Journal of Risk and Uncertainty

, Volume 42, Issue 3, pp 211–232 | Cite as

Is imprecise knowledge better than conflicting expertise? Evidence from insurers’ decisions in the United States

  • Laure Cabantous
  • Denis Hilton
  • Howard Kunreuther
  • Erwann Michel-Kerjan


This paper reports the results of the first experiment in the United States designed to distinguish between two sources of ambiguity: imprecise ambiguity (expert groups agree on a range of probability, but not on any point estimate) versus conflict ambiguity (each expert group provides a precise probability estimate which differs from one group to another). The specific context is whether risk professionals (here, insurers) behave differently under risk (when probability is well-specified) and different types of ambiguity in pricing catastrophic risks (floods and hurricanes) and non-catastrophic risks (house fires). The data show that insurers charge higher premiums when faced with ambiguity than when the probability of a loss is well specified (risk). Furthermore, they tend to charge more for conflict ambiguity than imprecise ambiguity for flood and hurricane hazards, but less in the case of fire. The source of ambiguity also impacts causal inferences insurers make to reduce their uncertainty.


Ambiguity Source of uncertainty Insurance pricing Decision-making 

JEL classification

C93 D81 D83 



We would like to thank the editor, Kip Viscusi, an anonymous referee, Diemo Urbig and seminar participants at the Wharton School, the University of Toulouse-Le Mirail and the Centre for Risk and Insurance Studies at Nottingham University Business School for insightful comments on a previous version of this article. Carol Heller provided excellent research assistance. We also would like to thank the American Insurance Association, the Property Casualty Insurance Association of America, and the National Association of Mutual Insurance Companies for helping us distribute the survey among their members. Partial financial support by the Wharton Risk Management and Decision Processes Center, the Center for Climate and Energy Decision Making (SES-0949710; cooperative agreement between the National Science Foundation and Carnegie Mellon University), NSF Cooperative Agreement SES-0345840 to Columbia University’s Center for Research on Environmental Decisions (CRED), the Travelers Companies, Inc. and the Fulbright program is acknowledged.


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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Laure Cabantous
    • 1
  • Denis Hilton
    • 2
  • Howard Kunreuther
    • 3
  • Erwann Michel-Kerjan
    • 3
  1. 1.Nottingham University Business School, The University of Nottingham, Jubilee CampusNottinghamUK
  2. 2.Laboratoire Cognition, Langues, Langage, et Ergonomie (CLLE) Maison de la RechercheUniversité de Toulouse II - le MirailToulouse Cedex 9France
  3. 3.Center for Risk Management and Decision Processes, The Wharton SchoolUniversity of PennsylvaniaPhiladelphiaUSA

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