The Uncertainty Problem in Cost-Benefit Analysis Expanded: A Current Review

Abstract

This article examines the current state of cost-benefit analysis and its limitations. The review was completed by looking at current literature of cost-benefit analysis with the most up to date developments. Currently, it faces known challenges in quantifying subjective human elements, incommensurable costs and benefits, difficulty in measuring and discounting future benefits and costs, and the potential lack of impartiality in regulatory settings. However, this article uniquely addresses a paradox in the analysis process itself related to the discovery of new information. Methods to mitigate risk and uncertainty, such as sensitivity analysis, Monte Carlo simulations, and scenario analysis, are analyzed. Additionally, quasi-option value is addressed as it relates the discovery of new information. Despite these approaches to mitigate uncertainty, uncertainty remains a fundamental challenge in achieving true optimality through cost-benefit analysis. However, it is found that despite the paradox identified in this article, it can still be a useful tool in evaluating decision alternatives.