Empirical Legal Studies

Atkins' Influence on Death Row Litigation

The Supreme Court's 2002 Atkins decision raised interesting questions amenable to empirical analysis. In An Empirical Look at Atkins vs. Virginia and its Application in Capital Cases, Cornell colleagues (and leading death penalty defense attorneys) John Blume, Sheri Johnson, and Christopher Seeds, publish preliminary results from their look-back study of Atkins' influence. The abstract follows.

"In Atkins vs. Virginia, the Supreme Court declared that evolving standards of decency and the Eighth Amendment prohibit the death penalty for individuals with intellectual disability (formerly, "mental retardation"). Both supporters and opponents of the categorical exemption, however, have criticized the Atkins opinion. The Atkins dissent, for example, urged that the decision would open the gates of litigation to a flood of frivolous claims. Another prominent criticism, heard from those more supportive of the Court's ruling, has been that the language the Court used—communicating that states must 'generally conform' to the clinical definitions of mental retardation—is ambiguous enough to permit states to stray from the clinical definitions and, consequently, for death eligibility to vary depending upon the jurisdiction in which a defendant is charged. This Article presents preliminary data responsive to these issues, and reports three basic findings. First, Atkins has not opened floodgates of non-meritorious litigation. Second, the success rates for Atkins claims vary dramatically between states and state deviations from the clinical definitions appear to have a palpable impact. Third, as compared to their representation on death row, African-American defendants both file and win a disproportionately high number of Atkins claims."

Bias in Spaeth Data?

With a hat tip to the Monkey Cage, I thought folks might be interested in taking a look at this paper.  I know my fellow editor Carolyn has done some research on the Spaeth data as well -- perhaps she'll weigh in on this research?  (FYI, I have not yet read the Harvey/Woodruff paper.)

Placebo Effect

Interesting discussion here.

Judging Women Judges Empirically

Given the public firestorm, it was only a matter of time before now-Associate Justice Sonia Sotomayor’s assertion, uttered prior to her Senate confirmation hearing, that female judges might be “better” than male judges would attract scholarly attention. That time is now, as a recent paper by Stephen Choi (NYU), Mitu Galati (Duke), Mirya Holman (Duke/UNC), and Eric Posner (Chicago), Judging Women, undertakes just such an exploration by exploiting a state and federal judges' dataset. Al Brophy's take on the paper is here. The abstract follows:

"Judge Sonia Sotomayor’s assertion that female judges might be “better” than male judges has generated accusations of sexism and potential bias. An equally controversial claim is that male judges are better than female judges because the latter have benefited from affirmative action. These claims are susceptible to empirical analysis. Primarily using a dataset of all the state high court judges in 1998-2000, we estimate three measures of judicial output: opinion production, outside state citations, and co-partisan disagreements. We find that the male and female judges perform at about the same level. Roughly similar findings show up in data from the U.S. Court of Appeals and the federal district courts."

"Empirical Holy War" -- Eisenberg v. US Chamber of Commerce

Reaction to a recent post on the Wall Street Journal Law Blog (here) makes it clear that my colleague Ted Eisenberg's (Cornell) data-driven critique (forthcoming in JELS) of the US Chamber of Commerce's annual state "rankings" of perceived "lawsuit climate" struck something of a raw nerve. As the WSJ notes, "The Chamber’s Institute for Legal Reform publishes an annual survey,  conducted by the Harris Poll, which ranks states from best to worst, according to how their judges treat class actions, the prevalence of punitive damages, and juries’ “predictability and fairness” among other factors." The WSJ's brief summary of Ted's critique of the survey follows:

"Eisenberg concludes that the survey itself is logically inconsistent. Respondents, for example, he writes, make incorrect conclusion about which states are the most favorable towards punitive damages due to erroneous impressions among the respondents or even misrepresentations of a state’s laws by the Chamber. He says that a state’s movement in the ranking — such as New Jersey’s, which plummeted in one year — could not be validated by a detailed analysis of legal events in the state. Another problem: respondents are given the prior year’s rankings before offering their opinions. This reduces the likelihood that a state could shake an unfavorable image, even if state law there had changed."

Anyone Using Stata v.11 Yet?

Before I finally commit to upgrading to Stata v.11 I'd appreciate any comments (pro or con) from anyone already using it. Major new versions of any software scare me a bit.

New Approaches in Single-Firm Event Studies

The single-firm event study design is a common one in the law and finance and securities litigation research literatures. One challenge to the standard t-statistic-based approach to inference involves a downward bias in asymptotic Type I errors. An interesting paper by Jonah Gelbach (Arizona), Eric Helland (Claremont McKenna College & RAND), and Jonathan Klick (Penn), Valid Inference in Single-Firm, Single-Event Studies, assesses this challenge and compares the standard approach to an alternative with the benefit of real-world data. An excerpted abstract summarizes the paper's findings.

"Our results show that the standard approach is plagued by systematic, downward bias in asymptotic Type I error rates relative to desired significance levels. We then offer a very simple but statistically sound alternative, called the SQ test. We show analytically that the SQ test’s asymptotic Type I error rate always equals the desired significance level. Using our CRSP data, we offer Monte Carlo evidence that in event studies with 99 pre-event observations, the SQ test performs very well at conventional significance levels. We then analyze the asymptotic power of the SQ test and the standard approach. The SQ test and the standard approach have the same size-corrected asymptotic power, which means that even when the standard approach is appropriate, there is no loss to using the SQ test. More relevant as an empirical matter, we show that the standard approach’s downward bias in asymptotic Type I error rates brings along severe power loss. As an empirical matter, then, use of the standard approach can be expected to lead to substantial anti-plaintiff bias in securities litigation, though either pro- or anti-plaintiff bias is possible as an analytical matter. By contrast, the SQ test has considerable asymptotic power, even against moderately sized fixed alternatives."

Funding Opportunity for Litigation Research

Bruce Green (Fordlaw Law) passes along the following announcement:

The ABA Section of Litigation invites applications to The Litigation Research Fund which makes individual awards of $5,000 to support original and practical scholarly work that significantly advances the understanding of civil litigation in the United States.  The Fund was established in 2007 to support research and writing projects relevant to litigation policy and practice, with preference given to works with an empirical foundation.  Projects addressing issues of low-income individuals’ access to civil justice are particularly welcome.

Additional information is available on here.

Training Opportunity: NSF-Funded Political Science and Genetics Methodology Workshop

The National Science Foundation (SES-0921008) is funding training for full, associate, and assistant professors to attend a 5-day workshop offered by the Institute for Behavioral Genetics.  This is a hands-on methods training course, not a lecture or seminar. Every participant will have a laptop provided to share with one other participant, take part in data analyses, develop structural models, and run various statistical packages among many other exercises.  A detailed description of the course can be found at

http://ibgwww.colorado.edu/workshop2008/schedule2008.html

(Note that this page contains the schedule for the last introductory workshop in 2008 -- the final schedule for the 2010 workshop will be posted in the coming weeks.)

Attendees will leave the workshop ready to take part in behavior genetic analyses, and have access to scripts, statistical packages, and training materials to take home (CD) for future use. Space is limited; 17 political scientists will be funded to attend (funding includes travel, lodging, and tuition).

When and Where:

March 2010; TBD (1st or 2nd week), University of Colorado, Boulder

Prerequisites:

There are no prerequisites to apply, but this is a methods training course. It is a hands-on workshop intended to build analytical skills, with a particular focus on family and twin data (2010). The advanced workshop (2011) will focus on molecular data. To get the most out of the course, it is expected that applicants be comfortable with structural modeling or Bayesian techniques, and be trained in basic regression and statistical analyses.

The application form (PDF) is available at:

http://bit.ly/2oe6i

If you have any questions, please contact Prof. Peter Hatemi (phatemi@gmail.com).

CSLS Visiting Scholars Program - UC-Berkeley

Once again, the Center for the Study of Law and Society (CSLS) at UC-Berkeley invites applications for its Visiting Scholars program for the 2010-2011 academic year.  Founded in 1961, the Center "fosters empirical research and theoretical analysis concerning legal institutions, legal processes, legal change, and the social consequences of law." Detailed information for applicants is available at the Center's webpage:

http://www.law.berkeley.edu/1273.htm

While the Center does not offer stipends or financial assistance, I'm hard-pressed to think of a more welcoming, stimulating place to spend a year.