Empirical Legal Studies

2013 Main Workshop on Research Design for Causal Inference

Information on the 4th annual workshop, organized by Bernie Black (Northwestern) and Mat McCubbins (USC), follows. This year's workshop is scheduled for June 24-28, 2013 at Northwestern University Law School. As the workshop enrollment is capped at 100, those interested are encouraged to register sooner rather than later.

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We would like to invite you to attend the fourth (annual) workshop on Research Design for Causal Inference, sponsored by Northwestern University, the University of Southern California, and the Society for Empirical Legal Studies. We have recruited a world-class faculty for the workshop – see below for details.

Bernie Black [Northwestern, Law School and Kellogg School of Management]

Mat McCubbins [USC, Law School, Marshall School of Business, and Political Science Department]

Dates and Location: Monday – Friday, June 24-28, 2013, at Northwestern Law School, Chicago, Illinois.

Registration: information is available here. Registration is limited to 100 participants. We filled up quickly last year, so please register soon. See below for cost and other details.

Overview of the Causal Inference Workshop: Research design for causal inference is at the heart of a “credibility revolution” in empirical research. We will cover the design of true randomized experiments and contrast them to simulations and quasi-experiments, where part of the sample is “treated” in some way, and the remainder is a control group, but the researcher controls neither the assignment of cases to treatment and control groups nor administration of the treatment. We will assess the kinds of causal inferences one can and cannot draw from a research design, threats to valid inference, and research designs that can mitigate those threats.

Most empirical methods courses begin with the methods. They survey how each method works, and what assumptions each relies on. We will begin instead with the goal of causal inference, and discuss how to design research to come closer to that goal. The methods reflect the goal and are often adapted to the needs of a particular study. Some of the methods we will discuss are covered in PhD programs, but rarely in depth, and rarely with a focus on causal inference and on which methods to prefer for messy, real-world datasets with limited sample sizes.

Each day will conclude with a Stata “workshop” where we will illustrate selected methods with real data and Stata code.

Target audience: Quantitative empirical researchers (faculty and graduate students)in social science, including law, political science, economics, many business-school areas (finance, accounting, management, marketing, etc), medicine, sociology, education, psychology, etc. – indeed anywhere that causal inference is important.

Minimum prior knowledge: We will assume knowledge, at the level of an upper-level college econometrics or applied statistics course,of how to run multivariate regressions, including OLS, logit, and probit; familiarity with basic probability and statistics including conditional and compound probabilities, confidence intervals, t-statistics, and standard errors; and some understanding of instrumental variables.

Despite its modest prerequisites, this course should be suitable for most researchers with PhD level training and for empirical legal scholars with reasonable but more limited training. For recent PhD’s, there will be overlap with what you already know, but much that you don’t know, or don’t know as well as you should.

Registration and Workshop Cost

Tuition is $850; with a discounted rate of $500 for graduate students (PhD, SJD, or law) and post-doctoral fellows. The workshop fee includes all materials, a temporary Stata12 license, breakfast, lunch, snacks, and Monday evening reception. All amounts will increase by $50 on April 1, 2013 (but we’re likely to fill up well before then). Registration deadline: June 10, 2013. You can register online at the url above. You can cancel by May 3, 2013 for a 75% refund and by May 31, 2013 for a 50% refund (in each case, less credit card processing fee), but there are no refunds after that.

For Northwestern or USC-affiliated attendees, we will charge the regular rate, but will give you a refund after the workshop to bring your cost down to $300 if you in fact attend at least a majority of the sessions. We adopted this policy because if you register and don’t come, you took a spot we could have provided to someone else.

We know the workshop is not cheap. We use the funds to pay our speakers and for meals and other expenses; we don’t pay ourselves.

Questions about the workshop: Please email Bernie Black ([email protected]) or Mat McCubbins ([email protected]) for substantive questions or fee waiver requests, and Michael Cooper ([email protected] for logistics and registration questions.

Baldy Center Fellowships Information

Information on various Baldy Center Fellowships follows. Please note that applications for the Baldy Fellowships in Interdisciplinary Legal Studies for 2013-2014 are due February 1, 2013. 

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The Baldy Center for Law & Social Policy at the State University of New York at Buffalo plans to award several fellowships for 2013-14 to scholars pursuing important topics in law, legal institutions, and social policy. Applications are invited from junior and senior scholars from law, the humanities, and the social sciences.

Fellows are expected to participate regularly in Baldy Center events, but otherwise have no obligations beyond vigorously pursuing their research. Fellows receive standard university research privileges (access to UB libraries, high-speed Internet, office space, computer equipment, phone, website space, working paper series, etc.) and are encouraged to develop collaborative research projects with SUNY Buffalo faculty members where appropriate. Those who wish to teach a course to aid their research or gain teaching experience will be accommodated on a case-by-case basis.

Post-Doctoral Fellowships are available to individuals who have completed the PhD or JD but have not yet begun a tenure track appointment. Post-Doctoral Fellows will receive a stipend of $40,000 and may apply for up to $2000 in professional travel support.

Mid-Career and Senior Fellowships are available as sabbatical supplements to established scholars who wish to work at the Center. Stipends will be commensurate with experience, need, and duration of visit.

Application materials include: (1) a description of the planned research (question, conceptual framework, method, possible findings, importance to the field), (2) a complete academic and professional resume, (3) an academic writing sample, and (4) the names and contact information of three academic references. Applications should be submitted no later than February 1, 2013. The application can be found on our website at: http://law.buffalo.edu/baldycenter

Additional questions about the Baldy Fellows Program should be addressed to Assistant Director Laura Wirth, [email protected] or 1-716-645-2581.

The Baldy Center for Law & Social Policy is an endowed, internationally recognized institute that advances interdisciplinary research on law, legal institutions, and social policy at the State University of New York at Buffalo. More than 150 faculty members from numerous SUNY Buffalo departments participate in Baldy Center research, conferences, consortia, and publications. The Center maintains cooperative ties to other research centers and hosts distinguished scholars from around the world as visitors, fellows, speakers, and conference participants.

Postestimation: Margins & Marginsplot in Stata

A helpful recent addition to the Stata archive of tutorial videos involves the "margins" and "marginsplot" postestimation commands. This particular video example illustrates how to graph predictions from a linear regression model with an interaction between continuous and categorical covariates.

Kahan on National Research Council critique of multivariate regression

Dan Kahan, Professor of Law and Psychology at Yale, has two posts (so far) up at the Cultural Cognition Project blog about the uses and abuses of multivariate regression in particular and empirical research more generally.  He takes as his jumping-off point two analyses by the National Research Council -- one, from 2004, about whether concealed-carry laws increase or decrease gun violence and another, from 2012, about whether the death penalty increases murder rates (presumably through deterrence) or decreases them through "a cultural 'brutalization effect.'" In both of these analyses, the NRC panels conclude that the many studies relying multivariate regression to try to tease out the effects of the relevant laws are simply useless.  The problem that the NRC finds in both sitautions is that the outcomes of these analyses depend on model specification and on the underlying assumptions of those models. 

Kahan then goes on to discuss the ways that opinion leaders rely on such studies when they support their policy views and dismiss them -- often on the very basis that, as the NRC explains, they are inherently inconclusive -- when they do not.  Likewise, ordinary people, perhaps relying on this "opportunitistic" use of scientific research, often believe that scientific consensus supports their own world-views or policy preferences even when it does not or even when scientific consensus does not exist.

Kahan hardly dismisses the usefulness of empirical research, however.  In his second post, he explains:

But I do have an idea (a conviction, in fact) about the sensible way to make sense of empirical evidence. It's that it should be evaluated not as "proving" things but as supplying more or less reason to believe one thing or another. So when one is presented with empirical evidence, one shouldn't say either "yes, game over!" or "pfffff ... what about this that & the other thing..." but rather should supplement & adjust what one believes, and how confidently, after reflecting on the evidence for a long enough time to truly understand why it supports a particular infernece and how strongly.

These posts raise important and interesting questions for empirical scholars of law and policy, who are rarely, if ever, able to rely on controlled experimental conditions, and for the consumers of their work.  See the previous post on this very blog for a related discussion.

Should We Expect Expectation Effects?

An interesting discussion recently emerged (here and here) of a study comparing two agricultural experiments (involving different seeds of cowpeas to farmers in Tanzania) -- one blinded, one unblinded. As Andrew Gelman (Columbia) notes: "Bulte et al. find much different results in the two experiments and attribute the difference to expectation effects (when people know they’re receiving an experiment they behave differently); Ozler is skeptical and attributes the different outcomes to various practical differences in implementation of the two experiments."