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

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.

[1]  A. Baillon,et al.  Aggregating imprecise or conflicting beliefs: An experimental investigation using modern ambiguity theories , 2012 .

[2]  Nicolas Vieille,et al.  Aggregation of multiple prior opinions , 2011, J. Econ. Theory.

[3]  Mohammed Abdellaoui,et al.  The Rich Domain of Uncertainty: Source Functions and Their Experimental Implementation , 2011 .

[4]  E. Michel-Kerjan.  Catastrophe Economics: The National Flood Insurance Program , 2010 .

[5]  William S. Neilson.  A simplified axiomatic approach to ambiguity aversion , 2010 .

[6]  P. Slovic,et al.  Do ambiguity avoidance and the comparative ignorance hypothesis depend on people’s affective reactions? , 2010 .

[7]  A. Snow.  Ambiguity and the value of information , 2010 .

[8]  P. Glimcher,et al.  Title: the Neural Representation of Subjective Value under Risk and Ambiguity 1 2 , 2009 .

[9]  Kyoungwon Seo,et al.  AMBIGUITY AND SECOND-ORDER BELIEF , 2009 .

[10]  Mark J. Machina,et al.  Risk, Ambiguity, and the Rank-Dependence Axioms , 2009 .

[11]  S. Chew,et al.  Source preference and ambiguity aversion: models and evidence from behavioral and neuroimaging experiments. , 2008, Advances in health economics and health services research.

[12]  Long Term Insurance (Lti) for Addressing Catastrophe Risk , 2008 .

[13]  Thibault Gajdos,et al.  Attitude toward imprecise information , 2008, J. Econ. Theory.

[14]  C. Gollier.  Whom should we believe? Aggregation of heterogeneous beliefs , 2007 .

[15]  Richard Shepherd,et al.  Effects of information from sources in conflict and in consensus on perceptions of genetically modified food , 2007 .

[16]  Laure Cabantous.  Ambiguity Aversion in the Field of Insurance: Insurers’ Attitude to Imprecise and Conflicting Probability Estimates , 2007 .

[17]  Arie W. Kruglanski,et al.  Social psychology: Handbook of basic principles, 2nd ed. , 2007 .

[18]  Ning Du,et al.  The Effects of Imprecise Probabilities and Outcomes in Evaluating Investment Options , 2005, Manag. Sci..

[19]  How Do Information Ambiguity and Timing of Contextual Information Affect Managers ’ Goal Congruence in Making Investment Decisions in Good Times vs . Bad Times ? , 2005 .

[20]  D. Hilton.  Knowledge-Based Causal Attribution : The Abnormal Conditions Focus Model , 2004 .

[21]  M. Marinacci,et al.  A Smooth Model of Decision Making Under Ambiguity , 2003 .

[22]  Adrian K. Rantilla,et al.  The effects of asymmetry among advisors on the aggregation of their opinions , 2003 .

[23]  T. Cameron,et al.  Updating Subjective Risks in the Presence of Conflicting Information: An Application to Climate Change , 2002 .

[24]  Massimo Marinacci,et al.  Ambiguity Made Precise: A Comparative Foundation , 1998, J. Econ. Theory.

[25]  Joanna L. Y. Ho,et al.  Effects of Outcome and Probabilistic Ambiguity on Managerial Choices , 2002 .

[26]  E. Salas,et al.  Linking Expertise and Naturalistic Decision Making , 2001 .

[27]  John McClure,et al.  Countering Fatalism: Causal Information in News Reports Affects Judgments About Earthquake Damage , 2001 .

[28]  D. Ellsberg,et al.  Risk, ambiguity, and decision , 2001 .

[29]  N. Warin.  Aux frontieres de l'assurabilite des risques de l'entreprise. Une analyse experimentale des decisions de l'assureur , 2000 .

[30]  W. Kip Viscusi,et al.  Hopes and Fears: the Conflicting Effects of Risk Ambiguity , 1999 .

[31]  M. Smithson,et al.  Conflict Aversion: Preference for Ambiguity vs Conflict in Sources and Evidence. , 1999, Organizational behavior and human decision processes.

[32]  Michael A. Becker.  Social Psychology: Handbook of Basic Principles , 1998 .

[33]  W. Viscusi,et al.  Alarmist Decisions with Divergent Risk Information , 1997 .

[34]  E. Higgins,et al.  Social psychology: Handbook of basic principles. , 1996 .

[35]  K. Taylor.  Testing credit and blame attributions as explanation for choices under ambiguity , 1995 .

[36]  Howard Kunreuther,et al.  Ambiguity and underwriter decision processes , 1995 .

[37]  D. Hilton,et al.  Processes of causal explanation and dispositional attribution. , 1995 .

[38]  Colin Camerer,et al.  Recent developments in modeling preferences: Uncertainty and ambiguity , 1992 .

[39]  W. Kip Viscusi,et al.  Bayesian decisions with ambiguous belief aversion , 1992 .

[40]  A. Tversky,et al.  Preference and belief: Ambiguity and competence in choice under uncertainty , 1991 .

[41]  R. Hogarth,et al.  Venture Theory: A Model of Decision Weights , 1990 .

[42]  Howard Kunreuther,et al.  Risk, ambiguity, and insurance , 1989 .

[43]  Jonathan Baron,et al.  Ambiguity and rationality , 1988 .

[44]  R. Hogarth,et al.  Ambiguity and Uncertainty in Probabilistic Inference. , 1985 .

[45]  B. Weiner.  "Spontaneous" causal thinking. , 1985, Psychological bulletin.

[46]  H. Kelley.  The processes of causal attribution. , 1973 .

[47]  Barbara Tufty,et al.  At War with the Weather , 1966 .

[48]  D. Ellsberg.  Decision, probability, and utility: Risk, ambiguity, and the Savage axioms , 1961 .