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Very Low Probabilities in the Loss Domain

Narges Hajimoladarvish ()
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Narges Hajimoladarvish: University of Leicester

The Geneva Papers on Risk and Insurance Theory, 2017, vol. 42, issue 1, 41-58

Abstract: Abstract This experimental study uses a non-parametric method to investigate probability weighting functions for very low probabilities in the loss domain. Probability weights in three loss situations containing small, large and heterogeneous losses composed of both small and large losses are elicited. While most of the probabilities under consideration are significantly overweighted, the probability weighting function exhibits the much replicated inverse S-shaped functions when losses are small. Interestingly, the more common probabilities, 0.1 and 0.01, get underweighted by more than half of the sample in small and heterogeneous loss situations, respectively. Probability underweighting is accompanied by risk-loving behaviour that can have implications for design of contracts and policies designed to control risky behaviours.

Keywords: decision making under risk; cumulative prospect theory; probability weighting functions; utility elicitation; low-probability events (search for similar items in EconPapers)
Date: 2017
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