Accessible Unlicensed Requires Authentication Published by De Gruyter January 13, 2015

Embedding (some) benefit-cost concepts into decision support processes with deep uncertainty

Robert J. Lempert

Abstract

Benefit-cost analysis (BCA) aims to help people make better decisions. But BCA does not always serve this role as well as intended. In particular, BCA’s aim of aggregating all attributes of concern to decision makers into a single, best-estimate metric can conflict with the differing world views and values that may be an inherent characteristic of many climate-related decisions. This paper argues that new approaches exist that can help reduce the tension between the benefits of providing useful, scientifically based information to decision makers and the costs of aggregating uncertainty and differing values into single best estimates. Enabled by new information technology, these approaches can summarize decision-relevant information in new ways. Viewed in this light, many limitations of BCA lie not in the approach itself, but with the way it is used. In particular, this paper will argue that the problem lies in a process that begins by first assigning agreed-upon values to all the relevant inputs and then using BCA to rank the desirability of alternative decision options. In contrast, BCA can be used as part of a process that begins by acknowledging a wide range of ethical and epistemological views, examines which combinations of views are most important in affecting the ranking among proposed decision options, and uses this information to identify and seek consensus on actions that are robust over a wide range of such views.


Corresponding author: Robert J. Lempert, Rand Corporation, Santa Monica, CA 90401, USA, e-mail:

Acknowledgments

The author thanks Klaus Keller and Ryan Sriver for their help in summarizing in Section 3 the work we did together. The author also thanks two anonymous reviewers, Anne Grambsch, and the other authors in this special issue, for their very helpful comments. This paper was supported in part by the Network for Sustainable Climate Risk Management (SCRiM) under NSF cooperative agreement GEO-1240507.

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Published Online: 2015-1-13
Published in Print: 2014-12-1

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