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


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2013-08

AUTHORS

Marielle Brunette, Laure Cabantous, Stéphane Couture, Anne Stenger

ABSTRACT

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. More... »

PAGES

153-174

References to SciGraph publications

Journal

TITLE

Theory and Decision

ISSUE

2

VOLUME

75

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11238-012-9321-8

DOI

http://dx.doi.org/10.1007/s11238-012-9321-8

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1006228854


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