample of 9000 American adults. We gathered data on respondents' families and then asked them how they would like to divide their property among those they leave behind. We find that people are more ambivalent about gifts to spouses and more generous to nonmarital partners than the law of intestacy generally assumes. People also give less to parents and more to siblings, extended relatives, and friends than expected and much more to stepchildren than expected. We find some significant differences by race, class, and gender, with women, African Americans, and people of less income and education preferring to give less to their spouses. Our findings improve upon empirical studies of probated wills by providing an unbiased sample, by including data on demographic characteristics, and by observing the preferences of people in unconventional families. We suggest that although intestacy law is often said to implement majoritarian preferences, it may be more consistent with a mix of majoritarianism, paternalism, and administrative efficiency.

An Assessment of Racial Disparities in Pretrial Decision‐Making Using Misclassification Models

Kimberly A. Hochstedler Webb, Sarah A. Riley, Martin T. Wells — Wed, 13 May 2026 21:48:43 -0700

ABSTRACT

Pretrial risk assessment tools are used in jurisdictions across the country to assess the likelihood of “pretrial failure,” the event where defendants either fail to appear (FTA) for court or reoffend. Judicial officers, in turn, use these assessments to determine whether to release or detain defendants during trial. While algorithmic risk assessment tools were designed to predict pretrial failure with greater accuracy relative to judges, there is still concern that both risk assessment recommendations and pretrial decisions are biased against minority groups. We use the Virginia Pretrial Risk Assessment Instrument (VPRAI) as a case study to investigate the accuracy and fairness of risk assessment algorithms and judicial decisions. In this paper, we develop methods to investigate the association between risk factors and pretrial failure, while simultaneously estimating misclassification rates of pretrial risk assessments and of judicial decisions as a function of defendant race. This approach adds to a growing literature that makes use of outcome misclassification methods to answer questions about fairness in pretrial decision-making. We give a detailed simulation study for our proposed methodology and apply these methods to data from the Virginia Department of Criminal Justice Services. We estimate that the VPRAI algorithm has near-perfect specificity, but its sensitivity differs by defendant race. Judicial decisions also display evidence of bias; we estimate wrongful detention rates of 39.7% and 51.4% among white and Black defendants, respectively.

Crime, Punishment, and Expectations

Mohammad H. Rahmati, David A. Hyman — Wed, 13 May 2026 21:48:43 -0700

ABSTRACT

Crime doesn't pay. Or does it? We study the role of expectations regarding sanctions and the likelihood of detection on whether people obey the law. We examine how expectations influence whether people obey the law and conduct simulations of various enforcement counterfactuals. We find the average assessment of the likelihood of detection is reasonably accurate, but those who (mistakenly) believe the probability is lower than it is are much more likely to break the law. Further, expectations with regard to the likely consequences of getting caught are also heterogeneous. In our simulations, perceived fines have little impact on willingness to break the law, but a higher perceived likelihood of apprehension has an appreciable impact. Because marginal respondents are pivotal in the rate of law-breaking, debiasing expectations among the whole population has little impact.