Economic Signaling and Distributive Efficiency of Judicial Decisions
Edmund H. Mantell
DOI : 10.3844/jssp.2010.198.205
Journal of Social Sciences
Volume 6, 2010
Problem statement: This study considered the problem of how a judge can render an optimal decision in a lawsuit where two litigants each assert a property right in a case where the relevant information is asymmetrically distributed between the parties and the judicial decision-maker. Approach: The research embodied in this study defines an optimal decision as one reflecting the distributive efficiency of the judicial vesting of the right. The research addresses a gap in the economic analysis of legal doctrine by reason of the fact that most of the economic literature on judicial decisionmaking focuses exclusively on implications for allocative efficiency with no regard the distributive effects of the judicial decision. Results: The analysis in the study is confined to cases where ex post bargaining between the parties is infeasible. It is assumed that each litigant has a quadratic utility function. The litigation is characterized by asymmetric information: each party knows the parameters of his own utility function but those parameters are not known by his adversary or by the judge. The judge regards the parties’ optima as random variables. The analysis in this study is based on an assumption that the judge will frame his decision so as to maximize a social welfare function, defined as the sum of the litigantsâ utility functions. The judge infers each litigantâs private information from the signals each transmits during the litigation. Conclusion: The results compared the distributive efficiency of a declaratory judgment with the distributive efficiency of a discretionary judgment. The results established a decision criterion that is distributively efficient in the sense that it maximizes the social welfare function when the judge is imperfectly informed as to the litigantâs valuations.
© 2010 Edmund H. Mantell. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.