Empirical Legal Studies

CELS 2014 Paper Submission Deadline--Extended

Anne O'Connell (Berkeley) and Eric Talley (Berkeley) have extended the CELS 2014 paper submission deadline to Tuesday, July 22, 2014, 11:59 PM (PDT).

To submit a paper for consideration, please click on SSRN's CELS 2014 submission page (here). (Do not use the "regular" SSRN paper submission system.)

The 9th Annual Conference on Empirical Legal Studies, sponsored by the Society for Empirical Legal Studies (SELS), will be hosted by UC Berkeley School of Law and take place on Nov. 7-8, 2014.

"p-Hacking" Data

While "p-hacking" is likely more prevalent in certain fields (e.g., psychology) and with experimental (rather than observational) data, such manipulations are becoming increasingly common and pose a real challenge to social science. Excerpts from an interesting post by Jerry Adler (commentary from Althouse here) summarize:

"In 2011, a psychologist named Joseph P. Simmons and two colleagues set out to use real experimental data to prove an impossible hypothesis. Not merely improbable or surprising, but downright ridiculous. The hypothesis: that listening to The Beatles’ “When I’m Sixty-Four” makes people younger. The method: Recruit a small sample of undergraduates to listen to either The Beatles song or one of two other tracks, then administer a questionnaire asking for a number of random and irrelevant facts and opinions—their parents’ ages, their restaurant preferences, the name of a Canadian football quarterback, and so on. The result: By strategically arranging their data and carefully wording their findings, the psychologists “proved” that randomly selected people who hear “When I’m Sixty-Four” are, in fact, younger than people who don’t."

The authors of the "When I'm Sixty-Four" paper "draw attention to a glaring problem with modern scientific protocol: Between the laboratory and the published study lies a gap that must be bridged by the laborious process of data analysis. As Simmons and his co-authors showed, this process is a virtual black box that, as currently constructed, ‘allows presenting anything as significant.’ And if you can prove anything you want from your data, what, if anything, do you really know?”

Bringing Data to the Student Loan Crisis Debate

Debates about the student loan crisis rightly concern higher education in general as well as law schools in particular. Much of the growing public debate on has been framed as follows: "College tuition and student debt levels have been increasing at a fast pace for at least two decades.  These well-documented trends, coupled with an economy weakened by a major recession, have raised serious questions about whether the market for student debt is headed for a crisis, with many borrowers unable to repay their loans and taxpayers being forced to foot the bill."

In a Brookings Institution research report, Is A Student Loan Crisis on the Horizon?, Beth Akers and Matthew Chingos bring helpful data to this public debate. Specifically, they "draw on data from the Survey of Consumer Finances (SCF) administered by the Federal Reserve Board to track how the education debt levels and incomes of young households evolved between 1989 and 2010." After analyzing more than two decades of data on the financial well-being of American households the authors find that "in reality, the impact of student loans may not be as dire as many commentators fear." (For a summary of the report, click here.) While not the last word on the topic, the data are a welcome addition.

Judges, Daughters, and "Feminist" Outcomes

Adam Glynn (Harvard, Govt.) and Maya Sen (Rochester, Poli-Sci) explore judicial decisions and find that male judges with daughters "consistently vote in a more feminist fashion on gender issues than judges who have only sons." Not surprisingly, the paper, Identifying Judicial Empathy: Does Having Daughters Cause Judges to Rule For Women's Issues?, has attracted media attention (here).

"In this paper, we ask whether personal relationships can affect the way that judges decide cases. To do so, we leverage the natural experiment of a child's gender to identify the effect of having daughters on the votes of judges. Using new data on the family lives of U.S. Courts of Appeals judges, we find that, conditional on the number of children a judge has, judges with daughters consistently vote in a more feminist fashion on gender issues than judges who have only sons. This result survives a number of robustness tests and appears to be driven primarily by Republican judges. More broadly, this result demonstrates that personal experiences influence how judges make decisions, and it is the first paper to show that empathy may indeed be a component in how judges decide cases."

Penn State Law and Dickinson Law Formally Split

I'm happy to report that Penn State's Dickinson School of Law has received formal approval from the ABA to operate two independent and fully accredited law schools: Penn State Law at University Park and Dickinson Law in Carlisle, PA. From the press release:

"Degrees and diplomas from the two law schools will be in the name of The Dickinson School of Law of The Pennsylvania State University but will clearly reflect their independent and separately accredited status.  Both campuses will refer to their affiliation with Penn State, but in general the Carlisle campus will be known as Dickinson Law and the University Park campus will be known as Penn State Law."

One take on the future of the two institutions in the wake of the split is here.

Kudos to interim dean Jim Hauck and his team for shepherding this through.

More on Conceal-Carry (or "Right-To-Carry") Gun Laws

The academic (and public) debate on the impact of conceal-carry laws on crime rates persists. In 2004, the National Research Council ("NRC") evaluated the "More Guns, Less Crime" hypothesis. In The Impact of Right to Carry Laws and the NRC Report: The Latest Lessons for the Empirical Evaluation of Law and Policy, Abhay Aneja (Stanford), John Donohue (Stanford), and Alexandria Zhang (Johns Hopkins) re-analyze and expand the NRC study. An excerpted abstract follows.

"We evaluate the NRC evidence, and improve and expand on the report’s county data analysis by analyzing an additional six years of county data as well as state panel data for the period 1979-2010. We also present evidence using both a more plausible version of the Lott and Mustard specification, as well as our own preferred specification (which, unlike the Lott and Mustard model presented in the NRC report, does control for rates of incarceration and police). While we have considerable sympathy with the NRC’s majority view about the difficulty of drawing conclusions from simple panel data models and re-affirm its finding that the conclusion of the dissenting panel member that RTC ["Right-To-Carry"] laws reduce murder has no statistical support, we disagree with the NRC report’s judgment on one methodological point: the NRC report states that cluster adjustments to correct for serial correlation are not needed in these panel data regressions, but our randomization tests show that without such adjustments the Type 1 error soars to 22-73 percent."

"Empirical Legal Studies"

A while back, I was asked to write the entry for "empirical legal studies" that will be included in the Second Edition of Oxford's International Encyclopedia of the Social & Behavioral Sciences. I've (finally!) completed a draft, a copy of which is here (non-SSRN link). I'd love to hear feedback and suggestions for additions or changes.

Patently Empirical

Understanding the Realities of Modern Patent Litigation, by John Allison (Texas), Mark Lemley (Stanford), and David Schwartz (Chicago-Kent), supplies a "comprehensive picture of the outcomes of modern patent litigation." The paper updates and expands upon prior work by coding "all substantive decisions rendered by any court in every patent case filed in 2008 and 2009 -- decisions made between 2009 and 2013." The study evaluates patent validity as well as infringement and unenforceability claims. Interestingly, the paper notes "a surprising amount of continuity in the basic outcomes of patent lawsuits over the past twenty years, despite rather dramatic changes in who brought patent suits during that time."

While the data only include litigation filed in 2008 and 2009 and the analyses only involve cases that persisted to the dispositive motion or trial stages (most lawsuits settle before this), the paper will certainly interest those seeking an empirical footing in patent litigation.

Understanding Output

An interesting thread, stimulated by a manuscript reviewer's confusion with a paper's conflating "correlation" with the slope in a regression estimation. The posted question prompted a very helpful response that, among other things, deftly explains ANOVA's presence in standard regression output.

"Analysis of variance (ANOVA) is just a technique comparing the variance explained by the model versus the variance not explained by the model. Since regression models have both the explained and unexplained component, it's natural that ANOVA can be applied to them. In many software packages, ANOVA results are routinely reported with linear regression."