I'm seeing increased discussion of the comparative advantages (and disadvantages) of "Bayesian versus 'frequentist'" approaches toward inference. A recent post by Andrew Gelman (here), and the comments it triggered, illustrate.
A recent Statalist discussion (here) includes a helpful illustration of how to execute and understand margins output (as well as common mistakes). As well, Richard Williams (Notre Dame--Sociology) hosts a webpage that includes a rich array of resources, including an extremely helpful PowerPoint discussion of the margins command (see "Selected other highlights" at the bottom of the page).
In recent years, various countries have started the process of establishing behavioral insight teams ("BIT") that will advise the government on usage of knowledge from psychology and behavioral economics. Both the UK and U.S. governments rely increasingly on insights from behavioral sciences, especially with regard to non-deliberative choice by individuals. The EU, a comparative late-comer to this game, has recently established a task force, which published a guideline report, describing how policy makers should use psychology when implementing behaviorally based legal policy in various areas.
In the last year, I have been to a few meetings with academics and practitioners who are involved in BIT in the U.K, U.S., and Israel as well as the EU, which made me wonder about the missing role of ELS in what seems to be an emerging regulatory trend. Moreover, in the first BIT international conference which will take place in London in September, there is a highly impressive roaster of some of the world's leading psychologists and behavioral economists, but with the exception of references to the work of Cass Sunstein, I didn’t recognize any scholars associated with ELS or even with any law school.
One might have thought that the BIT which is, by definition, an evidence-based approach to law-making could have become a natural hub for empirical legal studies. Many of their recommendations are built on very intense field experiments, which lie at the heart of some of the work done by ELS scholars. It might be the case that simply by path dependency ELS scholars are late to a new party and hence I am not discussing here anything which is sustainable, nonetheless, there is a chance that this might tell us something about both ELS and BIT.
The first point is highly related to the argument regarding the role of legal theory, I have discussed in this blog few weeks ago, based on the work of Dagan et al. and Fishman, on the role of legal theory in ELS. Presumably one might argue that without legal theory, ELS might lose some of their advantage relative to psychology and economics. Indeed, much of the previous discussion around the "nudge" approach came from legal theorists and philosophers and not from ELS scholars. Furthermore, as I also mentioned in a previous post, when legal theory is missing many in the social sciences might feel that methodology-wise their line of research is more technically advanced.
Looking at this question from the reverse perspective, I wonder whether it makes sense that the scholars who are involved in BIT initiatives should care about issues such as fairness, autonomy, liberalism and paternalism, and instrument choice or institutional constrains. I tend to believe that they should and that, in the long-run, as BIT will evolve, the need for ELS involvement will prove helpful to the success of these projects. I hope that with greater theoretical interest and interaction between the two communities, both will bring to the table their relative advantages and create a more coherent research paradigm which would allow behavioral knowledge a proper integration with state efforts to modify human behavior.
The first international workshop for junior empirical legal scholars will be held on December 17th and 18th 2015, at the Hebrew University of Jerusalem. The meeting is co-sponsored by the Society of Empirical Legal Studies (SELS) and The Center for Empirical Studies of Decision Making and the Law.
The workshop aims to foster the research of scholars who have recently completed their PhD or have recently been appointed to a tenure track position, by providing them with a forum in which they can present their research and receive feedback from fellow empirical researchers. Approximately ten scholars from around the world (submission criteria specified below) will be invited to the workshop. Each scholar will be assigned a commentator who will discuss their paper. The rigorous academic environment at the workshop will assist junior scholars to develop their ideas. The workshop is also intended to establish a sense of community among empirical legal scholars and help build cooperative relationships between participants.
Topics: Papers may touch on any legal field and can employ any empirical methodology.
Participation Criteria: To be eligible, an author must be an untenured faculty member at a research university in a tenure-track position; or a tenured faculty member if it has been less than five years since the initial entry level appointment; or a full time post-doctoral fellow or a visiting associate professor at a research university. In addition, the committee will consider the work of authors who do not fit these criteria, but are new to the field of empirical legal studies.
Travel: The costs of airfare (coach) and accommodations of authors who will be invited to participate in the workshop will be covered by the Center for Empirical Studies of Decision Making and the Law.
Paper Submission: Submissions should be sent to Ms. Ayelet Gordon (email@example.com) with the subject line: “Workshop for Junior Empirical-Legal Scholars.”
The deadline for submission is June 30th, 2015. Only drafts of complete papers will be considered.
Program Committee: David Abrams – University of Pennsylvania Law School Bernie Black – Northwestern University School of Law Valarie Hans – Cornell Law School Doron Teichman - Hebrew University Keren Weinshall-Margel - Hebrew University Eyal Zamir - Hebrew University
A fascinating paper exploring the effect of partition on violence does a wonderful job illustrating how creative efforts (and rich data) can potentially dampen (though not eliminate) endogeneity concerns. In Which Side Are You On? Political Violence and Partition in Ireland 1920-1921, Elissa Berwick (MIT--Poli Sci) analyzes a quasi-natural experiment produced by the partition of Ireland in 1921. Exploiting a truly unique data set, Berwick finds that "although partition decreased violence against civilians on Northern Ireland's side of the border as compared to the Irish Free State side, violence against civilians in the border areas as a whole significantly increased."
Along with her interesting findings Berwick's research design also warrants note, especially on how it addresses endogeneity concerns. As Berwick concedes, "Partition is usually provoked by conflict, and yet its effect on conflict is the outcome of interest." Notwithstanding this tension, however, Berwick goes on to observe that:
"As for endogeneity, the initial proposal of partition came from a backbench Liberal in June 1914, years before the start of any violent civil conflict. Although the partition itself occurred in a context of civil war, its original justification was not to end conflict between northern Protestants and southern Catholics. Instead, British legislators were concerned by their inability to coerce Northern Unionists, a point driven home by the Curragh Mutiny of March 1914, in which the British Army refused to disarm the Ulster Volunteer militia. Thus the partition of Ireland was not intended to separate two sides, but instead to forestall action by a minority."
While whether Berwick's methodological optimism is warranted, of course, requires further study, her transparent and helpful discussion of the issue deserves praise.
Andrew Gelman (Columbia--Statistics) notes (here) that among statistics' three essential elements, "measurement, comparison, and variation," measurement receives short shrift. Why?
"Part of it is surely that measurement takes effort, and we have other demands on our time. But it’s more than that. I think a large part is that we don’t carefully think about evaluation as a measurement issue and we’re not clear on what we want students to learn and how we can measure this." To this I would add one additional practical aspect. For those conducting secondary analyses of data sets put together by others, most typically defer to measurement decisions already baked into data sets.
Regardless, when measurement goes awry, measurement error emerges and bad things happen.
As previously mentioned, CELS 2015 will be held at Washington University Law School, in St. Louis, on Oct. 30-13, 2015. Conference organizers, Adam Badawi, Rebecca Hollander-Blumoff, and Pauline Kim recently announced the Call for Papers (here). Please note the June 26, 2015, submission deadline.
A small but interesting wrinkle. Many data sets include cases with missing data (hopefully not too many) and these cases will be excluded from many regression specifications. When "describing" the data set, does one use all of the cases (including those cases excluded from regression analyses) or just those cases included in the regression? If it's the latter, is there an easy way to generate basic summary statistics for the non-excluded cases? (The answer to the final question is "yes," and a helpful explanation--and illustrations--can be found here.)