Judicial opinion

About: Judicial opinion is a research topic. Over the lifetime, 5300 publications have been published within this topic receiving 64803 citations.

Predatory Pricing: Strategic Theory and Legal Policy

Abstract: This paper proposes a new legal rule on predatory pricing based on strategic analysis. The Supreme Court's decision in Brooke with its emphasis on closely analyzing the scheme of predation and recoupment calls for such an analysis. At the same time economic development over the last 20 years of a rigorous analysis of predatory pricing provides the tools required to achieve a more effective legal policy. Economics can now explain when predation can be rational, or in Brooke's terms when it can enable profitable recoupment, casting new light on earlier examples of predatory pricing. The further challenge for legal analysis is to develop workable legal rules to guide enforcement agency policy and judicial decisions. To accomplish this we propose a structured rule of reason, including a fully specified efficiencies defense. Under such an approach enforcement would focus on cases where market structure and conduct makes predation plausible and where anticompetitive effects have occurred, or are dangerously probable. Equally important, the finding of predation would be subject to an efficiencies justification where below-cost pricing is necessary to achieve significant efficiencies, including dynamic efficiencies.

Court Performance around the World: A Comparative Perspective

Abstract: Increasing importance has been placed on an effective and efficient judiciary by governments and civil society. However, apart from decisions that they render, little is known about court performance trends. The judicial reform experiences so far have made it clear that more information is needed to review and compare trends among different countries. This paper addresses the efficiency aspect of court performance, as it can be quantitatively measured using objective data. In addition, congestion, cost, and delay are some of the problems most often complained about by the public. This paper reviews data collected from eleven countries on three continents and provides a description of performance. The main areas of comparison include the number of cases filed, resolved, and pending per judge, the clearance and congestion rates, time to resolve a case, the number of judges, and the cost of a case. The paper also reviews the recent trends within each country and discusses some possible reforms.

The Behavior of Federal Judges: A Theoretical and Empirical Study of Rational Choice

Abstract: Judges play a central role in the American legal system, but their behavior as decision makers is not well understood, even among themselves. The system permits judges to be quite secretive (and most of them are), so indirect methods are required to make sense of their behavior. Here, a political scientist, an economist, and a judge work together to construct a unified theory of judicial decision-making. Using statistical methods to test hypotheses, they dispel the mystery of how judicial decisions in district courts, circuit courts, and the Supreme Court are made. The authors derive their hypotheses from a labor-market model, which allows them to consider judges as they would any other economic actors: as self-interested individuals motivated by both the pecuniary and non-pecuniary aspects of their work. In their view, this model describes judicial behavior better than either the traditional "legalist" theory, which sees judges as automatons who mechanically apply the law to the facts, or the current dominant theory in political science, which exaggerates the ideological component in judicial behavior. Ideology does figure into decision-making at all levels of the federal judiciary, the authors find, but its influence is not uniform. It diminishes as one moves down the judicial hierarchy from the Supreme Court to the courts of appeals to the district courts. As The Behavior of Federal Judges demonstrates, the good news is that ideology does not extinguish the influence of other components in judicial decision-making. Federal judges are not just robots or politicians in robes.

The Norm of Stare Decisis

Abstract: Theory: Precedent might affect Supreme Court decision making in a number of ways. One conception, the conventional view scrutinized by Segal and Spaeth, sees precedent as the primary reason why justices make the decisions that they do. A second regards precedent as a normative constraint on justices acting on their personal preferences. On this account, justices have a preferred rule that they would like to establish in the case before them, but they strategically modify their position to take account of a norm favoring respect for precedent in order to produce a decision as close as is possible to their preferred outcome. Hypothesis: If precedent is a norm, researchers would be unlikely to detect its presence by conventional examinations of the vote. Rather, it would manifest itself throughout the decision making process in some of the following ways: attorneys' attention to precedent and justices' appeals to and respect for the doctrine. Methods: Counts of attorneys' use of authorities in written briefs, of justices' appeals to precedent during conference discussion, of justices' invocation of precedent in their opinions, anid of the Court's alterations of stare decisis. Results: Since the data support our account of stare decisis as a norm that structures judicial decisions, we question research designs that focus solely on how precedent affects the disposition of cases.

Using machine learning to predict decisions of the European Court of Human Rights

Abstract: When courts started publishing judgements, big data analysis (i.e. large-scale statistical analysis of case law and machine learning) within the legal domain became possible. By taking data from the European Court of Human Rights as an example, we investigate how natural language processing tools can be used to analyse texts of the court proceedings in order to automatically predict (future) judicial decisions. With an average accuracy of 75% in predicting the violation of 9 articles of the European Convention on Human Rights our (relatively simple) approach highlights the potential of machine learning approaches in the legal domain. We show, however, that predicting decisions for future cases based on the cases from the past negatively impacts performance (average accuracy range from 58 to 68%). Furthermore, we demonstrate that we can achieve a relatively high classification performance (average accuracy of 65%) when predicting outcomes based only on the surnames of the judges that try the case.