Introduction to the Symposium

Abstract

Two years ago, a research team comprising two political scientists, Andrew Martin and Kevin Quinn, and two legal academics, Pauline Kim and Theodore Ruger, set out to forecast the votes cast and outcome reached in each case argued before the U.S. Supreme Court during its 2002–3 term. To generate the predictions, the researchers turned to approaches to decision making dominant in their respective fields. The political scientists devised a statistical model, which assumes, in line with the vast disciplinary literature on the subject, that judicial decisions are largely a function of politics and case facts. The legal academics went in a different direction. To tap a common belief in their field—that Court decisions reflect law and jurisprudential principles—they asked appellate lawyers and legal scholars (“experts” in particular areas of the law) to predict the outcome of each of the term's decisions. The researchers then posted all the forecasts on the Project's Web site (http://wusct.wustl.edu), along with the actual votes and outcomes as the Court handed down its decisions. As it turned out, the statistical model produced far more accurate predictions of case outcomes than the experts (75 percent versus 59.1 percent), while the experts did marginally better at forecasting the votes of individual justices (67.9 percent versus 66.7 percent).Lee Epstein thanks Jennifer L. Hochschild, Nancy Staudt, and the journal's reviewers for their comments on her essay, as well as for their help in shaping the symposium.