  It is often reasonable to assume that the dependence structure of a bivariate
continuous distribution belongs to the class of extreme-value copulas. The
latter are characterized by their Pickands dependence function. In this paper,
a procedure is proposed for testing whether this function belongs to a given
parametric family. The test is based on a Cram\'{e}r--von Mises statistic
measuring the distance between an estimate of the parametric Pickands
dependence function and either one of two nonparametric estimators thereof
studied by Genest and Segers [Ann. Statist. 37 (2009) 2990--3022]. As the
limiting distribution of the test statistic depends on unknown parameters, it
must be estimated via a parametric bootstrap procedure, the validity of which
is established. Monte Carlo simulations are used to assess the power of the
test and an extension to dependence structures that are left-tail decreasing in
both variables is considered.
