  This paper develops a Pareto scale-inflated outlier model. This model is
intended for use when data from some standard Pareto distribution of interest
is suspected to have been contaminated with a relatively small number of
outliers from a Pareto distribution with the same shape parameter but with an
inflated scale parameter. The Bayesian analysis of this Pareto scale-inflated
outlier model is considered and its implementation using the Gibbs sampler is
discussed. The paper contains three worked illustrative examples, two of which
feature actual insurance claims data.
