Value of Information for Policy Analysis

This dissertation considers the viability of applying Value of Information (VoI) methods in complex systems for policy analysis, concluding that these methods can be applied, but that different methods are appropriate in different cases. VoI is value to a decisionmaker of the difference information makes for a decision, or what a decisionmaker should pay for information. Compared to present practice, specific value of information techniques can potentially improve policy analysis and decision making. To that end, a methodology for policy applications of VoI is presented that can simplify practical application.

The dissertation applied computational methods for VoI to two case studies in disparate domains: biosurveillance and detection of violent extremists. Each of the case studies outlines how Bayesian methods can be used to evaluate VoI, including a novel formulation for considering additional information sources in the systems. The case studies are used both to consider the relative benefits and drawbacks of these approaches in policy decision making, and to identify potential challenges. Approaches for identifying and avoiding these challenges and for selecting appropriate methods are integrated into the overall methodology, which is presented in the final chapter.