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Article Dans Une Revue Theory and Decision Année : 2013

The impact of governmental assistance on insurance demand under ambiguity: a theoretical model and an experimental test

Résumé

This article deals with the impact of governmental assistance on insurance demand under ambiguity, i.e., in situations where probabilities are uncertain. First, using a model of insurance demand under ambiguity, we derive theoretical predictions about the impact of several governmental assistance programmes on optimal insurance demand. For example, governmental assistance through a fixed public support scheme implies that partial insurance is always optimal under fair insurance with ambiguity. Second, we present the results of an experiment designed to test these predictions. We find support for several of our theoretical predictions. For example, the presence of governmental assistance through a fixed public support scheme decreases individuals' willingness to pay to be fully insured. Finally, we compare these results with those obtained for a risk situation. We find that, regardless of the form of governmental assistance, participants in the ambiguity context are consistently willing to pay more to be fully insured than participants in the risk situation.

Dates et versions

hal-01001032 , version 1 (04-06-2014)

Identifiants

Citer

Marielle Brunette, Laure L. Cabantous, Stéphane S. Couture, Anne Stenger. The impact of governmental assistance on insurance demand under ambiguity: a theoretical model and an experimental test. Theory and Decision, 2013, 75 (2), pp.153 - 174. ⟨10.1007/s11238-012-9321-8⟩. ⟨hal-01001032⟩
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