Washington University in St Louis Andrew D Martin
  Andrew D Martin

All of Professor Martin's published work can be accessed via links on his curriculum vitae. This page contains links to project sites, working papers, and talks. Please contact Professor Martin if there are any problems with these links, or if you would like to receive a hard-copy version of a working paper or a published paper listed on his vitae.

Working Papers

Barry Friedman, Andrew D. Martin, Xun Pang, and Kevin M. Quinn. "Endogenous Jurisprudential Regimes." Click here for the paper.

Morgan L. W. Hazelton, Rachael K. Hinkle, and Andrew D. Martin. "On Replication and the Study of the Lousiana Supreme Court." Click here for the paper.

Barry Friedman and Andrew D. Martin. "Looking for Law in All the Wrong Places: Some Suggestions for Modeling Legal Decisionmaking." Presented at the What's Law Got To Do With It? Conference, Indiana University Maurer School of Law, March 2009. Click here for the paper.

Cliff Carrubba, Barry Friedman, Andrew D. Martin, and Georg Vanberg. "Does the Median Justice Control the Content of Supreme Court Opinions?" Presented Second Annual Conference on Empirical Legal Studies, November 2007. Click here for the paper.

Nathan M. Jensen, Andrew D. Martin, and Anton Westveld. "Modeling Foreign Direct Investment as a Longitudinal Social Network." Presented at the 2007 meeting of the Society for Political Methodology. Click here for the paper.

Christina L. Boyd, Lee Epstein, and Andrew D. Martin. "Untangling the Causal Effects of Sex on Judging." Presented at the 2007 meeting of the Midwest Political Science Association. Click here for the paper.

Andrew D. Martin. "Bayesian Analysis." Prepared for The Oxford Handbook of Political Methodology. Click here for the chapter.

Kevin M. Quinn, Jong Hee Park, and Andrew D. Martin. "Improving Judicial Ideal Point Estimates with a More Realistic Model of Opinion Content." Click here for the paper.

Andrew D. Martin and Kevin M. Quinn. "Can Ideal Point Estimates be Used as Explanatory Variables?" Click here for the paper.

René Lindstädt and Andrew D. Martin. "Discharge Petition Bargaining in the House, 1995-2000." Presented at the 2003 meeting of the Midwest Political Science Association. Click here for the paper.

Andrew D. Martin and Kyle L. Saunders. "Bayesian Inference for Political Science Panel Data." Presented at the 2002 meeting of the American Political Science Association. Click here for the paper.


Andrew D. Martin. "How Do Judges Make Decisions?" Presented at the American Association of Law Schools Annual Meeting, January 5, 2007. Click here for the slides.

Lee Epstein, Andrew D. Martin, and Matthew M. Schneider. "On the Effective Communication of the Results of Empirical Studies." Presented at the Vanderbilt University Law School, Vanderbilt Law Review Symposium on Empirical Scholarship, February 27, 2006. Click here for the slides.

Andrew D. Martin. "A Pragmatic Justification for the Use of Bayesian Methods in the Social Sciences." Presented at the University of South Carolina Political Science Research Workshop, October 7, 2005. Click here for the slides. Here are the Quicktime movies from the talk: [Sampling from a Mixture of Normals / Gibbs Sampling / Metropolis-Hastings Sampling]

Lee Epstein, Andrew D. Martin, Jeffrey A. Segal, and Chad Westerland. "The Judicial Common Space." Presented at the Northwestern University Law School, Law and Positive Political Theory Conference: Legal Doctrine and Political Control, April 29, 2005. Click here for the slides.

Andrew D. Martin and Kevin M. Quinn. "MCMCpack: An Evolving R Package for Bayesian Inference.'' Presented in plenary session at UseR! 2004: The R User Conference, Technische Universität Wien, Vienna, Austria. Click here for slides.

Andrew D. Martin. "Bayesian Inference and Computation in Political Science." Slides from a talk given to the Department of Politics, Nuffield College, Oxford University, March 9, 2004. Click here for the slides, and here for the example R code.

Project Sites

A number of ongoing or past projects have project-specific websites. Four of current interest include:
  • The Supreme Court Database. This website contains a modernized version of the Spaeth Supreme Court Database. The site allows users to access the underlying data without the use of statistical software. The site also distributes binary versions of the data, and supports a significant project to backdate the entire collection from the Founding forward.
  • The EEOC Litigation Project. This project collects and analyzes data on federal court litigation brought between 1997 and 2006 by the Equal Employment Opportunity Commission (EEOC). The data capture various aspects of the agency's litigation activities, including detailed information regarding the participants, motions, events, and outcomes.
  • Martin-Quinn Scores. Measuring the relative location of U.S. Supreme Court justices on an ideological continuum allows us to better understand the politics of the high court. In addition, such measures are an important building blocking of statistical models of the Supreme Court, the separation of powers system, and the judicial hierarchy. This website contains the so-called "Martin-Quinn" measures of judicial ideology developed by Kevin M. Quinn and me. The "Martin-Quinn" scores are estimated for every justice serving from the October 1937 term to the present.
  • The Supreme Court Forecasting Project. This project involved a friendly interdisciplinary competition to compare the accuracy of the different ways in which legal experts and political scientists assess and predict Supreme Court decision making. Legal scholars and political scientists have engaged in much debate about why the Supreme Court decides cases as it does, but this ongoing discussion is almost always retrospective in nature -- that is, scholars apply competing explanatory frameworks to existing Supreme Court decisions from the recent or not-so-recent past. To invert the temporal link, during the Court's 2002 term, we conducted a study where we predicted the outcome of each argued case. Two methods of prediction were used, and we compared their relative accuracy. The results of the study have been published in the Columbia Law Review and Perspectives on Politics. We contrasted a statistical forecasting model (based on information derived from past Supreme Court decisions and certain characteristics of each pending case) with forecasts provides by legal experts (each of whom is an expert in some area of the Supreme Court's docket and many of whom clerked at the Court). The project website contains a description of the project, replication materials, and all of the forecasts from the 2002 term.