Pricing Insurance and Warranties: Ambiguity and Correlated Risks

Abstract

This paper reports the results of a study of pricing decisions made by professional actuaries. The study formed part of a mail survey of members of the Casualty Actuarial Society conducted to investigate the effects of ambiguity -- in the form of uncertainty about probabilities of risks -- on prices on insurance and warranties. Theoretical hypotheses derived from the expected utility model were compared with the implications of procedures described by practicing actuaries which were found to coincide with several features of the Einhorn-Hogarth ambiguity model. Actuaries were asked to act as consultants to a computer manufactures concerning the price of a warranty. The design of the study involved comparing ambiguous and non-ambiguous probabilities, different levels of probabilities and size of potential loss, and the nature of risk involved, i.e., whether the risks were independent across items or perfectly correlated (if one fails, all fail). Results supported implications of procedures described by actuaries (as well as the Einhorn-Hogarth ambiguity model), but were inconsistent with predictions from expected utility theory regarding correlated risks. In addition to quantitative analyses of the data, further insight is provided by interviews with actuaries concerning their decision-making processes as well as an analysis of comments written on the questionnaire forms.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1988
Accession Number
ADA203773

Entities

People

  • Howard Kunreuther
  • Robin M. Hogarth

Organizations

  • University of Chicago

Tags

Communities of Interest

  • Biomedical
  • C4I
  • Human Systems

DTIC Thesaurus Topics

  • Ambiguity
  • Business Administration
  • Casualties
  • Classification
  • Commerce
  • Computers
  • Delphi Method
  • Economics
  • Guarantees
  • Insurance
  • Military Research
  • New York
  • North America
  • Personal Computers
  • Probability
  • Psychology
  • Random Variables

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  • Organizational Psychology.
  • Regression Analysis.