  A bivariate integer-valued autoregressive process of order 1 (BINAR(1)) with
copula-joint innovations is studied. Different parameter estimation methods are
analyzed and compared via Monte Carlo simulations with emphasis on estimation
of the copula dependence parameter. An empirical application on defaulted and
non-defaulted loan data is carried out using different combinations of copula
functions and marginal distribution functions covering the cases where both
marginal distributions are from the same family, as well as the case where they
are from different distribution families.
