Empirical Legal Studies

Empirically Assessing Iqbal & Twombly

The Supreme Court's Iqbal and Twombly decisions triggered important civil pleading policy changes. Not surprisingly, the decisions ignited significant scholarly attention to them and hypotheses about their likely effects. Important empirical scholarship has also emerged and many of these empirical inquiries uncover an array of complicated methodological issues, including various selection effects, as well as various strategies and research designs to address them. In Can We Learn Anything About Pleading Changes From Existing Data?, Jonah Gelbach (Penn) responds to critiques of his earlier work on this topic. The abstract follows.

"In light of the gateway role that the pleading standard can play in our civil litigation system, measuring the empirical effects of pleading policy changes embodied in the Supreme Court's controversial Twombly and Iqbal cases is important. In my earlier paper, Locking the Doors to Discovery, I argued that in doing so, special care is required in formulating the object of empirical study. Taking party behavior seriously, as Locking the Doors does, leads to empirical results suggesting that Twombly and Iqbal have had substantial effects among cases that face Rule 12(b)(6) motions post-Iqbal. This paper responds to potentially important critiques of my empirical implementation made by the FJC's Joe Cecil and Professor David Engstrom. An additional contribution of the present paper is to elucidate some important challenges for empirical work in civil procedure. First, researchers should carefully consider which covariates belong in statistical models, while also taking care in assessing the empirical importance of controlling for covariates. Second, data collection protocols should be designed with behavioral assumptions in mind. But third, researchers should not let the perfect be the enemy of the good: even data protocols that are less than perfectly designed may be broadly useful."

Empirical Methods in Law (2nd ed., 2016)

Many who teach empirical methods in law schools struggle with identifying satisfactory course materials (casebooks, textbooks, statistical packages, supplemental reading, etc.). For most, the decision on how to structure and teach the class often drives decisions on course materials. On the casebook front, the first edition (2010) of Empirical Methods in Law, co-edited by Robert Lawless, Jennifer Robbennolt, and Thomas Ulen (all at Illinois), enriched the small but growing number of available options. The Lawless et al.'s 2nd edition (2016) improves an already strong casebook.

Lawless, Robbennolt, and Ulen’s Empirical Methods in Law (2^nd ed., 2016) “brings the basic principles and concepts of social-science research to the desks of law students and lawyers who expect to work with data experts. Now available in a second edition, the updated text continues its focus on explaining basic principles and concepts in an intuitive style requiring no prior knowledge of math or statistics. The text also continues its emphasis on the importance of research design as well as statistical methods.” The second edition’s features include:

• "Available in softcover and competitively priced, making the book accessible either as a principal course text or as a supplemental text.
• An extensive online set of resources: Teachers Manual, PowerPoint slides, problems, example datasets, bibliography, glossary of terms.
• Broad perspectives from three authors from three different methodological traditions that results in a presentation of general best practices.
• Generous use of examples from the legal world that show how empirical techniques are applied in a range of substantive legal areas.
• Coverage of topics often overlooked in the research process such as data coding or communication of results."

Finally, as legal education's costs continues to rise, the casebook's move to a less expensive softcover and promise for "competitive" pricing joins a welcome (and much-needed) trend in casebook publishing.

Hands-On Educational Modules for Professional/Graduate Students

Joe Cecil at the Federal Judicial Center altered me to an interesting on-going project, sponsored by the National Academies of Sciences, Engineering, and Medicine's Committee on Science, Technology, and Law (CSTL). The CSTL has overseen the development of a series of educational modules that seek to elucidate the role of science in policy decision-making, “with a particular emphasis on scientific and statistical methods of inference.” Access to existing modules (with more promised in the future) is here. Click here for an introductory overview of the project.

2016 Journal of Law, Finance, and Accounting Conference--Submission Extension

The Journal of Law, Finance, and Accounting’s (JLFA) fourth conference, to be held at Northwestern Law School, 375 East Chicago Avenue, is scheduled for Friday, November 11th and Saturday, November 12th, 2016, ending by mid-afternoon on Saturday. The Conference’s Call For Papers deadline has been extended to July 18, 2016. Click here for information about JLFA; click here for submission information.

CELS 2016 -- Call For Papers Extension [New Deadline: 31 July 2016]

As previously mentioned (here), CELS 2016 will be held at Duke University Law School, in Durham, NC, on Nov. 18-19, 2016. To better accommodate summer research/writing schedules that vary across departments, schools, universities, and, in particular, nations, conference organizers have extended the Call for Papers deadline to: July 31, 2016. Click here for paper submission information.

What To Legally Infer From Statistical Disparities

Once the empirics are locked down, ELS scholars then typically turn to the legal implications of their empirical findings. In an interesting essay, Statistical Inequality and Intentional (Not Implicit) Discrimination, Michael Selmi (GWU) engages with the issue that while "not all statistical disparities are the product of discrimination but some are, and central to achieving greater racial equality will be determining how we can tell the difference--how we know when an observed statistical disparity should be equated with discrimination?" Two specific contexts frame Selmi's discussion: police automobile stops and school discipline.

Troubling racial disparities, according to Selmi, likely produce "one of three responses, what I will refer to as (1) 'Yes but . . . ,' (2) 'Racism is everywhere,' and (3) 'Tell me more.' Those in the 'yes but' category are discrimination skeptics who resist concluding that discrimination underlies the observed inequities and they seek alternative explanations. Those in the second group see discrimination everywhere there are disparities and may go so far as to cast racial aspersions on those in the first group. The third group wants to know more about the inequities, wants to know more about why wage gaps persist even at the highest levels, or why affluent African Americans tend to live in neighborhoods that are less affluent than their white cohorts.” In the end, Selmi "urges policymakers to treat repeated patterns of behavior as intentional, as opposed to implicit, discrimination, and offers a critique of the recent turn to implicit bias."