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Ambiguity Increases and Insurance Deductibles




               ambiguity increase.
                    Our results augment the literature on ambiguity as follows. First, our results extend
               the work of Birghila et al. (2023). They show that under the maxmin model, the optimal
               insurance contracts with and without the sabotage condition imposed on the indemnity

               function are in the deductible form, although with different shapes of the optimal
               indemnity function. We study how ambiguity affects the optimal deductible level under
               the more general α-maxmin model, without assuming the sabotage condition. In terms

               of studying the optimal deductible level when the risk is ambiguous, our results can be
               treated as a dual version of Alary et al. (2013) and Gollier (2014) but under a different
               model. Given certain ambiguity structures, these authors study how the optimal deductible
               changes under ambiguity aversion compared to ambiguity neutrality for individuals with
               smooth-ambiguity-aversion preferences. Alary et al. (2013) show that when ambiguity

               occurs only in the no-loss state, ambiguity aversion reduces the optimal deductible relative
               to ambiguity neutrality under the smooth ambiguity aversion model. Using the same
               model, Gollier (2014) studies a different ambiguity structure. When ambiguity affects only

                             *
               losses below D , he shows that, for possible loss distributions ranked according to FSD,
               introducing ambiguity aversion is sufficient to raise the optimal deductible. On the other
               hand, given ambiguity aversion, we examine how the optimal deductible changes under an
               ambiguity increase for α-maxmin preferences.



               3.2 A General Ambiguity Increase
                    We now discuss a general ambiguity increase. In this case, we do not preserve the
               cumulative loss probability at D , which is required in the case of a specific ambiguity
                                             *
                                             F
               increase. The general ambiguity increase is described in Definition 2. Let Ġ  (x,α) denote
                                                                                   i
               αG(x;π ) + (1 - α)G(x;¯π ), where i = F or T. The exogenous variables are suppressed to
                                     i
                    _ i
                                                                              *
               simplify notations. Accordingly, FOC (8) divided by (1 + τ)(1 - G(D ;π )) becomes
                                                                           *
                                                                           F
                                   ∗
                                                (  ∗  )
                                                                                             (9)
                          −                − 1          ∗     (  ∗ )        ∗    = 0.
                            (   )     ∗  ∗
                    As shown in Appendix E, finding the determining condition under which the general




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