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How Sure Can You Be? A Framework for Considering Delivery Uncertainty in Benefit Assessments Based on Stated Preference Methods


  • Klaus Glenk,

  • Sergio Colombo

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    • Klaus Glenk was with the Macaulay Institute, Aberdeen, UK and is now with the Scottish Agricultural College (SAC), Edinburgh, UK. E-mail: for correspondence. Sergio Colombo is with the Area de Economía y Sociología Agraria, IFAPA, Centro Camino de Purchil, Granada, Spain. This research was funded by The Scottish Government Rural and Environment Research and Analysis Directorate (RERAD) and the project RTA2009-00024-00-00 funded by the Spanish Institute for Agricultural Research INIA and co-funded by the FEDER fund. We are grateful for the able research assistance of Diana Feliciano. We would also like to thank Nick Hanley, Helaina Black, Willie Towers and Christine Watson for continuous support and valuable discussions, and Kirsty Blackstock and Antoinette Kriel for useful comments on earlier versions. Thanks, too, to two anonymous reviewers, to David Harvey and to Sue Chilton for the valuable comments on an earlier draft.


The economic valuation of benefits resulting from environmental policies and interventions often assumes that environmental outcomes are certain. In fact, these outcomes are typically uncertain. This article proposes a methodological approach to incorporate delivery uncertainty into benefit estimation based on stated preference methods. In the study design of a choice experiment survey on land-based climate change mitigation, we explicitly include delivery uncertainty as the risk that a proposed mitigation project fails to deliver emission savings. We find that respondents’ preferences do not change significantly after being confronted with choices that included risk of failure. However, failure risk itself does have an important impact on the preferences for delivering emission reductions. We show that delivery uncertainty can have a large impact on stated preference estimation of benefits of public programmes. This result should condition conclusions drawn from ex-ante environmental cost-benefit analyses that make use of such benefit estimates.