Empirical Legal Studies

Baldy Fellowships in Interdisciplinary Legal Studies, 2015-16 -- Call For Applications

Those intrigued by either a Post-Doctoral Fellowship or a Mid-Career or Senior Fellowship at the Baldy Center for Law & Social Policy at SUNY Buffalo need to apply by Mon., Feb. 2, 2015. (Application information here.)

Sponsored by Baldy Center for Law & Social Policy, the Center "plans to award several fellowships for 2015-16 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 university 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 can be accommodated on a case-by-case basis."

Plotting Marginal Effects

Just came across a neat user-created Stata  command, mcp, that can transform marginal effects' results into intuitive graphs. An extremely helpful description (and brief tutorial) is found here. A more technical description from the Stata manual follows.

"marginscontplot [mcp] provides a graph of the marginal effect of a continuous predictor on the response variable in the most recently fit regression model. When only xvar1 is provided, the plot of marginal effects is univariate at values of xvar1 specified by the at1() or var1() option.  When both xvar1 and xvar2 are provided, the plot of marginal effects is against values of xvar1 specified by the at1() or var1() option for fixed values of xvar2 specified by the at2() or var2() option.  A line is plotted for each specified value of xvar2.

marginscontplot has the distinctive ability to plot marginal effects on the original scale of xvar1 or xvar2, even when the model includes transformed values of xvar1 or xvar2 but does not include xvar1 or xvar2 themselves.  Such a situation arises in models involving simple transformations such as logs and more complicated transformations such as fractional polynomials or splines, for example, where nonlinear relationships with continuous predictors are to be approximated.  Transformed covariates are included in the model to achieve this."

Policing, Race, and Criminal Law Data

While "everyone agrees that there are enormous racial gaps in U.S. rates of stops, arrests, searches, and use of force," Sonja Starr (Michigan) observes that explanations for why this is so both vary and conflict. According to Starr, it is not simply data shortcomings that complicate efforts to study the intersection of policing and race, but also confusion about "what questions we should be asking." In Explaining Race Gaps in Policing: Normative and Empirical Challenges, Starr engages these issues. An excerpted abstract follows.

"The Article gives particular attention to how researchers should address two important research questions. The first is whether criminal conduct differences explain policing disparities. Empirical researchers as well as casual commentators typically purport to address this question either by comparing racial groups’ shares of police interactions to their shares of crime, or by comparing two groups’ ratio of police interactions to their ratio of crimes. Using examples and mathematical proofs, I show that neither of these comparison types answers the key question whether people with like criminal conduct are being treated the same way. These comparisons generally overcorrect for racial differences in criminal conduct, misleadingly masking the size (or even reversing the apparent direction) of disparities in policing of people with the same conduct. Second, I examine how researchers should investigate the effects of racial discrimination — a morally important and legally central question, but one that poses serious causal inference challenges. I review several methods in the current literature, which offer useful insights but have substantial limitations, and critique the recently dominant “hit-rate” approach, which relies on faulty normative and empirical premises. Instead, I propose supplementing existing tools with a new approach: the use of 'testers.'"

The Supreme Court Database

A recent thread on a listserv prompts this reminder about the availability of a leading Supreme Court database that traces its roots back to Prof. Harold Spaeth's pioneering efforts from a few decades ago.

“The Supreme Court Database is the definitive source for researchers, students, journalists, and citizens interested in the U.S. Supreme Court. The Database contains over two hundred pieces of information about each case decided by the Court between the 1946 and 2013 terms. Examples include the identity of the court whose decision the Supreme Court reviewed, the parties to the suit, the legal provisions considered in the case, and the votes of the Justices.”

The database includes "both Case Centered and Justice Centered data. In the Case Centered data the unit of analysis is the case; i.e., each row of the dataset contains information about an individual dispute. These data should be used unless the votes of the individual justices are of interest. The Justice Centered data include a row for each justice participating in each dispute."

An online codebook (here) and a brief history of the database (here) by Harold Spaeth accompany the database.

Wash U's 2015 "Conducting Empirical Legal Scholarship" Workshop

Wash U's Center for Empirical Legal Research in the Law will host it's 14th annual Conducting Empirical Legal Scholarship Workshop on June 15-17, 2015, at Wash U in St. Louis. Organized by Lee Epstein (Wash U) and Andrew Martin (Michigan):

"The workshop is for law school faculty, political science faculty, and graduate students interested in learning about empirical research and how to evaluate empirical work. Leading empirical scholars Lee Epstein and Andrew Martin will teach the workshop, which provides the formal training necessary to design, conduct, and assess empirical studies, and to use statistical software (Stata) to analyze and manage data. Participants need no background or knowledge of statistics to enroll in the workshop."

Information on the Workshop is here.

Importing Large Excel Datasets into Stata

Over at the Stata forum, a discussion involving importing large Excel datasets unearthed a very helpful coding nugget. The key is entry #3 that reveals an undocumented setting ("set excelxlsxlargefile on"). According to the poster, activating the setting:

"will allow -import excel- to bypass the size checking. But you should be warned, the library we use to import Excel files has a large memory footprint when dealing with large xlsx files. Also the library currently has no ability to allow user to break during the middle of loading an Excel file. Hence when you attempt to load [a large Excel] xlsx file, the Stata session will become unresponsive until it finishes. During this time, you will not be able to break out using the break button."